NMR Spectroscopy of Glycoconjugates

NMR Spectroscopy of Glycoconjugates. Edited by Jesús Jiménez-Barbero, Thomas Peters Copyright © 2002 Wiley-VCH Verlag Gm...

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NMR Spectroscopy of Glycoconjugates. Edited by Jesús Jiménez-Barbero, Thomas Peters Copyright © 2002 Wiley-VCH Verlag GmbH & Co. KGaA ISBNs: 3-527-30414-2 (Hardback); 3-527-60071-X (Electronic)

NMR Spectroscopy of Glycoconjugates Edited by J. Jiménez-Barbero and T. Peters


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NMR Spectroscopy of Glycoconjugates Edited by J. Jiménez-Barbero and T. Peters


Prof. Dr. Jesús Jiménez-Barbero Centro de Investigacíones Biológicas CSIC Ramiro de Maeztu, 9 28040 Madrid Spain

n This book was carefully produced. Nevertheless, editors, authors and publisher do not warrant the information contained therein to be free of errors. Readers are advised to keep in mind that statements, data, illustrations, procedural details or other items may inadvertently be inaccurate.

Prof. Dr. Thomas Peters Medical University of Lübeck Institute of Chemistry 23538 Lübeck Germany

Library of Congress Card No.: applied for British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library. Die Deutsche Bibliothek – CIP-Cataloguing-inPublication Data A catalogue record for this publication is available from Die Deutsche Bibliothek. © 2003 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim All rights reserved (including those of translation in other languages). No part of this book may be reproduced in any form – by photoprinting, microfilm, or any other means – nor transmitted or translated into machine language without written permission from the publishers. Registered names, trademarks, etc. used in this book, even when not specifically marked as such, are not to be considered unprotected by law. Printed in the Federal Republic of Germany Printed on acid-free paper Typesetting K+V Fotosatz GmbH, Beerfelden Printing Strauss Offsetdruck GmbH, Mörlenbach Bookbinding J. Schäffer GmbH & Co. KG, Grünstadt ISBN

3-527-30414-2


Contents Preface

XI

Abbreviations

XIII

Part A

Parameters, Techniques and Experiments

1

Relaxation and Dynamics

1.1 1.2 1.3 1.3.1 1.3.2 1.3.3 1.3.4 1.3.5 1.4 1.5 1.6

Göran Widmalm Introduction 3 Theory 4 Oligosaccharide Flexibility and Dynamics 10 Flexibility of a Disaccharide 10 Anisotropic Motion of a Pentasaccharide 13 Oligosaccharide Dynamics from Off-Resonance ROESY Rigid versus Flexible: a Trisaccharide Case 16 Slow Dynamics of a Tridecasaccharide 18 Concluding Remarks 19 Acknowledgements 19 References 20

2

Residual Dipolar Couplings in Bacterial Polysaccharides

2.1 2.2 2.3 2.4 2.4.1 2.4.2 2.4.3 2.4.4 2.5 2.6

Manuel Martin-Pastor and C. Allen Bush Introduction 23 Preparation of the Oriented Samples 24 NMR Experiments for the Measurement of Dipolar Couplings 25 Structure Determination using Residual Dipolar Coupling 29 Theory 29 Rigid Structure Calculations 32 Structure Calculations in the Presence of Flexibility 34 Structure Calculations in the Bound State 36 Conclusions 36 References 37

1

3

15

23

V

VI

Contents

3

Detection of Hydroxyl Protons

3.1 3.2 3.3 3.4 3.5

Hans-Christian Siebert, Martin Frank, Claus-Wilhelm von der Lieth, Jesus Jiménez-Barbero, and Hans-Joachim Gabius Introduction 39 Hydroxyl Groups of Free Carbohydrates 43 Hydroxyl Groups of Bound Carbohydrates 45 Conclusions 55 References 56

4

NMR of Carbohydrates: 1D Homonuclear Selective Methods

39

59

4.4 4.5 4.6

Jean-Robert Brisson, Shih-Che Sue, Wen-guey Wu, Gerald McManus, Pham T. Nghia, and Duˇsan Uhrín Introduction 59 Experimental Aspects 59 Description of the Pulse Sequences 59 Examples 62 Maltotriose: Overlapping Anomeric Resonances 62 Determination of the Bound Conformation of a Heparin Disaccharide, and Intermolecular NOEs 65 NMR of Mixtures 70 Measurement of Proton-Proton Residual Dipolar Coupling Constants in Oligosaccharides 80 1D Directed-COSY, 1D Directed-COSY-COSY and 1D-Directed TOCSYCOSY 81 Evaluation of Coupling Constants from Experimental Multiplets. Sign Determination and Parameterization of the Alignment Tensor 88 Conclusions 90 Acknowledgements 90 References 90

5

NMR Experiments for Large Carbohydrates

5.1 5.2 5.2.1 5.2.2 5.2.3 5.2.4 5.2.5 5.3 5.4 5.5 5.6

Sébastien J. F. Vincent Introduction 95 The “Standard” Structural Analysis 96 Chemical Analysis 96 NMR Spectroscopy 98 NMR Assignment 99 Primary Structure Determination 101 Cross-Correlated Dipole-Dipole Relaxation Current Limitations 105 Outlook 105 Acknowledgements 106 References 106

4.1 4.2 4.2.1 4.3 4.3.1 4.3.2 4.3.3 4.3.4 4.3.5 4.3.6

95

102

Contents

Part B

Structural and Conformational Analysis of Carbohydrate Molecules by NMR 109

6

Combining NMR and Simulation Methods in Oligosaccharide Conformational Analysis 111

6.1 6.2 6.2.1 6.2.2 6.2.3 6.2.4 6.2.4.1 6.2.4.2 6.2.4.3 6.2.5 6.2.5.1 6.2.5.2 6.2.5.3 6.3 6.3.1 6.3.2 6.3.3 6.3.4 6.4

6.5 6.6 6.7 6.8 7

7.1 7.2 7.3 7.4 7.4.1 7.4.2 7.4.3 7.5

Thomas Weimar and Robert J. Woods Introduction 111 Oligosaccharide Modeling: Background and Theory 112 Force Fields 112 Molecular Dynamics Simulation versus Monte Carlo Sampling 114 Explicit Solvation: Water Models 116 Boundary Conditions 117 Water Droplets 117 Periodic Boundary Conditions (PBC) 118 Minimum Image Convention 119 MD Simulation of Oligosaccharides 121 Initial Conformation 121 Solvation, Energy Minimization and Molecular Dynamics 121 Data Analysis 123 NMR Spectroscopy of Oligosaccharides 124 1H-1H NOE Experiments on Oligosaccharides 126 ROE Experiments 129 Relaxation Matrix Approach 129 One- and Two-Dimensional NOE Experiments 130 Example Application I: Conformational Analysis of a Disaccharide Employing NOE Curves in Conjunction with Monte Carlo and Molecular Dynamics Simulations [66] 132 Example Application II: PBC Simulation of the Oligomannoside Man9GlcNAc2 137 Conclusions 141 Acknowledgements 142 References 142 The Unique Solution Structure and Immunochemistry of the Candida albicans b1,2-Mannopyranan Cell Wall Antigen

145

Mark Nitz and David R. Bundle Introduction 145 Candida albicans Cell Wall 145 Host Defenses against Fungal Infection 146 Chemical Synthesis of 1,2-Linked b-Mannopyranose Oligomers 147 Synthesis of the Terminal Reducing Residue 148 Synthesis of Oligosaccharides 148 Synthesis of a (1? 2)-b-Mannopyranotetrose Terminated by a Thio-glycosidic Linkage 152 Molecular Modeling and NMR of (1 ? 2)-b-Mannopyranan Tri-, Tetraand Pentose 155

VII

VIII

Contents

7.6 7.6.1 7.6.2 7.6.3 7.6.4 7.6.5 7.7 7.8

Assignment of 1H and 13C Spectra for (1 ? 2)-b-Mannopyranan Tri-, Tetra- and Pentose Oligomers 156 Analysis of NOE Contacts for (1 ? 2)-b-Mannopyranan Oligomers 160 Molecular Dynamics Simulations 163 Results of Trisaccharide Modeling 163 Results of Tetrasaccharide Modeling 165 Results of Pentasaccharide Modeling 167 Conclusions about Molecular Modeling 168 Conformational Analysis of the Thio-tetrasaccharide 170 Analysis of the 1H and 13C NMR Spectra of Propyl b(1-2)-thio-tetramannopyranoside (6) 172 Conformational Analysis of Thio-linked Tetrasaccharide 6 173 Comparison of the Native Tetrasaccharide with the Thioglycoside Mimetic 173 Development of an Anti-Candida albicans Vaccine 176 Synthesis of C. albicans Conjugate Vaccines 177 Immunization of Experimental Animals 178 Analysis of Antibody Levels 178 Antibody Levels in Mice and Rabbits 179 Binding of Propyl (1 ? 2)-b-mannosides to Monoclonal Antibodies 180 Conclusions 184 References 184

8

NMR of Sulfated Oligo- and Polysaccharides

7.5.1 7.5.2 7.5.3 7.5.4 7.5.5 7.5.6 7.5.7 7.5.8 7.5.9 7.5.10 7.5.11

189

8.1.2 8.2 8.2.1 8.2.2 8.2.3 8.3 8.4 8.4.1 8.4.2 8.5

Miloš Hricovíni, Pedro M. Nieto, and Giangiacomo Torri Primary and Secondary Structures 189 The Effect of SO–3 Groups upon NMR Chemical Shifts and Coupling Constants 190 The Effect of SO–3 Groups upon the Structure 192 Three-Dimensional Structure 194 Coupling Constants 195 Nuclear Overhauser Effect (NOE) 203 Chemical Shifts 205 Dynamics of Sulfated Saccharides in Solution 206 Interactions with Ions and Proteins 213 Interactions with Metal Ions 213 Interactions with Proteins 216 References 222

9

Residual Dipolar Couplings: Structure and Dynamics of Glycolipids

9.1 9.2 9.3 9.4 9.5

James H. Prestegard and J. Glushka Introduction 231 Glycolipid Structure in Solution 232 Glycolipid Structure in a Membrane Environment 233 Larger Membrane Assemblies 234 Theory of Residual Dipolar Couplings 234

8.1 8.1.1

231

Contents

9.7 9.8 9.9 9.10 9.11

Data Collection and Structure of Oligosaccharides from Residual Dipolar Couplings 237 Insight into Dynamics 239 Glycolipids Anchored to Membranes 239 Glycolipid Structure using 13C Observation 241 Other Techniques and Future Trends 243 References 243

10

Activated Sugars 247

9.6

10.1 10.2 10.2.1 10.2.2 10.2.3 10.2.4 10.2.5 10.2.6 10.2.7 10.3 10.4 10.5 10.6 10.7

Céline Monteiro and Catherine Hervé du Penhoat Introduction 247 NMR Methods for Conformational Analysis of Sugar Nucleotides 248 Nomenclature 248 Sample Preparation 251 NMR Experiments 251 Vicinal Homo- and Heteronuclear Coupling Constants 252 Hydrodynamic Modeling 254 Homonuclear Relaxation Data 257 Relaxation and Frequency Shifts in the Presence of Paramagnetic Cations 260 Monovalent Cations 261 Divalent Cations 263 Trivalent Cations 267 Perspectives 267 References 269

Part C

Interactions of Carbohydrates with Biomolecules Investigated by NMR Techniques and Applications 273

11

NMR Analysis of Carbohydrate – Carbohydrate Interactions

11.1 11.2 11.3 11.4 11.5 11.6

Armin Geyer Introduction 275 Membrane Models for High-Resolution NMR 276 Carbohydrate – Carbohydrate Affinities 277 Lewisx Glycosphingolipids 278 Covalent Tethering of Lex Units [27] 280 References 287

12

TR-NOE Experiments to Study Carbohydrate-Protein Interactions

12.1 12.2 12.2.1 12.2.1.1 12.2.2 12.2.2.1 12.2.2.2

Jesus Jiménez-Barbero and Thomas Peters Introduction 289 The TR-NOE Experiment 290 Experimental Aspects 292 Sample Preparation and Experimental Set-up Variations in the Regular 2D Sequence 294 1D Experiments 294 3D Experiments 295

292

275

289

IX

X

Contents

12.2.3 12.2.3.1 12.2.3.2 12.2.3.3 12.2.3.4 12.2.3.5 12.2.4 12.2.5 12.2.5.1 12.2.5.2 12.2.5.3 12.2.5.4 12.2.5.5 12.2.5.6 12.2.6 12.3

How to Solve Experimental Complications 295 Suppression of the Protein Envelope 295 Presence of Spin Diffusion 295 Identification of Spin Diffusion by TR-ROESY 296 Suppression of Spin Diffusion via MINSY 297 Suppression of Spin Diffusion via QUIET-NOESY 297 Experimental Protocol for TR-NOE Experiments 298 Applications and Examples 299 Recognition of the Global Minimum Conformation 299 Simultaneous Recognition of Different Conformations 301 Protein-induced Conformational Selections 301 Protein-induced Conformational Variations 302 Use of Structurally Modified Carbohydrate Analogs 303 Other Developments 306 Perspectives 306 References 307

Subject Index

311


Preface Traditionally, NMR spectroscopy has been one of the major tools to foster the advance of carbohydrate chemistry. During recent years many novel NMR techniques have been discovered or developed, mainly for the analysis of proteins and nucleic acids. Since it is still not straightforward to isotope label carbohydrates, not all of the techniques will be transferable to the analysis of glycostructures. This book gives examples where these techniques have been applied in the field of NMR analysis of carbohydrates. From our viewpoint, it fills a gap that has existed for the community of carbohydrate and glycoconjugate scientists. No individual volume dealing with most of the different scientific and experimental NMR aspects and topics in which glycostructures are involved was available to the researchers working in this field. NMR of carbohydrates and glycoconjugates has now reached the maturity in which such a book was necessary, and we hope that this book will be of value to senior carbohydrate scientists as well as to those entering the field. We have tried to portray the current status of NMR applications in the area of glycoconjugates, by bringing together the expertise of well known specialists in experimental, technical, and applied aspects of NMR spectroscopy of carbohydrates. The combination of NMR with other techniques to gain structural or functional information is also dealt with in several chapters, showing the multidisciplinary character of this area of research. We would like to thank all the contributors to this book for their support and help to organize the different topics. Madrid/Lübeck August 2002

Jesús Jiménez-Barbero Thomas Peters

XI


List of Authors Jean-Robert Brisson Institute for Biological Sciences National Research Council of Canada Ottawa, ON K1A 0R6, Canada

Armin Geyer Institut für Organische Chemie Universität Regensburg 93040 Regensburg, Germany

C. Allen Bush Department of Chemistry and Biochemistry University of Maryland-Baltimore County Baltimore, MD 21250, USA

J. Glushka Complex Carbohydrate Research Center University of Georgia Athens, GA 30602, USA

David R. Bundle Department of Chemistry The University of Alberta Edmonton, AB T6G 2G2, Canada Martin Frank Zentrale Spektroskopie Deutsches Krebsforschungszentrum Heidelberg Heidelberg, Germany Hans-Joachim Gabius Institut für Physiologische Chemie Tierärztliche Fakultät Ludwig-Maximilians-Universität Veterinärstraße 13 80539 München, Germany

Jesús Jiménez-Barbero Centro de Investigaáones Biológicas CSIC Ramiro de Maeztu, 9 28240 Madrid, Spain Claus-Wilhelm von der Lieth Zentrale Spektroskopie Deutsches Krebsforschungszentrum Heidelberg Heidelberg, Germany Gerald McManus Institute for Biological Sciences National Research Council of Canada Ottawa, ON K1A 0R6, Canada

XIII

XIV

List of Authors

Manuel Martín-Pastor Unidade de RMN, Centro J.R.C. R.I.A.I.D.T., Universidad de Santiago de Compostela 15706 Santiago de Compostela, Spain

Hans-Christian Siebert Institut für Physiologische Chemie Tierärztliche Fakultät Ludwig-Maximilians-Universität Veterinärstraße 13 80539 München, Germany

Céline Monteiro C.E.R.M.A.V. – C.N.R.S. (affilated to Joseph Fourier University) B.P. 53 38041 Grenoble Cedex 9, France

Shih-Che Sue Department of Life Sciences National Tsing Hua University Hsinchu 30043, Taiwan

Pham T. Nghia Slovak University of Technology Chemical Technology, Central Laboratories Radlinskeho 9 81237 Bratislava, Slovakia

Duˇsan Uhrín Edinburgh Centre for Protein Technology Department of Chemistry University of Edinburgh Edinburgh EH9 3JJ, UK

Mark Nitz Department of Chemistry The University of Alberta Edmonton, AB T6G 2G2, Canada

Sébastien J. F. Vincent Nestle Research Center Vers-chez-les-Blanc Boîte Postale 44 1000 Lausanne 26, Switzerland

Catherine Hervé du Penhoat C.E.R.M.A.V. – C.N.R.S. (affilated to Joseph Fourier University) B.P. 53 38041 Grenoble Cedex 9, France Thomas Peters Institut für Chemie Medizinische Universität zu Lübeck 23538 Lübeck, Germany James H. Prestegard Complex Carbohydrate Research Center University of Georgia Athens, GA 30602, USA

Thomas Weimar Institut für Chemie Medizinische Universität zu Lübeck 23538 Lübeck, Germany Göran Widmalm Department of Organic Chemistry Arrhenius Laboratory Stockholm University 10691 Stockholm, Sweden

List of Authors

Robert Woods Complex Carbohydrate Research Center University of Georgia Athens, GA 30602, USA

Wen-guey Wu Department of Life Sciences National Tsing Hua University Hsinchu 30043, Taiwan

XV


Subject Index a absorption shape, pure 63 acyl azide 177 affinity constant 283 agglutinin – Aleuria aurantia 301 – Maclura pomifera 40, 136 – Viscum album 47 aggregation, macroscopic 231 Al2O3 54 albumin, bovine serum / human serum 177 alignment – frame, principle 236 – parameter, rhombic 236 alignment tensor 31, 89 – calculation 33 – superposition 34 alkyl glucoside 241 all-trans eclipsed 249 allyl glycoside 148 Amber 113 – force field 163, 172, 204 amination, reductive 177 amplitude modulation 88 angle spinning, variable 243 anisotropy – chemical shift 207 – – offset 242 – motion 13–15, 212 – susceptibility 235 – tumbling 7 annealing protocol, simulated 121, 165 anomeric – conformation 151 – effect 171 – resonance 76, 77, 100 anti conformer 64 – anti-} conformer 17 anti orientation 257

antibody – binding site 183 – horseradish peroxidase-conjugated 179 – IgG 180 – level, analysis 178–180 – monoclonal 168, 180–184 – oligosaccharide interaction 183 – protective 176 antigen – antigenic determinants, blood-group 113 – polysaccharide 181 – T-antigen disaccharide 132 – Thomsen-Friedenreich antigen 40 antithrombin 69, 193, 206 approach – full relaxation matrix approach 130, 258 – modal-free approach 6 – off-resonance 258 aprotic solvent 42 artifact, spin diffusion 129 atomic velocities 115 averaging, conformational 165

b bacterial polysaccharide 176 – residual dipolar coupling 23–37 bicelle 24, 235, 238, 276 – diameter 25 – membrane 242 bidentate ligand 265 binding site 182 – antibody 183 – cation 215 – lectin 302 – metal ion 213, 263 biomembrane 231 Boltzmann energy factor 115

311

312

Subject Index bound – fraction 283 – state 36 boundary simulation, periodic 119 Brucella polysaccharide B 156

c

13

C-13C dipolar data 242 C chemical shift 101 – anomeric 99 C5-C6 conformer 67 C-glycosidic bond 303 13 C-labelling 105 C-lactose 303 Ca2+ titration 216 calcium – affinity 275 – binding 214 – – proteins 216 – cation coordination 216 – complexation 278 – non-specific binding 282 Camelspin 129 Candida albicans 145–184 – cell wall 145, 146 – vaccine 176–178 candidiasis 145 CarbBank 100 carbohydrate – binding protein 290 – bound – – conformation 41 – – hydroxyl groups 45–55 – conformational analysis 113 – flexible 35 – head groups 277 – loading 177 – modeling philosophies 112 – molecular dynamics (MD) simulation 112 – natural abundance 104 – primary structure 102 – protein interaction 289 – sulfated, stereochemical analysis 201 carbohydrate-carbohydrate – binding 276 – interaction 275 carboxylate – groups 192 – protonation state 215 cardiotoxin 65 Carr-Purcell-Meiboom-Gill sequence 252 cation / sugar nucleotide complex 268 cation binding site 215 13

cell-recognition 275 ceramide 232 – backbone 242 chair form, 4C1 195, 197 charge density, polyion linear / linear 214 CHARMm 113 CHARMm22 254 chemical environment 124 chemical exchange process 10 – contribution 10 chemical shift 205, 206 – perturbation 293 p-Chlorobenzyl ether 149 chondroitin – 4-sulfate 189, 194 – 6-sulfate 189, 194 – sulfate-related disaccharide 204 1,2-cis linkage 149 cis-homophilic binding 287 cis-planar eclipsed 249 complex – calcium 278 – carbohydrates 86 – carbohydrate-protein 122 – cation / sugar nucleotide 268 – glycosyl donor / glycosyl transferase 268 – metal-nucleotide 260 – Mg2+ / UDP-Glc 263 – mixture 72 – protein-carbohydrate 289 – sugar nucleotide / divalent cation 263 computational method 112 computer performance 142 Con A 138 conformation / conformational 3 – analysis tool 47 – anti-conformation 165, 173, 302 – averaging 165 – bioactive 181, 290 – bound 79 – 1C4 201, 220 – chair 196 – constraints 54 – ensemble 112 – equilibrium 198, 203, 301 – extended 122 – flexibility 12 – fluctuation, internal 233 – global minimum 163, 299 – glycosidic linkage 201, 205 – iduronate ring 200 – low-energy 183 – minima 163

Subject Index – non-chair 196 – random 248 – randomly generated 115 – space 16, 114, 163 – starting 121 – state 137 – syn-conformation 173 – virtual 34, 111 constant time HSQC experiment 26, 237 contact shift 260 CORCEMA 69 correlation – experiment, double quantum-filtered 64 – function 6 correlation time 6, 62, 106 – average 292 – cross 256 – effective 7 – global (sM) 10 COSY – 13C-13C 242 – 1D directed 81, 86 – 1D directed COSY-TOCSY 86 – gradient selected 81 – transfer 86, 87 counterion valence 214 coupling – dipolar (see there) – strong 64 – three-bond 203 – vicinal 77 coupling constant 81 – dipolar 5, 8, 29, 31, 207 – long range heteronuclear 64 – passive 83 – proton-proton J 66 – scalar 195 – three-bond dipolar 88 CPCl 25 CPMG pulse sequence 19 CROSREL 130 cross-relaxation, dipole-dipole 102, 206, 211 cryo-probe 294 cutoff distance 119 cyclic glucan 18 b-cyclodextrin 15, 277

d 1D homonuclear selective method 59–90 2D-EXSY 44 3D structure 112 degenerate doublets 240 dermatan sulfate 190, 204, 205

deshielding 190 deuterium lock spectrum 25 DHPC 24 diastereoselectivity 151 diethyl squarate 177 diffusion coefficient 211, 222, 254 – translational 13 digalactosyldiacylglycerol 234, 242 digital resolution 63 diglycosyl lipid 234 diimide reduction 151 dimethyl sulfoxide (DMSO) 43 dimyristoyl phosphatidylcholine 276 dipolar contribution 83 – to T2 19 dipolar coupling – carbohydrate 240 – constant 8, 207 – – D 29 – – heteronuclear 5 – equation 31 – interaction 23 – proton-proton (DHH) 80, 81 – residual 231–243 – – 13C residual 241 – – homonuclear constants 59 – strong 240 dipolar data 238 dipole-dipole interaction 5, 234 disodium uridine diphosphogluconate 254, 261 dispersion range 11 dissaccharide – flexibility 10–12 distance matrices, ensemble average 258 distance profile 50 divalent cation 213 DMPC 24 dodecylphosphatidylcholine 276 dodecylphosphocholine 233 Dolichos biflorus 301 double selection 68 droplet model 117 DXD motif 247 dynamic exchange, different conformations 19 dynamics 3–19 – simulation 163 – – Langevin 16

e ECEP/2 113 electrostatic 219

313

314

Subject Index

FGF (fibroblast growth factor) 220, 221 – human acidic 220 – saccharide complex 220 – tetrasaccharide complex 221 filter, T1p / T2 295 Flavobacterium heparinase 71 flexibility 3 force field 112–114 – Amber 163, 172, 204 – MM2* 171, 204 Forssman pentasaccharide 301 free state 36 fungal infection 146, 147

geometry of glycopeptide (GEGOP) 113 geometry of saccharides (GESA) 113 Gibbs free energy 217 global energy minimum 114 glucan – b-glucan 155 – cyclic 156 glucoamylase 126 a-D-glucopyranose 83 glucosamine 2-sulfamino group 214 glucuronic acid 213 glycocalix 275 glycolipid 146, 231 – 13C-labeled 277 – membrane-anchored 237, 241 – micelle-anchored 276 – mimic 234, 242 – structure 232, 233 glycosaminoglycans 189 glycoside linkage 34, 183 – flexibility 215 glycosidic torsion angle 3, 123, 156 glycosilation 149, 150 glycosphingolipids 276 – cell-surface 278 – Lewis-X 278, 279 – mammalian 231 glycosyl donor – acceptor 247 – glycosyl transferase complex 268 GM1 232 GM3 237, 242 GROMOS 113 guanosine 257

g

h

GAG – sulfated 193 – counterion interaction 213 galactoside-binding protein 47 galectin 47 – galectin-1, bovine heart 303 ganglioside 232 Gaussian pulse 86 Gb3 237 GD1a 233 GDP-Hexose 252 GDP-Man 252, 262 generalized order – degree of order 35 – parameter 7

H NMR spectra, polysaccharides 99 2 H NMR spectroscopy 234 1 H chemical shift, anomeric 99 half-chair form 196 halide exchange 154 hard-sphere exo-anomeric (HSEA) 113 head group 242 helix 212 – twofold 205 heparin 190 – disaccharide 65 – epoxide 212 – fragment 215 – hexasaccharide 204

elipsoid, prolate 208 ELISA 178 elongated shape 208 entropy change 217 epimeric mixture 149 epitope 176 – carbohydrate 176, 181 – immunodominant 181 Escherischia coli b-galactosidase 303 E-selectin 301 Ewald summation 120 – particle-mesh 120 exchange – broadening 18 – rate 43, 44 excitation, partial 62 excitation bandwidth 68 – selective 60 exo-anomeric effect 113, 136, 155, 171, 173 exo-mannosidase 148

f

1

Subject Index – N-desulfated 215 – pentasaccharide 193, 209, 217 – structure 74 – sulfate 190 – tetrasaccharide 204 heptasaccharide, J22 32 hevein 45 hexose 249 HGF (hepatocyte growth factor) 221 homonuclear selective excitation 59 homophilic interaction between carbohydrates 276 homopolymer 155 homotype binding, between oligosaccharides 275 HSQC experiment, constant time 26, 237 human milk oligosaccharide 13 hyaluran dissaccharide 215 hydration shell 257 hydrodynamic – modeling 13, 254–257, 262 – radius 233, 256 hydrogen bond 43, 124, 140, 300 – intramolecular 44 – intramolecular / intermolecular 205 hydrophobic – contact 287 – core / surface 170 hydroxyl groups 11 hydroxyl proton – detection 39–56 – resonance 43

i IdoA, sulfated 192, 198 – residue 200 iduronate ring conformation 2-O-sulfated a-L-iduronic acid IgG-antibody 180 IgM response 179 image convention, minimum immune response, protective immunogen 148, 181 INEPT, double 209 inertia tensor, momement of inositol hexasulfate 220 in-phase multiplet 83 interaction – dipolar coupling 23 – dipole-dipole 5, 234 – GAG-counterion 213 – induced fit–type 221 – intermolecular 119

200 197

122 184

35

– ligand-receptor 206 – metal-polyanion 214 – protein-carbohydrate 194 – steric 160 – sugar / metal 248 – water-mediated 140 – water-water 117 internal motion 207, 208 inter-proton distance 165, 292 – false 292 – fluctuation 208 – time-averaged 167 ionic interactin 217 IRMA 204 isopropyl thiogalactoside 305 isotope – enrichment 241 – synthetic labeling 243 isotropic motion 6 ISPA (isolated spin-pair approximation) 9, 137

j J22 heptasaccharide 32 1 JC-H 201 3 JC-H 201

k Karplus – equation 139 – relation 203, 254 KD-value 47 keratan sulfate 189, 194, 205 keyhole limpet hemocyanin 177

l L-selectride 149 labeling, isotope 254 lamellar phase 25 Langevin dynamics simulation 16 lathanide – chelate 267 – ion 261 lathanide-induced shift (LIS) 260, 267 lectin 39 – binding site 302 – function, table 40 – ligand 303 – mistletoe 47 Lewis-x – oligosaccharide – pentasaccharide 278 – sialyl tetrasaccharide 301

315

316

Subject Index – sialyl memetic 171 – sphingolipids 278, 279, 287 – trisaccharide 15, 279 librational motion 6 ligand-receptor interaction 206 line-broadening – effect, differential 260 – experiment 264 Lipari-Szabo generalized order parameter 31 lipid – aggregate 234 – bilayer 232 – – disk 235 – 13C-labeled 242 liposome 276 liquid crystal 24, 235 – cooperative 235 – medium 25 – NMR 240 LNF-2 pentasaccharide 34 low frequency motion 112

m Maclura pomifera agglutinin 40, 136 maltose 124 – heteroanalogs 126 maltotriose 62–65 a-D-Manp-(1?3)-b-D-Glcp-OMe 10 Manning model 214 mannooligomer 147 mannopyranan 145 – b-mannopyran 155 b-mannopyranoside 147 (1?2)-b-mannopyranotetrose, synthesis 152–155 mannotriose 147 matrix analysis – full 70, 137 – full relaxation 290 – – and conformational exchange 217 matrix approach, full relaxation 130, 258 membrane – assemblies 233 – environment 231 – surface 231 metabolic stability 152 metal ion – affinity, sugar 278 – binding 213, 263 – cation 213 – coordination 214 metal-polyanion interaction 214 methyl b-lactoside 300

methylation analysis 97 Metropolis Monte Carlo calculation 301 25 Mg linewidth 264 micelle 233, 276 microdomain 231, 276 microviscositiy correction factor 257 mimetic, thioglycoside 173–176 MINSY experiment 297 MMC simulation 133 modal-free approach 6 modeling – carbohydrate 112 – hydrodynamic 13, 254–257, 262 – method 111 – pentasaccharide 167 – tetrasaccharide 165–167 – trisaccharide 163–165 molecular dynamic trajectory 49 – UDP-Glc 262 molecular dynamics 255 – analysis 206 – simulation 12, 112, 114, 140, 255 – – carbohydrates 113 – – trajectory 137 molecular volume 256 molecule orientation, average 30 monogalactosyldiacylglycerol 234 monoglycosyl lipid 234 monosaccharide monosaccharide – absolute configuration 97 – analysis 96 – coupling network 100 Monte Carlo sampling 114 motion / motional – anisotropy 212 – averaging 209 – internal 233 – parameter 20 – properties 6 multiplet pattern 63

n narrowing regime, extreme 11 neoglycoconjugate 148, 180 N-linked glycoside 237, 238 NOE (heteronuclear nuclear Overhauser effect) 5, 203–205 – constraints 65 – 1D 294 – DPFGSE 258 – enhancement 127 – experiment 126, 129, 136

Subject Index – factor 5 – 1H-1H experiment 126–129 – heteronuclear 127, 252 – – multi-field heteronuclear 255 – homonuclear 127 – hydroxyl proton 233 – inter-residual 65, 68, 78, 211 – interglycosidic 133, 161, 163, 204 – intermolecular 65, 70 – intraresidue 257 – long range 265 – negative 291 – one- and two-dimensional 130–132 – rotating frame 259 – steady-state 130, 251, 258 – theoretical curve 134, 203 – transferred 65, 217 – water-sensitive 49 NOESY 12, 62 – 1D 73 – 1D DPFGSE 251 – 1D NOESY-TOCSY 73, 76 – data, back-calculation 258 – experiment 131 – HMQC 295 – TR-NOESY 289–306 – WATERGATE 293 non-bonded terms 119 non-ionic force 217 NPT ensemble 118 NVT ensemble 118

o off-rate constant 293 off-resonance approach 258 oligomannoside 181 oligosaccharide – BSA-conjugated 179 – human milk 13 – isolated 159 – Lewis-X 286 – N-linked 137 – NMR spectroscopy 124–126 – – sulfated 189–222 – oversulfated synthetic 196 – protein-bound 290 – sterically crowded 64 – synthesis 148–151 order parameter 239 oscillation, square wells 236 overall motion – isotropic 213 – non-isotropic 207, 209

Overhauser effect – heteronuclear nuclear Overhauser effect (see NOE) – rotating-frame Overhauser effect (see ROE) overlap 78

p

31

P spectra 264, 265 partial excitation 62 PAS (principle axis of symmetry) 237 PBC stimulation 121 pentasaccharide – anisotropic motion 13–15 – Forssman 301 – Lewis-X 278 – modeling 167 Pf1 phage 85 phage media 238 phase – modulation 88 – transition 25 phosphatidylcholine 24 phosphoinositol 146 phospholipid bilayer 24 phospholipomannan 146 phosphomannan 147 photo addition 151 picosecond timescale 210 pivaloyl nitrile 151 platelet factor-4 221 polyclonal sera 179 polyelectrolyte 214 – effect 217 polysaccharide 60 – Brucella polysaccharide B 156 – NMR 96 – – sulfated 189–222 polyvalent contact 275 protection, in vivo 183 protein carrier 177 protein-carbohydrate – complex 217 – interaction 194 proteoglycans 189 proton – anomeric 86 – exchange, rapid 54 pseudo-contact shift 260 pseudorotational wheel 252 pulse – double selective 83 – Gaussian 86

317

318

Subject Index – selctive 86 – sequence, description 59–62 pulsed field gradient 60, 294 – spin-echo 81, 256 pyranose ring, distorsion 305 pyrimidine 257 pyrophosphate 249 – backbone 254

q q-SNEEZE pulse 60

r Ralstonia solanacearum 18 Ramachandran-type analysis 123 refinement method, NMR 33 relaxation 3–19 – carbon longitudinal 207 – cross-correlated 4, 106, 210 – – dipole-dipole 102, 206 – cross 4, 8, 102, 126, 206, 211 – CSA 210 – dipolar 4 – electron-nuclear 260 – – T2 260 – matrix 292 – measurement, multiple field 11 – parameter 206 – proton, homonuclear 8 – rate 5 – spin-lattice 4, 207 – spin-spin 4 – theory 4–10 – vector, orientation 209 relaxation time 260 – effective 81 – 23Na 214 – spin-lattice 211 – – 13C spin-lattice 211 – spin-spin 213 reorientation rate, molecular 212 residual dipolar coupling – bacterial poolysaccharide 23–37 – measurement 25 resonance, isolated 79 restraints – experimental 116 – NMR 112 R-factor 203 methyl-b-D-ribopyranoside 277 ribose 249 – conformer 261 ricin-B 300, 303

rigid fragment 32 ring – geometry 123 – proton, chemical shift 159 – puckering motion 34 Rnase 251 ROE (rotating-frame Overhauser effect) 8 – experiment 129 – intraglycosilic 286 – tilted (T-ROE) 8 ROESY 9, 129 – compensated 285 – off-resonance 9, 15, 16 – T-ROESY 9, 160, 296 rotamer population 139 rotational diffusion tensor 8 rotational motion 6

s 2

S0 form 196, 198, 219 S-lactose 305 S2 value 14 Salmonella polysaccharide 302 samples, strongly aligned 81 Saupe order matrix 30 scatter plot 124 self-aggregation 205 semi-rigid fragment 236 Sfi39 polysaccharide 98, 104 sialic acid 181, 242, 263 signal – anomeric 160 – dispersion 156 silver triflate 151 simulated annealing, restrained (r-SA) 33 simulation protocol 123 – annealing 121 Solomon equation 126 spectral densitiy 5 – model-free 258 – function 208 – – reduced 7 spectroscopy, J-modulated 81 spherical shape 208 sphingolipid, Lewis-X 278, 279, 287 spin diffusion effect 54, 292, 295, 296 – artifact 296 spin-echo, pulsed field gradient 81, 256 spin-pair approximation, isolated (ISPA) 9, 137, 292 spin pattern 76 spin simulation 63

Subject Index spin-spin coupling, heteronuclear 12 spin system – individual 73 – isolation 65 staggered orientation 249 statistical convergence 121 STD experiment 306 Stejskal-Tanner equation 252 steric interaction 160 Stokes-Einstein relation 257 Streptococcus thermophilus Sfi39 polysaccharide 98, 104 structur – analysis, standard 96–105 – calculation method 33 – change, calcium-induced 214 – 3D 112, 203 – reporter group 124 sucrose – octasulfate 201 – 13C-labeled 201 sugar – activated 247–268 – metal ion affinity 278 – nucleotides 247 – – 13C-labeled 254 – – conformational analysis 248–261 SUGARBASE 100 sulfate groups 190 sulfation – degree 204 – pattern 192 sulfonyloxymethyl group, conformational preference 204 sulfoquinovosyldiacylglycerol 234 supercooling 43 supermolecular structure 169 surface, hydrophobic 170 symmetric top 7 – model 209 symmetry, principle axis (PAS) 237 syn orientation 257 synthetic scaffold, self-organizing 276

t T-ROESY 9, 160, 296 sM (global correlation time) 10 T1 data, multi-field 255 t1-coupled 1H-13C HSQC 26 t2-coupled 1H-13C HSQC 26 temperature coefficient 44, 205

tetanus toxoid 177 tetrasaccharide 173–176 – 6, thio-linked 173 – heparin-derived 71 – mixture 79 – modeling 165–167 – thio-tetrasaccharide, conformational analysis 170–172 thermal rearrangement 150 thioglycoside – b-thioglycoside 152 – linkage 152, 171, 173 thioglycosilation 153 thiotetrasaccharide 173 Thomsen-Friedenreich antigen 40 time-averaged – distance 209 – structure 257 time correlation function (TCF) 4 timescale, NMR 112 TIP3P water model 118 TOCSY 62 – 1D 73 – 1D directed COSY-TOCSY 86 – 1D NOESY-TOCSY 73, 76 – 1D TOCSY-TOCSY 75 – transfer 9, 87 torsion angle, glycosidic 3, 123 trajectory – coordinate 123 – MD 137 – molecular dynamic 49 – unstable 122 trans-homophilic binding 287 trehalose 240 trimannoside core 237, 238 trisaccharide 16–19 – glucosyl 16 – Lewis-x 15, 279 – modeling 163–165 – slow dynamics 18, 19 TR-NOESY 289–306 – TR-QUIET 298 two-site model 215 two-spin approximation 128 tyrosine kinase receptor 220

u UDP-Glc 248, 261 – disodium salt 265 – molecular dynamics trajectories 262 – 31P spectra 264, 265 ulopyranoside 147

319

320

Subject Index ulosyl bromide 147 uracil carbonyl group 267

v vaccine – anti-Candida albicans 176–178 – carbohydrate-based 181 – conjugate 147 – polysaccharide 176 – synthetic carbohydrate 176, 181 van der Waals contact 300 vector orientation, internuclear 235 Verlet algorithm 114 verotoxin 1 237 viscosity 11 Viscum album agglutinin 47

w W arrangement 198 water – droplets 117, 118 – model – – rigid / polarizable 116, 117 – – TIP3P 118 – position 117 – water-water interaction 117 WATERGATE 293 weak alignments 83 wobbling in a cone model 6

y yeast 145

z Z-filters 60


Part A Parameters, Techniques and Experiments


1

Relaxation and Dynamics Göran Widmalm

1.1

Introduction

NMR spectroscopy is undoubtedly a technique of the utmost importance in studies on the structure, dynamics and function of many kinds of molecules, including those pertaining to the fields of carbohydrate chemistry and biochemistry. Several approaches to the characterization of glycoconjugates based on spin-spin and dipole-dipole couplings as well as relaxation processes are in use. Although the conformation, flexibility, and dynamics of monosaccharides cannot be disregarded in a proper analysis of any carbohydrate structure [1, 2], the present chapter will focus on the properties of oligosaccharides. In many glycoconjugates, such as glycolipids or glycoproteins, the carbohydrate portion is composed of two to twelve saccharides, a range often quoted in the description of an oligosaccharide. In the realm of polysaccharides, NMR spectroscopy is of equal importance. However, analysis methods may differ since tens or hundreds of repeating units are to be treated (see Chapter 5). One specific concept present in the analysis of polymers is that of “persistent length”. In most cases, this description is not applicable to oligosaccharides, although the analysis of oligomers can illuminate polysaccharide behavior [3]. In the analysis of the three-dimensional structure of an oligosaccharide one may identify the following three descriptors: (i) the conformation, that is, the static structure viewed in a three-dimensional coordinate system; (ii) the flexibility, that is, the extent of three-dimensional excursions in space; (iii) the dynamics, that is, the flexibility in relation to time. For oligosaccharides, the major degrees of freedom that will change the conformation are the glycosidic torsion angles } (H1-C1-OX-CX, where X is the position of substitution) and w (C1-OX-CX-HX). In the case of 6-substitution of a hexopyranoside, the torsion angle x (O5-C5-C6O6) needs to be investigated as well. It should be noted that several ways to define the torsion angles at glycosidic linkages are in use. A schematic representation of an oligosaccharide from a glycoprotein is shown in Fig. 1.1, with several of these torsion angles indicated. This oligosaccharide was studied by carbon-13 multiple field nuclear spin relaxation to investigate its flexibility and dynamics [4] using the techniques described herein.

3

4

1 Relaxation and Dynamics

Schematic of a glycoprotein pentasaccharide. Synthetic material was used for relaxation studies and R represents a linker that could be used for conjugation in the preparation of neoglycoconjugates. Torsion angles }, w, and x are indicated at glycosidic linkages.

Fig. 1.1

A fundamental property in NMR is relaxation, which is particularly useful for studying molecular dynamics processes on a fast time scale. When the net equilibrium magnetization aligned along the static magnetic field is tilted away from the longitudinal z axis into the x, y transverse plane by one or several radio frequency pulses, relaxation processes will restore it back to equilibrium [5]. The spin-lattice relaxation process is given by the relaxation time T1, and it is a measure of how fast the longitudinal magnetization grows back to its original position. The spin-spin relaxation process is denoted by T2 and measures how fast the FID decays in the transverse plane. Several mechanisms are known for these processes such as dipolar or chemical shift anisotropy. In the form of auto-relaxation, the commonly used carbon-13 inversion-recovery T1 experiment is an example. Cross-relaxation is the basis of the well-established 1H,1H NOESY experiment. Cross-correlated relaxation may take place in the form of dipole-dipole [6] or dipole-chemical shift anisotropy [7]. However, in the present chapter, mainly dipolar relaxation will be treated and subsequently relevant molecular systems will be discussed. Examples have been chosen both from our own research group and from systems described in the literature investigated in other laboratories. In addition, the simultaneous use of molecular simulations does augment the understanding of the systems investigated by NMR spectroscopical methods, and therefore some examples of this will also be given. For details on the measurement of relaxation rates for low natural abundance I = 1/2 nuclei, the recent review by Kowalewski and Mäler is recommended [8].

1.2

Theory

The motional properties of a molecule reorienting randomly and isotropically in solution, in which it makes many collisions with other molecules before turning around, thus undergoing Brownian motion, can be described by a time correla^LF, connecttion function (TCF) [9]. The correlation function C(t) of a unit vector l ing two nuclei in the laboratory frame, is described by [10, 11]

1.2 Theory

1 ^LF 0 lLF ti Ct hP2 l 5

1

where P2(x) is the second Legendre polynomial: 1 P2 x 3x2 2

2

1

The Fourier transform of the TCF yields a spectrum of motional frequencies (x). The value of the function, J(x), at each frequency is known as the spectral density [12]: Z1 cos xtCtdt

Jx 2

3

0

and determines relaxation parameters. The relaxation rates R1 and R2 are the inverse of T1 and T2, respectively. The heteronuclear nuclear Overhauser effect (NOE) factor (1 + g) is a measure of the intensity increase of, for instance, a given carbon signal as a result of cross-relaxation between a carbon and protons under 1H-decoupling conditions. For protonbearing carbon-13 nuclei the relaxation is usually dominated by dipole-dipole interactions with their neighboring protons. Assuming that chemical shift anisotropy and cross-correlation effects are negligible, the relaxation parameters for carbons with directly bonded protons can be calculated according to [13]: 1 R1 T1 1 DCH 2 JxH 4

xC 3 JxC 6 JxH xC

1 R2 T2 1 DCH 2 4 J0 JxH 8

4

xC 3 JxC 6 JxH 6 JxH xC 5

c 6 JxH xC JxH xC g H cC JxH xC 3 JxC 6 JxH xC

6

The heteronuclear dipolar coupling constant describes the strength of the dipolar interaction: DCH l0 =4pcC cH hrCH3 , where l0 is the permittivity of free space; rCH is the proton-carbon internuclear distance; cH and cC are the magnetogyric ratios for proton and carbon, respectively; and h is Planck’s constant divided by 2 p. The Larmor frequencies of carbon-13 and proton at the appropriate magnetic field strength are denoted by xC and xH, respectively. A value of 111.7 pm for rCH [14] has been used in our more recent studies [15], and falls within the range of C–H bond distances reported for a series of disaccharides [16]. For carbons with two directly bonded protons, the relaxation rates R1 and R2 can be obtained by multiplying the calculated rates by a factor of two, while the expression for g remains the same.

5

6


A very convenient formalism used to describe motional properties has been developed by Lipari and Szabo [10, 11] and is known as the “model-free” approach. For a molecule such as a protein or an oligosaccharide, the simplest case is that where the overall rotational motion can be described by a single correlation time, that is, isotropic motion (Fig. 1.2). Librational motion of a non-rigidly attached 13 1 C, H vector can be described by the wobbling in a cone model [17]. In the following, we assume that the overall and internal motions are independent. The total correlation function can be factored as [10] Ct CO tCI t

7

The correlation function for the overall motion is 1 CO t e 5

8

t=sM

where sM is the correlation time for the molecule (Fig. 1.3). The correlation function for the internal motion is

Isotropic reorientation of a spherical molecule with a global correlation time described by sM. A diffusive process as a wobbling in a cone can model additional internal motions. Fig. 1.2

Fig. 1.3 Auto-correlation function C(t) of an isotropically reorienting C–H bond vector. A: sM = 0.5 ns; B: sM = 5.0 ns.

1.2 Theory

^ti CI t hP2 ^ l0 l

9

^ now describes the orientation in a reference frame that is where the unit vector l rigidly attached to the molecule. The spatial restriction of motion can be described by a generalized order parameter, S [10, 18]. The long time limit of the correlation function for internal motions is equal to the square of the generalized order parameter: ^ti l0 l S2 lim hP2 ^

10

t!1

An effective correlation time se can also be defined as: se 1

S2

Z1 CI t

S2 dt

11

0

Thus, se is proportional to the area under the correlation function. Subsequently, a total correlation function can be described by: 1 Ct S2 e 5 with s

1

t=sM

1 1 5

S2 e

t=s

sM1 se 1

12 13

The reduced spectral density function accounting for the dynamic information [19] then becomes Jx

2 2 S sM 1 S2 s 5 1 x2 s2M 1 x2 s2

14

If the first term in Eq. (14) is much larger than the second, that is, in the limit when the internal motions are infinitely fast (se?0) and/or the internal motions have a limited amplitude (S2?1), the equation may be truncated to obtain [20] 2 2 S sM Jx 5 1 x2 s2M

15

The spectral density J(x) is clearly a function of the correlation time sM for the molecule (Fig. 1.4). It can be described as the power available for relaxation from fluctuations of local fields at the relevant transition frequency. An equivalent approach to the formalism by Lipari and Szabo is the “two-step” model developed by Halle and Wennerström [21]. When the tumbling is anisotropic, that is, when the principal rotational diffusion tensors Dx, Dy and Dz are non-equal, Eq. (14) may not be adequate. For a symmetric top, we instead have [22]

7

8

1 Relaxation and Dynamics Spectral density functions J(x) calculated from Eq. (15) with S2 = 1; A: sM = 0.5 ns; B: sM = 5.0 ns. Fig. 1.4

! X 2 sk 1 S2 s 2 S Jx Ak 5 1 x2 s2 1 x2 s2k k1;2;3

16

where A1 = (1.5 cos2 h–0.5)2, A2 = 3 sin2 h cos2 h, A3 = 0.75 sin4 h, s1 = (6D^)–1, s2 = (5D^+D||)–1, s2 = (2D^+4D||)–1. The angle between the C–H bond vector and the symmetry axis is denoted by h, and D||, and D^, are the elements of the rotational diffusion tensors parallel and perpendicular to this axis, respectively. Advantages with this method are twofold. Firstly, the degree of anisotropy in the rotational diffusion tensor can be investigated by inclusion of the vector orientations in a predefined molecular axes frame, and, secondly, the interpretation of the generalized order parameters and internal correlation times is unchanged. For molecules in solution, the homonuclear proton relaxation is dominated by the dipolar interactions between protons that are close in space. The strength of these interactions is dependent on the dipolar coupling constant of the protons, –3 , and consequently the distance between them. The cross-reDHH = (l0/4 p)c2HhrHH laxation rate, r, can be expressed as combinations of spectral density functions taken at zero frequency, the proton Larmor frequency and twice the proton Larmor frequency [23]. The 1H,1H NOE [24] is measured in the laboratory frame and the cross-relaxation rate is given by 1 rNOE DHH 2 6 J2x 4

J0

17

The rotating-frame Overhauser effect (ROE) has its cross-relaxation rate given by [25] 1 rROE DHH 2 2 J0 3 Jx 4

18

Using the spin-lock conditions devised by Hwang and Shaka [26–28], the transverse ROE (T–ROE) cross relaxation rate, rT–ROE, can be calculated as the mean of rNOE and rROE and is described by:

1.2 Theory

rT

ROE

1 DHH 2 6 J2x 3 Jx J0 8

19

Although the value of rT–ROE will be smaller than that of rROE, the T–ROESY pulse sequence [29] has the advantage that it efficiently suppresses signals arising from TOCSY (Hartmann-Hahn) transfer, a problem frequently encountered with the ordinary ROESY pulse sequence. If a reference proton-proton pair with a known distance can be found in the molecule, the isolated spin-pair approximation (ISPA) makes it possible to extract unknown distances between protons i and j by comparing cross-relaxation rates according to [30, 31] rij rref rref =rij 1=6

20

The interproton distances may also be calculated using the combinations of spectral density functions, for example in the form of the model-free approach by Lipari and Szabo. For the homonuclear case, the internal motions include the angular as well as the radial part of the dipolar interaction. If the dynamics determined from heteronuclear relaxation data also describe the dynamics of the homonuclear interactions, then we are in a position to calculate proton-proton distances. This has been shown to be the case in our studies of di- and trisaccharides [15, 32, 33]. In addition, it was concluded from molecular dynamics simulations that the angular and radial parts contributing to the generalized order parameter are separable to a good approximation [34]. A recent investigation of these effects for a disaccharide showed that differences for generalized order parameters calculated in different ways were negligible [35]. Some time ago, a novel approach was introduced based on off-resonance ROESY experiments for the study of dynamic processes [36–41]. It is based on the ROESY pulse sequence. However, with respect to the initial hard pulse, the spin-lock period with a field strength of *10 kHz is frequency shifted. The offset of the irradiation leads to an average effective field at an angle h with the static magnetic field axis: h arctan x1 =D

21

where x1 is the amplitude of the radio frequency (RF) field and D is the distance between the RF field carrier and the central frequency of the spectrum. Typically, several experiments are carried out in the interval 108 < h < 558, since any contribution from TOCSY transfer can be neglected when h < 608. As in the above Overhauser experiments, build-up curves are generated by a series of mixing times. Subsequently, the data sets containing the off-resonance ROE cross-relaxation rates, rOR–ROE, can be least-square-fitted to obtain rNOE and rROE according to rOR

ROE

rNOE cos2 h rROE sin2 h

22

The cross-relaxation rates between protons i and j can then be used to obtain correlation times per pair of protons (scp), as well as their interproton distances (rij),

9

10


when a specific model has been chosen for the behavior of the spectral density function. The off-resonance ROESY approach thus attempts to take internal dynamics into account prior to solving the molecular structure. From the heteronuclear relaxation parameters described above, the dynamic information is limited to relatively rapid motions on the picosecond to nanosecond time scales. The global correlation time sM acts as a filter [42] and makes it hard to obtain dynamic information on longer time scales. In contrast to the fast time scales, motions on the microsecond to millisecond time scales are described as the intermediate time regime. Under these conditions, chemical exchange processes are fast on the chemical shift time scale, and single, population averaged, resonance lines are observed [43, 44]. However, these intermediate motional processes will influence the observed T2 values. If the dipolar contribution to the 13C spin-spin relaxation (Tdip 2 ) can be obtained by independent experiments [45], one may obtain the chemical exchange contribution Dex from Dex

1 T2obs

1 dip

T2

23

where Tobs 2 is the measured spin-spin relaxation time. There is also a quadratic dependence on the chemical shift separation (Xex) in radians of the different chemical species, given by Dex

1 X2ex 8 kex

24

where kex is the chemical exchange rate constant. These processes can also be investigated by T1q experiments or T2-CPMG experiments, where the delay between the p pulses is changed [44]. When the exchange process is even slower (milliseconds to seconds), one may observe separate resonance lines in the NMR spectrum, each corresponding to the interconverting chemical species or conformations [46]. The dynamics of these processes are thus described as slow on the NMR time scales.

1.3

Oligosaccharide Flexibility and Dynamics 1.3.1

Flexibility of a Disaccharide

To investigate the degree of flexibility in saccharides, a relatively simple model system was chosen. The disaccharide a-d-Manp-(1 ? 3)-b-d-Glcp-OMe (1) shown in Fig. 1.5 had previously been analyzed by a grid search and energy minimization. This protocol produced a potential energy Ramachandran map and identified the conformational region of the global energy minimum [47].

1.3 Oligosaccharide Flexibility and Dynamics Schematic of disaccharide 1, a-d-Manp(1?3)-b-d-Glcp-OMe.

Fig. 1.5

To utilize information that can be extracted from carbon-13 relaxation experiments for a small molecule such as disaccharide 1, the overall tumbling of the molecule has to be slow enough. Under these slow motion conditions, the relaxation parameters become dependent on the magnetic field strength; that is, the molecule enters the dispersion range. For a rapidly reorienting small molecule, only an “effective” correlation time can be determined, as the molecule is in the extreme narrowing regime. To obtain conditions for relaxation measurements in the dispersion range, at the static magnetic field strengths available, we have utilized a solvent mixture consisting of D2O : DMSO-d6 in a molar ratio 7 : 3. The viscosity of such a mixture is more that twice as high as that of water [48]. In addition, a substantially lowered freezing point results, and for a 3:1 molar ratio of H2O : DMSO it is –62 8C [49]. By performing multiple field relaxation measurements of several relaxation parameters (T1, T2, 1 + g), it is possible to obtain dynamic descriptors (S2, sM, se) by least-square-fitting of Eqs. (4–6) and (14) or (15). It can also be useful to perform experiments at several temperatures to elucidate the temperature dependence of the dynamic parameters. In these cases, we usually fit the experimental data separately at each temperature. In the study of 1 [32], measurements were performed at four temperatures in the range 268–323 K. The resulting global correlation times sM were 2.2 ns at the lowest temperature and 0.2 ns at the highest. The extent of flexibility, as described by S2, was in the range 0.81–0.75. In studies of four disaccharides in DMSO-d6 at 303 K, similar values of S2 were also obtained [16]. It should be noted that the magnitude of S2 is dependent on the choice of the C–H bond distance used to describe the heteronuclear dipolar coupling constant. The issue was addressed in the latter study. Interestingly, for the four disaccharides studied, the global correlation time was found to correlate well with the number of hydroxyl groups in the disaccharides, being shorter when fewer hydrogen bond donors were present. Later, it was shown by MD simulations of 1 in DMSO that a well-ordered solvent shell of DMSO molecules is present around the solute. Indeed, hydrogen bonding occurs from hydroxyl groups to the acceptor oxygen atom in DMSO [50]. In the study of 1 we were not able to fit the experimental NMR data with sufficient precision to also obtain se for internal motions. In the light of our later studies on 1 [51], this is not surprising. Calculation of the long time limit of the correlation function describing internal motions, such as C-H vectors in a molecule fixed frame, facilitates the identification of S2 as the plateau value [Eq. (10)]. As shown in Fig. 1.6, some differences between C-H vectors are present, but an S2 value of *0.8, as found experimentally, is a reasonable description of the short

11

12

1 Relaxation and Dynamics Reorientational correlation functions calculated for different C-H vectors in a molecule fixed frame of 1. From [51] © American Chemical Society. Reproduced with permission.

Fig. 1.6

time dynamics with a very short se. In other MD simulations of 1, both in water and in the solvent mixture, S2 was even higher [35]. One-dimensional 1H,1H NOESY experiments were carried out on 1 [32], from which cross-relaxation rates, rNOE, for both intra- and inter-residue proton-proton interactions were obtained. These rNOE values were used together with the dynamics determined from the heteronuclear relaxation measurements [Eqs. (15) and (17)]. The quite well-defined intra-residue distance obtained between H1 and H2 in the mannosyl group was in good agreement with that from molecular modeling. Subsequently, the trans-glycosidic distance from H1 in the mannosyl group to H3 in the glucosyl residue was calculated and found to be *2.47 Å. That it should indeed be possible to use the intra-ring dynamics for the trans-glycosidic proton pair was supported by the fact that the ratios of the intra- and inter-glycosidic cross-relaxation rates at two magnetic field strengths attained roughly the same values at different temperatures. At this point, molecular simulations facilitated interpretation of the experimentally obtained NMR data. MD simulations [35, 51] revealed the presence of a major conformational state or region. However, the trans-glycosidic H1m-H3g averaged [52] distance was too short, *2.3 Å, and together with heteronuclear spinspin couplings 3JC,H over the glycosidic linkage, it could be concluded that one or two additional conformational states should be populated to some extent. Transitions to these regions, for example the “non-exo” conformation of the } torsion angle [53], should then take place on a slower time scale than that of the global reorientation of the molecule, sM. The conformational flexibility of 1 in the major state is depicted in Fig. 1.7 as an overlay of conformations populated in the MD trajectory. The analysis of disaccharide 1 clearly shows that different flexibility must be present and that the combination of NMR spectroscopy data and molecular simulations lead to an understanding of the dynamics.

1.3 Oligosaccharide Flexibility and Dynamics Overlay plot of 1 from MD simulations enabling the vizualization of S2&0.8 (cf. Fig. 1.6). From [51] © American Chemical Society. Reproduced with permission. Fig. 1.7

1.3.2

Anisotropic Motion of a Pentasaccharide

Human milk oligosaccharides can act as soluble receptors and thereby prevent infections. Oligosaccharide 2 (Fig. 1.8) was investigated by relaxation experiments at several magnetic field strengths, ranging from 7.0 to 14.1 T [22]. In addition to the relaxation parameters obtained for 1, the spin-spin T2 relaxation time was also obtained. This is of additional and particular interest, since this relaxation time contains a contribution from J(0), and this parameter depends on the correlation time(s) of the molecule only [Eq. (5)]. Clearly, the molecular shape of 2 is anisotropic, and thus the pentasaccharide was modeled as a symmetric top (Fig. 1.9). The least-squares fitting of the relaxation data showed an improvement compared to the isotropic fitting also performed. In addition, information was obtained on the degree of anisotropic motion. The anisotropy of the moment-of-inertia tensor showed Ixx : Iyy : Izz *4 : 4 : 1. However, the NMR relaxation data revealed D||/D^ * 1.5 : 1. It is well known from hydrodynamic modeling that “addition of a water shell” is required to obtain agreement between modeling methods and experiment. Thus, a shell of about one water molecule per hydrogen bonding group (Fig. 1.10), for example a hydroxyl group, gave good agreement between modeling and NMR experiment for 2 when analyzed for anisotropic motion and its translational diffusion coefficient, experimentally determined as Dt = 1.8 · 10–6 cm s–1 in D2O solution at 303 K.

Fig. 1.8 Schematic of pentasaccharide 2, a-L-Fucp-(1?2)-b-d-Galp-(1?3)b-d-GlcpNAc-(1?3)-b-d-Galp-(1?4)-d-Glcp.

13

14

1 Relaxation and Dynamics Schematic of the axially symmetric model used to fit 2 to carbon-13 relaxation data. Depicted are the approximate angles of the reducing sugar residue‘s anomeric bond vectors to the unique molecular axis. From [22] © American Chemical Society. Reproduced with permission. Fig. 1.9

The S2 values of different sugar residues showed the highest order at the terminal fucosyl residue a with S2 = 0.75 and decreased toward the reducing end as b: S2 = 0.72; c: S2 = 0.72; d: S2 = 0.60; e(H3): S2 = 0.43. For the reducing sugar residue e in particular, different C-H vectors showed significantly altered S2 values, with

Fig. 1.10 A heavy atom space-filling model of 2 showing orthogonal views with bound waters. From [22] © American Chemical Society. Reproduced with permission.

1.3 Oligosaccharide Flexibility and Dynamics 2

e(H1): S = 0.68 being dependent on the orientation relative to the principal axis of the moment-of-inertia tensor, which was approximated to be equal to the diffusion tensor of the molecule. These results could be interpreted as a quite flexible reducing end where large amplitude motions take place within a single conformational well. Thus, it is important to investigate possible anisotropy in order to make sure that dynamics are interpreted correctly. 1.3.3

Oligosaccharide Dynamics from Off-Resonance ROESY

Two molecules exemplify a homonuclear approach based on off-resonance ROESY experiments. b-Cyclodextrin (3, Fig. 1.11) has a topology that imposes restraints on the trans-glycosidic distances. 1H,1H-Cross-relaxation rates were obtained for 3 as a function of the off-resonance angle h [38]. The different rOR–ROE values were obtained from the initial slopes of the experimental data points up to a mixing time of 200 ms. Subsequently, least-squares fitting of the data at different angles, Eq. (22), resulted in rNOE and rROE. Typical functions from off-resonance data are shown in Fig. 1.12 depicting intraand inter-residue interactions from H1'-H2' and H1'-H4, respectively. Assuming a Lorentzian-type spectral density function, proton-proton distances and correlation times for each pair were obtained, in good agreement with a model generated from a crystal structure. It should be noted, however, that small differences in the correlation times for the proton pairs were observed. The Lewis-x trisaccharide analog 4 (Fig. 1.13) has a methylene group bridging two sugar residues. Proton-proton distances and correlation times were obtained from off-resonance ROESY experiments, and as many as 30 interproton distances could be deduced [41]. The deviation around the average correlation time per pro-

Fig. 1.11 Schematic of heptasaccharide 3, b-cyclodextrin.

15

16


Fig. 1.12 Dipolar cross-relaxation rates, rOR–ROE, in 3 as a function of the off-resonance angle h. A: the trans-glycosidic H1'-H4 pair; B: the intra-residue H1'-H2' pair.

Fig. 1.13 Schematic of the Lewis-x trisaccharide analog 4, in which a methylene group acts as a bridge at the (1?3)-linkage.

ton pair (scp = 0.32 ns) was small, and a simulated annealing procedure generated a structure close to that of the O-glycosidic analog. In particular, the flexibility of 4 seemed to be highly reduced, indicating a relatively rigid pseudo-trisaccharide. 1.3.4

Rigid versus Flexible: a Trisaccharide Case

Trisaccharide 5 (Fig. 1.14) was originally synthesized as one in a series of glucosyl trisaccharides having the same substitution pattern but different anomeric configurations [54]. The accessible conformational space was investigated by Ramachandran potential energy maps, which showed a slightly reduced conformational freedom compared to their constituent disaccharides. However, 5 differed clearly from the other trisaccharides in that a conspicuously limited flexibility was present, based on a restricted conformational space of sugar residues at one of the glycosidic linkages. At a later stage, 50 ns Langevin dynamics simulations, in which solvent is modeled by frictional and random forces, were performed on 5 [55]. Interestingly, an anti-} conformer was found to be significantly populated at the (1 ? 2)-linkage, revealing a highly flexible molecular system. The presence of such an anti-}2 confor-

1.3 Oligosaccharide Flexibility and Dynamics Fig. 1.14 Schematic of the glucosyl trisaccharide 5, bd-Glcp-(1?2)-b-d-Glcp-(1?3)-a-d-Glcp-OMe. The torsion angles at the b-(1?2)-linkage are denoted by }2 and w2.

mer was supported by 2D T-ROESY experiments in DMSO-d6 where, inter alia, an Overhauser effect was observed between H2'' in the terminal sugar residue and H2' in the middle glucosyl residue. The presence of an anti-} conformer was an important finding per se. However, as in the case where a conformer with an antiw torsion was identified, [56] DMSO-d6 as a solvent may alter the relative population of the anti-conformer compared to D2O to such an extent that it becomes identifiable by the Overhauser experimental techniques used. In addition, quantification of the anti-conformers was not performed at this point. To further deepen the insight into its conformational flexibility, 5 was also analyzed in water solution, both by different NMR experiments and by MD simulations [15]. 13C NMR relaxation experiments were performed at two magnetic field strengths. Subsequent least-squares fitting as described above revealed a quite rigid trisaccharide with S2 & 0.9. Thus, from this analysis the flexibility of 5 is limited to the sub-nanosecond time scale, since sM&0.45 ns, at the experimental conditions employed. The presence of the anti-}2 conformer (Fig. 1.15) in water was supported by 1D T-ROESY experiments [29], and so was a small occurrence of an anti-w conformer at the same (1 ? 2)-linkage. In conjunction with extensive MD simulations in water (83 ns), the relative populations at the (1 ? 2)-linkage were: syn 91%; anti-}2 7%; anti-w2 2%. Thus, a highly flexible description of 5 is also relevant and necessary. The dynamics of these processes should then take place on the intermediate NMR time scale, nanosecond to microsecond, since no indication of slow exchange processes on the chemical shift time scale could be identified directly

Fig. 1.15 Anti-}2 conformer of 5 from MD simulation with key protons annotated.

17

18


from NMR spectra. Subsequently, in discussing flexibility of a molecular system, one should also take into account the dynamics and the different time scales of various molecular processes. 1.3.5

Slow Dynamics of a Tridecasaccharide

The cyclic glucan of Ralstonia solanacearum is special in that all but one residue is b-(1 ? 2)-linked [57]. The single a-(1 ? 6)-linkage of tridecasaccharide 6 (Fig. 1.16) leads to NMR spectra in which all individual anomeric proton resonances could be identified. Initial off-resonance ROESY experiments on 6 revealed a mean sCP of 0.9 ns. However, line broadening of one anomeric proton resonance indicated that additional dynamics could be present. A first indication of slow dynamics came from a constant-time 1H,13C HSQC experiment. Whereas all H1-C1 correlations were of similar intensity, those from the aglyconic H2-C2 vectors differed substantially among themselves. Also, contributions to T2 relaxation from anisotropic motion or chemical shift anisotropy could safely be ruled out. A further indication of chemical exchange effects on line broadening came from temperature studies. The contribution to exchange broadening should decrease at higher temperatures, since the chemical exchange rate should increase. This hypothesis was supported by the recording of constanttime 1H,13C HSQC spectra from 20 to 60 8C which showed a significant differ-

Fig. 1.16 Schematic of the cyclic tridecaglucan 6. Note the following structural features: residue a is a-linked; residue f is 6-substituted; residue b is diametrically opposed to the a and f residues.

1.5 Acknowledgements

ence in intensity for H2-C2 resonances at glycosidic linkages. The corresponding resonance in the 6-substituted sugar residue f could be used as a reference point as it hardly changed intensity upon temperature alteration. A quantitative estimate of chemical exchange contributions came from the identification of deviations from a purely dipolar contribution to T2, which was measured with a delay d = 500 ls in the CPMG pulse sequence. Based on the parameters scp = 0.9 ns (see above) and S2 = 0.85 at 14.1 T, one finds Tdip 2 = 190 ms. However, except for the a and f residues, T2 values of C2 resonances were < 70 ms. For some residues Dex were >50 Hz. The presence of exchange processes was further supported by measurement of T2 at a lower magnetic field, 7.1 T. The quadratic dependence of the chemical shift separation for a chemical exchange contribution, Eq. (24), could be substantiated, since doubling of the magnetic field strength led to an increase of Dex by a factor of 4. Additional analyses of T2 were performed by decreasing the d delay down to 10 ls in the CPMG pulse sequence. However, such short delays are hampered by experimental difficulties such as increased power dissipation delivered by the train of pulses. Further detailed analysis corroborated the exchange phenomena observed above and revealed that 6 should be in dynamic exchange between different conformations on the microsecond time scale. Structurally, it is noteworthy that the main exchange takes place around residue b, where both the C1 and C2 resonances show important exchange contributions. For the remaining sugar residues involved in substantial exchange, that is all but a and f, the contributions arise at the C2 resonances. Thus, the most important exchange contribution should take place at the w-torsion angles of 6.

1.4

Concluding Remarks

NMR relaxation measurements on oligo- and polysaccharides have during the last decade been used as an important tool in unraveling dynamic information [58– 73]. The description of processes on different time scales will be an integral part in future studies of biomolecular systems such as carbohydrates. A specific strength of NMR spectroscopy in these studies is the ability to generate spatially resolved dynamics for different regions of a molecule. This may turn out to be of particular importance if one tries to address issues on functional dynamics.

1.5

Acknowledgements

The work described herein from the author‘s laboratory was supported by grants from the Swedish Research Council. Dr. L. Mäler is thanked for valuable comments on the manuscript.

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20


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G. Lippens, J.-M. Wieruszkski, D. Horvath, P. Talaga, J.-P. Bohin, J. Am. Chem. Soc. 1998, 120, 170–177. M. Kadkhodaei, H. Wu, D. Brant, Biopolymers 1991, 31, 1581–1592. A. Ejchart, J. Dabrowski, Magn. Reson. Chem. 1992, 30, S115–S124. A. Imberty, S. Perez, M. Hricovíni, R. N. Shah, J. P. Carver, Int. J. Biol. Macromol. 1993, 15, 17–23. J. Kowalewski, G. Widmalm, J. Phys. Chem. 1994, 98, 28–34. L. Mäler, J. Lang, G. Widmalm, J. Kowalewski, Magn. Reson. Chem. 1995, 33, 541–548. J.-R. Brisson, S. Uhrinova, R. J. Woods, M. van der Zwan, H. C. Jarell, L. C. Paoletti, D. L. Kasper, H. J. Jennings, Biochemistry 1997, 36, 3278–3292. A. Poveda, J. L. Asensio, M. MartínPastor, J. Jiménez-Barbero, Carbohydr. Res. 1997, 300, 3–10. L. Catoire, C. Derouet, A.-M. Redon, R. Goldberg, C. Hervé du Penhoat, Carbohydr. Res. 1997, 300, 19–29. A. Poveda, M. Santamaría, M. Bernabé, A. Rivera, J. Corzo, J. Jiménez-Barbero, Carbohydr. Res. 1997, 304, 219–228. L. Catoire, I. Braccini, N. BouchemalChibani, L. Jullien, C. Hervé du Penhoat, S. Perez, Glycoconjugate J. 1997, 14, 935–943. A. Kjellberg, T. Rundlöf, J. Kowalewski, G. Widmalm, J. Phys. Chem. B 1998, 102, 10113–1020. A. Poveda, M. Martín-Pastor, M. Bernabe, J. A. Leal, J. Jiménez-Barbero, Glycoconjugate J. 1998, 15, 309–321. M. Martin-Pastor, C. A. Bush, Biopolymers 2000, 54, 235–248. R. B. Best, G. E. Jackson, K. J. Naidoo, J. Phys. Chem. B 2001, 105, 4742–4751. A. Almond, J. Brunkenborg, T. Franch, C. H. Gotfredsen, J. Ø. Duus, J. Am. Chem. Soc. 2001, 123, 4792–4802. M. K. Cowman, J. Feder-Davis, D. M. Hittner, Macromolecules 2001, 34, 110– 115.

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2

Residual Dipolar Couplings in Bacterial Polysaccharides Manuel Martin-Pastor and C. Allen Bush

2.1

Introduction

Carbohydrates serve as recognition molecules in numerous biological processes [1]. Knowledge of the three-dimensional structure and dynamic properties of the carbohydrate moieties involved in a recognition process, both free in solution and in the bound state with the receptor, are essential for understanding a biological process which depends on protein-carbohydrate interaction. Most previous NMR investigations of the conformation of oligosaccharides in solution are based on the observation of 1H-1H NOE through its dependence on the inter-proton distance [2]. While NOE in combination with computer molecular modeling has proven reasonably effective for some relatively rigid oligosaccharides [3–6], its shortcomings for the interpretation with more flexible oligosaccharides combined with the typically limited number of measurable NOEs in most carbohydrates have stimulated the search for other NMR structural restraints to complement NOE data such as scalar coupling methods and the residual dipolar couplings considered in this chapter. Two structural parameters affect the strength of the dipolar coupling interaction between two nuclei. One is the distance r3 separating the two nuclei in the molecule and the other is the angle h which defines the direction of the vector joining the two interacting magnetic dipoles with respect to the magnetic field of the NMR, as depicted in Eq. (1) and Fig. 2.1. Dipolar coupling interaction / 3 cos2 h

1=r 3

1

The dipolar interaction is typically observed in solid state NMR where the fixed angle h of the interacting nuclei with respect to the magnetic field results in the observation of dipolar coupling at maximum strength. In solution NMR the molecular motions result in a random and isotropic variation in time of the orientation h of the dipole with respect to the magnetic field. In this situation the term 3 cos2 h–1 averages to zero, and no static contribution to the dipolar coupling interaction remains. Only the distance dependence can be indirectly observed by measuring NOE, which depends on fluctuations in the dipolar coupling interaction.

23

24

2 Residual Dipolar Couplings in Bacterial Polysaccharides Dipolar coupled 13C-1H spin pair in a carbohydrate. The bond length is assumed fixed and the primary variable is the angle, h, between the magnetic field B0 and the internuclear vector. Fig. 2.1

An intermediate situation between that of solids and liquids can be achieved in solution by using certain mixtures that form liquid crystals, which can be oriented in the magnetic field. Such an anisotropic medium imposes a preferred orientation to the molecule under study so that the dipolar interaction does not average to zero. Most previous investigations in this area reported methods that rely on dipolar couplings measured for glycolipids oriented as a result of the hydrophobic attachment to a magnetically oriented liquid crystal [7]. Recently, it has been shown that orientation of molecules can be conveniently achieved in phospholipid bilayers known as bicelles [8] when the molecule under study is not anchored but is oriented by hydrodynamic interactions with the bicelles [9]. The degree of orientation achieved by these weak hydrodynamic interactions [10] is small, typically of the order of 1 molecule in 1000 being oriented. A scaled or reduced dipolar interaction occurs resulting in measurable dipolar couplings [9, 11] and dipolar shifts [12, 13], while the spectrum retains high resolution and the spectral simplicity of the regular isotropic phase (Fig. 2.2). Using this technique, several groups have reported residual dipolar couplings in oligosaccharides [14–16], which can provide valuable long range structural information such as the relative orientation of the pyranose sugar residues in an oligosaccharide and the intra-residue sugar puckering.

2.2

Preparation of the Oriented Samples

Several different liquid crystal orienting media have appeared in the literature for the measurement of residual dipolar couplings with carbohydrates and other biomolecules. Several authors have proposed the use of media such as mixtures of lipids [17–21], membrane fragments [22], rod-shaped viruses [23, 24], and cellulose crystallites [25]. The binary mixture of long- and short-chain phosphatidylcholines forms a welloriented discotic nematic phase over a reasonably wide range of temperature, concentration, pH, and phospholipid composition [17], which has been well characterized by NMR studies [8, 26]. Mixtures of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and 1,2-dihexanoyl-sn-glycero-3-phosphocholine (DHPC) form mod-

2.3 NMR Experiments for the Measurement of Dipolar Couplings

erately viscous, optically clear, solutions that orient spontaneously in strong magnetic fields [8, 17, 26] and have been used to orient carbohydrates [14–16]. The ratio DMPC/DHPC 3:1 is necessary to achieve a convenient bicelle diameter. The total lipid concentration affects the degree of alignment obtained and hence the magnitude of the residual dipolar couplings to be measured. This concentration can be adjusted in the range 5–40% (w/w) and the temperature can be used to modulate a phase transition [8, 17, 26], so that the system remains isotropic at *20 8C, while at *35 8C the liquid crystal is formed and oriented in the NMR magnetic field (Fig. 2.2). A system of 1,2-di-O-tridecanyl-sn-glycero-3-phosphocholine and 1,2-di-O-hexyl-sn-glycero-3-phosphocholine behaves quite similarly to the phospholipid system with the advantage of the chemical stability of the ether linkage [27]. Since carbohydrates themselves are generally quite stable, the instability to hydrolysis of the acyl linkage of the phospholipids can be the limiting factor in the useful lifetime of a sample. Another useful liquid crystal solution is formed by the cetylpyridinium chloride (CPCl)/hexanol 1:1 and brine (0.2 M NaCl) system [20, 28, 29]. This system forms a positively charged lamellar phase, which has been used to orient carbohydrates [30, 31]. The range of concentrations of CPCl/hexanol in the sample is 3–15% (w/ w). Since the liquid crystal is stable over a wider range of temperatures, a second sample of the carbohydrate in an isotropic solution is required to measure dipolar couplings. Before diluting the carbohydrate in a liquid crystal medium, it is advisable to consider the chemical properties of both the liquid crystal and the carbohydrate under study to assure their compatibility. Some factors to consider are the presence of charged groups, which could disrupt the liquid crystal, the pH, the salt concentration, and the solubility. Once the carbohydrate is mixed with any of these media, the formation of the liquid crystal in the NMR magnet can be easily monitored in the deuterium lock spectrum. A splitting in the deuterium lock signal is typically observed which depends on the degree of orientation achieved depending linearly on the concentration of the liquid crystal in the sample.

2.3

NMR Experiments for the Measurement of Dipolar Couplings

In general, the NMR experiments proposed for the measurement of scalar coupling constants in solution can be applied for the measurement of residual dipolar couplings. In these sequences, the through space residual dipolar coupling D interaction evolves simultaneously with the corresponding J scalar coupling pathway, so that the sum of the two interactions, D+J, is obtained in the liquid crystal oriented sample. The determination of the dipolar coupling, D, can be accomplished by subtracting the scalar coupling J in a similar experiment in a non-oriented medium for which D is zero. Among the residual dipolar couplings that can be measured in carbohydrates, many authors have focused their attention on the one bond carbon-proton, 1DCH,

25

26

2 Residual Dipolar Couplings in Bacterial Polysaccharides

Schema of an oligosaccharide in a discotic liquid crystal bicelle solution used for the measurement of residual dipolar couplings. At 35 8C the liquid crystal is formed

Fig. 2.2

and the carbohydrate tumbles rapidly but anisotropically in large aqueous inter-bicelle spaces.

and the long range inter-proton, nDHH, because of the favorable magnitude of the dipolar couplings and the sensitivity of the experiments. One bond 1DCH and 1JCH can be measured for CH and CH3 groups in carbohydrates by using a t1-coupled 1 H-13C HSQC, i.e. a regular HSQC experiment in which the proton 180 8 refocusing pulse in the middle of t1 evolution is removed [32] (Fig. 2.3 a and Fig. 2.4), or by using a t2-coupled 1H-13C HSQC experiment in which the carbon decoupling during acquisition is removed. Higher accuracy in the determination of the one bond 1DCH and 1JCH can be achieved by using a constant time, coupled enhanced HSQC experiment [33], (Fig. 2.3 b) or by quantitatively fitting the intensities of a series of constant time 1JCH modulated HSQC experiments [15, 34, 35]. Multiple bond nDHH and nJHH can be determined using a homonuclear CTCOSY experiment. In this experiment, the magnitude of nDHH is determined quantitatively by the trigonometric dependence of the intensities in a series of experiments with different constant time delays [33, 36]. For complex carbohydrates for which 13C chemical shift resolution is critical to avoid overlap, a heteronuclear 1 H-13C, 1H-1H TOCSY experiment [37] can be applied (Fig. 2.5). This experiment provides E. COSY type signals resolved in the 1H and 13C dimensions from which

2.3 NMR Experiments for the Measurement of Dipolar Couplings

Fig. 2.3 Pulse schemes for the measurement of 1DCH and 1JCH. Narrow and wide pulses correspond to 90 8 and 1808 pulses, respectively; t delays correspond to 1/(4·1JCH). (A) t1coupled HSQC with gradients for z filters [32]. The phase cycling is giving by }1 {y, y, y, y, –y, –y, –y, –y}, }2 {x, –x}, }3 {x, x, –x, –x} and }acq

{x, –x, –x, x, –x , x, x, –x}. In the absence of the 1808 1H pulse outlined in dashes, coupling appears during t1. (B) Constant time, coupled enhanced HSQC [33]. The phase cycling is given by }1 {y, –y}, }2 {x, x, –x, –x}, }3 {x, x, x, x, y, y, y, y}, and }acq {x, –x, –x, x, –x , x, x, –x}.

the splitting in the proton dimension can be used to determine the sign and magnitude of nDHH (Fig. 2.6) [31]. The structural determination usually requires the sign of the dipolar coupling to be known; otherwise both possibilities positive and negative should be considered, causing additional indeterminacy in the structure. Some methods such as fitting data acquired by experiments such as the CT-COSY do not explicitly give the sign of the coupling. Other possibilities for the measurement of residual dipolar couplings are the long range heteronuclear nDCH, which can be measured using E. COSY type experiments [33, 37, 38] or quantitatively obtained by fitting the intensities of a series of J modulated HMBC experiments [39]. A SPITZE-HSQC sequence has been proposed for the simultaneous measurement of 1DCH and nDHH in CH2 (methylene) groups [40]. This experiment could find application for the study of the conformation and stereospecific assignment of the C-6 hydroxymethyl group in carbohydrates. The

27

28


a)

Fig. 2.4 t1-Coupled HSQC experiment for the measurement of 1DCH in pentasaccharide LNF-3 [16] using DMPC/DHPC bicelles, (a) at

b)

19 8C isotropic solution and (b) at 35 8C oriented sample.

2.4 Structure Determination using Residual Dipolar Coupling

Fig. 2.5 1H-13C, 1H-1H TOCSY experiment for the measurement of nDHH and nJHH [37]. (a) Pulse scheme. Narrow and wide pulses correspond to 908 and 1808 pulses, respectively, D delays correspond to 1/(4·1JCH). The phase

cycling is given by }1 {x, –x}, }3 {y, y, –y, –y}, }acq {x, –x, –x, x}. Pulse marked with an asterisk (*) has its phase incremented by TPPI. (b) E. COSY type patterns generated with this sequence.

measurement of the 1DCH in methyl groups of sugars such as fucose or rhamnose provides information about the orientation of the C5–C6 bond [41].

2.4

Structure Determination using Residual Dipolar Coupling 2.4.1

Theory

In a molecule or molecular fragment of fixed shape (Fig. 2.1), the dipolar coupling between a pair of spin 1=2 ; nuclei N and M, can be expressed by Eq. (2) [13], Dn;m

cn cm h 3 cos2 h 2 3 2p hrn;m i 2

1

2

where cn and cm are the magnetogyric ratios of N and M, h is Planck’s constant, rn,m is the distance between N and M, and h is the angle between the internuclear vector and the external magnetic field. The angle brackets denote a time average over the molecular motions with times scales that are short compared to the reciprocal of the dipolar splitting. For a molecule in a liquid crystal solution these motions are the fast internal motions and the anisotropic overall motion imposed by the liquid crystal. A simple approach to include the motional average in Eq. (2) is to consider the average molecule or fragment orientation with respect to the magnetic field. For a

29

30


Fig. 2.6 1H-13C 1H-1H TOCSY experiments for the measurement of nDHH in the heptasaccharide from S. mitis J22 [31]. (a) D2O isotropic solution, (b) CPCl/hexanol/brine 3% ori-

ented sample. Proton/carbon correlations type Hx/Cx-1, Hx/Cx-2, Hx/Cx+1 and Hx/Cx+2 are indicated with the superscript –, –, + and ++, respectively.

molecule with coordinates defined in an arbitrary cartesian system, the average molecule orientation can be described by the elements of a 3 ´ 3 Saupe order matrix A (Eq. 3). [13, 42] Ai;j

3 cos hi cos hj 2

dij

3

i; j x; y; z; dij 1 for i j; dij 0 for i 6 j In Eq. (3), hi is the instantaneous orientation of the ith molecular axis with respect to the magnetic field, dij is the Kronecker delta, and the brackets denote time or ensemble average. The order matrix A is real, symmetric (Aij = Aji) and traceless (Axx+Ayy+Azz = 0), so it has only five independent elements. By diagonalizing this matrix the eigenvectors and eigenvalues correspond to the three axes,


the magnitude and the rhombicity of the molecular alignment tensor. The coordinate frame in which the order matrix is diagonal is often referred to as the principal averaging frame or the principal order frame. The transformation matrix that accomplishes this diagonalization relates the initial arbitrary molecular frame with the oriented principal order frame. For a pair of spin 1=2 nuclei, N and M, separated by a distance rMN, the DMN dipolar coupling is related to the average orientation of the whole molecule or fragment by DM;N

Sl0 cM cN h X Ai;j cos yMN cos yMN i j 3 i i;jfx;y;zg 8p3 hrM;N

4

S is the Lipari-Szabo generalized order parameter, which scales DMN for the effect of fast internal motions, [43] m0 is the magnetic permeability of vacuum, cM and cN are the magnetogyric ratios of nuclei N and M, rMN is the internuclear disis the angle between the M-N internuctance, h is the Planck’s constant and }MN i lear vector and the ith molecular axis (Fig. 2.7). Equations for dipolar couplings can also be expressed using a different formalism in cylindrical coordinates [9]. In the principal order frame one may write DM;N h; y S

l0 cm cN h Aa 3 cos2 hMN 4p

3 3 1 Ar sin2 hMN cos2 2yMN =4p2 rMN 2 5

where Aa and Ar are the axial and rhombic magnitude components of the alignment tensor and the angles hMN and }MN are the fixed polar angles of the inter-

Definition of angles with respect to the principal order frame for a CH group. }x, }y, }z: angles of an internuclear vector with respect to the arbitrary molecular frame. hx, hy, hz: angles defining the instantaneous orientation of the magnetic field (B0) with respect to the arbitrary molecular axis. Fig. 2.7

31

32


nuclear vector M-N within the oriented principal order frame. These two formalisms are equivalent and it is possible to convert from one formalism to the other [44]. 2.4.2

Rigid Structure Calculations

Residual dipolar couplings can be interpreted for a rigid fragment in the molecule for which five or more dipolar couplings with independent directions can be measured. All the atoms in such a rigid fragment can be oriented to achieve a common principal order frame or in other words a common alignment tensor. In carbohydrates, pyranose sugar rings in the regular chair conformation can be assumed to be rigid. If the flexibility along one or more glycosidic linkages is moderate, an extended rigid fragment involving two or more sugar rings could be considered in the calculation. The multivalued orientations of Eqs. (4) and (5) allows

Views of the best conformer found in the r-SA calculations and the alignment tensor obtained during r-SA: (a) fragment formed by residues a-b-g-c of J22 heptasac-

Fig. 2.8

charide, (b) fragment formed by residues e–f, (c) superimposition of several relevant structures of J22 heptasaccharide [31].


determination within a degeneracy of two, the orientation of any rigid fragment in a molecule with respect to the magnetic field from five independent (i.e. vectors are not parallel) dipolar coupling measurements [11]. Once the structure and alignment tensor of the individual rigid fragments considered for a carbohydrate are known, in absence of flexibility, the complete structure of the carbohydrate can be obtained by superimposing the three axes of the alignment tensor of each fragment into a common reference frame. Because the interactions measured are insensitive to inversion of the director, there will, in general, be four possible orientations of the two fragments. Additional constraints imposed by the covalent structure or obtained from other NMR structural data such as NOE and scalar couplings generally resolve this degeneracy problem so that only a single reasonable orientation is found. Different structure calculation methods have been developed using the residual dipolar couplings for other types of molecules such as proteins. While a detailed analysis of the structure using the dipolar couplings requires that both the magnitude and axis of the orientation tensor be known, in the absence of structural information only the magnitudes of the alignment tensor are required to derive information about the shape of the molecule [45]. For the case of a protein, for which a large number of 15N-1H dipolar coupling vectors pointing in different directions can be readily measured, the two magnitudes Aa and Ar in Eq. (5) can be estimated from the minimum and maximum values of the dipolar couplings, which correspond to vectors lying along the c (h = 90, h = 0) and z (h = 0) axes in Eq. (5), respectively [45]. Given a structural model, it is possible to predict theoretically the alignment tensor based on the shape of the molecule and the steric interactions with certain liquid crystals [10]. The calculation of the alignment tensor can also be made for a given structure using a best fit approach of the experimental residual dipolar couplings. For this purpose, a singular value decomposition method has been developed to fit the dipolar data using the order matrix formalism of Eq. (4) [13], and a Powell optimization algorithm can be used to fit the data to Eq. (5) [27, 46, 47]. These methods are useful for testing the quality of a proposed conformational model, such as an X-ray crystallographic structure of a protein. For small oligosaccharides, a relaxed energy }/w grid-search approach can be used to generate a series of trial conformations. For each conformation in the map, an optimum alignment tensor is calculated in order to reproduce the experimental residual dipolar couplings. Only those conformers that can satisfy the experimental dipolar couplings within the experimental error (Fig. 2.9) are finally selected [16]. NMR refinement methods such as restrained simulated annealing (r-SA) have been adapted to include the residual dipolar couplings as structural restraints [48, 49]. In the method proposed, these restraints are introduced as orientational penalty functions in the force field. The three axes of the orientation tensor are represented by a floating tetra-atomic molecule in the same coordinate frame of the molecule under study. The orientation of this tetra-atomic molecule is optimized during the r-SA refinement of an initial model to reproduce the corresponding ex-

33

34


Interresidue NOE distance contours for 2.5 and 3.0 Å and conformations in best agreement with 10 1DCH residual dipolar couplings (crosses) measured for residues c–d of pentasaccharide LNF-2 [47]. The intersection Fig. 2.9

of these areas defines the glycosidic dihedral angles with high accuracy. Regular molecular mechanics force fields may be applied to distinguish whether this conformation is an energy minimum or a virtual conformation.

perimental residual dipolar couplings. This r-SA method has been applied to some oligosaccharides (Fig. 2.8) [15, 31, 50]. 2.4.3

Structure Calculations in the Presence of Flexibility

High amplitude flexibility (>30 8) in some glycosidic linkages and ring puckering motions in certain furanose rings introduces an extra difficulty for the interpretation of the residual dipolar couplings. In an oligosaccharide with flexible linkages, we cannot expect to calculate an orientation tensor for any single model, and the calculated values of dipolar coupling generally give a poor fit to experimental data. In such a situation the superposition of the alignment tensors of the individual fragments would result in a virtual conformation [33, 51]. An essential step for the interpretation of residual dipolar couplings is first to detect those regions in the carbohydrate with high amplitude flexibility. There may be indications of flexibility from internal inconsistencies in the NOE and scalar coupling data, and a number of these data could be required for the characterization of all conformers involved and their respective populations [52]. Recently, a


method has been proposed to detect flexible regions directly from the residual dipolar coupling data [33, 51]. In this method, the orientation tensors for domains known to be rigid are calculated, and a single parameter m, called the generalized degree of order (GDO), is defined as a single quantity that describes molecular order of a rigid fragment in the molecule. It is calculated from the terms of the Saupe order matrix elements of Eq. (3) and represents a single parameter, Eq. (6), to define the overall motion of the fragment [51]. s 2X 2 A m 3 i;j ij

6

For rigidly connected fragments, GDO values are identical. However, in the presence of internal motions between fragments, m will be attenuated by an amount that depends on the amplitude of motion. For oligosaccharides, the individual pyranoside rings are excellent candidates for rigid fragments if a sufficient number of independent dipolar coupling values can be measured [33]. Different protocols can be used for the structure calculations in flexible carbohydrates using the dipolar coupling data. In cases in which there are not enough NMR restraints to characterize all the conformations and populations present in the equilibrium, some authors have relied on the ability of force fields and molecular modeling tools, such as solvated molecular dynamics and Monte Carlo methods, to generate realistic ensembles of structures, which are tested for agreement with the residual dipolar couplings and other NMR data [53]. These protocols generally require some assumptions be made to allow calculation of the order tensor for each conformer directly from the molecular model, e.g., from the moment of inertia tensor. The r-SA method previously described for the refinement of individual rigid fragments in a carbohydrate can be easily extended to consider a structure composed of a number of rigid fragments connected by flexible regions. A tetra-atomic axis molecule to describe the alignment tensor can be defined independently for each rigid fragment. During the r-SA protocol every tetra-atomic axis molecule is oriented to satisfy the dipolar couplings of its fragment, while the flexible regions (Fig. 2.8) are modeled by the force field and the favorable or unfavorable interactions among the fragments [31]. An order matrix analysis can also be applied to determine conformations and populations from residual dipolar couplings in flexible carbohydrates [33]. This method can be used to calculate independently an orientation tensor for each single sugar unit of the carbohydrate and determine the range of possible solutions of each. With this information, flexible models based on transitions between two or more conformers can be proposed [33, 54].

35

36


2.4.4

Structure Calculations in the Bound State

In analogy with TRNOE experiments, the residual dipolar couplings can also be used to determine the bound structure of a small ligand such as an oligosaccharide, which is in fast exchange with a larger receptor like a protein [50]. Under fast exchange conditions, the measurable dipolar couplings of the ligand in a liquid crystal solution with the receptor correspond to a weighted average of the couplings in the free and bound states given by Eq. (7). average

DM;N

vbound Dbound M;N 1

free

vbound DM;N

7

In this equation, vbound represents the molar fraction of bound ligand. Since the magnitude of alignment of the ligand-receptor complex is larger than that of the free ligand, the dipolar couplings in the complex will be substantially larger than in the free ligand and any known symmetry properties of the protein can be used to simplify calculation of the orientation tensor. Providing the affinity constant, Kd, of the ligand for the receptor and the concentrations of ligand and receptors are known, the fraction of ligand bound, vbound can be determined, and hence the 100% ligand-bound dipolar couplings, Dbound M,N can be used for the structural determination [50]. The use of 13C-enriched carbohydrate ligand facilitates this type of experiment.

2.5

Conclusions

A number of liquid crystal media can be conveniently mixed with oligosaccharide samples to provide weak orientation suitable for measurement of residual dipolar coupling. Being much more polar than proteins, carbohydrates exhibit less hydrophobic interaction with most liquid crystal media, alleviating a problem which often occurs in protein applications. The residual dipolar coupling data can provide valuable NMR structural and dynamic restraints for the conformational study of oligosaccharides in both the free and bound state. Compared to NOE and scalar coupling measurements, residual dipolar coupling experiments are relatively easy. The former experiments yield small effects which may be difficult to measure and interpret, and the most useful scalar coupling experiments generally require isotope enrichment [55, 56]. By contrast, many more dipolar coupling values can be readily measured even in natural abundance samples: the effects are larger and the fundamentals of the interpretation are straightforward even though some of the details are not yet firmly established. The structural interpretation of the residual dipolar couplings requires at least five dipolar vectors pointing in different directions to orient a rigid fragment in the molecule. For rigid oligosaccharide epitopes such as blood groups, this can be easily done with one-bond C-H data. For oligosaccharides whose rigidity is more

2.6 References

open to question, additional residual dipolar couplings may be required, and several types are accessible in oligosaccharides, such as the long range nDCH and the long range proton-proton nDHH. An interesting possibility is to study an oligosaccharide in different liquid crystal media in which the oligosaccharide may orient differently, providing additional non-redundant residual dipolar couplings [31, 33]. The main structural information that can be obtained from residual dipolar couplings in oligosaccharides concerns the orientation of inter-atomic vectors in the molecule. Unlike NOE and scalar coupling data, which give information on very local features of the structure, residual dipolar coupling data are sensitive to the relative orientations of vectors in the molecular frame: the structural regions to be oriented may be distant. On the other hand, since several dipolar vectors can be measured for the same sugar ring, dipolar couplings can also provide local information on the intra-residue sugar puckering [57]. The existence of flexibility in oligosaccharides is readily detected by attempts to fit residual dipolar coupling data to a single model. For a flexible oligosaccharide, the agreement with experiment of data calculated for any model is generally poor [31]. With availability of sufficient data, the GDO method of Prestegard and coworkers [33, 51] provides a more quantitative measure of flexibility. Although there is no generally accepted method for calculation of statistical weights of multiple conformers in flexible oligosaccharides, it should be possible with an adequate number of residual dipolar coupling data to achieve this goal.

2.6

References 1 2

3 4 5 6

7 8 9 10

R. A. Dwek, Chem. Rev. 1996, 96, 683–720. D. Neuhaus, M. P. Williamson, The Nuclear Overhauser Effect in Structural and Conformational Analysis, VCH Publishers, New York, USA, 1989. H. van Halbeek, Curr. Opin. Struct. Biol. 1994, 4, 697–709. S. W. Homans, Glycobiology 1993, 3, 551– 555. T. P. Peters, B. M. Pinto, Curr. Opin. Struct. Biol. 1996, 6, 710–720. C. A. Bush, M. Martin-Pastor, A. Imberty, Annu. Rev. Biophys. Struct. Biol. 1999, 28, 269–293. Y. Aubin, J. H. Prestegard, Biochemistry 1993, 32, 3422-3428. R. R. Vold, R. S. Prosser, J. Magn. Reson. Ser. B 1996, 113, 267–271. N. Tjandra, A. Bax, Science 1997, 278, 1111–1114. M. Zweckstetter, A. Bax, J. Am. Chem. Soc. 2000, 122, 3791–3792.

11 12

13

14 15 16 17 18

19

J. H. Prestegard, Nature Struct. Biol. NMR supp. 1998, 517–522. G. Cornilescu, J. L. Marquardt, M. Ottiger, A. Bax. J. Am. Chem. Soc. 1998, 120, 6836–6837. J. A. Losonczi, M. Andrec, M. W. F. Fischer, J. H. Prestegard, J. Magn. Reson. 1999, 138, 334–342. P. J. Bolon, J. H. Prestegard, J. Am. Chem. Soc. 1998, 120, 9366–9367. G. R. Kiddle, S. W. Homans, FEBS. Lett. 1998, 436, 128–130. M. Martin-Pastor, C. A. Bush, Biochemistry 2000, 39, 4674–4683. C. R. Sanders II, J. P. Schwonek, Biochemistry 1992, 31, 8898–8905. H. Wang, M. Eberstadt, E. T. Olejniczak, R. P. Meadows, S. W. Fesik, J. Biomol. NMR 1998, 12, 443–446. J. A. Losonczi, J. H. Prestegard, J. Biomol. NMR 1998, 12, 447–451.

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21

22

23

24

25

26 27

28

29

30

31 32 33

34 35 36 37

R. S. Prosser, J.A. Losonczi, I.V. Shiyanovskaya, J. Am. Chem. Soc. 1998, 120, 11010–11011. S. Cavagnero, H. J. Dyson, P. E. Wright, J. Biomol. NMR 1999, 13, 387– 391. B. W. Koenig, J.-S., Hu, M., Ottiger, S., Bose, R.W., Hendler, A. Bax, J. Am. Chem. Soc. 1999, 121, 1385–1386. G. M. Clore, M. R. Starich, A. M. Gronenborn, J. Am. Chem. Soc. 1998, 120, 10571–10572. H. M. Al-Hashimi, H. Valafar, M. Terrel, E. R. Zartler, M. K. Eidsness, J. H. Prestegard, J. Magn. Reson. 2000, 143, 402–406. K. Fleming, D. Gray, S. Prasannan, S. Matthews J. Am. Chem. Soc. 2000, 122, 5224–5225. M. Ottiger, A. Bax, J. Biomol. NMR 1998, 12, 361–372. H. F. Azurmendi, M. Martin-Pastor, C.A. Bush, Biopolymers 2001, (submitted). G. Porte, R. Gomati, O. El Haitamy, J. Appell, J. Marignan, J. Phys. Chem. 1986, 90, 5746–5751. G. Gomati, J. Appell, P. Bassereau, J. Marignan, G. Porte, J. Phys. Chem. 1987, 91, 6203–6210. T. Rundlöf, C. Landersjö, K. Lycknert, A. Malinak, A. G. Widmalm, Magn. Reson. Chem. 1998, 36, 773–776. M. Martin-Pastor, C. A. Bush, J. Biomol. NMR 2001, 19, 125–139. B. K. John, J. Magn. Reson. Ser. A 1992, 101, 113. F. M. Tian, H. M. Al-Hashimi, J. L. Craighead, J. H. Prestegard, J. Am. Chem. Soc. 2001, 123, 485–492. J. Santoro, C. G. King, J. Magn. Reson. 1992, 97, 202–207. N. Tjandra, A. Bax, J. Magn. Reson., 1997, 124, 512–515. F. Tian, P. Bolon, J. H. Prestegard, J. Am. Chem. Soc. 1999, 121, 7712-7713. W. Willker, D. Leibfritz, J. Magn. Reson. 1992, 99, 421–425.

38 39 40 41 42 43 44

45

46 47 48

49

50

51

52 53

54 55 56 57

M. Sorensen, A. Meissner, O. Sorensen, J. Biomol. NMR 1997, 10, 181–186. W. Willker, D. Leibfritz, Magn. Reson. Chem. 1995, 33, 632–638. T. Carlomagno, W. Peti, C. Griesinger, J. Biomol. NMR 2000, 17, 99–109. M. Ottiger, A. Bax, J. Am. Chem. Soc. 1999, 121, 4690–4695. A. Saupe, Angew. Chem. Int. Ed. Engl. 1968, 7, 97–112. G. Lipari, A. Szabo, J. Am. Chem. Soc. 1982, 104, 4546–4558. M. W. F. Fischer, J. A. Losonczi, J. L. Weaver, J. H. Prestegard, Biochemistry 1999, 38, 9013–9022. G. M. Clore, A. M. Gronenborn, A. Szabo, N. Tjandra, J. Am. Chem. Soc. 1998, 120, 4889–4890. N. Tjandra, S. Grzesiek, A. Bax, J. Am. Chem. Soc. 1996, 118, 6264–6272. M. Martin-Pastor, C. A. Bush, Carbohydr. Res. 2000, 323, 147–155. N. Tjandra, D. S. Garret, A. M. Gronenborn, A. Bax, G. M. Clore, Nature Struct. Biol. 1997, 4, 443–449. G. M. Clore, A. M. Gronenborn, N. Tjandra, J. Magn. Reson. 1998, 131, 159– 162. H. Shimizu, A. Donohue-Rolfe, S. W. Homans, J. Am. Chem. Soc. 1999, 121, 5815–5816. J. R. Tolman, M. Al-Hashimi, L. E. Kay, J. H. Prestegard, J. Am. Chem. Soc. 2001, 123, 1416–1424. A. Gorler, N. B. Ulyanov, T. L. James, J. Biomol. NMR 2000, 16, 147–164. C. Landersjö, C. Höög, A. Maliniak, G. Widmalm, J. Phys. Chem. B 2000, 104, 5618–5624. E. Sayers, J. H. Prestegard, Biophys. J. 2000, 79, 3313–3329. Q. Xu, C.A. Bush, Carbohydr. Res. 1998, 306, 334–339. M. Martin-Pastor, C.A. Bush, Biopolymers 2000, 54, 235–248. D. I. Freedberg, J. Am. Chem. Soc. 2002, 124, 2358–2362.


3

Detection of Hydroxyl Protons Hans-Christian Siebert, Martin Frank, Claus-Wilhelm von der Lieth, Jesus Jiménez-Barbero, and Hans-Joachim Gabius

3.1

Introduction

Looking at the branched antennae of glycan chains of glycoproteins or uniquely sulfated sections of glycosaminoglycans, it is easy to see that such structures could have merit as hardware for information storage. In fact, theoretical calculations on this property prove that the capacity of carbohydrates for isomer formation by far surpasses that of oligomers of nucleotides or amino acids – a strong argument for the concept of the sugar code [1, 2]. Since carbohydrates are “ideal for generating compact units with explicit informational properties”, their presentation on carriers can “impart a discrete recognitional role on the protein or lipid” [3]. To read and process such signals and to initiate cellular responses, decoding devices with specificity to distinct glycan determinants are required. Indeed, research over the last three decades has taught us the lesson that the supply of diverse signals is matched by the expression of more than five families of endogenous lectins to read them [4–8]. Although suggestive, evidence for coexistence does not necessarily prove a concerted action with functional implications. In addition to remarkable progress in the characterization of lectin structure, great strides have also been made in discerning aspects of lectin activity. As compiled in Table 3.1, the range of lectin functions clearly demonstrates the reality of protein-carbohydrate interactions. Bearing in mind that viral, bacterial and protozoan lectins are famed for their capacity to home in on host cells in the first step of an infection, the opportunity for drug design with lectins as targets becomes evident [9]. In general, several sugar compounds have already gained attention in clinical applications or as potential candidates (Table 3.2). The data presented in this table also support the proposition that the concept of drug design in glycosciences offers, in principle, promising medical benefits. The success of respective projects will definitely hinge on the extent of accessible information about structural details of the interplay between the receptor under study and its ligands. In this respect, NMR spectroscopy is appreciated to deliver salient information about intimate details of the interaction in solution [10, 11]. Remarkably, such experiments can even uncover differences between the ligand conformations of complexes in crystalline form and those in solution. A recently published study on the

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3 Detection of Hydroxyl Protons Tab. 3.1 Functions of animal lectins. For detailed information, please see Refs. [4–9]

Activity

Example of lectin

Ligand-selective molecular chaperones in endoplasmic reticulum

Calnexin, calreticulin

Intracellular routing of glycoproteins and vesicles

ERGIC-53, VIP-36, P-type lectins, comitin

Intracellular transport and extracellular assembly

Non-integrin 67 kDa elastin/lamininbinding protein

Cell type-specific endocytosis

Hepatic asialoglycoprotein receptor, macrophage C-type lectins, hepatic endothelial cell receptor for GalNAc4-SO4-bearing glycoproteins

Recognition of foreign glycans (b1,3-glucans, LPS)

CR3 (CD11b/CD18), Limulus coagulation factors C and G

Recognition of foreign or aberrant glycosignatures on cells (incl. endocytosis or initiation of opsonization or complement activation)

Collectins, C-type macrophage receptors, pentraxins (CRP, limulin), l-ficolin, tachylectins

Targeting of enzymatic activity in multimodular proteins

Acrosin, Limulus coagulation factor C

Bridging of molecules

Homodimeric and tandem-repeat galectins, cytokines (e.g. IL-2:IL-2R and CD3 of TCR), cerebellar soluble lectin

Effector release (H2O2, cytokines etc.)

Galectins, selectins, CD23

Cell growth control and apoptosis

Galectins, C-type lectins, amphoterinlike protein, cerebellar soluble lectin Selectins, I-type lectins, galectins

Cell routing Cell-cell interactions

Selectins and other C-type lectins, galectins, I-type lectins

Cell-matrix interactions

Galectins, heparin- and hyaluronic acid-binding lectins

Matrix network assembly

Proteoglycan core proteins (C-type CRD), galectins, non-integrin 67 kDa elastin/ laminin-binding protein

binding of the Thomsen-Friedenreich antigen to a plant lectin (Maclura pomifera agglutinin) describes how water-mediated hydrogen bonds in the crystal artificially stabilize the galactose unit in a low-energy conformation at interglycosidic angles }/w = 398/–88, whereas the NMR data point to ligand selection from two conformational families characterized by the following average angle sets: 458/–658 and –658/–188 [12]. Beyond the general interest in describing solution parameters as

3.1 Introduction Tab. 3.2 Examples of sugar compounds as pharmaceuticals

Disease

Target

Compound

Diabetes mellitus

b-Glucosidases (amylases)

Acarbose

Blood coagulation

Antithrombin III

Heparin/heparinoids

Viral infection

a-Glucosidases (N-glycan processing)

N-butyldeoxynojirimycin

Viral infection

Neuraminidase

Derivatives or mimetics of 2-deoxy-2,3-dehydro-Nacetylneuraminic acid

Bacterial infection

Adhesins and toxins (lectins)

Derivatives or mimetics of milk oligosaccharides

Protozoan infection (e.g. African sleeping sickness)

GPI-mannosyltransferase I

GlcN-(2-O-hexadecyl) phosphatidylinositol

Congenital disorder of glycosylation Ib

Phosphomannose isomerasedeficiency

d-Man

Glycosphingolipid storage disorders

Glycosphingolipid synthesis

N-butyldeoxygalactonojirimycin

Inflammatory reaction

Selectins

Derivatives or mimetics of sialylated/sulfated Lea/xepitopes

thoroughly as possible, such an example shows how welcome are experimental data on the bound state of a ligand in solution. In general, the precision in the definition of the conformation of a bound carbohydrate (or any other type of ligand) depends on the number of distance constraints. For peptides and proteins, nuclear Overhauser effect (NOE) contacts and also J-coupling constants are rather frequent [13, 14]. Their number is conspicuously lower for saccharides. As shown in Fig. 3.1, recruiting only protons of C–H bonds for the delineation the sugar’s topology will not completely eliminate ambiguities. It is also undoubtedly desirable to enlist protons from hydroxyl groups for the task of optimizing the description of the bound ligand’s conformation. Since their covalent linkage to exocyclic oxygen atoms gives them higher flexibility than protons directly attached to a C-atom within the hexapyranose ring, they can access a larger volume segment in which NOE contacts could be made. Also, the dispersion of chemical shifts is likely to be more favorable than for ring proton spectra, e.g. for d-glucose and related sugars. Mastering the problem of collecting those signals will mean that “new information can be gained, and this may necessitate a revision of conformation(s) based on a smaller number of interactions between C-linked protons alone” [15]. Several approaches based on NMR spectrosco-

41

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3 Detection of Hydroxyl Protons

Illustration of the potential for a substantial gain of information on carbohydrate conformation provided by including new NOE contacts involving water-exchangeable protons. The upper panel shows that up to two NOE contacts can be expected between C-H protons of the reducing end sugar unit and the C-H proton of the anomeric C-atom of the non-reducing end unit of a disaccharide in

Fig. 3.1

water (Gala1-3Galb-1). This information can be insufficient to define the dihedral angles }, w of the glycosidic linkage precisely, depicted by blurring of the second hexopyranose ring. Detection of new water-sensitive contacts (in our case a third contact, bottom panel) by measurements in an aprotic solvent considerably improves the definition of the position of the second ring (see also Figs. 3.4 and 3.8).

py have proved their value in obtaining information about these elusive protons of carbohydrates in solution. They resolve the problems of fast chemical exchange and short relaxation times encountered in water.

3.2 Hydroxyl Groups of Free Carbohydrates

3.2

Hydroxyl Groups of Free Carbohydrates

The classical approach is to eliminate the problem of exchange between hydroxyl protons of the ligand and the bulk solvent by using aprotic solvents. With dimethyl sulfoxide (DMSO) as a suitable solvent for carbohydrates, hydroxyl proton resonances were recorded as sharp peaks as described in the pioneer work by Casu [16]. As well as oligosaccharides, glycolipids can be readily dissolved in DMSO, where they do not form the large micelles characteristic of the behavior of gangliosides in water. As experimentally documented, insights into the glycan’s structure and flexibility are rendered possible, which justify the solvent selection by demonstrating rather similar conformational behavior in the two environments [17–24]. When water is added to the aprotic solvent, the concern to give up the advantage of absence of exchangeable protons can immediately be allayed. The proton exchange will be slowed by (a) drastic decreases in temperature made possible by dramatic lowering of the freezing point (e.g. a 1:3 DMSO/water mixture reaches its freezing point at –628C) and (b) suppression of the water signal by adequate pulse sequences such as 1-1-echo-type sequences, watergate, or the NOHOSS technique [20, 25–32]. Absence of traces of ionic contamination acting as a catalytic agent of proton exchange and adjustment to a neutral pH value are further adjustable parameters to minimize the exchange rate [33]. When aqueous solutions are subjected to supercooling, experiments can even be performed without adding an aprotic solvent [34]. Otherwise, addition of a small percentage of acetone or methanol (10–15%) may permit lowering the temperature to around – 10 to –15 8C without freezing, depending on the concentration of the sugar in the NMR tube. From an NMR technical point of view, different parameters of hydroxyl groups provide conformational information on the carbohydrate in solution in almost pure water [35]: · · · · ·

chemical shifts vicinal 3JH,OH coupling constants temperature coefficients rate of exchange with water NOEs for hydroxyl protons.

Obviously, the first step in any NMR analysis involves the assignment of hydroxyl proton resonances, which can be done on the basis of scalar connectivities to the aliphatic C–H protons by using COSY/TOCSY/NOESY experiments. On the basis of chemical shifts alone, it is difficult to assess the neighborhood of a given OH proton. In principle, it is generally accepted that protons involved in hydrogen bonds are deshielded compared to those that are not. However, tiny variations in O–H · · · O distances, lone pair dispositions and even local conformational mobility may profoundly affect chemical shifts. Regarding coupling constants, H–O groups that show conformational averaging usually have vicinal 3JH,OH couplings of 5.5 ± 1.5 Hz. Values greater than 8 Hz indicate the preference of a trans orienta-

43

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tion, while coupling constants less than that suggest the presence of a major synarrangement. The presence of preferred syn or anti orientations can suggest the existence of intramolecular (intra- or inter-residue) hydrogen bonding, which has to be confirmed by other experimental parameters. In particular, temperature coefficients (Dd/DT) can be correlated with protection from exchange with solvent. For instance, Dd/DT around 10 ppb/deg indicates accessibility to the water molecules of the solvent, while values smaller than 5 ppb/ deg intimate that the respective hydroxyl groups are strongly protected from exchange with the solvent. It is noteworthy that these temperature coefficients are relatively close to those reported for sugars dissolved in DMSO, ca. 3 ppb/deg. At this point, it should not be overlooked that the range of temperature for which the temperature coefficient can be measured is rather small (ca. 25 8C) unless a substantial amount of aprotic solvent is added or the sample is subjected to supercooled conditions. A key parameter indicating the presence of an intramolecular hydrogen bond is probably the exchange rate. However, accurate measurement of this parameter poses an experimental problem difficult to solve, since these rates are extremely sensitive to pH and to catalysis by impurities (even in very small amounts). Nevertheless, important differences in chemical exchange rates have been reported for different O–H groups in different compounds (from 1 to 60 s–1), which reveal that this parameter can be useful to infer the presence of hydrogen bonding. From the experimental viewpoint, any type of 2D-EXSY experiment with a water suppression scheme can be used to measure these rates. Short mixing periods should be used to avoid the existence of water-relayed cross peaks. Regarding NOEs, an alternative approach with advantages is to combine NOESY/ROESY data to distinguish between chemical exchange and dipole-dipole relaxation. In ROESY, the interactions due to both processes have a different sign, while in NOESY experiments, at low temperature, both processes give rise to cross-peaks with the same sign as the diagonal peaks. At any rate, care should be exercised in ROESY experiments, since relayed peaks (ROE + exchange, or vice versa) cannot be distinguished from direct ROEs. Also, exchange-type cross-peaks can be indicative of spatial proximity and also of hydrogen-bond interaction. As stated above, for long mixing periods, cross-peaks can appear that are mediated by water molecules. In any case, the NOEs may help in an important manner to define the 3D structure of the glycostructure in water solution, although, in principle, assistance from molecular mechanics and dynamics calculations should be sought to exclude or at least reduce ambiguities in order to ensure reliability of the experimental data. In overview, these experimental protocols have substantial merit in reaching the aim schematically depicted in Fig. 3.1. Whether they might direct the exploration of conformations of carbohydrates (or any other hydroxyl/amino-group-presenting ligands) both in the free state and, more importantly, when bound to biologically active receptors has been the subject of lively discussion. Building on this experience, a successful route for the delineation of bound-state geometry of hydroxyl groups by combination of selective water excitation with 13C-filtering using a 13C-

3.3 Hydroxyl Groups of Bound Carbohydrates

labeled ligand has been described [36]. Intrigued by the elegance of the concept for working with aprotic solvents and confident that the stability of receptors – at least in several instances – might enable recording of signals from receptor-ligand complexes, we have recently developed an integrated technique to show when this is feasible [37]. Combined with custom-made modeling programs and biochemical activity assays as described [37], this protocol could well find applications beyond glycosciences.

3.3

Hydroxyl Groups of Bound Carbohydrates

As conditio sine qua non, the maintenance of receptor activity and structural features is to be fulfilled. Although we accepted that information on the behavior of an individual protein in an aprotic solvent cannot be reliably extrapolated to any other case, it was nonetheless encouraging for us to note that various enzyme activities can resist a complete solvent exchange [38–41]. In the purification of glycolipids or glycolipid-derived oligosaccharides, the stability of an immobilized invertebrate lectin (HPA) enabled affinity chromatography to be performed starting with sample loading in tetrahydrofuran containing 5% H2O (v/v) [42]. However, at concentrations above 50% aprotic solvent, glycolipids and also glycolipid-derived glycans other than the cognate Forssman-epitope-carrying glycolipid bound to the resin, an indication for non-specific binding under these conditions. This observation underlines the role of adequate specificity controls. The non-cognate substances were washed out with a 50%/50% mixture of water and solvent (v/v) [42]. Likewise of interest in this context is the reactivity of peanut agglutinin (PNA) when exposed to a denaturing agent. Even a substantial loss of tertiary structure (*70%) while retaining the secondary structure in 2 M guanidine hydrochloride did not significantly impair its sugar binding [43]. These case reports demonstrate that it can turn out to be rewarding to initially study sugar receptors in DMSO, the role model of an aprotic solvent in glycoconjugate research. To probe the limits of the approach, we deliberately started with the smallest known plant lectin (hevein). Its solution structure in complex with sugar has already been completely solved [44–46]. Although it lacks an extensive network of secondary-structure interactions in contrast to a jelly-roll folding pattern or an immunoglobulin(Ig)-like-domain, its backbone might still have the capacity to withstand harmful solvent effects. To show whether this is the case, we determined the affinity of ligand binding by hevein in water and solvent mixtures. As shown in Fig. 3.2 a, addition of DMSO to water drastically reduces hevein’s affinity to the ligand. This result does not bode well for our study. However, it should be kept in mind that the character of the receptor-ligand interactions would be affected by the solvent exchange. Hydrophobic and stacking interactions are expected to be weakened or even lost, with polar contacts now being favored, as revealed by a detailed interaction analysis [37]. To answer the question on hevein’s stability itself, we have performed appropriate NMR experiments. The spectrum of hevein in

45

46


a

b Influence of increasing the DMSO concentration in a mixture with water on the binding constant of the interaction between N, N' N''-triacetylchitotriose and hevein as obtained in an NMR titration study (a). 1D NMR spectrum of hevein in [D6]DMSO (b); from [37]. Fig. 3.2

pure [D6]DMSO was well resolved (Fig. 3.2 b), a good starting point to see line broadening upon ligand addition. However, no evidence of this could be detected, and neither could evidence be collected of a well-defined secondary or tertiary structure in DMSO [37]. We concluded that work with sugar receptors in aprotic solvents will most probably require a stretch of stable folding pattern which confers the essential stability to solvent exchange.


We thus turned to three types of non-homologous galactoside-binding proteins which harbor extensive secondary-structure elements, i.e. a human immunoglobulin G fraction, the mistletoe lectin (VAA, Viscum album agglutinin) and galectins. It is noteworthy that xylene- and ethanol-treated tissue specimen routinely used in histology still test positive for galectin activity. The histochemical observation that galectins maintain binding activity in tissue sections even after treatment with organic solvents was a factor for their selection as is their wide spectrum of functions in cell adhesion and growth regulation [4, 5, 8]. The purification to homogeneity of the three sugar receptor types was the starting point in this part of our investigation. In the next step, we examined the spectra of known carbohydrate ligands free in solution or complexed with the receptors in [D6]DMSO for changes in the half-width of proton signals. If negative, the concept would have been proven wrong. Given as example, Gal'a1-3Galb1-R signals were indeed non-uniformly affected by the presence of receptor (Fig. 3.3). This result reveals binding activity in the aprotic solvent and stimulated further analysis on specificity and affinity of the detectable interaction. For this purpose, we adapted two independent sensitive biochemical activity assays to assess ligand-specific interaction under the given conditions with the aim of describing the influence of the solvent exchange on KD-values quantitatively [37]. In contrast to hevein, specific activities with minor (immunoglobulin G fraction) or significant but not dramatic decreases (VAA, galectin-1) in KD were determined [37], corroborating the interpretation of line broadening. Having thus consistently verified specific binding of ligand to the sugar receptors, it then was expedient to gauge by experiments and computer-assisted calculations whether it is possible to pick up a hydroxyl-dependent signal. To this end, the free-state conformation is to be characterized. As shown in Fig. 3.4 a for Gal'a1-3Galb1-R, a central valley of the }, w-map is the result of molecular mechanics calculations. The profile of the map shown at e = 4 was not affected by increasing the dielectric constant to e = 49 (DMSO) or e = 80 (water) [37]. This central valley but not the side minimum is almost exclusively populated according to molecular dynamics calculations with explicit inclusion of DMSO molecules (Fig. 3.4 b). Experimental input for pinning down the disaccharide’s conformation is provided by measuring NOE contacts. Using the distance constraints from five NOE contacts defined in the lower left panel of Fig. 3.4, three of them water-exchangeable, it becomes apparent that regions of overlap of contour lines converge close to a low-energy region defined by cluster 3 [37]. Omitting the three OH-group-sensitive NOE contacts from the set of contour lines reveals to what extent the precision of the }, w-angle description will be enhanced if additional information on the bound state by hydroxyl sensors could be provided. The fact that the NOE cross-peak intensities of the two contacts of non-exchangeable protons were identical in D2O emphasizes that no major conformational change of the ligand occurred in this case [37]. This result confirms the conclusion drawn from the computer-assisted molecular dynamics calculations. Beyond their exploitation in this respect, these data can be turned into a sensitive tool, developed by M. Frank and termed the conformational analysis tool (CAT). It

47

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a

b

Fig. 3.3 1D NMR spectrum of Gal'a1-3Galb1-R in [D6]DMSO complexed with VAA (a) or with the a-galactoside-binding IgG subfraction (b). In both cases, a 10-fold molar excess of the ligand was used; from [37].


49

b

c a Energy profile of Gal'a1-3Galb1-R obtained by random walk molecular mechanics calculations. Crosses refer to individually attained low-energy positions (clusters) reached from different starting points according to the conformational clustering approach at e = 4 (left panel, top). Representation of the conformational behavior of Gal'a1-3Galb1-R in an MD simulation using the consistent-valence

Fig. 3.4

force field with explicit inclusion of DMSO molecules (left panel, bottom). Distance map obtained from ROESY measurements of Gal'a1-3Galb1-R in the free state (b). The symbol code for the five pairs of contour lines is given in c (the left D-galactose unit is defined as Gal'). In addition to the third contact of Gal'H1 shown in Fig. 3.1, two other watersensitive contacts are detectable; from [37].

predicts whether a water-sensitive NOE contact could actually be expected. With the “search NOE contact” option of this convenient program, each conformation in a given molecular dynamics trajectory is scanned regarding defined inter-proton distances and weighted with the factor of (r–6)–1/6 due to the r–6 dependence for NOE values [37]. As illustrated in Fig. 3.5, the population density of each pair of protons can be printed for the complete distance profile. Since the program design takes the complete population of relevant conformations during the simulation period into account with all dynamic fluctuations (example given in

50


a

b Calculated distance profiles between inter-residual protons (CH-CH, CH-OH and OH-OH proton pairs with involvement of Gal'H1 and Gal'OH2) based on the frequency of their occurrence during the MD simulation for Gal'a1-3Galb1-R at T = 400 K (a) or Gal'a1-3Galb1-R at T = 300 K (b). MD simulations are carried out in the gas phase (vacuum) (a, b-top) or with explicit consideration of DMSO molecules (b-bottom); from [37]. Fig. 3.5

Fig. 3.4 b), marked distortions of conformations from low-energy positions will not be recorded. The presently collected evidence on the binding of carbohydrate ligands supports the validity of this procedure. In sum, bound-state conformations are almost exclusively selected from low-energy positions of }, w-maps [47–50]. In order to figure out whether a water-sensitive contact could be accessible, it is thus expedient to inspect graphs as given in Fig. 3.5. A notable sampling in distance


a Histograms of the distance profile between the protons of OH2'-OH3 of Glc'a14Glcb (top panel, left) and the protons of OH2'-OH4 of Gal'a1-3Galb (top panel, right) in DMSO. Separate correlation plots of the distances between the involved oxygen atoms and protons for O2'-O3 vs OH2'-OH3 of Glc'a1-4Glcb (middle panel, left) and O2'-O4 vs OH2'-OH4 of Gal'a1-3Galb (middle panel, right). Schematic illustration of different ways Fig. 3.6

to yield the same proton-proton distance: inter-residual H-bonding in the disaccharide or contact formation with a solvent molecule as mediator (bottom panel, left). While an interresidual H-bond is formed in the case of OH2'-OH3 of Glc'a1-4Glcb in the region of its global minimum conformation, a mediator DMSO molecule participates to yield the OH2'-OH4 distance of approximately 2.6 Å in Gal'a1-3Galb (bottom panel, right).

values below 3.5 Å is an indication of the occurrence of an NOE contact under the premise that a low-energy conformation equals the bound state of the ligand. This illustration, too, highlights the importance of running the calculations not in vacuum but in an environment of solvent. Modeling with explicit inclusion of solvent molecules affords the additional opportunity to contribute to an understanding of the interaction between solvent and ligand, especially to infer the mechanism to yield a maximum in the distance

51

52


b

c Fig. 3.6 b, c


Fig. 3.7 Relevant part of a 2D TR-NOE spectrum (mixing time: 80 ms) of the Gal'a1-3Galb1-R/antibody complex in the presence of Al2O3 (upper panel) and without this substance (lower panel); from [37].

53

54


profile. In fact, the positioning of the pair of involved protons can reflect a solvent effect. As an example of how to explain proximity of protons, Fig. 3.6 a shows the distance profile for two pairs of disaccharide protons. Although the profiles look very similar, computation of inter-proton and inter-oxygen distances of the set of hydroxyl groups disclosed marked differences (Fig. 3.6 b). As explanations, formation of an inter-residual (direct) hydrogen bond or mediation of two hydrogen bonds by a solvent molecule (without direct contact) emerge from the computer simulations (Fig. 3.6 c). In any case, protons from hydroxyl groups showing up in this profile at a distance below 3.5 Å are reason to proceed to the next experimental step. With these insights from modeling as well as from biochemical and spectroscopic experiments, our hypothesis that it might be possible to refine conformational description of bound ligands by measurements in an aprotic solvent could be tested. Since a major cause for concern in the interpretation of TR-NOE spectra originates from the possibility of spin diffusion and rapid proton exchange, we systematically varied the mixing time and performed data collection also in the rotating frame to avoid three-spin processes [37]. To suppress proton exchange, we furthermore took advantage of the capacity of Al2O3 to act as a proton acceptor blocking magnetization transfer [51]. The way in which addition of the hygroscopic substance removes interfering signals not originating from legitimate TRNOE contacts is shown in Fig. 3.7.

Improved description of the ligand’s conformation bound to the receptor. Introduction of the experimentally determined conformational constraints based on the two water-insensitive and the additional water-sensitive inter-residual NOE contacts of Gal'a1-3Galb1-R into the }, w energy plot reveals to what extent the number of angle combinations is lowered by the third contact (see also Fig. 3.1). The area of overlap between the contour line pairs from the two water-insensitive contacts lies in the central low-energy valley (see also Fig. 3.4). The reduction in size of the allowed conformational area by the third water-sensitive contact is highlighted. The symbol code for the three pairs of contour lines is given in the right part of the figure; from [37]. Fig. 3.8

3.4 Conclusions

The upper part of this figure presents experimental evidence for the presence of an inter-residual water-sensitive contact of the ligand bound to the sugar receptor (in this case, an immunoglobulin G fraction). Recalling the information from Fig. 3.4 on the free ligand, it is obvious that association of the ligand to this receptor restricts the conformational flexibility of the disaccharide in the central low-energy valley, a striking demonstration of conformer selection. By using the third contact (in addition to the two solvent-independent contacts) the definition of the topology of the bound ligand is distinctly refined (Fig. 3.8). When turning back to Fig. 3.1, it is satisfying to conclude that our aim to reduce the impact of blurring can be attained. Further experiments with the mistletoe lectin and galectins have proven that this result is not exceptional [37]. In that report, we also point out that water/solvent mixtures deserve to be thoroughly tested to extend the range of potential applications to proteins which might not be stable in pure aprotic solvents (see Fig. 3.2 a as example).

3.4

Conclusions

Water-exchangeable protons are a generally hidden source of information about the bound ligand’s topology. Our combined approach gives a guide toward access to these new conformational constraints by carrying out experiments in an aprotic solvent. To estimate the chances of experimental success at an early stage, computer calculations and plots visualizing inter-proton distances in molecular dynamics runs provide insights into whether and to what extent such solvent-sensitive contacts can occur in the conformational space of the ligand in solution. It is indispensable to perform these procedures with simulation of explicit solvent presence. The spectroscopic verification of the results of the calculations for the sugar molecule affords solid justification for pursuing this line of investigation. Having dealt with the ligand, it is next necessary to prove by biochemical assays that the receptor is still active under the chosen solvent conditions. Our two presented assay types will provide a definite answer with only lg-quantities of protein to be invested. A stretch of secondary structure such as that characteristic for Ig domains or jelly-roll folds is rather likely to be a key factor in maintaining the functionality of proteins in aprotic solvents. The involvement of an extended cluster of loosely bound water molecules to mediate ligand binding to the receptor by a network of hydrogen bonds is most likely a negative factor, when the solvent is exchanged. In addition to the biochemical assays, monitoring 1D NMR spectra of receptorligand mixtures can conveniently provide corroborating evidence for ligand binding, for example by recording non-uniform increases of the line width of certain ligand signals. However, the possibility that the architecture of the actual binding site is affected in the aprotic solvent should be kept in mind. In this case, the measured features include solvent-dependent parameters. Because maintenance of activity is favorably influenced by rather rigid secondary structures, proteins with

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binding sites embedded into e.g. a series of b-strands such as galectins may not cause serious problems in this respect. Our report attests that the outlined series of steps to predict the occurrence of NOE contacts involving OH-groups, to experimentally verify them for the free ligand and to ensure receptor activity can lead to new information on the bound ligand’s topology in the aprotic solvent (or in solvent mixtures with water). The given demonstration of the feasibility of performing meaningful trNOE experiments on bound ligands in an aprotic solvent also provides a route to extending our knowledge on the role of water in the binding process. Finally, we see no reason why the application of this concept should be exclusively limited to glycosciences [52, 53].

3.5

References 1

2 3 4 5 6 7

8 9

10 11 12 13

R. A. Laine, in Glycosciences: Status and Perspectives H.-J. Gabius, S. Gabius (Eds), Chapman & Hall, London – Weinheim, 1997, pp. 1–14. H.-J. Gabius, Naturwissenschaften 2000, 87, 108–121. P. J. Winterburn, C. F. Phelps, Nature 1972, 236, 147–151. H.-J. Gabius, Eur. J. Biochem. 1997, 243, 543–576. H. Kaltner, B. Stierstorfer, Acta Anat. 1998, 161, 162–179. H. Lis, N. Sharon, Chem. Rev. 1998, 98, 637–674. K. Yamashita, S. Hara-Kuge, T. Ohkura, Biochim. Biophys. Acta 1999, 1473, 147–160. H.-J. Gabius, Anat. Histol. Embryol. 2001, 30, 3–31. H. Rüdiger, H.-C. Siebert, D. Solís, J. Jiménez-Barbero, A. Romero, C.-W. von der Lieth, T. Díaz-Maurio, H.-J. Gabius, Curr. Med. Chem. 2000, 7, 389– 416. J. M. Moore, Curr. Opin. Biotechnol. 1999, 10, 54–58. G. C. K. Roberts, Curr. Opin. Biotechnol. 1999, 10, 42–47. T. Weimar, R. Bukowski, N. M. Young, J. Biol. Chem. 2000, 275, 37006–37010. H. Kessler, S. Seip, in: Two-Dimensional NMR Spectroscopy: Applications for Chemists and Biochemists (Eds.: W. R. Croasmun, R. M. K. Carlson), VCH Publish-

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ers, New York – Weinheim, 1994, pp. 619–654. H. J. Dyson, P. E. Wright, in Two-Dimensional NMR Spectroscopy: Applications for Chemists and Biochemists W. R. Croasmun, R. M. K. Carlson (Eds), VCH Publishers, New York – Weinheim, 1994, pp. 655–698. J. Dabrowski, L. Poppe, J. Am. Chem. Soc. 1989, 111, 1510–1511. B. Casu, M. Reggiani, G. G. Gallo, A. Vigevani, Tetrahedron 1966, 22, 3061– 3083. D. Acquotti, L. Poppe, J. Dabrowski, C.-W. von der Lieth, S. Sonnino, G. Tettamanti, J. Am. Chem. Soc. 1990, 112, 7772–7778. L. Poppe, C.-W. von der Lieth, J. Dabrowski, J. Am. Chem. Soc. 1990, 112, 7762–7771. H.-C. Siebert, G. Reuter, R. Schauer, C.-W. von der Lieth, J. Dabrowski, Biochemistry 1992, 31, 6962–6971. B. R. Leeflang, J. F. G. Vliegenthart, J. Magn. Reson. 1990, 89, 615–619. B. R. Leeflang, J. F. Vliegenthart, L. M. Kroon-Batenburg, B. P. van Eijck, J. Kroon, Carbohydr. Res. 1992, 230, 41– 61. Z. Y. Yan, B. N. N. Rao, C. A. Bush, J. Am. Chem. Soc. 1987, 109, 7663–7669. A. Rivera-Sagredo, J. Jiménez-Barbero, M. Martin-Lomas, Carbohydr. Res. 1991, 221, 37–47.

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K. Bock, T. Frejd, J. Kihlberg, G. Magnusson, Carbohydr. Res. 1988, 176, 253– 270. B. Adams, L. Lerner, J. Am. Chem. Soc. 1992, 114, 4827–4829. B. Adams, L. Lerner, Magn. Reson. Chem. 1994, 32, 225–230. L. Poppe, H. van Halbeek, J. Am. Chem. Soc. 1991, 113, 363–365. H. van Halbeek, L. Poppe, Magn. Reson. Chem. 1992, 30, S74. L. Poppe, H. van Halbeek, J. Am. Chem. Soc. 1992, 114, 1092–1093. S. Sheng, H. van Halbeek, Biochem. Biophys. Res. Commun. 1995, 215, 504– 510. S. Sheng, R. Cherniak, H. van Halbeek, Anal. Biochem. 1998, 256, 63–66. M. J. Minch, J. F. G. Vliegenthart, H.-C. Siebert, H.-J. Gabius, NMR Newsletter 2000, No. 498, 2. S. Bekiroglu, C. Sandström, T. Norberg, L. Kenne, Carbohydr. Res. 2000, 328, 409–418. L. Poppe, H. van Halbeek, Nat. Struct. Biol. 1994, 1, 215–216. C. Sandström, H. Baumann, L. Kenne, J. Chem. Soc. Perkin Trans. 1998, 2, 2385– 2393. E. W. Sayers, J. L. Weaver, J. H. Prestegard, J. Biomol. NMR 1998, 12, 209–222. H.-C. Siebert, S. André, J. L. Asensio, ãda, X. Dong, J.-F. Espinosa, F. J. Can M. Frank, M. Gilleron, H. Kaltner, T. Kozár, N. V. Bovin, C.-W. von der Lieth, J. F. G. Vliegenthart, J. Jiménez-Barbero, H.-J. Gabius, CHEMBIOCHEM 2000, 1, 181–195. M. N. Gupta, Eur. J. Biochem. 1992, 203, 25–32. A. M. Klibanov, Trends Biotechnol. 1997, 15, 97–101. A. K. Gladilin, A. V. Levashov, Biochemistry (Moscow) 1998, 63, 345–356.

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G. Carrea, S. Riva, Angew. Chem. 2000, 112, 2312–2341. D. F. Smith, B. V. Torres, Methods Enzymol. 1989, 179, 30–45. G. B. Reddy, V. R. Srinivas, N. Ahmad, A. Surolia, J. Biol. Chem. 1999, 274, 4500–4503. ãda, M. Bruix, J. L. Asensio, F. J. Can A. Rodriguez-Romero, J. Jiménez-Barbero, Eur. J. Biochem. 1995, 230, 621– 633. ãda, M. Bruix, J. L. Asensio, F. J. Can C. Gonzalez, N. Khiar, A. RodriguezRomero, J. Jiménez-Barbero, Glycobiology 1998, 8, 569–577. ãda, H.-C. SieJ. L. Asensio, F. J. Can bert, J. Laynez, A. Poveda, P. M. Nieto, U. M. Soedjanaatmadja, J. J. Beintema, H.-J. Gabius, J. Jiménez-Barbero, Chem. Biol. 2000, 7, 529–543. T. Peters, B. M. Pinto, Curr. Opin. Struct. Biol. 1996, 6, 710–720. A. Poveda, J. Jiménez-Barbero, Chem. Soc. Rev. 1998, 27, 133-143. C.-W. von der Lieth, H.-C. Siebert, T. Kozár, M. Burchert, M. Frank, M. Gilleron, H. Kaltner, G. Kayser, E. Tajkhorshid, N. V. Bovin, J. F. G. Vliegenthart, H.-J. Gabius, Acta Anat. 1998, 161, 91–109. J. Jiménez-Barbero, J. L. Asensio, F. J. ˜ ada, A. Poveda, Curr. Opin. Struct. Can Biol. 1999, 9, 549–555. J. Dabrowski, H. Grosskurth, C. Baust, N. E. Nifant’ev, J. Biomol. NMR 1998, 12, 161–172. M. Fioroni, M. D. Diaz, K. Burger, S. Berger, J. Am. Chem. Soc. 2002, 124, 7737–7744. M. D. Diaz, M. Fioroni, K. Burger, S. Berger, Chem. Eur. J. 2002, 8, 1663– 1669.

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4

NMR of Carbohydrates: 1D Homonuclear Selective Methods Jean-Robert Brisson, Shih-Che Sue, Wen-guey Wu, Gerald McManus, Pham T. Nghia, and Duˇsan Uhrín

4.1

Introduction

Recently, several reviews have dealt with carbohydrate structural determination by NMR spectroscopy using selective excitation techniques [1–5]. In this article, applications of homonuclear selective excitation techniques with emphasis on the structural and the conformational analysis of oligosaccharides will be presented. Specifically, the accurate measurement of spectral parameters for overlapping anomeric resonances in maltotriose and in a complex mixture of heparin-derived tetrasaccharides will be presented. The use of selective excitation techniques for determining the bound conformation of a heparin disaccharide and the detection of intermolecular interactions will also be given. Finally, new selective excitation techniques and the theory for the measurement of residual homonuclear dipolar coupling constants of oligosaccharides in phage-oriented media will be presented.

4.2

Experimental Aspects 4.2.1

Description of the Pulse Sequences

1D selective excitation experiments are analogs of standard 2D and 3D experiments where hard pulses have been replaced by selective pulses. The original phase cycled experiments [6–19] have more recently been adopted for the use of pulsed field gradients [20–32]. Particularly useful are 1D techniques analogous to 3D experiments [5, 27, 31]. For example, the 1D TOCSY-NOESY [5] (Fig. 4.1 e) is the 1D analog of the 3D TOCSY-NOESY. From a different point of view, this technique can be looked at as originating from a combination of 1D building blocks of 1D TOCSY and 1D NOESY. These techniques are mainly used to isolate specific spins and determine their scalar or dipolar interactions. They are used when the information cannot be obtained by using standard 2D and 3D NMR methods or when a 1D approach offers a much more effective, less time-consuming alter-

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4 NMR of Carbohydrates: 1D Homonuclear Selective Methods

native. Applications will be given for 1D TOCSY, 1D NOESY, 1D TOCSY-TOCSY, 1D TOCSY-NOESY and 1D NOESY-TOCSY. The 1D NOESY-NOESY will not be discussed since it was not applied in the present case. Its use is mainly for polysaccharides with large negative NOEs, and several applications have been well documented elsewhere [2, 3]. The technical aspects of these sequences have recently been reviewed in some detail [2, 5]. We will focus on a particular implementation of 1D experiments as shown in Fig. 4.1. An on-resonance q-SNEEZE pulse [33] (appropriate bandwidth from 10 Hz to 200 Hz) was usually chosen as a selective 90 8 pulse and applied mostly on the chemical shift of the selectively excited proton. The power level and pulse length are generated according to the product of bandwidth (BW in Hz) and pulse length (PW in seconds), such that BW ´ PW = 4.85. The proton carrier frequency is usually set at the HOD resonance and a phase ramp is applied to the shape of a selective pulse in order to achieve a selective excitation at an appropriate frequency [34, 35]. Purging pulsed-field gradients (PFGs) are used rather than gradient coherence selection in all experiments in order to maximize sensitivity. Z-filters are typically used for the removal of antiphase components in order to obtain pure absorption lineshapes for measurement of coupling constants. The use of a z-filter in experiments of polysaccharides can also suppress the ROE effects during the TOCSY spin-lock. These experiments are now quite easy to set up using automation routines that generate shaped pulses. Typically, a proton spectrum is acquired and the 90 8 hard pulse is calibrated. Then, similarly to integration of resonances, the spin that is to be selectively excited is selected by the use of two cursors, one on each side of its multiplet. A pulsed shape file for this spin is then automatically generated for a specified shaped pulse. The parameters that are contained in the shaped pulse file for a spin constitute the name of the used shape pulse: the offset from the carrier frequency, the excitation bandwidth, and the 90 8 hard pulse and power used. Thanks to linear amplifiers, one only needs to calibrate the 90 8 pulse at high power. Automation scripts routinely set up the different 1D selective experiments based on the proton spectrum. Then, the only parameter that needs to by supplied is the name of the shape pulse file generated for a specific spin. The length of the shaped pulse and the power used are automatically extracted. For the 1D TOCSY and 1D NOESY experiments, parameters that need to be optimized are the selective excitation bandwidth and the mixing time. The selective excitation bandwidth should not be too small since this will lead to a very long se" 1D selective pulse sequences that are gradient-enhanced: (a) 1D TOCSY, (b) 1D NOESY, (c) 1D TOCSY-TOCSY, (d) 1D NOESY-NOESY, (e) 1D TOCSY-NOESY, (f) 1D NOESY-TOCSY. The pulsed field gradients were 1 ms in length and had the following strengths: G1 = 8.0 Gauss/cm, G2 = 6.4 Gauss/ cm, G3 = 11.0 Gauss/cm, G4 = 8.8 Gauss/cm. The following phase cycling was applied: u1 = Fig. 4.1

x, –x; u2 = 2x, 2(–x); u3 = x, 2(–x), x. The 1808 selective pulse in (d) is applied for two scans on-resonance and for two scans off-resonance. The delay, d, in TOCSY experiments can be optimized for suppression of ROESY peaks in macromolecules or made variable for removal of antiphase components of multiplets.

4.2 Experimental Aspects

61

62


lective pulse, and signal intensity will be reduced because of relaxation effects. This is more of a concern for polysaccharides. The bandwidth does not need to be centered on the resonance, and one can increase the bandwidth and shift it to one side to avoid partial excitation of nearby resonances [2]. The mixing time used for a TOCSY depends on the spin system. Usually a range of mixing times (spinlock times) is used so that the spin system can be assigned. The mixing time for a 1D NOESY depends on the correlation time of the molecule. For conformational analysis, a range of mixing times is used to obtain a buildup curve. For the doubly selective experiments, the selective pulses should be as short as possible to avoid loss of signal intensity due to relaxation effects. Usually, the parts are optimized one at a time. For a typical concentration of sugars in the mM range, a 1D TOCSY can be carried out in a matter of minutes. A 1D NOESY can take from minutes to 1 h depending on the magnitude of the NOE. Doubly selective experiments can take up to overnight. The 1D TOCSY-TOCSY and 1D TOCSY-NOESY are the most efficient. The experiments containing NOESY parts are most efficient for large molecules with negative NOEs. The nomenclature used in the figure legends to describe the use of the sequences shown in Fig. 4.1 will be 1D EXP (spin irradiated, selective excitation bandwidth, mixing time) and 1D EXP1-EXP2 (spin1 excited, bandwidth, mixing time; spin2, bandwidth, mixing time), where EXP, EXP1 and EXP2 stand for either TOCSY or NOESY. For a TOCSY the mixing time is the spin-lock time. In the text, the bandwidth and mixing time will be omitted since it is stated in the figure legends. Letters will label all residues and numbers will label the spins, so that A1 refers to the H1 resonance of residue A. For TOCSY spectra only one spin will be labeled with a letter (usually the anomeric resonance, for example A1). For the other spins the letters will be omitted, since all the spins in a TOCSY spectrum for an isolated resonance belong to the same residue. Also, in the figures, the selected resonance will be underlined. A doubly underlined resonance means that this resonance will be selected as the second selection step in the next experiment shown in the figure [ for example, in 1D TOCSY (a2) followed by 1D TOCSY-NOESY (a2, a4)].

4.3

Examples 4.3.1

Maltotriose: Overlapping Anomeric Resonances

Usually, spectra of homopolymers are difficult to assign because of overlap of anomeric resonances. In the case of maltotriose a-d-Glcp-(1-4)-a-d-Glcp-(1-4)-a/b-dGlcp (B-C-Aab), the anomeric resonances of the B and C residues overlap making the assignment and measurement of NOEs difficult for these units. However, unambiguous assignments can be obtained by making use of selective excitation

4.3 Examples

experiments (Fig. 4.2). A 1D TOCSY for the B1 and C1 overlapping anomeric resonances shows all the resonances of both residues (Fig. 4.2 b). The 1D TOCSYTOCSY where the second selection step is for a resonance from each residue yields the complete spin patterns for the two residues (Fig. 4.2 c, d). From the shape of their multiplet and chemical shift, the resonances can then be assigned. Since H3 and H4 have the same multiplet pattern, the mixing time can be varied to distinguish the two spins, since magnetization will be transferred to H3 before H4 as the mixing time increases. The assignment of maltotriose (Tab. 4.1) is then completed by a 1D TOCSY on the anomeric A1a and A1b resonances (Fig. 4.2 e, f). The multiplet pattern for each resonance in the 1D selective experiments can be clearly observed because of the same digital resolution as a 1D 1H spectrum. Also, with a 1D TOCSY with a z-filter, pure absorption shapes can be obtained, which permitted the measurement of coupling constants for maltotriose with accuracy (Tab. 4.2). Optimal accuracy is achieved by performing a spin simulation. This is important since measurement of only peak intensities can sometimes result in systematic errors, especially for J34 and J45 of glucose [36]. In our case, accurate vicinal (H-C-C-H) coupling constants were required for the analysis of residual dipolar couplings presented later in this article. As can be seen in Fig. 4.2 g, spin simulation reproduces well the 1D TOCSY spectra for A1a. From measurement of J34 from a peak listing a value of 10.0 ± 0.5 Hz is obtained. From the spin simulated spectrum, which takes into account all spin scalar interactions, a value of J34 of 9.5 ± 0.1 Hz is obtained. Spin simulation also reproduces well the un-

1D selective experiments for maltotriose, a-D-glucopyranosyl-(1-4)-a-D-glucopyranosyl-(1-4)D-glucose. Residues are labeled CB-A. The a and b forms of the reducing residue A are denoted as Aa and Ab, respectively. (a) 1H NMR spectrum, 25 mg/mL in D2O, 25 8C, 600 MHz. (b) 1D TOCSY(BC1, 20 Hz, 150 ms). (c) 1D TOCSY-TOCSY(BC1, 20 Hz, 150 ms; C4, 40 Hz, 150 ms). (d) 1D TOCSY-TOCSY(BC1, 20 Hz, 150 ms; B3, 40 Hz, 150 ms). (e) 1D TOCSY(Ab1, 20 Hz, 150 ms). (f) 1D TOCSY(Aa, 20 Hz, 150 ms). (g) Spin simulation of resonances for Aa. (h) 1D NOESY(BC1, 30 Hz, 1 s). (i) 1D TOCSYNOESY(C4, 30 Hz, 150 ms; C1, 40 Hz, 1 s). (j) 1D TOCSYNOESY(B2, 16 Hz, 60 ms; B1, 40 Hz, 1 s). Fig. 4.2

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64

4 NMR of Carbohydrates: 1D Homonuclear Selective Methods Tab. 4.1 1H chemical shifts a) (ppm) of maltotriose [a-d-glucopyranosyl-(1-4)-a-d-glucopyranosyl(1-4)-d-glucose] C-B-A. The a and b forms of residue A are denoted as Aa and Ab, respectively

Aa b) Aa Ab B C

H1

H2

H3

H4

H5

H6

H6'

5.225 5.225 4.650 5.398 5.395

3.566 3.565 3.272 3.620 3.583

3.967 3.967 3.765 3.96 c) 3.684

3.648 3.647 3.647 3.650 3.418

3.935 3.933 3.590 3.850 3.724

3.840 3.810 3.904 3.880 3.853

3.813 3.843 3.769 3.820 3.765

a) Measured at 25 8C, 600 MHz, in D2O with internal acetone at 2.225 ppm. Average error ± 0.002 ppm. b) Spin simulation data. c) average of 3.968 and 3.952 ppm for the a and b forms of residue A.

Tab. 4.2 Coupling constants a) (Hz) of maltotriose [a-d-glucopyranosyl-(1-4)-a-d-glucopyranosyl(1-4)-d-glucose] C-B-A. The a and b forms of residue A are denoted as Aa and Ab, respectively

Aa b) Aa Ab B C

J12

J23

J34

J45

J56

J56

J66'

3.8 3.9 8.0 4.0 3.9

9.9 9.9 9.5 10.0 9.9

10.0 9.4 9.0 9.0 9.0

9.5 9.5 9.5 9.5 10.0

2.6 2.4 2.2 2 2.2

4.4 4.4 5.3 4.5 5.2

–12.3 –12.3 –12.3 –12.3 –12.2

a) Measured at 25 8C, 600 MHz, in D2O. Average error ± 0.5 Hz. b) Spin simulation data (average error ± 0.1 Hz).

equal line intensities of the H6 and H6' multiplets because of their small difference in chemical shifts. Hence, spin simulation affords the best way of making sure assignments are correct, since if a spin is not correctly assigned its multiplet pattern cannot be simulated properly. For sugars it is also important to do spin simulation, especially when strong coupling occurs [36]. For example, these techniques were applied to properly assign the spectra of an unusual sterically crowded oligosaccharide containing 12 residues, where spin simulation of every residue was possible [37]. This was done in order to analyze in detail the NOEs and long range heteronuclear coupling constants and demonstrate for the first time the presence of a an anti conformer [38], which has a dihedral angle (C1'-O1'-C4-H4) near 180 8, for a b-d-Glcp-(1-4)-d-Glcp unit of the oligosaccharide. There are significant differences in the chemical shifts and in the coupling constants (up to 1.9 Hz) from those of maltotriose obtained by 1D methods versus 2D methods where the assignments were done using phase-sensitive double quantum-filtered correlation experiments and proton-carbon heteronuclear correlation spectra [39]. These differences are attributable to the lower digital resolution and dispersive lineshapes present in some 2D experiments. The H5 resonance of the Aa unit was wrongly assigned as one of the H6s resonances in the 2D spectra.

4.3 Examples

However, from a 1D experiment and spin simulation, the correct assignment was made based on observation of the resolved multiplets. There were some long range effects on the chemical shift for B3 due to the a/b equilibrium for residue A, which could be detected because of the high digital resolution of 1D selective methods. As can be seen in Fig. 4.2 d, B3 appears as a quartet instead of a doublet of doublets. Interestingly, no such long range effects were detected for the other spins of residues B and C. Even though the B1 and C1 anomeric resonances overlap, inter-residue NOEs for the C-B and B-A can still be observed from 1D TOCSY-NOESY experiments. As shown in Fig. 4.2 h, for a 1D NOESY of the B1 and C1 overlapping anomeric resonances, it is not possible to distinguish which spin is contributing to the NOEs. However, by performing a 1D TOCSY from C4 first, it is ensured that only the signal of the anomeric proton of residue C will be selected for a consecutive NOESY step. The TOCSY mixing time (150 ms) was optimized to maximize the intensity of the C1 resonance. Once the 1D TOCSY is optimized, the 1D TOCSYNOESY was performed where the second selection step is for the C1 resonance. As can be seen in Fig. 4.2 i, only the NOEs for B-C can then be observed. Similarly for the B-A NOEs, B1 is isolated from C1 by first performing a 1D TOCSY from B2. The mixing time to maximize the B1 resonance was 30 ms in this case. Then, the 1D TOCSY-NOESY(B2, B1) is performed by selecting the B1 resonance in the NOESY part (Fig. 4.2 j). Hence, 1D selective experiments are sometimes preferable to 2D methods for the structural analysis of oligosaccharides, as recently applied, for example, in some enzymatically synthesized oligosaccharides [40, 41]. The 1D TOCSY-NOESY permits the isolation of spin systems of interest and the detection of NOEs from proton resonances within the ring, thus obtaining NOE constraints which cannot be otherwise determined from 2D experiments [42, 43]. Also, because of the high resolution obtained in the 1D NOESY experiment, spectral deconvolution or some other line shape analysis program could be carried out to quantify the NOEs of interest. 4.3.2

Determination of the Bound Conformation of a Heparin Disaccharide, and Intermolecular NOEs

The conformation of the heparin disaccharide (DUA2S(1?4)-a-d-GlcNS6S, Fig. 4.3) bound to a cardiotoxin, CTX A3, from Taiwan cobra (Naja atra) was investigated using 1D TOCSY, 1D NOESY and 1D TOCSY-NOESY. The conformation of the heparin disaccharide bound to CTX A3 in solution was determined using a 1 : 1 protein/sugar ratio (5 mM to 5 mM) at 25 8C, pH 6. Because of the low molecular weight of CTX A3 (about 7 kDa), it was possible to work at an equimolar ratio, where both protein and sugar resonances can be clearly observed, along with transferred and intermolecular NOEs. Changes upon binding in protein and sugar chemical shifts could also be measured as well as changes in J coupling constants for the sugar. Since high digital resolution and good signal to

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Structure of the heparin-derived disaccharide and tetrasaccharides. For the disaccharide the residues are labeled as b-a. For the three forms of the tetrasaccharide the residues are labeled as Da-Ca-Ba-Aa, Db-Cb-Bb-Ab, and Dc-CcBc-Ac. Fig. 4.3

noise is necessary to observe these small changes in spectral parameters, 1D selective techniques were employed. 1D TOCSY was used to assign the proton resonances (Tab. 4.3) of the disaccharide with and without the presence of CTX A3 (Fig. 4.4). Two 1D TOCSY experiments (a2 and b1) are shown in Fig. 4.4 to indicate the proton assignments of the two residues (b-a) in the presence of CTX A3. The JHH coupling constants were also measured from 1D NOESY and 1D TOCSY by using the spectral deconvolution. Proton-proton J coupling constants are known to be useful in deriving the average conformation of the carbohydrate ring and to provide insights into confor-

4.3 Examples

Assignment of the heparin-derived disaccharide: (a) 1H NMR spectrum of CTX A3:disaccharide (1 : 1) complex (5 mM : 5 mM). (b) 1D TOCSY(a1, 40 Hz, 90 ms). (c) 1D TOCSY(b1, 20 Hz, 90 ms). Asterisks mark extra signals due to partial excitation. Two 1D TOCSY-NOESY spectra of a5 (with 1D selective TOCSY transfer from a2) corresponding to the free (a2, 100 Hz, 60 ms; a5, 125 Hz, 300 ms) and bound disaccharide (a2, 100 Hz, 60 ms; a5, 40 Hz, 800 ms) are given in the inset. It is possible to demonstrate the orientation change of 6-O-sulfate side-chain upon binding to CTX A3 by monitoring the J coupling values and NOEs between a5 and a6. Fig. 4.4

mational equilibrium. As shown in Tab. 4.4, the JHH values determined by 1D TOCSY and 1D NOESY spectra also exhibited a significant change for the heparin-derived disaccharide after binding. The J coupling values of J12, J23 in the unsaturated uronic acid have been proposed to represent the relative population of two energy-favored conformers, 1H2 and 2H1 [44]. The changes of J12, J23 after binding to CTX A3 were a strong indicator that the sugar ring of DUA2S converted fully to the 1H2 conformation. The coupling values of J56R, J56S in GlcNS6S are also interesting since they indicated that either the dynamic or the conformation of the 6-O-sulfated side chain was perturbed. The change of the a5 multiplet pattern in the two 1D TOCSY-NOESY experiments shown in the inset of Fig. 4.4 b elicited the perturbation of the 6-Osulfate orientation. Its orientation is determined by the three eclipsed C5-C6 conformers, gg, gt and tg [gauche (g) or trans (t)] defined by the two dihedral angles,

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4 NMR of Carbohydrates: 1D Homonuclear Selective Methods Tab. 4.3 1H chemical shifts a) of the heparin-derived disaccharide (b-a) in aqueous solution, df, and in the presence of CTX A3 (1 : 1), db

H1

H2

H3

H4

H5

H6S

H6R

4.160 4.176 0.016

4.214 4.271 0.057

4.350 4.404 0.054

GlcNS6S

df db db–df

5.454 5.487 0.033

3.280 3.295 0.015

3.763 3.741 0.022

3.829 3.871 0.042

DUA2S

df db db–df

5.503 5.620 0.117

4.574 4.677 0.103

4.343 4.356 0.013

5.974 6.048 0.074

a) Measured at pH 6.0, 25 8C and 100% D2O, with an estimated error of ± 0.002 ppm.

Tab. 4.4 Coupling constants a) of the heparin-derived disaccharide in aqueous solution and in the presence of CTX A3 (1 : 1)

DUA2S

GlcNS6S

Disaccharide only CTX A3 complex

J12

J23

J34

J45

J56R

J56S

J12

J23

J34

3.4 3.4

10.3 10.4

9.2 9.1

9.5 10.2

4.0 2.6

2.2 1.8

3.4 2.5

2.7 2.0

4.4 4.7

a) Measured at pH 6.0, 25 8C and 100% D2O, with an estimated error of ± 0.1 Hz.

H5-C5-C6-H6S and H5-C5-C6-H6R [45]. In the absence of CTXs, the 6-O-sulfate group exists in a gt and gg equilibrium (4.0 and 2.2 Hz for J56R and J56S, respectively). After binding to CTX A3, J56R and J56S had smaller values of 2.6 and 1.8 Hz, respectively, indicating that the 6-O-sulfated side chain had undergone a change in orientation, corresponding to 100% gg conformer. In addition, the 1H chemical shifts of H6S and H6R in GlcNS6S were perturbed the most upon disaccharide binding to CTX A3 (Tab. 4.3). 1D NOESY was used to acquire the NOE information. As shown in Fig. 4.5, for the free heparin disaccharide, the sign of the NOE peaks is negative with respect to the irradiated resonance because of the fast tumbling rate of the molecule. Upon binding to CTX A3, the NOE peaks change sign, an indication that the molecule is indeed bound to and tumbling at a slower rate with CTX A3. When necessary, 1D TOCSY-NOESY with double selection was used to extract the NOE data of the protons buried within the protein signals, for instance a4 (Fig. 4.5 c). The 1D TOCSY-NOESY (a2, a4) helped to extract another inter-residual NOE a4/b2, which was important for the determination of the bound conformation of the disaccharide. One noticeable point is that the second excitation bandwidth for a4 (Fig. 4.5 d) was not centered on the resonance but shifted to the left, and the bandwidth was increased in order to decrease the long selective excitation pulse, as mentioned previously.

4.3 Examples 1D selective spectra for the free disaccharide and for the CTX A3:disaccharide 1 : 1 complex at 25 8C and 600 MHz: (a) 1D NOESY(b1, 20 Hz, 600 ms) spectrum for the disaccharide and (b) 1D NOESY(b1, 20 Hz, 300 ms) for the CTX A3:disaccharide 1 : 1 complex. The NOE peaks are negative for the free form and positive for the complex, indicating binding: (c) 1D TOCSY(a2, 150Hz, 60ms) and (d) 1D TOCSY-NOESY(a2, 150 Hz, 60 ms; a4, 150 Hz, 300 ms) for the CTX A3/disaccharide 1:1 complex. Double arrows indicate the selective excitation bands. Other signals due to partial excitation of neighboring peaks are marked with asterisks. The b1 and b2 inter-residual NOEs with a4 were used to derive the bound conformation of the disaccharide.

Fig. 4.5

In Fig. 4.6, a stack plot of the 1D NOESY for b1 with ten NOE mixing times ranging from 100 to 1000 ms is shown. Selective excitation allowed the determination of NOEs with improved sensitivity and resolution. The NOE intensities were normalized against the excited peaks decay, which was fitted to an exponentially decaying function and extrapolated back to an intensity of 100% at zero mixing time. Then, the NOE build-up curve for each transferred NOE can be generated with respect to this normalized intensity. Recently, the solution conformation of a homogeneous heparin-derived tetrasaccharide in the presence and absence of the plasma protein antithrombin [46] was determined by using a combination of full relaxation and conformational exchange matrix analysis (CORCEMA) of the 1H NOE data [47, 48]. Here, a similar approach was used, taking advantage of selective excitation techniques to solve the conformation of the disaccharide for the free and bound conformation with CTX A3. The derived carbohydrate conformation using CORCEMA indicated that the glycosidic linkage perturbation (UH, wH) changed from (26 8, –77 8) to (64 8, –5 8), when bound to CTX A3. During the fitting of experimental and theoretical data of bound disaccharide, convincing kinetic parameters, such as kon, koff and Kd values, were derived thanks to a good R-factor of 0.13 [49]. Intermolecular NOEs between the sugar and protein could also be observed. Because of the low molecular weight of CTX A3, it was possible to work at a 1 : 1 ra-

69

70


Stack plot of the 1D NOESY for selective excitation of b1 with mixing times from 100 msec to 1000 msec for the CTX A3:disaccharide 1 : 1 complex at 25 8C and 600 MHz. The intensities of peaks reflect the time

Fig. 4.6

dependence of the transfer NOEs and the decay of the excited b1 resonance. The 20 Hz on-resonance excitation band was centered on the b1 resonance.

tio where both protein and sugar resonances could be clearly observed (Fig. 4.4). The selective excitation of the H4b resonance of DUA2S led to a detectable NOE for the 2,6H of Phe10 signal, and the excitation of the 2,6H resonances of Phe10 also led to intermolecular NOEs for b3 and b4 of DUA2S (Fig. 4.7). The intermolecular NOE between the 2,6 proton resonances of Phe10 and the b4 resonance of DUA2S was very small (0.3%) yet accurate because of the high signal to noise ratio. Using all these constraints, molecular modeling and full-matrix analysis of the NOE data allowed the structure of the heparin-derived disaccharide to be determined as well as the binding site of the protein (Fig. 4.8) [49]. In this case, the use of selective 1D techniques was necessary in order to obtain NOE data of great accuracy, permitting extraction of kinetic parameters. They were also used to measure changes in J coupling constants upon binding, to obtain NOE data from sugar resonances buried within the protein signals, and to measure very small yet accurate intermolecular NOEs between the sugar and the protein. 4.3.3

NMR of Mixtures

Many samples of biological origin are heterogeneous in nature and difficult to separate. 1D selective methods have been used to determine the structure of minor components, since if the resonances of the minor component can be ob-

71

Detection of an intermolecular NOE between CTX A3 and the disaccharide for the CTX A3:disaccharide 1 : 1 complex at 10 8C and 600 MHz. (a) 1D NOESY (b4, 20 Hz, 300 ms). (b) 1D NOESY (F10 2,6H, 65 Hz, 300 ms) . The dotted lines indicate intermolecular NOEs. The assignments of the proton resonances with significant NOEs are also labeled.

Fig. 4.7

Molecular modeling diagram of the CTX A3/heparin-derived disaccharide complex. CTX A3 is a highly basic protein with a three-fingered bsheet structure. Three lysine residues (K5, K12, K35) located in the protein convex side provide a heparin disaccharide binding region by forming a positive cluster. The protein residues involved in the heparin binding are represented as black sticks and the heparin disaccharide is drawn as thick sticks. Arrows indicate the two intermolecular NOEs between the resonances of the F10 2,6 H and H3b and H4b.

Fig. 4.8

served, they can be selected and used to characterize the minor components. This has been applied in several instances in our laboratory [50–55]. In this next example, 1D selective methods will be applied to the assignments of a mixture of heparin-derived tetrasaccharides (Fig. 4.3) and the measurement of NOEs in the free and bound form with cardiotoxin CTX A3. Heparin-derived tetrasaccharides were obtained from enzymatic depolymerization with Flavobacterium heparinase [56]. The NMR sample of free heparin-derived tetrasaccharide was prepared to reach a final concentration of 15 mM, and the sample for determining the bound conformation of the heparin tetrasaccharide

72


was prepared to a protein/sugar ratio of 1 : 10 (1 mM to 10 mM) (Fig. 4.9). Both samples were dissolved in 500 mL 100% D2O and the sample pH adjusted to 6.0 by titrating with NaOH or HCl after considering the isotope effect with pD = pH * + 0.4. Three major components can be identified by 1D selective techniques. The ratios of the three major components of heparin tetrasaccharides were determined from the integration of the 1D NMR proton spectrum normalized to the intensity of D4 (Fig. 4.9). The depolymerization by heparinase produces a terminal uronate with an unsaturated 4,5 carbon bond (DUA) at the reducing end. Thus, the DUA with 2-O-sulfate (DUA2S) seems to be the common residue shared by the all tetrasaccharide components. The 1D spectrum also reflects the same observation that only one resonance at 6 ppm can be assigned to D4. The integrated intensity of the resonance of D4 was set to 100%, and the other proton intensities were normalized to it. The percentages of the three major compounds were found to be 44 ± 5% for a, 38 ± 5% for b, and 16 ± 3% for c. 1D selective methods were used to assign the three major components in the mixtures and obtain NOE data. As can be seen in Fig. 4.10, with selective methods the multiplet patterns are more clearly observed because of the higher digital resolution than that of standard 2D experiments. Also, for such a complex mixture, chemical shifts of closely related compounds are difficult to differentiate by 2D methods, especially in the ring region between 3 and 4.5 ppm.

Assignments of the three major heparin tetrasaccharides (a, b and c) at the anomeric proton region for (A) the free tetrasaccharide (15 mM) and (B) bound tetrasac-

Fig. 4.9

charide (10 mM) with CTX A3 (1 mM) in D2O at 25 8C and 600 MHz. The labeling of the resonances is according to the structures shown in in Fig. 4.3.

4.3 Examples

Fig. 4.10 Comparisons of 1D slice of TOCSY and 1D selective TOCSY (left) and 1D slice of NOESY and 1D selective NOESY (right) for C1c of the heparin tetrasaccharide mixture. The corresponding 2D TOCSY and NOESY spectra are shown, and the cross-section of

1D slice of C1c was taken from the F1 dimension at 5.36 ppm. Mixing times of 90 ms and 600 ms were used in TOCSY and NOESY, respectively. The proton resonances for the Bc and Cc residues are labeled in the 1D selective spectra.

The individual spin systems for each residue in the mixture is presented in Fig. 4.11 and the chemical shifts in Tab. 4.5. The DUA residue (D) is common to all tetrasaccharide components and its chemical shifts are very distinct from the other residues. C1b, A1b, C1a and C1c are isolated and can be selectively excited. A1a and A1c overlap as do B1a and B1c. The type of sugar residue (GlcNS6S, GlcNS, IdoA2S, GlcA) can be identified by the multiplet pattern and chemical shifts [56]. The strategies used to identify the residues and their sequences will now be presented. In Fig. 4.12, the preliminary experiments showing overlap of the anomeric resonances experiments are shown. In Figs. 4.13 to 4.15 the final experiments used to identify each individual tetrasaccharide are shown. Sequence D-C: D is common to all the tetrasaccharides. Comparison of the 1D TOCSY for D1 and the 1D NOESY for D1 revealed a major inter-residue NOE at 3.8 ppm (Fig. 4.12 b). Resonances in the 1D NOESY that do not match up with any of the 1D TOCSY resonances can only arise from an inter-residue NOE. Hence, in order to identify the aglycon resonances, a 1D NOESY-TOCSY was done on this resonance labeled C4 (Fig. 4.12 c). All resonances of the aglycon were then detected along with three anomeric resonances labeled as C1a, C1b and C1c (Fig. 4.12 c). Then 1D TOCSYs on these resonances will reveal each individual spin system (Fig. 4.11 c–e). An array of mixing times from 30 ms to 150 ms in

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74

4 NMR of Carbohydrates: 1D Homonuclear Selective Methods Fig. 4.11 Isolated spin systems for each residue in a mixture of heparin-derived tetrasaccharides by means of 1D TOCSY or 1D TOCSY-TOCSY: (a) 1D proton spectrum of tetrasaccharides (15 mM) at 25 8C and 600 MHz, (b) 1D TOCSY(D1abc, 15 Hz, 90 ms), (c) 1D TOCSY(C1a, 10 Hz, 150 ms), (d) 1D TOCSY(C1b, 25 Hz, 150 ms), (e) 1D TOCSY(C1c, 15 Hz, 150 ms), (f) 1D TOCSY-TOCSY(A1ac, 10 Hz, 150 ms; A5a, 50 Hz, 150 ms), (g) 1D TOCSY(A1b, 10 Hz, 150 ms), (h) 1D TOCSY(A5c, 20 Hz, 150 ms), (i) 1D TOCSY-TOCSY(B1ac, 50 Hz, 150 ms; B4a, 25 Hz, 150 ms), (j) 1D TOCSYTOCSY(B1ac, 50 Hz, 150 ms; B4c, 25 Hz, 150 ms), (k) 1D TOCSY(B1b, 40 Hz, 60 ms).

Tab. 4.5 1H chemical shifts a) of the three major compounds for a mixture of heparin-derived tetrasaccharides in aqueous solution

D Ca Ba Aa Cb Bb Ab Cc Bc Ac

DUA2S GlcNS6S IdoA2S GlcNS6S GlcNS6S GlcA GlcNS6S GlcNS6S IdoA2S GlcNS

H1

H2

H3

H4

H5

H6

H6'

5.495 5.416 5.203 5.430 5.555 4.589 5.448 5.357 5.196 5.433

4.612 3.285 4.303 3.245 3.292 3.372 3.260 3.286 4.293 3.220

4.308 3.631 4.198 3.682 3.631 3.839 3.694 3.645 4.219 3.671

5.984 3.823 4.097 3.732 3.823 3.771 3.721 3.824 4.065 3.698

4.024 4.765 4.117 3.976 3.812 4.142 4.008 4.796 3.917

4.237

4.341

4.290 4.188

4.350 4.333

4.330 4.231

4.330 4.342

3.860

3.860

a) Measured at pH 6.0, 25 8C and 100% D2O, with an estimated error of ± 0.002 ppm.

steps of 15 ms can then be used to assign the spins and distinguish the H3 from the H4 resonance, since their multiplet pattern is the same. Based on a comparison of the shifts with known heparin structures [56], these residues were identified as GlcNS6S. Tetrasaccharide Da-Ca-Ba-Aa: Once C1a has been identified, a 1D NOESY for C1a revealed the aglycon NOEs (Fig. 4.13 b). The NOE peak at 4.2 ppm caused by inter-residual effect was selectively excited to perform 1D NOESY-TOCSY(C1a, B3a) (Fig. 4.13 c). The 1D NOESY-TOCSY identifies the anomeric proton of Ba residue

4.3 Examples

Fig. 4.12 1D selective spectra of a mixture of heparin-derived tetrasaccharides showing the need for 1D NOESY-TOCSY and 1D TOCSYNOESY and 1D TOCSY-TOCSY to complete the assignments because of overlap of anomeric resoances: (a) 1D proton spectrum of tetrasaccharides (15 mM) at 25 8C and 600 MHz, (b) 1D NOESY(D1, 20 Hz, 600 ms), (c) 1D NOESY-TOCSY(D1, 20 Hz, 600 ms; C4, 100 Hz, 90 ms) with labeling of C1a, C1b, and C1c. Spectra in (b, c) were obtained from the CTX A3/tetrasaccharide complex since the NOEs were bigger and the NOESY-TOCSY more efficient than for the tetrasaccharide. (d) 1D TOCSY(B1ac, 20 Hz, 150 ms) indicated the presence of two spin systems of unequal proportions seen most clearly for the resonances at 4.097 ppm (B4a) and 4.065 ppm (B4c). (e) 1D NOESY(B1ac, 20 Hz, 600 ms) also showing heterogeneity in the NOE spectrum. The large NOE at 3.7 ppm is from the A4ac resonances. (f) 1D NOESY-TOCSY(B1ac,

20 Hz, 600 ms; A4ac, 100 Hz, 90 ms) showing overlap of the anomeric aglycon resonances (A1ac) and detection of Aa and Ac resonances. (g) 1D TOCSY (A1ac, 10 Hz, 150 ms) showing a similar TOCSY pattern to the previous experiment in (f), indicating that A1a and A1c do overlap. From the shape of their multiplet, 5a and 5c are putatively assigned. Ca resonances indicated by asterisks are also observed due to partial excitation of C1a. (h) 1D TOCSY(B4a, 50 Hz, 150 ms). The B4a shaped pulse was selected from the spectrum in (d). The mixing time was optimized for maximum transfer to B1a, in order to perform later a 1D TOCSY-NOESY on B1a. (i) Similar 1D TOCSY to that in (h) but with B4c showing that the B1c and B5c can be separated from the B1a and B5a in order to observe inter-residue NOEs using 1D TOCSY-NOESY for the Ba-Aa and Bc-Ac sequences, although A1ac overlap and B1ac overlap.

(5.2 ppm). The resonances observed in Fig. 4.13 c matched with the resonances from the 1D TOCSY for the signal at 5.2 ppm (Fig. 4.12 d). But this spectrum (Fig. 4.12 d) also revealed overlap of two anomeric resonances at 5.2 ppm and two spin systems of unequal proportion. From this spectrum, the resonance labeled 4a was used to resolve the spin pattern for Ba by performing a 1D TOCSY-

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Fig. 4.13 Identification of Da-Ca-Ba-Aa in a mixture of heparin-derived tetrasaccharides. (a) 1D proton spectrum of tetrasaccharides (15 mM) at 25 8C and 600 MHz. (b) 1D NOESY(C1a, 10 Hz, 600 ms). The only major intra-residue NOE is for C2. Other NOEs are from the aglycon Ba resonances. (c) 1D NOESY-TOCSY(C1a, 10 Hz, 600 ms; B3a, 90 Hz, 90 ms) identifying Ba resonances that match up exactly with those in (d), the 1D

TOCSY(B5a, 30 Hz, 150 ms). (e) 1D TOCSYNOESY(B4a, 50 Hz, 150 ms; B1a, 100 Hz, 600 ms) to detect the B1a NOEs with the Aa resonances, since B1a and B1a overlap The anomeric resonance marked with an asterisk is residual signal from the first 1D TOCSY step (Fig. 4.12 h). The aglycon NOEs in (e) only match up with the resonances from the 1D TOCSY-TOCSY(A1ac, 10 Hz, 150 ms; A5a, 50 Hz, 150 ms) shown in (f).

TOCSY(B1a; B4a) (Fig. 4.11 i). B5a was then found to be isolated and could be used also to confirm the assignment (Fig. 4.13 d). The presence of only 5 spins and its JHH values identified this residue as IdoA2S. B1a overlaps with another minor anomeric resonance (later assigned as B1c). The 1D NOESY for the resonances of B1ac revealed the major aglycon resonances labeled as A4ac in Fig. 4.12 e. A 1D NOESY-TOCSY using these resonances, B1ac and A4ac, revealed only one aglycon anomeric resonance at 5.43 ppm (Fig. 4.12 f). This means that both the A1a and A1c resonance also overlap. This was confirmed from the 1D TOCSY(A1ac) where the spin pattern observed is similar to the previous one for 1D NOESY-TOCSY(B1ac, A4ac) (Figs. 4.12 g and 4.12 f). In order to identify the aglycon NOEs for B1a only, this resonance must be isolated from the overlapping B1c resonance. This was done by means of a 1D TOCSY from B4a (4.1 ppm) (Fig. 4.12 h). It was chosen instead of the isolated B5a since the magnetization transfer from B5a to B1a was too weak. Although other resonances were excited when choosing B4a, the B1a resonance was isolated. As seen for the 1D TOCSY-NOESY(B4a, B1a) in Fig. 4.13 e, the spectrum is devoid of NOEs from B1c (Fig. 4.12 e). Artifacts in the anomeric region are due to residual spins generated from the 1D TOCSY(B4a) in Fig. 4.12 h, but they are of no consequence. This experiment also helped assign the A6'a NOE. Although there are

4.3 Examples

some minor artifacts, it does show that when the needs arise individual spin systems can be isolated. From the 1D TOCSY(A1ac) in Fig. 4.12 g, two isolated spins putatively assigned as 5a and 5c based on their multiplet shape could be used to isolate each individual spin system by means of 1D TOCSY-TOCSY experiments (A1ac, A5a) (Fig. 4.13 f). Because of the match of the resonances of A4a, A6'a between Fig. 4.13 e and 13 f, residue Aa can be confirmed and identified as GlcNS6S. Tetrasaccharide Db-Cb-Bb-Ab: The sequence Db-Cb-Bb-Ab could easily be established by means of comparing the 1D NOESY, 1D NOESY-TOCSY and 1D TOCSY for Cb-Bb and then for Bb-Ab (Fig. 4.14), since the anomeric resonances for Cb, Bb and Ab did not overlap with any other signals. Since the vicinal couplings for all the spins are similar (8–10 Hz), the assignments for Bb were verified by means of spin simulation and 1D TOCSY experiments with various mixing times. Since the line intensities for each multiplet are reproduced correctly by spin simulation, the 1D TOCSY spectrum in Fig. 4.11 k could be reproduced correctly. The residue Bb was identified as GlcA, instead of IdoA, after comparing the chemical shifts of B1b (4.59 ppm) and B2b (3.37 ppm) with the shifts of known heparin structures [56]. The structure of component b was determined as DUA2S-GlcNS6S–GlcA–GlcNS6S. Tetrasaccharide Dc-Cc-Bc-Ac: The assignment strategy for this sequence was similar to that for Da-Ca-Ba-Aa. The Cc-Bc sequence was established by means finding

Fig. 4.14 Identification of Db-Cb-Bb-Ab in a

mixture of heparin-derived tetrasaccharides: (a) 1D proton spectrum of tetrasaccharides (15 mM) at 25 8C and 600 MHz, (b) 1D NOESY(C1b, 15 Hz, 600 ms). The only major intra-residue NOE is for C2 Other NOEs are from the aglycon Bbresonances. (c) 1D NOESY-TOCSY(C1b, 50 Hz, 600 ms; B4b, 35 Hz, 90 ms) identifying Bb resonances that

match up exactly with those in the 1D TOCSY(B1b, 20 Hz, 90 ms) shown in (d). The 1D NOESY(B1b, 20 Hz, 600 ms) spectrum in (e) identifies inter-residue NOEs at 3.7 ppm which are then used to detect the Aa resonances by means of a 1D NOESYTOCSY(B1b, 20 Hz, 600 ms; A4b, 60 Hz, 90 ms).

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out which resonances for the individual residues (Fig. 4.11) matched those in the 1D NOESY for C1c (Fig. 4.15 b) and those of the aglycon resonances in the 1D NOESY-TOCSY(C1c, B3c) (Fig. 4.15 c). 1D TOCSY of B5c (Fig. 4.15 d) matched with the resonances in Fig. 4.15 c exactly, identifying the residue of Bc. Since B1a and B1c overlapped, the aglycon NOEs for B1c were detected by means of the 1D TOCSY-NOESY(B4c, B1c) (Fig. 4.15 e). The only resonances from the 1D TOCSY spectra in Fig. 4.11 that matched with these aglycon NOEs were those from residue A1c. Since it was found that the 5c resonance was isolated in the 1D TOCSY(A1ac) in Fig. 4.12 g, it was used to detect all the spins for that residue (Fig. 4.15 f). The structure of component g was determined as DUA2S-GlcNS6SIdoA2S-GlcNS. Hence, a judicious combination of 1D TOCSY, 1D NOESY, 1D TOCSY-TOCSY, 1D NOESY-TOCSY and 1D TOCSY-NOESY can be used to assign fairly complex mixtures which have very close structural similarities and overlapping anomeric resonances. The general strategy for the assignment was to compared the 1D TOCSY(H1g) to the 1D NOESY(H1g) for the glycon anomeric resonance H1g. This will identify the inter-residue NOEs on the aglycon. Then a 1D NOESYTOCSY (H1g, NOEa) is done where NOEa is an inter-residue NOE for H1g. This will identify some resonances for the spin system of the aglycon. The resonances from 1D TOCSY (H1a) for the aglycon must then match up with these from the 1D NOESY-TOCSY (H1g, NOEa). When there is overlap of two anomeric reso-

Fig. 4.15 Identification of Dc-Cc-Bc-Ac in a

mixture of heparin-derived tetrasaccharides: (a) proton spectrum of tetrasaccharides (15 mM) at 25 8C and 600 MHz, (b) 1D NOESY(C1c, 20 Hz, 600 ms). The only major intra-residue NOE is for C2. Other NOEs are from the aglycon Bc resonances. (c) 1D NOESY-TOCSY(C1c, 20 Hz, 1s; B3c, 100 Hz, 90 ms) identifying Bc resonances that match

up exactly with those in the 1D TOCSY(B5c, 20 Hz, 150 ms) shown in (d). B1a and B1c overlap, so a 1D TOCSY-NOESY(B4c, 50 Hz, 150 ms; B1c, 100 Hz, 600 ms) was done to detect the B1c NOEs with the Ac resonances (e). These only match up with the resonances from the 1D TOCSY(A5c, 20 Hz, 150 ms) shown in (f).

4.3 Examples

nances, 1D TOCSY-TOCSY is used to resolve the two spin systems by finding isolated resonances for each residue. The 1D TOCSY-NOESY is used to obtain an NOE spectrum for each individual anomeric resonance, even though they overlap. Detection of transferred NOEs for a mixture of tetrasaccharides and CTX A3: Once the assignment of each individual residue has been made, the bound conformation of this tetrasaccharide mixture with a cardiotoxin A3 can be investigated. For instance, the changes in chemical shifts between the two samples were observed for the sugar resonances, especially for the H5 resonances of the IdoA2s residue (Fig. 4.9 b). The change of J values also can be monitored i.e., the reduction of J12 of residue D upon binding to CTX A3 (Fig. 4.9 b). Most importantly, the changes of NOEs can be estimated accurately by 1D techniques. In Fig. 4.16, the NOEs for B1a, B5a and C1a for the tetrasaccharide mixture and the tetrasaccharide mixture bound to CTX A3 are shown. Since the complete assignments are known, even though the B1a and B1c overlap, if the need arises, the NOEs can be extracted by use of spectral deconvolution or other lineshape analysis method. The 1D NOESY for B5a reveals that the IdoA2s conformation is probably different in the bound form because of the appearance of the B5a-B2a NOE. For the 1D NOESY for C1, the ratio of the inter-residue NOE to the intra-residue NOE has changed, an indication that the bound conformation is different from that of the free form. In order to quantify these results, further experiments need to be done as for the disaccharide binding to the cardiotoxin. However, they do indicate the potential of 1D selective techniques for the study of the bound conformations of a mixture of compounds.

Fig. 4.16 Comparison of NOE spectra of Da-Ca-Ba-Aa for the tetrasaccharide : CTX A3 (1 : 10) complex (b, d, f) and tetrasaccharide (c, e, g): (a) proton spectrum of tetrasaccharide : CTX (1 : 10) complex at 25 8C and 600 MHz, (b) 1D NOESY(B1ac, 15 Hz, 300 ms), (c) 1D NOESY(B1ac, 20 Hz, 600 ms), (d) 1D NOESY(B5a, 25 Hz, 300 ms), (e) 1D NOESY(B5a, 25 Hz, 600 ms), (f) 1D,NOESY(C1a, 10 Hz, 300 ms), (g) 1D NOESY(C1a, 10 Hz, 600 ms). In (f) and (g) the C2 resonance has been normalized to the same height.

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4.3.4

Measurement of Proton-Proton Residual Dipolar Coupling Constants in Oligosaccharides

Understanding of intermolecular interactions of carbohydrates requires a thorough description of their three-dimensional structures. Such structures are mostly obtained by high-resolution NMR spectroscopy [57–59]. A traditional source of spatial restraints used in NMR structure calculations, the nuclear Overhauser effect (NOE) [60], has been supplemented during the last decade by additional NMR parameters, which promise to increase the accuracy of conformational analysis of carbohydrates. Residual dipolar coupling constants are the latest addition to the arsenal of such parameters [61, 62]. The size of a dipolar coupling constant depends, beside other factors, on the distance between interacting dipoles and the orientation of the internuclear vector with respect to a common molecular axis. Consequently, the dipole-dipole interaction encodes information on both the angular and radial distributions of internuclear vectors and can be used as a long range structural sensor. By imposing a very weak orientation of molecules by dissolving them in dilute liquid crystalline media, dipolar couplings are scaled down compared to those seen in solid-state NMR spectra [62–72]. Networks of residual dipolar couplings are limited, and their sizes are comparable with typical J values. Consequently, residual dipolar couplings can be measured in high-resolution NMR spectra with relative ease using methods similar to those for measurement of scalar coupling constants. Initial applications of dipolar coupling constants in conformational analysis of carbohydrates were focused on relatively rigid oligosaccharides [73–77]. Dipolar couplings of ligands in the bound state, which are justifiably presumed to be rigid, were also measured, taking advantage of the weak affinity of many protein-carbohydrate complexes [78–81]. For flexible carbohydrates, the interpretation of dipolar couplings is more complicated [82–84]. Methods have been proposed describing the direction and level of ordering forces from the point of view of a coordinate frame fixed in a rigid molecular fragment [85–87]. In oligosaccharides, such rigid bodies are the individual monosaccharide units. A minimum of five dipolar coupling constants are required to perform such an analysis. Unfortunately, the one-bond proton-carbon residual dipolar coupling constants, which are straightforward to measure, do not provide sufficient information because of near parallel orientations of many CH vectors in pyranose rings. Proton-proton dipolar couplings (DHH) are an obvious choice for supplying the missing parameters. So far, the proton-proton residual dipolar coupling constants have been obtained from the ratio of the intensities of the diagonal and cross peaks in 2D COSY spectra [88] and from E.COSY spectra [84]. The precision of both methods is limited by the digital resolution of two-dimensional techniques and the possibility of overlap, which increases with increasing orientation of samples. As the 1H spectra of carbohydrates are rich in overlapping cross peaks even in isotropic media, only a limited set of DHH values is typically obtained from these experiments.

4.3 Examples

4.3.5

1D Directed-COSY, 1D Directed-COSY-COSY and 1D-Directed TOCSY-COSY

We have developed a general approach for mapping the network of residual dipolar proton-proton coupling constants in carbohydrates, which is applicable to a broad range of molecular alignments. These techniques are based on a selective one-dimensional COSY experiment [89] and provide coupling constants by fitting the peak intensities obtained in a series of experiments to a known transfer function [90]. They belong to J-modulated spectroscopy [90–92], an approach which yields very precise values of coupling constants regardless of whether the signal multiplets are resolved or not. Indeed, the residual dipolar proton-proton coupling constants of oligosaccharides in partially oriented media are usually unresolved. This is the case in very weakly aligned systems, where such coupling constants are typically smaller than the spectral line widths, but also in more strongly aligned samples. In the latter instance the dipolar couplings between adjacent protons are larger, but there are also numerous smaller, long-distance dipolar couplings present giving rise to broad, unresolved multiplets resembling 1H spectra of polysaccharides. This is a misleading observation since, regardless of the strength of the alignment, the spin-spin relaxation times of oligosaccharides are very similar to those of pure samples. Consequently, pulse sequences with long evolution intervals can be used for the determination of DHH also in strongly oriented samples. The proposed techniques belong to the family of 1D experiments, and thus require some sort of selective excitation. This requirement was addressed in several ways by using selective pulses [93], single and double pulsed field gradient spin-echoes (SPFGSE and DPFGSE) [28], and/or concatenation of polarization transfer steps [4, 16, 32]. Undesirable effects of passive coupling constants were removed by the application of double-selective pulses [34, 35, 94]. These building blocks were combined in such a manner that a selection of a single pair of interacting protons was achieved, resulting in a determination of coupling constants with a very high precision. The basic pulse sequence is shown in Fig. 4.17 a. We refer to this sequence as 1D directed-COSY. A short initial SPFGSE is used to select the magnetization of proton k. During the following variable SPFGSE the coupling between protons k and l evolves, while the effective evolution of all the other coupling constants of proton k is suppressed. A double-selective 180 8 pulse, applied to protons k and l amid the T interval, achieves this. The amount of magnetization which is transferred to proton l during the gradient selected COSYstep is proportional to the length of the T interval. The intensity of the auto (Ik) and cross peaks (Il) is a simple function of T: eff

0 Ik Ikk cospKkl T Dk sin2 0:5p Kkl T Dk 1cosbexp T Dk =T2k 1 eff

Il Ikl0 sinpKkl T Dl exp T Dl =T2k ;

2

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Fig. 4.17 Pulse sequences for the determination of residual dipolar proton-proton coupling constants. Full narrow bars represent 908 pulses. Pulses indicated by a single or double open Gaussian envelope are single- or double-selective 1808 Gaussian pulses, respectively. Selectively inverted (excited) protons are enclosed in circles. Unless indicated otherwise, pulses are applied along the x axis. Parts of the pulse sequences enclosed in square brackets are optional: RD – relaxation delay, s1 = 1.2 ms, T – variable delay, 2sb and 2sr – refocusing delays, sg = 1 ms. All pulsed field gradients were 1ms long and are represented by open (applied along z axis) and filled (applied along y axis) rectangles, respectively. (a) 1D directed-COSY experiments. The following phase cycling was used:

u1 = x, y; u2 = 2x, 2(–x); w = x, –x. (b) 1D directed-COSY-COSY. The first selective pulse marked by a filled Gaussian curve is a 908 Gaussian pulse: 2sa–0.5G90 j £ 0.5/Jjk or in the case of an optional double-selective 1808 Gaussian pulse applied amid the defocusing 180 period 2sa–0.5G90 j – Gj,k = 0.5/Jjk and 2sb– 180 90 Gj,k = 0.5/Jjk, where Gj and G180 j,k are the lengths of j-selective 908 Gaussian and j, k double-selective 1808 Gaussian pulses, respectively. The following phase cycling was applied: u1=x, –x; u2 = 4y, 4(–y); u3 = 8x, 8y; u4=2x, 2(–x) and w = 4(x, –x), 4(–x, x). (c) 1D directed-TOCSY-COSY. The initial 908 selective pulse was a quiet-SNEEZE pulse [33]. G3' = 1.2 · G3 and the following phase cycling was used: u1 = x, –x; u2 = 4x, 4y; u3 = 8x, 8y; u5 = 2x, 2(–x) and w = 2(x, –x), 4(–x, x), 2(x, –x).

0 where Ikk and Ikl0 are the scaling factors, Dk and Dl describe the effective evolution of coupling Kkl during the double-selective pulse, b is the effective flip angle of eff proton I and T2k is the effective relaxation time. Here K is either J or J + D, standing for scalar or the sum of scalar and dipolar coupling constants. When the coupling is very small compared to the linewidth of the signal of proton l, the inten-

4.3 Examples

sity of a cross peak can be enhanced significantly by inclusion of a refocusing interval with a k, l double selective pulse prior to the acquisition. For weak alignments, the residual dipolar coupling constants may be very small, and it is also important to measure precisely all scalar coupling constants in isotropic media so that the dipolar contribution to the overall splitting can be determined accurately. The first example of the use of 1D directed-COSY shows the determination of J13 coupling constants of a-d-glucopyranose in isotropic media. The experiment starts with an acquisition of a 1D COSY spectrum using a pulse sequence of the 1D directed-COSY modified by replacing both k, l double selective 180 8 pulses by nonselective 180 8 1H pulses. The role of the refocusing interval (sr*1.5 ms) in this modification is to eliminate the chemical shift evolution caused by the refocusing gradient after the 90 8 polarization transfer pulse. Such a 1D COSY spectrum contains, at least in principle, information about all coupling constants of a selectively excited proton. Unfortunately, in such spectra passive coupling constants modulate intensities of all cross peaks in a complicated manner, causing a significant reduction in the signal-to-noise ratio and making their analysis difficult and inaccurate. The main purpose of this experiment is therefore to identify all J or D coupled partners of the selectively excited proton k. Returning to our example, a 1D COSY spectrum of a-d-glucopyranose in isotropic solution with selective excitation of H1a is shown in Fig. 4.18 a. This spectrum is dominated by two signals, those of protons H1a and H2a, since the J12 is the only large coupling constant of proton H1a. When the same experiment is repeated with progressively longer delay T, additional signals start appearing (see inset of Fig. 4.18 a) because of the evolution of small coupling constants of proton H1a. In general, it is advisable to acquire several 1D COSY spectra, initially using very short values of T focusing on large coupling constants. Then, using progressively longer time intervals, ideally set at local maxima of the cosine product of large coupling constants, Kjk [P j cos (p Kjk T)]. The later experiments will reveal protons which have small coupling constants with proton k. In the case of measurements in oriented media, many of these will be dipolar coupling constants. For a-d-glucopyranose, such a spectrum (Fig. 4.18 b), acquired using T = 2/J12 [cos (p Kjk T) = cos (p ´ 3.75 ´ 0.5) = 0.92], shows an intense signal due to transfer of magnetization via at least three small coupling constants. Once the resonance frequencies of coupled spins were identified, appropriate double-selective pulses (H1a, H3a in our example) can be created for use in 1D directed-COSY experiments. In these experiments the magnetization is transferred to only one of the long range coupled protons (H3a in Fig. 4.18 c). When the signal of proton l is strongly attenuated by cancellation of its antiphase component, i.e. for small coupling constants or broad multiplets, it is advisable, at least partially, to refocus the coupling constants prior to acquisition. In the absence of relaxation the refocusing interval 2 sr could be set to *0.5/J. In practice, it is optimized by repeating the experiment while keeping the T interval constant and looking for the maximum intensity of proton l. A k, l double selective 180 8 pulse needs to be applied in the middle of the refocusing interval, although it might appear that with only two signals in the spectrum, a nonselective pulse could be used instead. The point is that none of the coupled partners of proton l other than k can be inverted, otherwise the evolu-

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Fig. 4.18 Setting up a 1D directed-COSY experiment. An example of determination of the J13 in a-D-glucopyranose. Gaussian envelopes represent inversion profiles of applied Gaussian pulses. (a) 1D COSY with selective excitation of H1a acquired using pulse sequence of Fig. 4.17 a with both 1808 kl double selective pulses replaced by nonselective 1808 pulses. The main spectrum was acquired using T = 0.1 s; the partial spectra shown in the inset were obtained using T =

0.1–0.7 s. The H1a selective pulse was a 45 ms Gaussian pulse, s1 = sr = 1.2 ms. (b) the same as (a) but with T = 0.5 s. (c) Non-refocused 1D directed-COSY spectrum with directed-COSY transfer from H1a to H3a. A double selective 1808 Gaussian pulse applied to H1a and H3a was 45 ms long, T = 0.7 s. (d) is the same as (c) but acquired with inclusion of a refocusing interval (sr = 0.6 s). Spectra (c) and (d) were plotted using identical vertical scales.

tion of additional coupling constants of proton l would prevent the creation of an inphase multiplet. A significant increase in intensity of proton H3a was observed in the refocused version (Fig. 4.18 d) compared with the non-refocused spectrum (Fig. 4.18 c). This is due to the fact that the coupling constant J13 = 0.54 Hz is approximately three times smaller than the line width of the H3a signal. Once the parameters of a 1D directed-COSY experiment have been optimized, a series of spectra with variable T interval can be acquired. Fig. 4.19 a shows H3a multiplets from twenty-five 1D directed-COSY spectra acquired using the evolution interval, T, from 0.1 to 2.5 s. The intensity of protons H1a (Fig. 4.19 b) ob-

4.3 Examples

Fig. 4.19 Signals as a function of the evolution interval T. (a) and (b) show multiplets from the 1D directed-COSY spectrum of a-D-glucopyranose in D2O acquired with 25 ms (H1a) and 45 ms double selective (H1a, H3a) 1808 Gaussian pulses. T = 0.1–2.5 s, sr = 0.6 s. The plotted signal intensities in (b) were scaled down three times compared to those in (a). The inset in (a) shows a comparison of maximum signals acquired with and without the refocusing interval. The inset in (b) shows the result of the fitting of the H1a and H3a signals according to Eqs (1) and (2); J13 = 0.45 Hz. (c) The 1D directed-COSY spectrum of maltotriose in phage (reducing end, a-anomer) acquired with 22.5 ms selective (H1a) and 7.5 ms dou-

ble selective (H1a, H3a), H5a 1808 Gaussian pulses. Refocusing was not applied. T = 0.1– 1.4 s. Inset shows the analysis of H1, H3 and H5 signals using Eqs (3–5); K13 = –0.43 Hz, K15 = 1.43 Hz. (d) The 1D directed-COSYCOSY spectrum of maltotriose in phage (reducing end, a-anomer) acquired using the polarization pathway H1a ? H2a ? H4a. A 908 Gaussian pulse (37.6 ms) was applied to H1a, 2sa = 74 ms, sb = 90 ms. No pulse was applied during 2sa. Double selective 1808 Gaussian pulses were 30 ms (H1a, H2a) and 9 ms (H2a, H4a) long. Refocusing prior to acquisition was not used. T = 0.1–1.25 s. Inset shows the analysis of H2a and H4a according to Eqs (1) and (2); J24 = 2.61 Hz.

tained from non-refocused experiments was three times that of the H3a. When modulated by only one frequency, auto peaks in 1D directed-COSY spectra are the most suitable for the precise measurement of very small coupling constants. The inset of Fig. 4.19 b shows experimental signal intensities fitted to Eqs. (1) and (2). Details of such analysis will be discussed later. The next example shows measurement of K13 and K15 for the reducing a-d-glucopyranose of the maltotriose in Pf1 phage [56]. In this molecule, the proton resonances of H3a and H5a were partially overlapped, and therefore a semiselective 180 8 pulse simultaneously inverting both protons was used. Under these circumstances, the transfer functions given by Eqs. (1) and (2) need to be modified in order to take into account an effect of a passive spin. The signal intensities of H1a, H3a and H5a (Fig. 4.19c) were simultaneously fitted, as shown in the inset of Fig. 4.19 c, using Eqs. (3–5).

85

86

4 NMR of Carbohydrates: 1D Homonuclear Selective Methods 0 Ik Ikk cospKkl T Dk sin2 0:5pKkl T Dk 1 cos bcospKkm T Dk eff

sin2 0:5pKkm T Dk 1 cos c exp T Dk =T2k Il Ikl0 sin pKkl T Dl cos pKkm T Dl

3 4

eff

sin2 0:5pKkm T Dl 1 cos c exp T Dl =T2k 0 sin pKkm T Dm cos pKkl T Dm Ikm Ikm eff

sin2 0:5pKkl T Dm 1 cos b exp T Dm =T2k

5

The meaning of symbols is analogous to those used in Eqs. (1) and (2), c is the effective flip angle of proton m. In complex carbohydrates typically only anomeric protons are amenable to a straightforward selective excitation by selective pulses. Coupling constants of other ring protons can still be measured provided that their magnetization can be obtained by RELAY or TOCSY transfers. Examples are shown in 1D directed-COSYCOSY and 1D directed-COSY-TOCSY (Figs. 4.17 b, c). The first COSY step of a 1D directed-COSY-COSY experiment starts with a 90 8 selective 1H pulse on proton j and is followed by a COSY transfer to proton k. If j is a complicated multiplet it may be impossible to set the evolution interval 2sa so that a high proportion of magnetization is transferred to proton k. A double selective 180 8 pulse could be applied to protons j, k amid the defocusing interval in order to refocus all other couplings than Jjk, increasing the efficiency of the transfer significantly. Following the polarization transfer pulse, the inphase magnetization of proton k is created during the 2sb interval. The 180 8 jk double-selective pulse surrounded by pulsed field gradients also serves the purpose of selecting only the magnetization of these two protons. Starting with the variable T interval, the rest of the pulse sequence is identical to that of the 1D directed-COSY. Setting up a 1D directed-COSY-COSY experiment starts with optimization of the initial COSY transfer from proton j. This involves deciding whether the initial 180 8 j, k double-selective pulse is required or not and accordingly finding the optimum length of 2sa delay by acquiring a series of 1D COSY spectra. The 2sb inter180 val can be shortened from its theoretical value of 0.5/Jjk–Gj,180 k , where Gj, k is the length of the double selective Gaussian pulse, in order to minimize the relaxation. From this point onwards the optimization of the experiment is identical to setting up the 1D directed-COSY, and the k, l double-selective pulses are initially replaced by nonselective 180 8 pulses for mapping interactions of k proton. The 1D directed-COSY-COSY experiment is illustrated by measurement of the J24 coupling constant of the reducing a-d-glucopyranose of maltotriose in phage. During the initial COSY step the magnetization was selectively transferred from the H1a to the H2a proton. Protons H2a and H4a resonate close to each other; therefore a 9 ms Gaussian pulse was used for their simultaneous inversion. Fig. 4.19 d shows multiplets of these protons as a function of the evolution interval T, and the analysis with Eqs. (1) and (2) of H2a and H4a signals is given in the inset.

4.3 Examples

When starting on anomeric protons, the magnetization in a 1D directed-COSYCOSY can only be transferred to H2 protons. Mapping of the dipolar interactions of protons H3, H4 and H5 therefore requires a multiple step RELAY or TOCSY transfers to precede the 1D directed-COSY step. This approach is illustrated by the pulse sequence of a 1D directed-TOCSY-COSY, which is obtained by replacing the initial nonselective 90 8 pulse of 1D directed-COSY by a selective TOCSY transfer [32]. The rest of both sequences is identical. Using the determination of the coupling constant of proton H3a of the reducing a-d-glucopyranose of maltotriose in phage as an example, the initial TOCSY transfer from H1a was optimized to obtain maximum in-phase magnetization of proton H3a (Fig. 4.20 b). As the next step in optimizing the pulse sequence, the magnetization of H3a was selected during a short (2s1) gradient spin-echo (Fig. 4.20 c). From this point onwards the optimization of the experiment proceeds as described for the 1D directed-COSY. The initial TOCSY transfer to H3a was not particularly efficient, with only 10% of the H1a signal for a mixing time of 65 ms. Nevertheless, this was enough to measure J34 with high accuracy for which the experiment was consequently optimized. Figs. 4.20 d and 4.20 e show multiplets of H3a and H4a, respectively acquired in a series of 1D directed-TOCSY-COSY experiments with T as a parameter.

Fig. 4.20 1D directed-TOCSY-COSY. (a) A partial 1H spectrum of maltotriose; (b) 1D TOCSY spectrum acquired using the first part of the pulse sequences of Fig. 4.17 c. H1a was selectively excited by a 107.8 ms quietSNEEZE pulse, mixing time of 65 ms yielding 10% transfer efficiency; (c) 1D TOCSY as in (b) but followed by 36 ms 1808 Gaussian

pulses applied to H3a; (d) and (e) are H3 and H4 multiplets, respectively, from a series of 1D directed-TOCSY-COSY experiments acquired using the pulse sequence of Fig. 4.17 c. Parameters as in (a) and (b); T = 0.02–0.5 s; a double selective 1808 Gaussian pulse (H3a, H4a) was 45 ms long.

87

88


Please note that the first COSY and TOCSY transfers in 1D directed-COSYCOSY and 1D directed-TOCSY-COSY experiments were not gradient selected, in order to avoid loss of half of the signal. The final COSY transfer on the other hand was gradient selected, i.e. only half of the signal was obtained compared to a phase cycled experiment. The main reason for this choice was that the phase of proton k varies significantly depending on the length of the T interval (see Fig. 4.19 b). Such phase modulation in a phase-cycled experiment is translated by the polarization transfer pulse into amplitude modulation and superimposed on top of the desired amplitude modulation because of evolution of couplings. Such superposition of two amplitude modulations is difficult to separate and is best avoided. When gradients are used for coherence selection the phase change acquired by proton k during the evolution interval T is transferred to proton l. On the other hand, the phase and amplitude modulations are easily separable, as will be shown in the next section. 4.3.6

Evaluation of Coupling Constants from Experimental Multiplets, Sign Determination and Parameterization of the Alignment Tensor

Signals acquired in 1D directed-COSY experiments are modulated in phase and amplitude; however, only the latter modulation reflects the value of the coupling constant used for polarization transfer. In order to separate these two effects, the following procedure has been adopted. FIDs are zero filled (0.09Hz/point or better) before the Fourier transformation, and a small region containing only the multiplet of interest is extracted from a series of spectra, inverse Fourier transformed. The most intense signal of the series is selected and assigned a role of a reference spectrum, V1 v11 ; v12 ; . . . ; v1n , where n runs through all the selected points. A second spectrum, V2 v21 ; v22 ; ; v2n , identical to V1 is created and phase-shifted by 90 8. Any other experimental spectrum Yexper y1 ; y2 ; . . . ; yn from the same series can then be expressed as: Yexper IT V1 cos a V2 sin a ;

6

where IT is the intensity and a is the phase of spectrum Y. These two variables are determined by the least square fit running through all n points. We have also incorporated into the minimization procedure a mutual shift of the reference and fitted multiplets on a frequency axis by few points in order to compensate for a frequency shift, which we have occasionally observed. Finally, an array of IT values is then subjected to the analysis using appropriate transfer functions with Eqs. (1–5). The results are precise values of coupling constants, usually with absolute errors of a few hundreds of Hz. Signs of the three-bond dipolar coupling constants are immediately obvious upon comparison of the two sets of coupling constants measured in different media. Signs of the four-bond coupling constants, on the other hand, are not known with certainty for the J + D set and possibly not for the J set either. For some of

4.3 Examples Tab. 4.6 Coupling constants (Hz) of a-d-glucopyranose in isotropic media and of the reducing

a-d-glucopyranose unit of maltotriose in both partially oriented and isotropic states Coupling [Hz] compound

K12

K23

K34

K45

K13

K15

K24

Maltotriose (J+D)

5.64 ± 0.01 3.6 a)

9.86 ± 0.01 9.9 a)

9.51 ± 0.01 9.7 a)

10.8 a)

–0.43 ± 0.02

1.43 ± 0.01

2.60 ± 0.01

–0.45 ± 0.01 0.02 0.09

0.54 ± 0.01 0.89 0.82

–0.06 ± 0.03 2.66 2.67

Maltotriose (J) Glucose (J) Maltotriose (D)exp Maltotriose (D)pred

2.04 2.01

–0.04 –0.05

–0.19 –0.21

9.4 a)

1.4 1.4

a) Determined from z-filtered 1D TOCSY spectra (± 0.1 Hz).

the bigger coupling constants these can be determined experimentally from E.COSY spectra [84] provided that the relevant cross peaks are free from overlap. This additional experiment might not be necessary, as there are several ways of dealing with this uncertainty. When at least five dipolar coupling constants (which may include some one-bond proton-carbon dipolar coupling constants as well) are known in well-defined rigid structures such as pyranoses, the parameters of the alignment tensor can be calculated [86]. Values, including signs of any additional residual dipolar coupling in the same fragment, can then be predicted and compared with the experiment. Another approach, possibly requiring less than a full set of five dipolar coupling constants to be know accurately, is to create all possible 4n sets of dipolar couplings (n is the number coupling pairs with unknown signs) while taking into account all four solutions of the equation |D| = |J + D|–|J|. The correct solution will give the lowest sum of squares of differences between experimental and predicted couplings. The latter approach was adopted to analyze the measured coupling constants of a-d-glucopyranose in isotropic media and those of the reducing a-d-glucopyranose unit of maltotriose in both partially oriented and isotropic states. The results are summarized in Tab. 4.6. In this case, four three-bond residual dipolar proton-proton coupling constants were known accurately. When these were combined with 43 = 64 sets of three fourbond dipolar couplings by far the best fit was obtained for D13 = 0.02 Hz, D15 = 0.89 Hz and D24 = 2.66 Hz. During the calculations, the five elements of the order tensor were determined from the AM1-optimized co-ordinates of the a-dglucopyranose ring. The principle components of the alignment tensor, jSz0 z0 j > jSy0 y0 j > jSx0 x j; were calculated as (5.63 ± 0.29) ´ 10–4, (–5.55 ± 0.27) ´ 10–4 and (–0.08 ± 0.03) ´ 10–4, respectively.

89

90


4.4

Conclusions

Several examples have been shown where 1D selective experiments are useful to obtain spectral information that could not be obtained by 2D methods. In practice, 2D experiments are always done first since they are the most robust, routine and sensitive. Then, 1D selective methods can be used to complete acquisition of data necessary for structural or conformational analysis. 1D selective methods are also most useful for mixtures of compounds or when there is overlap of anomeric resonances. They are also useful to obtain data with high digital resolution, which is necessary for the measurement of accurate coupling constants in isotropic or phage-oriented media.

4.5

Acknowledgements

DU and PTN would like to acknowledge support by the British Council, and JRB and WW support from the NSC/NRC joint research program.

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5

NMR Experiments for Large Carbohydrates Sébastien J. F. Vincent

5.1

Introduction

Carbohydrates form a vast family of molecules, and constitute the most widely distributed and the most abundant class of organic compounds on Earth. The properties and functions of oligosaccharides, nucleotides, glycoconjugates and polysaccharides cover a wide range, from energy storage and structural blocks to the definition of the specificity of intercellular interactions in many immunological responses. At the molecular level, each monosaccharide can be substituted and can present up to sixteen different isomers. When incorporated in a larger structure, one type of monosaccharide can be combined with a multitude of others. Additional possibilities of branching of the backbone make the variety of carbohydrate primary structures far greater than that of proteins. Polysaccharides have several important biological roles and functions. They are the main energy storage molecules and the major components of cell walls, and they modulate immunological reactions and mediate cell attachment as a result of intermolecular interactions. They may also alter the biological environment for favored selective growth and microorganism protection, thus promoting anti-ulcer activities [1], biofilm formation [2], stimulation of the immune system in T-cell activation [3, 4], apoptosis activation and cancer [5], mediation of host-pathogen interactions [6, 7] and prebiotic effect [8]. NMR has been the method of choice for studying the structure, conformation and dynamics of oligosaccharides [9–13] and nucleotides [14–18] because of their biological relevance, high solubility, and generally good NMR properties, resulting from (relatively) small molecular sizes, narrow lines and sufficiently slow relaxation. The study of oligosaccharides has led to the development of numerous NMR methods including the initial work of the structural reporter group [19] and the first conformational studies carried out by Lemieux and coworkers [20] and by Carver and coworkers [21]. Generally, relatively simple 1D and 2D NMR methods were used to achieve this task. Later, the use of selective pulses for oligosaccharides (see Chapter 4) [22, 23] was implemented as well-defined NMR modules for measurements of scalar couplings in monosaccharides [12, 24] and in several heteronuclear two-dimensional experiments [25–27] expanded the range of applications of NMR in the characterization of the

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structural and conformational features of oligosaccharides. Lately, combinations of NMR experiments and MD calculations for characterizing monosaccharide dynamics within small oligosaccharide structures [28] have been demonstrated to be useful [11, 13, 29, 30]. A few examples have used 13C-labeled oligosaccharides, which in principle are difficult to obtain. Basically, organic synthesis methods have to be used for this task. Nevertheless, as for nucleotides, the synthesis of 13 C-labeled RNA samples [31, 32] has provided the impetus for a continuous stream of NMR methodology and structural work [14, 18, 33, 34]. On the other hand, polysaccharides cannot easily be 13C-labeled [28, 35, 36] and, moreover, present the many disadvantages of being very large (> 1 MDa) molecules, such as wide lines and overlap. Although sufficient local motion and stability at high temperatures may allow the recording of relatively decent liquid-state-like spectra for MDa-sized molecules, the low 13C-natural abundance and the gel-like state of the solutions at mg/mL concentrations necessary for NMR studies limit the methods available. Therefore, the field of polysaccharide NMR has not enjoyed a methodological development in recent times. This chapter will describe the current status of structural analysis of polysaccharides using chemical analysis and NMR. The current limitations and future possibilities will also be described.

5.2

The “Standard” Structural Analysis

Structural analysis of carbohydrates consists of five major steps: (1) Determination of the monosaccharide composition by chemical hydrolysis of the carbohydrate backbone, with cleavage of all glycosidic linkages. (2) Methylation analysis through a series of chemical reactions, which provides monosaccharide derivatives whose identity can be revealed by mass spectrometry. Thus, the determination of the various monosaccharides present in the polymer, together with their substitution, may be deduced. (3) Recording of the NMR data and assignment of all 1Hand 13C-NMR resonances. (4) Determination of the sequence of the glycosidic linkages and the eventual substituent positions. (5) Finally, study of polysaccharide three-dimensional structure by using NMR parameters assisted by molecular modeling techniques. This last part is outside the scope of this contribution, and reviews of its current status can be found in the literature [37–41]. It should be noted that several other analytical methods exist [42], including mass spectrometry profiling, high-sensitivity chromatographic methods, and specific derivatization with fluorescent groups, but that these methods have been applied to small size oligosaccharides and are essentially not accessible to polysaccharides. 5.2.1

Chemical Analysis

Monosaccharide analysis can be applied to polysaccharide samples similarly to oligosaccharide samples, with the added simplification that no precautions need to

5.2 The “Standard” Structural Analysis

be taken concerning the reducing end moiety, as this unit represents such a small fraction of the whole that it can safely be neglected. Although the sensitivity of the commonly used apparatus may allow access to very small amounts of sample, laboratory equipment typically requires polysaccharide quantities on the order of 100–500 lg for a monosaccharide analysis. The first step in such analysis is the cleavage of all glycosidic linkages by acid hydrolysis, where the usual conditions are TFA 2M heated for 1 h at 120 8C. After quenching the reaction by rapidly lowering the temperature, the sample can be injected directly into either an HPAECPAD or a GC-MS apparatus. Each of these two methods of detection will yield a combination of signals for each type of monosaccharide and a ratio of intensities. The typical elution times, ratios of different peaks and correction factors for each monosaccharide must be established beforehand on the analytical tool and column(s) chosen, by using standard monosaccharide samples. The result is in all cases a molar ratio for the individual monosaccharides within the carbohydrate moiety. Uncertainties result first from the incompleteness of the chemical hydrolysis, particularly as polysaccharides are often subject to a preferential hydrolysis of side chains compared to backbone, or to partial decomposition as a result of low solubility in the reaction solvents. Moreover, the subsequent chromatographic separation and the detection are additional sources of error. These make the monosaccharide analysis results for a polysaccharide sample very much subject to variability. A rule of thumb is an error of 10–25% on molar ratio obtained from monosaccharide analysis. The second step is the determination of the absolute monosaccharide configurations by chromatographic analysis of the corresponding trimethylsilylated (–)-2-butyl glycosides, as described by Gerwig et al. [43, 44]. This procedure amounts to a methylation followed by hydrolysis done using an optically active reactant. This sequence yields monosaccharide derivatives with chromatographic migration times that are different for d and l monosaccharides. Although most monosaccharides encountered are d, cases such as l-Rhap are frequently encountered. Here too, 100–500 lg of sample is generally used. The third step is a methylation analysis, which gives access to the first glycosidic linkage information. For this analysis, 250 lg to 1 mg polysaccharide samples are generally required. This destructive procedure starts by replacing all free OH groups by Omethyl groups, followed by a total hydrolysis of all glycosidic linkages. This protocol yields partially methylated monosaccharides, with free hydroxyl groups at the positions that were substituted in the polysaccharide. A reduction with sodium borodeuteride opens all monosaccharide rings, with concomitant labeling of the opening side with a 2H atom. By successive acetylation of the remaining free hydroxyl groups, a volatile compound is obtained that can be analyzed by GC-MS. The retention times are monosaccharide-specific, while the MS fragmentation patterns depend on the substitution features (methyl and acetyl) and deuteration. The results obtained enable identification of the monosaccharides, their ring form (hexose or furanose), their relative molar ratio, and the positions involved in the glycosidic linkages. The monosaccharide identity and the molar ratio should match the results from the monosaccharide analysis, taking into account that here, too, uncertainties resulting from the chemical reactions and the quantifica-

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tion of the chromatographic data may result in errors in the molar ratio of between 10 and 25%. 5.2.2

NMR Spectroscopy

For the preparation of polysaccharides for NMR, 1–10 mg samples are lyophilized from their purification solvent and dissolved in 500 lL of 2H2O. In the case of highly hygroscopic polysaccharides, several successive dissolutions into 99.9% 2 H2O, followed by lyophilization, are frequently used to enable optimal removal of unwanted water molecules and exchange of the OH-hydroxyl groups by OD. A compromise in the polysaccharide quantity to be used must be found. Obviously, the scientist would like to dissolve the maximum amount of material in order to increase the signal-to-noise (S/N) intensity ratio, especially for 13C-NMR measurements, therefore reducing the NMR experiment time. However, the solubility of the polysaccharide is often a limiting factor; samples with mg/mL of polysaccharides are very viscous, and therefore their NMR properties degrade with increasing quantities. Therefore a compromise between S/N and spectral properties should be found. In addition, the chemical shifts need to be properly referenced

(top) Structure of the exocellular polysaccharide produced by milk fermentation by the bacterium Streptococcus thermophilus Sfi39. (bottom) 1D 1H NMR spectrum of 3 mg Sfi39 polysaccharide in 500 lL 2H2O 99.96% recorded at 600 MHz and 67 8C. Anomeric (H-1) resonances are identified by the corresponding residue letter code assigned in decreasing anomeric 1H chemical shift (A to D). Fig. 5.1


to allow comparison with reported data, a convenient method being the use of an external reference such as the a-anomeric signal of [13C-1]-d-glucose (H-1 5.15 and C-1 92.90 ppm) or acetone (H-1 2.23 and C-1 31.1 ppm). Usually one or more one-dimensional 1H spectra (see Fig. 5.1) at different temperatures, various phasesensitive 1H-1H TOCSY experiments with mixing times of 10–100 ms, and one or two phase-sensitive 1H-1H NOESY datasets with mixing times of 50–250 ms are recorded. A sensitivity-enhanced gradient 1H-13C heteronuclear single-quantum coherence (PEP-HSQC) spectrum [45] is recorded with carbon decoupling, for 13C assignment. One or more magnitude mode gradient-filtered 1H-13C HMBC spectra are recorded with a J-evolution time of 25–60 ms. While the optimization of experimental parameters is to be carried out for each sample, standard values for 1 H frequency are: spectral width of 7 ppm, 1k real points, carrier on water at 4.7 ppm. For 13C frequency: spectral width of 50 ppm, 64 to 256 real points, and carrier around 75 ppm, if deoxy sugars are not present in the sample. For 1H homonuclear two-dimensional datasets, 8 to 64 scans are used, while for 1H-13C heteronuclear datasets, 32 to 128 scans for 1H-13C HSQC and 128 to 512 scans are usually required for 1H-13C HMBC. A 90o shifted square sine-bell is used in all dimensions, with zero-filling once. 5.2.3

NMR Assignment

The 1D 1H NMR spectra of polysaccharides (see Fig. 5.1) should confirm the sample purity (absence of oligonucleotides, protein, or lipid signals). It should also give the actual number of monosaccharides from the number of anomeric proton resonances by looking at signals present between 4.4 and 5.8 ppm, thus providing a third estimate of the monosaccharide molar ratio based on the relative integrals of the anomeric proton resonances. At this stage, the chemical analysis results should agree with the 1D 1H NMR. The linewidths may vary significantly for different anomeric resonances, typically between 5 and 30 Hz in the same sample, as a result of widely variable dynamical motions for the different monosaccharide units. Nevertheless, relative NMR integrals are generally as precise as the chemical analysis results, if not better. Many (protonated) substituents can be identified or their presence suspected based on the 1H 1D NMR spectrum. Then, by observation of the anomeric region of the two-dimensional heteronuclear 1H-13C HSQC spectrum (Fig. 5.2), the exact number of monosaccharides can be determined. Anomeric 1H chemical shifts (4.4–5.8 ppm) are reasonably separated from non-anomeric 1H resonances (3.2–4.5 ppm), while anomeric 13C chemical shifts (95–110 ppm) are well separated without overlap from other non-anomeric 13C resonances (60–85 ppm). Ring forms (hexose or furanose) and anomeric configurations are deduced from the combined information available from H-1 chemical shifts (Ha resonate between 5.0 and 5.8 ppm while Hb resonate between 4.4 and 5.2 ppm) and onebond C-1, H-1 scalar couplings (1JC-1,H-1 165–175 Hz for a while 1JC-1,H-1 158– 165 Hz for b). The one-bond heteronuclear scalar couplings 1JC-1,H-1 can be ob-

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5 NMR Experiments for Large Carbohydrates H-13C HSQC spectrum of Sfi39 polysaccharide. (C-1, H-1) cross-peaks are identified with the residue letter code (A to D). Fig. 5.2

1

tained either from an undecoupled 1H-13C HSQC spectrum or conveniently from the cross-correlated dipole-dipole experiment described below. Another option is to record an undecoupled 13C 1D spectrum, but this is not a recommended approach, since it is plagued by the combined effects of overlap and lack of sensitivity inherent in the direct detection of insensitive nuclei such as 13C. The 1H assignment of a polysaccharide starts from the anomeric resonances of each residue in the TOCSY spectra recorded with increasing mixing times (10–100 ms). By increasing the mixing time, transfer occurs from H-1 to the directly coupled H-2 (via 3JH-1,H-2), for longer times from H-2 to H-3 via 3JH-2,H-3, and then from H-3 to H-4 via 3JH-3,H-4. Since monosaccharide coupling networks are linear (3J >> 4J), TOCSYs with increasing mixing times allow a “walk” along the monosaccharide ring. Connectivities from H-1 to H-2,3,4 can generally be traced for all residues, but, because of frequent overlap of non-anomeric proton resonances and the linewidths on the order of the chemical shifts difference (linewidths of * 15 Hz = 0.02 ppm for Dd* 0.02 ppm), complete 1H assignments can rarely be obtained based on the H-1 TOCSY traces alone. Additional information can be obtained from H-2,3,4,5 TOCSY traces, then from intra-residue intense NOESY cross-peaks, and finally by assigning both the 1H and the 13C resonances in the HSQC spectrum and by comparing to standard chemical shifts [46–48] and a database such as SUGABASE’s access to CarbBank (5.1) [49]. Tab 5.1 summarizes reference data taken from SUGABASE’s access to CarbBank [49] for the four most common monosaccharides found in polysaccharides, the a and b forms of glucose and galactose. The main limitations in the interpretation of this type of data are overlap, similarities between different species and the small chemical shift range covered by all chemical shifts. Additional drawbacks may be frequent improper referencing, the usage of a very large temperature range (typically 20–80 8C) and numerous varying neighboring effects resulting from substituents or branching by glycosidic linkages. This chemical shift information, together with chemical analysis, enables the assignment of the resonances and a confirmation by NMR of the chemical identity of each monosaccharide unit.

5.2 The “Standard” Structural Analysis Tab. 5.1 Standard chemical shifts taken from the SUGABASE database [49] for both forms of

glucose and galactose, the two most common monosaccharides. Each line of data results from the analysis of more than 100 compounds from the database. The values are given as an average and a deviation describing a range of values resulting from the combined effect of substituents inducing changes on positions neighboring glycosidic linkages and from varying measuring conditions and references for the chemical shifts. The chemical shifts, both 1H and 13C from aglyconic positions, were excluded from the table. The SUGABASE chemical shift data were calibrated by reference to acetone for 1H (2.225 ppm) and 13C (31.08 ppm). Monosaccharide

H-1 C-1

H-2 C-2

H-3 C-3

H-4 C-4

H-5 C-5

H-6a C-6

H-6b

a-d-Glcp

5.11±0.30 97.5 ± 4.5 4.84±0.46 102.9±2.4 5.16±0.35 99.1 ± 3.1 4.68±0.26 103.5±2.4

3.52±0.06 72.5 ± 1.0 3.31±0.05 74.1 ± 1.1 3.89±0.12 68.9 ± 1.3 3.53±0.17 71.7 ± 2.1

3.76±0.10 73.8 ± 0.4 3.55±0.07 76.3 ± 1.4 3.93±0.16 70.2 ± 1.7 3.80±0.16 73.5 ± 1.7

3.41±0.05 70.7 ± 0.6 3.51±0.13 70.4 ± 1.0 4.12±0.19 68.6 ± 1.9 4.08±0.18 67.9 ± 2.0

3.74±0.10 72.9 ± 0.5 3.55±0.09 76.0 ± 1.3 4.11±0.29 71.0 ± 2.0 3.74±0.20 75.5 ± 1.1

3.64±0.16 61.4 ± 0.4 3.77±0.05 61.5 ± 1.0 3.73±0.07 61.7 ± 0.8 3.74±0.05 61.8 ± 0.7

3.78±0.08

b-d-Glcp a-d-Galp b-d-Galp

3.94±0.05 3.73±0.04 3.74±0.05

5.2.4

Primary Structure Determination

Substituted monosaccharide positions, called the aglyconic positions, correspond to carbon atoms involved in the non-anomeric part of the glycosidic linkage. From the NMR data, linkage positions are inferred based on the usual large increases (> + 3 ppm) in their 13C chemical shifts in comparison to reference chemical shifts of the non-substituted monomers (see Tab 5.1) [46–49]. This analysis yields, by an independent method, the same information content as the methylation analysis, and should therefore be consistent with these results. The sequence of the residues in the polysaccharide is defined by the series of glycosidic linkages and represents the main targeted structural information. It can be inferred from two types of NMR experiments, 1H-13C HMBC and NOESY. The sensitivity of the HMBC experiment is very low in the absence of 13C enrichment (Fig. 5.3 b), since only the natural abundance of 1.1% of 13C-carrying molecules yields an observable signal. Moreover, magnetization flows from proton to carbon and back via weak long-range scalar couplings (3JCH < 8 Hz), and rapid transverse relaxation resulting from the very large molecular size reduces signal intensities very effectively during the long transfer times (1/2J, several tens of ms). The unambiguous interpretation of NOESY spectra is not trivial in polysaccharides as a result of the combined effect of resonance overlap, line-broadening, and spin diffusion (Fig. 5.3 a). These limitations make unambiguous structural determination rather difficult in polysaccharides.

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(a) 12 h, 100 ms NOESY (b) 48 h, 50 ms 1H-13C HMBC (c) 18 h, 2T = 20 ms

Fig. 5.3

cross-correlated dipole-dipole relaxation spectrum of the Sfi39 polysaccharide.

5.2.5

Cross-Correlated Dipole-Dipole Relaxation

This section presents an NMR experiment allowing the determination of connectivities of the glycosidic linkages in unlabeled oligo- and polysaccharides using cross-correlated dipole-dipole relaxation [50]. This method provides an alternative and robust second tool for the major step in the determination of carbohydrate primary structure, the unambiguous determination of glycosidic linkages. Crosscorrelated relaxation mechanisms have been used increasingly as a structural tool and for probing dynamical behavior at the atomic level. Cross-correlated relaxation rates were shown to give access to dihedral angle information in labeled proteins [51, 52] and to allow the study of protein dynamics [53, 54]. In the field of carbohydrates, cross-correlated relaxation rates have been measured in 13C-labeled RNA and used for establishing sugar ring pucker modes [33, 55]. Most of these experiments were not only carried out on fully 13C-labeled molecules, but also relied on relaxation mechanisms involving several heteronuclei, an approach that is clearly not applicable to natural abundance polysaccharide samples where only 1.1% of the sites are (naturally) labeled. The NMR experiment schematized in Fig. 5.4 relies on cross-correlated relaxation between two dipoles centered on the same carbon atom around the glycosidic linkage, the C-1,H-1/C-1,H-n and C-n,H-n/C-n,H-1 dipole-dipole pairs where n is the aglyconic position linked to the anomeric 1 position by a glycosidic linkage, to transfer magnetization across the glycosidic bond (Fig. 5.5) [50]. The sequence starts with an INEPT transfer:


Pulse sequence for the determination of glycosidic linkages in C natural abundance carbohydrates by cross-correlated dipole-dipole relaxation. = 1/(4 ´ 1 JCH) and 2T = total cross-correlated relaxation time. Phase cycle was: U1 = x,–x; U2 = 4(x),4(y),4(–x),4(–y); U3 = x,x,–x,–x; and Urec = x,–x,–x,x,–x,x,x,–x. TPPI was applied to 1. Gradients were: G1 = –51, G2 = 93, G3 = –17, G4 = –17, and G5 = 23. Fig. 5.4 13

Schematic representation of the two dipole-dipole pairs giving rise to cross-correlated dipole-dipole relaxation in carbohydrate glycosidic linkages.

Fig. 5.5

H1x ! INEPT ! 2C1y H1y

1

This antiphase 2Cy1H1y carbon coherence evolves for the constant-time period 2T under the effect of cross-correlated dipole-dipole relaxation between the 13C-1,H1/13C-1,H-n dipole pairs, CCCDDR(2T), while proton-carbon scalar couplings are decoupled. Meanwhile, the carbon chemical shifts evolve during the indirect time period t1. As a result, two carbon antiphase terms are created: 2C1y H1y ! CCCDDR 2T ! X13 Ct1 ! 2C1y H1z 2C1y Hnz

2

After the final two p/2 pulses, these two terms have been flipped back into proton magnetization: 2C1y H1y ! p=21 H;13 CC ! 2C1z H1y 2C1z Hny

3

103

104


while orthogonal terms have been purged by the G5 gradient. The two terms of Eq. (3) are then refocused during t2 through evolution under their respective scalar couplings: 2C1z H1y ! 1 JCH t2 ! H1x

4

2C1z Hny ! 3 JCH t2 ! Hnx

5

The antiphase proton coherence 2C1zH1y refocuses through the large scalar coupling 1JCH and is the source of an undecoupled “direct peak” at (x1, x2) = (X(C-1), X(H-1)), while the term 2C1zHny is refocused through the small long- range scalar coupling 3JCH and generates a “cross-peak” at (X(C-1), X(H-n)). Decoupled in the x1 dimension, the cross-peaks are antiphase in the x2 dimension with respect to the small long-range proton-carbon scalar couplings but in-phase with respect to proton-proton scalar couplings. The presence of the full intensity undecoupled direct peak allows one to determine the one-bond heteronuclear large scalar coupling 1JCH, which is key in determining the anomeric configurations of the monosaccharide units [56]. The cross-peaks are characteristic of the glycosidic linkage between the anomeric C-1 carbon atoms and the aglyconic C-n carbon atoms. Corresponding symmetrical peaks are found at (X(C-n), X(H-n)) and (X(C-n), X(H1)), resulting from the cross-correlated relaxation between the C-n,H-n/C-n,H-1 dipole-dipole (Fig. 5.5 b), which provides another identifier of glycosidic linkages. The cross-correlated dipole-dipole relaxation experiment of Fig. 5.4 is directly applicable to all natural abundance carbohydrates for determining glycosidic linkages. Fig. 5.6 shows the cross-correlated dipole-dipole relaxation spectrum resulting from the application to Streptococcus thermophilus Sfi39 polysaccharide (Fig. 5.1 top) [57]. Fig. 5.6 shows all expected cross-peaks linking the anomeric proton resonances with the aglyconic carbon chemical shifts in the Sfi39 polysaccharide. Streptococcus thermophilus is one of the two types of lactic acid bacteria used in the

Sfi39 polysaccharide cross-correlated dipole-dipole relaxation spectrum recorded with 2T = 20 ms. Interglycosidic cross-peaks are identified with arrows.

Fig. 5.6

5.4 Outlook

industrial fermentation of milk into yogurts. Lactic acid bacteria acidify the medium, milk, by secreting lactic acid, but also release flavor molecules, which give their some of their taste specificities to cheeses and yogurts, and the exopolysaccharides essential for the texture and consistency of the yogurt [58]. In this case, structural studies of polysaccharides are carried out to improve the understanding of the main factors responsible for texture formation.

5.3

Current Limitations

Several limitations prevent the direct application to polysaccharides of NMR pulse sequences developed for oligosaccharides or oligonucleotides. Most of the problem results from the rapid spin relaxation in macromolecules of MDa range molecular weights. 1H linewidths are usually broad (5–50 Hz), resulting from short T2* (1H), preventing, for example, the direct determination of scalar coupling by measurement of peak separation. For the same reason, it is not possible to use selective pulses, which have been efficiently applied by Uhrín et al. [21–23] for simplifying spectral analysis in oligosaccharides (see chapter within this book). In large polymers, a significant amount of magnetization has returned to equilibrium after one single selective pulse. Another limitation is the combined effect of linewidths and spectral overlap, a problem especially limiting for 1H. Since most hydrogen atoms in carbohydrates share a common chemical environment, their chemical shifts are very similar: between 5.8 and 4.4 ppm for H-1 and between 4.5 and 3.2 ppm for H-2 to H-6. Even in the carbon frequencies, C-1 carbons resonate between 95 and 110 ppm, unsubstituted C-2 to C-5 between 68 and 78 ppm, while unsubstituted C-6 carbons are around 61 ppm. Their involvement in a glycosidic linkage is correlated with a downfield shift in carbon chemical shift of several ppm. Then, the absence of 13C-labeling, or to be more exact, the lack of a general strategy for the production of 13C-labeled samples still prevents the use of the multi-frequency NMR techniques which have been developed and commonly used in the field of proteins.

5.4

Outlook

Cross-correlated dipole-dipole relaxation can generate coherences through the glycosidic linkage faster than those resulting from the (small) proton-carbon scalar couplings across the glycosidic linkage. A constant-time period 2T of 10 ms was found to be sufficient for substantial transfer mediated by cross-correlated relaxation, while periods between 30 and 80 ms are generally needed for a 1H-13C HMBC. The cross-correlated dipole-dipole relaxation experiment of Fig. 5.4 can therefore be more sensitive than 1H-13C HMBC in cases where transverse relaxa-

105

106


tion is fast. Moreover, the diagonal peaks are present with a sensitivity similar to an x2-undecoupled 1H-13C HSQC. In the case of 1H-13C HMBC, direct peaks are left to evolve arbitrarily for the duration of the long transfer time, and therefore transverse relaxation during the arbitrarily chosen (tens of ms) evolution delay reduce their intensity. By acquisition of the cross-correlated dipole-dipole relaxation experiment of Fig. 5.4, it becomes unnecessary to acquire a separate x2-undecoupled 1H-13C HSQC for measuring anomeric one-bond proton-carbon scalar couplings necessary for determining the absolute configuration of the monosaccharide units. Cross-correlated relaxation rates are a function of the correlation times describing molecular tumbling [33, 55], thus making NMR experiments based on these relaxation mechanisms particularly well suited for the study of very large molecular weight molecules such as polysaccharides. The combined use of different NMR processes and experiments based on different transfer mechanisms is an important plus in the structural determination of glycosidic linkages where the information is often ambiguous and limited. In conclusion, the application of cross-correlated dipole-dipole relaxation is an additional tool for the structure determination of non-labeled carbohydrates, especially suited for polysaccharides. As for other developments in the field of polysaccharide NMR, the measurement of scalar J-couplings is high on the priority list, together with the hope of increasing methods for producing 13C-labeled polysaccharide samples, at least in some bacterial systems where precursor incorporation can be controlled. Then, the combination of NMR methods with array methods based on the lectin technology should increase exponentially the currently very limited overall structural information on polysaccharides structures. Finally, automated analysis procedures that have been pioneered for carbohydrates by Lipkind et al. [59, 60] and Jansson et al. [61–63] should be further developed and made available to the community for widespread usage.

5.5

Acknowledgements

I am grateful to C. Zwahlen for all shared discussions and the common work and to J.-R. Neeser and F. Stingele for their support.

5.6

References 1

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23 24

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27 28

29

30 31 32

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P. D. J. Grootenhuis, C. A. G. Haasnoot, Mol. Simul. 1993, 10, 75–95. (a) S. Pérez, M. Kouwijtzer, K. Mazeau, S. B. Engelsen, J. Model. Graph. 1996, 14, 307–321. (b) S. Pérez, A. Imberty, S. B. Engelsen, J. Gruza, K. Mazeau, J. Jiménez-Barbero, A. Poveda, J. F. Espinosa, B. P. van Eick, G. Johnson, A. D. French, M. L. C. E. Kouwijzer, P. D. J. Grootenhuis, A. Bernardi, L. Raimondi, H. Senderowitz, V. Durier, G. Vergoten, K. J. Rasmussen, Carbohydr. Res. 1998, 314, 141–155. (a) C.-W. von der Lieth, T. Kozár, W. E. Hull, J. Mol. Struct. (Theochem) 1997, 395-396, 225-244. (b) J. L. Asensio, M. Martin-Pastor, J. Jiménez-Barbero, J. Mol. Struct. (Theochem) 1997, 395, 245– 270. Manzi, A. E. and van Halbeek, H., Principles of Structural Analysis and Sequencing of Glycans, Cold Spring Harbor Laboratory Press, 581–598, 1999. G. J. Gerwig, J. P. Kamerling, J. F. G. Vliegenthart, Carbohydr. Res. 1978, 62, 349–357. G. J. Gerwig, J. P. Kamerling, J. F. G. Vliegenthart, Carbohydr. Res. 1979, 77, 1–7. L. E. Kay, P. Keifer, T. Saarinen, J. Am. Chem. Soc. 1992, 114, 10663–10665. K. Bock, H. Thøgersen, Annu. Rep. NMR Spectrosc. 1982, 13, 1–57. K. Bock, C. Pedersen, Adv. Carbohydr. Chem. Biochem. 1983, 41, 27–66. K. Bock, C. Pedersen, H. Pedersen, Adv. Carbohydr. Chem. Biochem. 1983, 42, 193–225. A. van Kuik, The SUGABASE database: a carbohydrate-NMR database that combines CarbBank Complex Carbohydrate

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Part B Structural and Conformational Analysis of Carbohydrate Molecules by NMR


6

Combining NMR and Simulation Methods in Oligosaccharide Conformational Analysis Thomas Weimar and Robert J. Woods

6.1

Introduction

Carbohydrate modeling has a long history, beginning with the need to provide a structural interpretation for experimental NMR data. More recently, the expanding awareness of the importance of carbohydrates in biology has fueled a huge interest in the mechanisms of carbohydrate recognition. A diverse range of experimental techniques is now used to establish the energetics of carbohydrate-protein interactions as well as to derive 3-dimensional (3-D) models for carbohydrates and carbohydrate-protein complexes. However, none of the experimental methods are able to generate a 3-D structure for these systems without relying to varying degrees on theoretical models. The two most commonly applied experimental structural methods, NMR and X-ray crystallography, deserve to be highlighted in particular. NMR spectroscopy can provide information that is directly related to the 3-D structure of a molecule, and for this reason it remains the most widely used experimental method for studying the conformational properties of carbohydrates in solution. Parameters such as NOE intensities, scalar J-couplings, residual dipolar couplings and chemical shifts each depend on a molecule’s 3-D structure. Nevertheless, it is generally necessary to assume a model and iteratively adjust it until the resultant computed NMR parameters are in agreement with those obtained experimentally. For molecules that exist primarily in a single conformation, such as globular proteins or blood group trisaccharides, this approach is very effective. Solution NMR data represent only the average molecular structure over the time course of the NMR experiment, and for flexible molecules it is extremely difficult to decompose the data into contributions from the individual conformations. It is in this situation that modeling methods are often used to complement the NMR data. When experimental data are used to guide or restrain the outcome of the modeling, it is possible to generate a single average structure that satisfies the restraints. However, if a molecule exists in more than one distinct conformational state, its average structure may not represent any single real conformation. Thus, placing too much weight on the experimental data can lead to the generation of what is known as a virtual conformation. This may be avoided by lowering the

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6 Combining NMR and Simulation Methods in Oligosaccharide Conformational Analysis

weights of the NMR restraints, thereby generating an ensemble of conformations each of which satisfies only some of the NMR restraints. Such an ensemble may more accurately reflect the flexibility of the molecule. In recent years the accuracy of computational methods has increased to the point where they may be used to generate an ensemble of conformations that are consistent with the NMR data, without the need to include experimental restraints. While this is a very desirable goal, as it enables modeling to be applied in a predictive capacity, there remain several limitations. Most notably, the NMR timescale is much longer than that accessible to modeling methods. Thus, it is extremely difficult at present to model low frequency motions, such as those associated with protein loops. Other limitations include difficulties in treating pH effects, charge polarization, or other quantum effects. In the case of X-ray crystallography, a 3-D structure is generated by threading a model through the electron density while iteratively optimizing the fit. For highresolution X-ray or neutron scattering data there may be little ambiguity in the resultant structure, but in many cases the resolution is not sufficient to remove all of the dependency on the model. This is often the case for the outer arms of the glycan in a glycoprotein. Further, the final structure does not directly address issues relating to dynamics which may be present in the crystal and which certainly are present in the solution state. Both NMR and X-ray data provide excellent reference points for computational methods. Before performing modeling without experimental restraints, it is essential to confirm that the theoretical method is capable of accurately reproducing experimentally consistent structures. However, it is possible to gain considerable insight into molecular motions, as well as interaction energies, from modeling methods alone. In the following sections we present an overview of modeling techniques and NMR methods used in the conformational analysis of oligosaccharides. Particular focus is being given to molecular dynamics (MD) simulation and NOE experiments.

6.2

Oligosaccharide Modeling: Background and Theory 6.2.1

Force Fields

In contrast to protein modeling, where most force fields have converged to a common mathematical form [see Eq. (1)], there remains a division in carbohydrate modeling philosophies. The individual components in Eq. (1) include contributions from internal energies, such as bond stretching, angle bending, and torsion rotation, as well as from energies associated with non-bonded interactions, arising from van der Waals and electrostatic forces. Biomolecular force fields are often well suited for application to solvated systems, and so provide a protocol that enables the simulation of remarkably complex systems.

6.2 Oligosaccharide Modeling: Background and Theory

Vtotal

X bonds

X

X X Vn 1 cosny 2 angles dihedrals n " # X Aij Cij qi qj 2 xeq R12 R6ij eRij ij non-bonded

req 2

Kr r

Kx x

improper torsions

X

Kh h

heq 2

cn 1

i<j

Although it is increasingly common for biomolecular force fields, e.g. as shown in Eq. (1), to be employed in MD simulations of carbohydrates and carbohydrate protein complexes, preliminary carbohydrate conformational analyses are still often performed with a very basic force field that is based on the hard-sphere exoanomeric (HSEA) approximation introduced nearly 30 years ago [see Eq. (2)] [1, 2]. In addition to a van der Waals term, the HSEA method includes separate rotational energy functions that incorporate the exo-anomeric effects associated with a- and b-anomers [3]. Vtotal

X

Vexo-anomeric

2

van der Waals

Despite the very approximate nature of the HSEA force field, it has been reported to generate conformations that are consistent with the (admittedly limited) NMR data [3, 4]. Early HSEA-based predictions of the conformations of the blood-group antigenic determinants remain examples of the success of the HSEA method when applied to molecules that exist predominantly in one conformation in solution [5]. A modification of the HSEA implementation, known as Geometry of Saccharides or GESA, was introduced in 1984 to help describe more accurately the energetics of flexible oligosaccharides [6]. Although a rigid ring assumption was retained, iterative minimization could be performed on each of the inter-residue torsion angles. The GESA modifications removed much of the excessive inflexibility of the original HSEA implementation [7] and have found application in Monte Carlo simulations [8]. A modified GESA force field has also been incorporated into an approach for modeling glycoproteins, based on the rigid residue ECEPP/2 [9] force field for proteins. This combination is referred to as Geometry of Glycopeptides (GEGOP) [10]. Each of the traditional biomolecular force fields (for example CHARMm, AMBER and GROMOS) has been parameterized for carbohydrates, and in several instances more than one parameter set may exist, offering alternative levels of sophistication, internal consistency, and compatibility with parameters for other biomolecules. Each force field employs a similar quadratic energy function; nevertheless, each has unique features, particularly in the treatment of carbohydrates. For example, the dihedral angle term in the energy expression is often augmented by a component intended to reproduce the conformational energies associated with the exo-anomeric effect. A detailed review of these features was presented in 1998 [11]. Because of the generality of biomolecular force fields, they have found application in the simulation of many classes of oligosaccharides and glycoconjugates, in-

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cluding N- and O-linked glycoproteins, glycolipids, and carbohydrate-protein complexes [12–23]. Simulations involving these methods are frequently more complicated to set up than those using the HSEA approach, and they can be extremely computationally intensive. However, the broad range of systems that may be examined frequently justifies these extra demands. 6.2.2

Molecular Dynamics Simulation versus Monte Carlo Sampling

Historically, modeling has been associated with the search for the “global energy minimum” of a molecule. For small molecules with limited degrees of rotational freedom, energy minima may be located through a variety of conformational search procedures. To search the conformational space of a single rotatable bond by dividing it into 30 8 increments and evaluating the energy at each point, 12 individual energy minimization calculations would be required. A search of a molecule with three rotatable bonds would require 123 or 1728 calculations. By the time the molecule has 9 bonds, there are more than 109 calculations required. For an oligosaccharide or glycoconjugate, this is not a feasible approach to locating low energy conformations. Two alternative approaches are frequently applied in carbohydrate modeling: Monte Carlo (MC) sampling, employing the HSEA or related potential energy function, and MD simulation, employing a biomolecular force field. A detailed discussion of MD and MC methods has been presented by Leach [24]. All molecules are in motion except at absolute zero. The motion can be associated with overall translation, rotation or vibration, which are related to the temperature and pressure of the system. More importantly from a conformational perspective, some of the motions are internal. These internal motions can drastically alter the conformation of the molecule, particularly through torsion angle rotation. In MD simulations the motion is divided into very short time steps (Dt = 1–2 fs). Given the position (x) of a particle at time t, its new position after time Dt may be obtained from the familiar Taylor expansion: 1 xt Dt xt vtDt atDt2 . . . 2

3

where v = atomic velocity and a = acceleration. This is an infinite series, and for practical implementation it must be truncated. Several methods have been proposed for the treatment of this truncation. The method of Verlet is one of the most common. The Verlet algorithm uses the positions and accelerations at time t and the positions from the previous step (t–Dt) to compute the new positions at t + Dt. The equations for the positions at (t + Dt) and (t –Dt) are: 1 xt Dt xt vtDt atDt2 2

4


xt

Dt xt

1 vtDt atDt2 2

5

These may be added together and rewritten to give the position at t + Dt as: xt Dt 2xt

xt

Dt atDt2

6

The accelerations are computed from the force field by solving Newton’s first law: Fi

@V mi ai @xi

7

where V is the potential energy function (i.e. the force field). The Verlet algorithm is fast and efficient because it does not require frequent calculation of the atomic velocities. However, it can suffer from numerical inaccuracies. Other methods have been developed which offer some advantages, but the principles are similar. In choosing a suitable integration scheme, a key concern should be time step size Dt, since the larger the step the more conformational or configurational space can be sampled. The highest frequency motion in the molecule limits the choice of time step size, with a value of 1 fs generally being the upper limit. To use a larger time step, the highest frequency motions, generally those associated with covalent bonds to hydrogen, may be omitted. This common approximation has no effect on carbohydrate conformation and usually enables a time step of 2 fs to be employed. The direct result is that twice the sampling is obtained for a given simulation duration. Longer time steps lead to unstable trajectories in which the total energy does not remain in equilibrium, and which eventually fail because of invalidation of Eq. (3). MC methods were developed in the late 1940s to study the diffusion of neutrons in fissionable material. The name “Monte Carlo” refers to the use of random numbers in the generation of the conformations. In contrast to MD simulations, MC methods do not have a time-dependency, and rely only on the immediately previous conformation in the generation of the next conformation. The resulting randomly generated conformation is accepted only if it meets specific energetic criteria. The new conformation may be generated by randomly moving a single atom or a group of atoms, or by randomly rotating a bond. The challenge is to ensure that at the end of the simulation each conformation has occurred with an appropriate probability. In all cases, the new conformation is automatically accepted if its energy is lower than the previous energy. If its energy is higher (Vnew–Vold > 0), a decision must be made as to the likelihood that it is a reasonable energy difference. This decision is based on the Boltzmann energy factor computed from the new and the previous structures. Boltzman Factor e

Vnew Vold kB T

8

115

116


In the Metropolis method, developed in the 1950s, once the Boltzmann factor is determined, a random number between 0 and 1 is computed, and if the random number is less than the Boltzmann factor the new conformation is accepted. It is then used for the selection criteria for the subsequent conformation. However, if the random number is greater than the Boltzmann factor the new step is rejected and the system remains in its immediately previous state. This approach ensures that over the course of the simulation the conformations are accepted with a probability equal to the Boltzmann factor and ultimately lead to a distribution that has the correct probability behavior, that is, the population of the conformations is given by the Boltzman distribution: Vi

ni e kB T N N X Vi e kB T

9

i1

In the limit, time-averaged properties and ensemble-averaged properties are identical. This fundamental principle is known as the ergodic hypothesis, and relates time-dependent MD simulations and time-independent MC sampling. Nevertheless, there are instances in which it is preferable to employ MD rather than MC or vice versa. The most significant reason for electing to use MD simulations is that there are more force fields for carbohydrates developed for use with MD calculations. Further, the MD methods are all based on general biomolecular force fields, which are well suited to the inclusion of explicit solvent in the simulation, and to the study of carbohydrate-protein (or polynucleic acid) complexes. For these reasons, the following sections will address issues of particular relevance to explicitly solvated MD simulations. Experimental restraints may be included in either MD or MC calculations. Further, given sufficient experimental data the restraints alone may be sufficient to force the simulation into an experimentally consistent conformation, regardless of the specific force field parameters. This traditional approach relies only tangentially on current advances in modeling and so is not discussed in detail in the following sections. 6.2.3

Explicit Solvation: Water Models

The choice of solvent model depends on an assessment of which properties are important in the simulation. Generally, the more sophisticated the water model, the slower the calculation. Therefore, it is necessary to decide on a suitable level of accuracy. Will a rigid water model that displays approximately correct bulk water behavior (density, radial distribution, diffusion rate) suffice? Or is a relaxed model that allows the bonds to stretch and the valence angle to bend necessary? Further, the option exists to employ polarizable water models. Ultimately, these decisions may depend on available computer facilities. However, it should also be


Schematic representation of current water model geometries. Additional non-nuclear charge centers are identified as M or Lp [25–29].

Fig. 6.1

noted that if the solute is not being treated with the same level of accuracy, there might be little justification for extremely accurate simulation of the solvent. Regardless of the geometry of the model, the majority of the CPU-time for a solvated MD simulation will be spent on issues related to determining water positions. To minimize the computer time, without compromising the accuracy of the simulation, requires careful choices regarding both the number of waters to include and the treatment of water-water interactions. 6.2.4

Boundary Conditions 6.2.4.1 Water Droplets

If a molecule is simply surrounded by a droplet of solvent, a surface will exist between the droplet and the vacuum around it. During an MD simulation it may become difficult to prevent the molecules from diffusing into the vacuum. To prevent the solvent from drifting beyond the boundary, an artificial restraint may be applied. This can be a useful method for simulating the binding region in a protein-carbohydrate complex, for which a completely solvated simulation would be extremely time consuming. However, the droplet model does not correspond to a

Schematic representation of a water droplet.

Fig. 6.2

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118


traditional thermodynamic ensemble, and care must be exercised when interpreting resulting interaction energies.

6.2.4.2 Periodic Boundary Conditions (PBC)

An alternative to the droplet model is to arrange the solute and solvent into a regular lattice structure. By mirroring the contents (positions and velocities) of the central “box” a periodic system is generated, which avoids edge effects. When a molecule drifts out of one side of the box, it reenters on the other. Thus, a constant density can be maintained. If the box dimensions are allowed to change with temperature, it is possible to maintain a constant internal pressure (NPT ensemble). Alternatively, if the box dimensions are kept constant, the internal pressure will fluctuate with temperature (NVT ensemble). In terms of thermodynamics, the NPT ensemble gives rise to Gibbs free energies; NVT to Helmholtz. In order to prevent the introduction of artificially correlated motions, the simulations are commonly performed so that no particle in the central box can “see” its image in any other box. Intermolecular interactions are excluded on the basis of a cut-off distance, which itself relies on the assumption that no significant inter-atomic forces exist beyond the cut-off distance. This is straightforward for short-range forces, such as van der Waals interactions, which vary as r–6. For many neutral systems a cut-off of 8 Å is employed. It should be noted that the commonly used TIP3P water model was developed for use with an 8 Å cut-off, and, under NPT conditions, changes in the cut-off distance will affect the density of the solvent.

Two-dimensional schematic representation of periodic boundary conditions (PBC).

Fig. 6.3


6.2.4.3 Minimum Image Convention

The calculation of the intermolecular interactions is the most time-consuming part of an MD simulation. The number of non-bonded terms (van der Waals and electrostatic) that need to be calculated increases with the square of the number of molecules. Since the strengths of these interactions decrease with distance, it is possible to invoke a cutoff distance (R) beyond which it is assumed that two molecules are independent of one another. In a periodic boundary simulation, a molecule should not be able to sense the presence of its mirror image. Nor should it see more than one copy of any other molecule. To ensure this, the non-bonded interaction cutoff (R) must be less than 1/2 of the box length (L). This is the minimum image convention. A cube is commonly used for the periodic boundary system, but other choices are possible, including, for example, a truncated octahedron or a rhombic dodecahedron. Using non-cubic lattices may reduce the number of non-bonded contacts that need to be computed. For example, a cubic box might contain 256 molecules, whereas the corresponding truncated octahedron would contain 197 and the rhombic dodecahedron would contain only 181 molecules. The choice of lattice can therefore greatly affect the time required for the simulation. There arises a problem, however, when the forces are not negligible at the cutoff distance. For example, in charged systems, inter-atomic forces extend well beyond 8 Å. Truncation of these forces can lead to catastrophic results, such as protein unfolding or ligand dissociation. Within the PBC formalism, correct treatment would require a much larger cut-off and a correspondingly larger box. This would result in a large number of waters and consequently a very slow calculation, with excessive time being spent on computing water-water interactions. There are two common approaches to overcoming this problem. The first is relevant for the case in which the solute is a charged biomolecule in a pure water environment. In this case it is possible to use two cut-offs, namely a large one (or

Relationship between box dimension L and non-bonded interaction cut-off R in a 2-D PBC system.

Fig. 6.4

119

120

6 Combining NMR and Simulation Methods in Oligosaccharide Conformational Analysis Schematic representation of non-bonded interactions computed using Ewald summation in a 2-D PBC system.

Fig. 6.5

alternatively no cut-off at all) within the solute, and the typical 8 Å cut-off for all interactions involving water molecules. A large box may still be required, but the time spent computing water-water interactions will be greatly reduced. The second more rigorous approach is called Ewald summation. Ewald summation was developed in the early part of the 20th century for computing long-range forces in ionic crystals [30]. The solute (A in Fig. 6.5) is considered to interact not only with its nearest solvent neighbors (B) in the simulation cell, as defined by a standard cut-off, but also with each of the images of the solvent neighbors in the adjacent cells. However, the solute does not interact with images of itself. The energies are computed and summed in order according to the proximity of the cells to the central cube. As the energies are computed, more and more cells are added, leading in the limit to the formation of an approximately spherical system. At the edge of the sphere, a dielectric must be assigned and a corresponding contribution computed and included in the total energy. This method is accurate, but computationally intensive, scaling as N2. A more approximate and considerably faster method, which scales as N, is known as particle-mesh Ewald (PME) summation. Here the electrostatic potentials for the long-range interactions are mapped onto a mesh of points. The forces on each particle are then computed from the mesh-field by interpolation. The PME approach is becoming the standard for biomolecular simulations. A complete discussion is provided by Allen and Tildesley [31].


6.2.5

MD Simulation of Oligosaccharides 6.2.5.1 Initial Conformation

Before beginning any simulation it is necessary to select a suitable starting conformation for the solute. In principle, the simulation should reach statistical convergence regardless of the initial configuration. This is certainly true for any rotatable bond with a low rotational energy barrier, such as for hydroxyl groups. But for rotamers with high-energy barriers, a poor initial configuration can delay convergence excessively. Further, a very high-energy starting configuration can lead to irreversible conformational changes, or even to instabilities in the trajectory. To avoid these potential difficulties it is common to select the starting conformation from a known experimental reference structure, such as from NMR or X-ray crystallographic analyses. For oligosaccharides, this may be impossible because of the paucity of experimental data, in which case several avenues are open for generating an initial conformation. Extensive conformational data, both experimental and theoretical, are available for disaccharides, and these data may be used to construct an initial conformation for an oligosaccharide [32]. For an oligosaccharide containing previously unstudied linkages, a general rule of thumb is to orient the }-glycosidic angle in the conformation expected on the basis of the exo-anomeric effect [33] and to orient the w-angle to approximately 0 8 [1]. In the case of 1–6 linked oligosaccharides, it is necessary to select a suitable conformation for the x-angle. Generally, this angle populates predominantly two conformations in solution [34], and there are two philosophies to simulating 1–6 linked oligosaccharides. The first is to initiate a simulation for each of the rotamers of the x-angle, and the second is to assume that, given a sufficiently long simulation, a common statistical distribution will be obtained, regardless of which rotamer is employed. This topic is discussed further with examples in the following section.

6.2.5.2 Solvation, Energy Minimization and Molecular Dynamics

For a PBC simulation, the solute is solvated with sufficient water molecules to satisfy the minimum image convention. For example, employing a cut-off distance of 8 Å with a solute of approximate radius “X” Å, it would be necessary to have a simulation box with minimum dimensions (2 ´ 8 + “X”) Å. Solvation is accomplished by placing the solute in a cavity cut out from within a pre-equilibrated box of water. Although the cavity is large enough to encompass the van der Waals surface of the solute, there will often be large electrostatic repulsions arising from non-ideal water-solute orientations. Thus, it is essential that this initial configuration be subjected to thorough energy minimization, generally followed by a simulated annealing protocol. There is a further significant point to note, which is particularly relevant for extremely anisotropic solutes such as linear oligosaccharides. In the case of ellipsoidal solutes, the initial box will be a parallelepiped. During a simulation, the minimum image convention may be violated if the oligosaccharide tumbles sufficiently, placing its long axis orthogonal to the long axis of the simulation box. The

121

122


use of a cubic box, based on the largest solute dimension, is one approach to avoiding this problem. An alternative is to remove translational and rotational motion at frequent periodic intervals, typically every 1–2 ps. A second problem may arise during the simulation if the oligosaccharide adopts a more extended conformation than that for which the initial box dimensions were selected. In this case, there is generally no alternative other than to restart the simulation after resolvating the more extended structure. Both situations argue for the use of a larger solvent box than that required by the minimum image convention. Energy minimization of the initial configuration will remove high-energy interactions arising from close contacts, but will not allow the solvent molecules to reorient significantly. Failure to ensure that the solvent molecules are well oriented prior to beginning a simulation may result in high forces within the solvent, despite the initial minimization, and may lead to an unstable trajectory. Moreover, in the case of a carbohydrate-protein complex, the forces resulting from poor water relaxation can distort the orientation of the ligand relative to the protein. For these reasons, it is generally worthwhile to perform a short MD simulation with the solute restrained, allowing only the solvent to reorient. Because this in-

Typical protocol for a solvated MD simulation of an oligosaccharide or oligosaccharideprotein complex.

Fig. 6.6


volves heating the solvent from near zero up to room temperature, maintaining it at that temperature for a relatively short period (often 50 ps is sufficient) and then slowly cooling it again, it is known as simulated annealing. Prior to beginning the MD simulation, the entire configuration is subjected to a thorough energy minimization. The system must then be heated to the desired temperature, typically 300 K, over a period of 50–100 ps. The production MD run may then be continued for as long as necessary, with coordinate sets (snapshots) collected at regular intervals.

6.2.5.3 Data Analysis

Once the trajectory has been obtained, analysis may proceed. Despite the use of an accurate force field and a rigorous simulation protocol, it should not be assumed that the trajectory is error free. Depending on the particular oligosaccharide and force field, there may arise situations for which the force field was not accurately parameterized. Further, there is the possibility that the simulation conditions were not appropriate because of violation of the minimum image convention, or that other errors have occurred that affect the trajectory but which do not cause the simulation to fail. For these reasons it is essential to carefully scrutinize the outcome of the simulation. Provided that the bulk properties of the system, temperature and density, for example, have behaved appropriately, it is then necessary to examine the behavior of the solute. The purpose of this preliminary examination is to assess the conformational behavior of the solute and to determine which properties are likely to be reasonable and which properties, if any, may be artifacts arising from a problem with the simulation. The dynamic fluctuations of the glycosidic torsion angles are frequently plotted as a function of the simulation time (a time course or trajectory) or may be plotted as a scatter plot of } versus w (a Ramachandran-type analysis). The former approach provides insight into the frequency of internal transitions as well as their lifetimes, and thus gives a good indication as to whether the simulation has reached conformational equilibration. The latter can be useful in establishing the presence of more than one conformational state. The average values for the }and w-angles may be readily computed and compared with experimental values. The standard deviations in these angles provide a measure of their relative flexibility. Further, given the trajectories for the }- and w-angles, it is straightforward to compute the heteronuclear scalar J-couplings, which may also be compared with experiment. Similarly, inter-proton distances may be determined and relevant nuclear Overhauser enhancements (NOEs) computed (compare below). The average Cremer and Pople ring-pucker parameters provide a quantitative measure of the ring geometry and may be the simplest way to monitor ring flips. Other properties that may be computed from the coordinate trajectory include diffusion rates, radial distribution functions, and order parameters. When complexed to a protein, the motions of the ligand are generally dampened relative to the free state, and the standard deviations in the glycosidic angles reflect this feature, as do changes in the population distributions shown in a

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scatter plot of } versus w. In a complex, there are several additional parameters that may be used to assess the simulation. For example, the presence of hydrogen bonds between the carbohydrate and the protein may be monitored. The dynamic simulation can be used to determine which hydroxyl groups function as proton donors or acceptors, a feature that cannot generally be determined by X-ray diffraction or NMR spectroscopy. Further, the MD data can provide detailed information regarding the dynamic character of these interactions and can be used to categorize hydrogen bonds in terms of strengths [22, 23]. Lastly, an effective measure of the stability of the complex may be obtained from the root-mean-squared (RMS) atomic displacements over the course of the simulation. The RMS may be used to measure ligand reorientation relative to the protein, or to estimate the extent of motion associated with the protein itself. When computing relative RMS values, it is first necessary to remove translational and rotational displacements of the solute. This is accomplished by performing an initial RMS fit of the solute in each trajectory frame to a reference structure, such as that present in the first frame of the trajectory.

6.3

NMR Spectroscopy of Oligosaccharides

Hydrogen (1H) is the most commonly observed nucleus for NMR studies of carbohydrates. Most of the hydrogen atoms in carbohydrates are attached to carbon atoms carrying hydroxyl groups (C2, C3, C4 and C6 in hexapyranosides) and consequently share a similar chemical environment. Unfortunately, the resultant 1H NMR signals for these atoms span only the narrow part of the spectrum between * 3.5 and 4.2 ppm. For this reason, in oligosaccharides the majority of the 1H resonances are found in a very crowded region of the NMR spectrum, making the assignment of these resonances challenging. However, hydrogen atoms that occur in different chemical environments give rise to resonances that may be found outside this region, and are often referred to as “structural reporter groups” because of their ability to identify the monosaccharide units or the glycosidic linkage patterns in oligosaccharides [35, 36]. Structural reporter groups include the anomeric hydrogen atoms, hydrogen atoms in methyl groups, hydrogen atoms from deoxysugars, and hydrogen atoms at the aglyconic side of the glycosidic linkage. The effect of chemical environment on 1H NMR spectra is illustrated in Fig. 6.7 for a series of disaccharides in which the anomeric or ring oxygen atoms are replaced by sulfur or selenium [37]. Maltose [a-d-Glc-(1 ? 4)-d-Glc] is a disaccharide that is obtained in large quantities when polymers like starch, in which glucose units are a-(1 ? 4) and a-(1 ? 6) linked, are hydrolyzed. Therefore, a-methyl maltoside (1) presents a model for the a-(1 ? 4) linkage in this polymer. However, both glucose units in 1 are a-linked, and thus the chemical shifts of the 1H nuclei are very similar, giving rise to a complicated NMR spectrum even for this disaccharide. Only the signals from H1, H1', H4' and the methyl group are found outside the narrow region containing

6.3 NMR Spectroscopy of Oligosaccharides

Fig. 6.7 One-dimensional 1H-NMR spectra (D2O) of a-(1) and b-methyl maltoside (2) at 500 MHz and heteroanalogs of 1 where the oxygen atom in the terminal ring is replaced by sulfur and in the glycosidic linkage by sulfur and selenium (3–5, 600 MHz). Different temperatures resulted in different chemical shifts for the solvent signal (HDO). In all a-

methyl compounds (1, 3, 4, 5) the O-methyl group resonance is at the same position. Note also that the chemical shift of H1 in these compounds does not change very much. Signals for hydrogen nuclei with differing chemical environments, like H1', H4 and H5', show marked shifts.

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the majority of the disaccharide signals. The situation improves for methyl b-maltoside (2). The NMR spectrum of this compound is much better resolved, and therefore 2 instead of 1 was used in a conformational analysis [38]. Replacement of the oxygen atoms by sulfur or selenium in the terminal ring or the glycosidic linkage resulted in maltose heteroanalogs 3–5 [37], which are reasonably good inhibitors of glucoamylase [39]. Using transferred NOE experiments (see Chapter 12), the conformation of 4 bound to glucoamylase was solved recently [40]. Because of the effects of the sulfur and selenium nuclei in compounds 3–5, the 1H NMR spectra are much easier to interpret than the spectra of 1 or 2. Signals from hydrogen nuclei in close proximity to the chalcogens, like H4, H1' and H5', show markedly different shifts from those in the parent molecules. NMR observables that bear structural information include NOE effects, 3-bond homo- and heteronuclear J-coupling constants and residual dipolar couplings (observed in magnetically aligning media such as dilute liquid crystals). Long-range coupling constants and residual dipolar couplings are discussed in detail (see Chapters 2 and 8). Here we will focus on the application of NOE effects to the conformational analysis of oligosaccharides in solution. 6.3.1 1

H-1H NOE Experiments on Oligosaccharides

When two spins, usually called I and S, experience each other’s magnetic dipole moment, a dipole-dipole interaction phenomenon called cross-relaxation can transfer magnetization through space from one spin to the other. Thus the signal intensity of spin I changes when the equilibrium state of a neighboring spin S is disturbed by saturation (S refers originally to the saturated spin) or inversion with radio-frequency pulses. The change in intensity arising from this dipolar interaction is called nuclear Overhauser enhancement (NOE) [41, 42]. The intensity change of spin I is governed by the three transition probabilities for zero-, one- and double quantum transitions, namely W0IS, W1I and W2IS, respectively, which describe the cross-relaxation pathways in an idealized two-spin system. With these transition probabilities, the intensity change of spin I with time is defined by the Solomon equation [43] as: dIZ dt

IZ

IZ0 W0IS 2W1I W2IS

SZ

S0Z W2IS

W0IS

10

In Eq. (10), SZ and IZ are the longitudinal components of the magnetization of spins S and I (S0Z and I0Z at time zero). The Solomon equation is strictly applicable only for an idealized spin system, that is, for two isolated spins that are not scalar coupled and that exist in a rigid and isotropically tumbling molecule. Depending on tumbling rate, the zero- and double quantum transition probabilities cause negative and positive NOE enhancements, respectively. The difference between these probabilities (W2IS–W0IS), called the cross-relaxation rate constant (rIS), describes the rate of dipole-dipole transitions giving rise to the NOE en-


hancement, and therefore defines how fast an NOE enhancement is transferred between spins I and S. The term W0IS + 2W1I + W2IS is called the dipolar longitudinal relaxation rate constant (qIS) and is part of the relaxation mechanism responsible for restoring the equilibrium state of spin I. Incorporating these definitions, and taking into account that, while saturating spin S at steady state dIZ/dt = SZ = 0, we obtain: IZ0

IZ S0Z

rIS qIS

11

Since the longitudinal components of spins S and I at the beginning of the experiment are identical (S0Z = I0Z), S0Z can be further substituted by I0Z to give the maximum steady state NOE enhancement g for spin I after saturation of spin S: g

IZ0

IZ IZ0

cS rIS cI qIS

12

The relationship between the two gyromagnetic ratios (cS and cI) means that Eq. (12) is also applicable to systems in which I and S are spins with different precession frequencies (x), such as 1H and 13C, which give rise to a heteronuclear NOE. For a homonuclear 1H-1H NOE cS = cI. The transition probabilities, and therefore also rIS and qIS, depend strongly on the precession frequencies (x) of the spins and the overall correlation time (sc) of the molecule, which is a measure of the rate of reorientation in solution. When these terms are incorporated into Eq. (12) the maximum homonuclear steady-state NOE becomes: g

5 x2 s2c 4x4 s4c 10 23x2 s2c 4x4 s4c

13

Employing Eq. (13), the variation of the homonuclear NOE with the rate of reorientation of the molecule is presented in Fig. 6.8 for a given precession frequency x. For molecules that tumble rapidly in solution, for example small organic compounds in organic solvents, a maximum theoretical NOE enhancement of + 50% is obtained. This region of the NOE curve is often called the extreme narrowing limit. Large molecules, such as proteins or polysaccharides, tumble much more slowly and result in a maximum theoretical NOE enhancement of –100%. Using the transition probabilities, we see that for short correlation times (small molecules) W2 dominates and leads to a positive NOE, whereas for large molecules (with long correlation times) the W0IS transition is dominant, leading to negative NOE effects. At xsc = (5/4)1/2 = 1.12 the NOE curve passes through zero, causing the maximum theoretical NOE enhancement to disappear. Unfortunately, it is within this region of the curve that oligosaccharides of the size of di- to penta- or hexasaccharides (* 400 to 1500 Da) are located. In reality we are not working with idealized spin-systems, and the longitudinal dipolar relaxation between spins I and S is not the only relaxation mechanism

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Dependence of the maximum homonuclear NOE and ROE enhancement on the product of the spectrometer frequency (x0) with the overall correlation time of the molecule (sc) x0sc for a two-spin system at 500 MHz [see Eq. (13)]. Saturation of the Fig. 6.8

source spin was assumed (steady-state NOE conditions). In the case of inverted spins (transient NOE experiments) the dependence is almost identical, but starts at an enhancement of 0.38 for rapidly tumbling molecules (extreme narrowing limit).

present. In such real molecules the NOE enhancement is inversely proportional to the distance (r) between the nuclei. g

sc r6

14

Given a NOE between a pair of nuclei (C and D), which are separated by a known distance, it is possible to determine the distance between two other nuclei (A and B) using the simple relationship shown in Eq. (15). This method is referred to as the two-spin approximation. NOEAB rAB6 NOECD rCD6

15

The inverse exponential dependence on r of the NOE enhancement places a limit on the maximum distance between two hydrogen nuclei for which a NOE effect is generally detectable. In oligosaccharides the upper limit is approximately 4 Å, whereas in either very large or very small molecules this limit may extend to 5 or 6 Å. Therefore, the combination of the weak intensity of the NOEs (due to the inherent values of xsc) and the need for the spins to be physically close to one another results in few and generally weak NOE effects between monosaccharide units in an oligosaccharide. Interpretation of the available NOE effects in terms of


conformation is further aggravated by the presence of internal motion, especially related to glycosidic linkage flexibility. 6.3.2

ROE Experiments

When the magnetization of spins is locked in the x-y plane of the coordinate system, which rotates with the speed and direction of nuclear precession (called the rotating coordinate system or rotating frame) with a long and weak pulse (spin-lock pulse), dipolar relaxation leads to so-called ROE effects (Rotating frame Overhauser Enhancement [44]). This experiment was first called Camelspin (Cross-relaxation appropriate for mini-molecules emulated by spin-locking [45]), later ROESY, and has the advantage that the ROE enhancement is always positive (Fig. 6.8). Therefore, it is often used for small to intermediate sized molecules, in which only NOE effects are minimal. Unfortunately it is impossible to apply a uniform spin-locking field over the whole spectral width, and each spin experiences a slightly different effective spin-lock field. As a consequence, the ROE effect depends not only on the internuclear distance but also on the offset between the resonance and the frequency at which the spin-lock field is applied. A very closely related experiment, called TOCSY (Total correlation spectroscopy), also uses spin-lock fields to transfer magnetization through the bonds of a spin system. TOCSY uses stronger spin-lock fields than the ROESY experiment, and in this way it is possible to correlate resonances that are scalar coupled. Unfortunately, TOCSY cross-peaks are a source of artifacts in ROESY spectra [44, 46, 47]. Additionally, the combination of ROESY and TOCSY magnetization transfer can also lead to unwanted cross-peaks. Given these complications, ROESY spectra are frequently difficult to interpret, and it is not surprising that conformational analyses of oligosaccharides more often rely on NOE than on ROE effects. Notably, ROESY experiments may be employed to uncover spin diffusion artifacts in transferred NOE experiments (see Chapter 12). 6.3.3

Relaxation Matrix Approach

Molecules very seldom have only two 1H nuclei between which a NOE effect can be measured, and therefore they display much more complicated NOE behavior than that predicted by the idealized two-spin model. NOE intensities in multispin systems are more accurately described by matrix equations [48, 49]. For transient NOE experiments, the NOE intensities (a) vary as a function of the experimental mixing time sm according to the following NOE matrix, asm e

Rsm

16

where R is the full relaxation matrix, consisting of the diagonal elements qi (longitudinal relaxation rate constants of spin i) and the off diagonal elements rij = rji (cross relaxation rate constants involving spins i and j).

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2

q1 6 r21 R6 4 rn1

r12 q2

3 r1n 7 7 5 qn

17

Eq. (16) may be solved numerically by calculating the diagonal matrix of the eigenvalues (D) and the matrix of eigenvectors (T) of R. asm T exp Dsm T

1

18

As both qi and rij depend on r–6 ij , the relaxation matrix can be used to calculate theoretical NOE effects, given the internuclear distances, or, given a complete set of NOESY intensities, a matrix of internuclear distances may be determined [42]. The full relaxation matrix approach is applicable only for weakly coupled spins and is based on the assumption that the molecule tumbles isotropically, that is, that rotation and translation for the entire molecule may be described by a single parameter (sc). Effects from anisotropic tumbling [50], cross-correlation [51], or strong scalar coupling [52] are not taken into consideration. It has been shown, however, that internal motions in carbohydrates can influence proton relaxation parameters, and thus theoretical NOE values for oligosaccharides calculated with the full relaxation matrix approach may also depend on the flexibility of the glycosidic linkages [53]. A solution to this problem, albeit quite tedious to implement, is to assign individual correlation times for each glycosidic linkage in the oligosaccharide [54, 55]. In the program CROSREL [56, 57], the full relaxation matrix approach is extended to take the offset dependence of ROE effects into account. This program can therefore calculate theoretical NOE as well as ROE effects for a given molecular conformation. 6.3.4

One- and Two-Dimensional NOE Experiments

In order for cross-relaxation to occur between one or more spins, the equilibrium state of one spin must be disturbed by saturation or inversion. Saturation of resonances in one-dimensional steady-state NOE experiments has been used by several generations of NMR spectroscopists to measure NOE effects for carbohydrates and other small and intermediate sized molecules. Steady-state NOE experiments are well established, but quantification of the obtained data is limited because of several shortcomings, including incomplete saturation and lack of selectivity of irradiation. To overcome these limitations, modern NOE experiments rely on the transient NOE approach, in which spins are inverted by radio frequency pulses. From a theoretical perspective, the maximum NOE enhancement for a transient NOE experiment in the extreme narrowing limit is 38.5% compared to the maximum NOE enhancement for the steady-state NOE experiment, which is 50% [42]. Apart from this, the dependence of the transient NOE on x sc matches the curve presented in Fig. 6.8. The basic pulse sequence of the two-dimensional


NOESY experiment, as well as one-dimensional variants and the ROESY experiment, is given in Fig. 6.9. The first two 90 8 pulses and the evolution period D in the NOESY experiment together select and invert spins. By incrementing the evolution period during the experiment, a second dimension is opened. In the following mixing time (sm), cross-relaxation leads to magnetization transfer. The raw data are read by the last 90 8 pulse and transferred into a two-dimensional spectrum by two consecutive Fourier transformations. In principle, the acquisition of a NOESY experiment requires only the careful calibration of the 90 8 pulse together with the determination of the delays. However, vital prerequisites for measuring NOE effects in small- to medium-sized molecules include stability of the magnetic field and the temperature in the probe

Schematic representation of pulse sequences for one- and two-dimensional 1 H-1H NOE and ROE experiments. Unselective pulses (hard pulses) are drawn as filled rectangles. Shaded rectangles represent spinlock pulses. Selective pulses (soft pulses) and pulsed field gradients are usually shaped to avoid or reduce artifacts. For 180 8 or 270 8 Fig. 6.9

selective pulses, gaussian shapes are preferably used. One-dimensional experiments are created by selective excitation or inversion of the resonances of interest and deletion of the evolution period (D). The hard pulses in the two-dimensional ROESY experiment marked with an asterisk are optional.

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[42]. With the introduction of digitally operated NMR spectrometers and improved temperature control of the probes, artifacts in NOESY spectra have been largely reduced. A recent example of a NOESY spectrum of a disaccharide is given in the next section (Fig. 6.11). A one-dimensional experiment may be derived from any two-dimensional pulse sequence by deleting the evolution period and combining the first two pulses of the sequence [58]. 1D NOESY [59, 60], 1D transient NOE [42, 61] and 1D ROESY [62] experiments follow these rules (see Fig. 6.9). Because of their superior phase properties, 270 8 gaussian-shaped pulses are preferable to 90 8 gaussian or halfgaussian pulses for 1D NOESY and 1D ROESY experiments [63]. The 1D DPFGSE (double pulsed-field-gradient spin-echo) NOE experiment [64, 65] selectively excites a resonance, while dephasing all magnetization outside the selected region. This is achieved by dephasing all magnetization after the first 90 8 pulse by a pulsed-field-gradient (PFG) and selectively rephasing only the resonance where the shaped pulse is applied by the gradient spin-echo sequence. Through this approach, all unwanted magnetization is completely dephased before the start of the mixing time and hence does not contribute to the resulting spectrum. This strongly reduces artifacts and optimizes usage of the analog-to-digital converter when acquiring the raw signal.

6.4

Example Application I: Conformational Analysis of a Disaccharide Employing NOE Curves in Conjunction with Monte Carlo and Molecular Dynamics Simulations [66]

When presented on human cell surfaces outside the blood system, the O-linked TAntigen disaccharide (b-d-Gal-(1 ? 3)-a-d-GalNAc) is a well-defined tumor antigen [67, 68]. Knowledge about the biological recognition of this disaccharide by proteins is therefore relevant for diagnostic as well as therapeutic purposes. A detailed understanding of the biological recognition mechanism of such a tumor marker benefits from a thorough understanding of the conformational and dynamical aspects of the uncomplexed oligosaccharide in aqueous solution. For a conformational analysis of the methyl glycoside of the T-Antigen disaccharide 6 (b-d-Gal-(1 ? 3)-a-d-GalNAc-OMe), 2-D NOESY spectra with mixing times between 100 ms and 1.3 s (Fig. 6.11) in D2O were acquired. In total, seven inter-glycosidic

Fig. 6.10 The T-Antigen disaccharide 6 contains a b-(1 ? 3) glycosidic linkage.

6.4 Example Application I

Fig. 6.11 Section of a NOESY spectrum of the T-Antigen disaccharide 6 with 1.1 s mixing time. Reproduced from [66].

NOEs (H1'-H3, H1'-H4, H1'-H2, H1'-NHAc, H2'-H3, H2'-H4 and H5'-H4) could be observed, most of them displaying a maximum NOE enhancement of < 0.3%. The only interglycosidic NOE that showed an enhancement above 1% was the one across the glycosidic linkage (H1'-H3). In previous conformational studies of the T-Antigen, the maximum number of observed inter-glycosidic NOE effects was two [69–71]. The seven interglycosidic NOE effects observed here formed the experimental basis to which theoretical NOE curves from MMC as well as MD simulations were compared. Fig. 6.12 shows population plots of the glycosidic angles } and w at the b(1 ? 3) linkage in 6 generated from MMC and MD simulations. To ensure that the conformational space was sampled sufficiently, both types of simulations were run considerably longer than usual. A total of 9.5 ´ 106 Monte-Carlo steps, with a temperature factor of 600 K, were collected. In previous MMC simulations with the GEGOP force field, this temperature factor was found to reproduce the experimental data very well [72]. MD simulations were performed in a box of 623 TIP3P

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Fig. 6.12 Population plot of MMC and MD simulations of 6 showing the relative population of conformational space for the b-(1 ? 3) linkage. The contours were calculated by dividing the }/w population maps from MMC and MD simulations into bins of 10 8 spacing in both dimensions. The number of conformations in every bin was counted, and then con-

tour levels were calculated relative to the populated bin. The contour levels define regions with (from the inside to the outside of the contour plot) > 90%, 70–90%, 50–70%, 30– 50%, 10–30% and 1–10% of the number of conformations in the most highly populated bin. Reproduced from [66].

water molecules at 300 K for a total simulation time of 10 ns. From these simulations averaged relaxation matrices were constructed. An overall correlation time (sc) of 70 ps was used to generate theoretical NOE curves from the relaxation matrices. The population plots from MMC and MD simulations generally agree very well; both define two regions of conformational space (A and B in Fig. 6.12) in which a major and a minor conformation are located. A closer inspection of the population maps reveals two areas in which the plots differ slightly. The w-angle of the population maximum at the b-(1 ? 3) linkage is located at approximately –10 8 (A1 in Fig. 6.12) in the MMC simulation, whereas it is shifted to more negative values around –30 8 (A2 in Fig. 6.12) in the MD simulation. Second, the MMC simulation shows a slightly higher population of conformations in area B than that found in the MD simulation. The very satisfying agreement between the experimental and theoretical NOE curves is evident from the data in Fig. 6.13. Given the weak intensities of most of the experimental NOE data, this is an important achievement. The better fit of the experimental NOE curve H1'-H4 to the MMC simulation reflects the higher population of conformations in which short distances between these two protons are found (see Fig. 6.12). The very small inter-glycosidic NOE H2'-H3 shows a

6.4 Example Application I

Fig. 6.13 Comparison of experimental and theoretical NOE curves for 6. Experimental data points are connected by solid lines, MD by dotted, and MMC data by dashed lines. For the NOE H1'-H2, the experimental data point at 300 ms mixing time is missing. Reproduced from [66].

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NOE enhancement of only * 0.1% at long mixing times (over 1000 ms). For this effect, no experimental NOE curve could be obtained; however, a short distance between these two protons (* 2.2 Å) can only be found in the region of conformation B (compare Fig. 6.14). This NOE effect has not been detected in previous conformational analysis and indicates that the }-angle of the b-(1 ? 3) linkage in 6 populates not only the conformational region consistent with the exo-anomeric effect (* 60 8, region A), but also a relatively uncommon one (* 1808, region B). By comparison with the theoretical NOE data, it may be estimated that conformations in region B are populated only to approximately 5%. These results indicated that the T-Antigen disaccharide is more flexible than previously thought [69–71] and formed the basis for an investigation of the conformational behavior of the TAntigen when bound to the lectins Jacalin or Maclura pomifera agglutinin [73].

Fig. 6.14 Ball and stick representation of conformations A1 and B from MMC and A2 from MD simulations of 6 (produced with Molscript [74]). Hydroxyl protons have been omitted for clarity. Nitrogen atoms are black, carbon atoms dark gray and oxygen atoms light gray. Reproduced from [66].

6.5 Example Application II

6.5

Example Application II: PBC Simulation of the Oligomannoside Man9GlcNAc2

N-linked oligosaccharides derived from the parent structure Man9GlcNAc2 (7) shown in Fig. 6.15 are early intermediate structures during N-glycan processing. They are also found on an extensive range of mature glycoproteins. Because of their biological significance, oligomannosides have been the subject of conformational analysis by NMR spectroscopy and MD simulation [75–79]. The MD simulations have been performed both with [77] and without [80] explicit solvation. A 1 ns solvated PBC MD simulation of 7 has been reported [77], which provides an example of the level of insight into the conformational properties afforded by such a simulation. The results of this simulation were compared with an extensive set of 1H NOE data. The motions of the glycosidic torsion angles, determined from the simulations, were shown to be consistent with the experimental NMR data (inter-residue NOEs) for most of the glycosidic linkages. The comparisons were based both on NOE intensities, computed from a full relaxation matrix analysis of the MD trajectory, and, conversely, on torsion angles derived from the experimental NOE data, employing the isolated spin pair approximation (ISPA). Presented in Fig. 6.16 are the experimental and theoretical NOE build-up curves for the outer Man-a-(1-3)-Man-a linkage in 7. In the case of this 1–3 linkage, both the MD and ISPA data (Fig. 6.17) indicated that this linkage populated several conformational states. In the light of this fact, no single structure could generate a set of NOEs that were completely consistent with the experimental data. The validity of the MD simulation may be judged by the observation that there is excellent agreement between the experimental and theoretical NOEs seen in Fig. 6.16, as well as, independently, between the MD and ISPA-predicted populations of the glycosidic torsion angles (Fig. 6.17). In discussing the simulated properties of glycosidic linkages, it is often remarked that one linkage is more or less rigid than another. This is a valid statement only when both have been examined over a comparable time span. That is, it is impossible to conclude that one linkage is more flexible than another unless the conformational states have been fully sampled. For example, on the nanosecond timescale of the simulation reported for 7, each of the linkages shows varying degrees of motion. On this time scale it appeared that the 1-6 linkages were the most rigid (see Fig. 6.18). While this may be the case, as found for the

Fig. 6.15 Schematic representation of Man9GlcNAc2 (7) showing the linkage and branching patterns. Core trimannoside (8) is shown in boldface.

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Fig. 6.16 Theoretical (solid lines) NOE build-up curves and experimental intensities (with error bars) for the outer Man-a-(1-3)-Man-a linkage in 7.

Fig. 6.17 Experimentally allowed (ISPA) values (contours) and computed values (dots) for the outer Man-a-(1-3)-Man-a glycosidic torsion angles in 7.

relatively rigid inner 1–6 linkage in 7, it may also reflect the short time scale of the simulation. Because of the low frequencies of the transitions between rotamers of the x-angle, the properties of 1–6 linkages have been particularly challenging to simulate. For example, the NMR data for the outer 1–6 linkage in 7 suggested a ratio of 4 : 1 for the gg : gt rotamers, while the MD data indicated a preference for the gt rotamer but showed insufficient transitions to compute a statistically accurate distribution. Recently, much longer simulations have indicated that rotations of the x-angle occur on the order of every 5–10 ns (Fig. 6.19) [22, 81]. As part of a study investigating the role of water in carbohydrate-lectin binding [22], simulations of the complex between the lectin Con A and trimannoside 8 have been reported. In the course of that work, long PBC MD simulations of 8 in water were performed.

6.5 Example Application II

Fig. 6.18 Upper panel: experimentally-allowed (ISPA) values (contours) and MD values (dots) for the inner Man-a-(1-6)-Man-a glycosidic torsion angles in 7. Lower panel: theoretical (solid lines) NOE build-up curves and experimental intensities (with error bars) for the inner Man-a-(1-6)-Man-a linkage in 7.

The results for 8 suggest that extremely long simulations may be required to achieve statistically converged sampling of the x-angle. In the case of 8, the vicinal coupling constants, 3JH5,H6R = 4.5 Hz and 3JH5,H6S = 1.8 Hz, were used to determine the rotamer population of the x-angle of the a(1 ? 6) linkage. By application of a set of Karplus-type empirical equations employing Haasnoot’s parameters [82], a ratio of gg : gt : tg = 72 : 43 : –15 was obtained. The presence of a negative tg population has been attributed to inadequacies in the Karplus-type equations, and is commonly corrected by setting the tg population to zero [83]. Following this procedure, a population ratio of gg : gt = 59 : 41 was obtained for the x-angle in 8. Conversely, given an MD trajectory, it is possible to compute average values for 3 JHH coupling constants and compare them directly with the experimental values, thus avoiding the need to make assumptions about the rotamer populations. Applying the Karplus-type equations to the trajectory for 8 resulted in theoretical values of 3JH5,H6R = 4.8 Hz and 3JH5,H6S = 3.5 Hz. While the values for 3JH5,H6R were

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Fig. 6.19 MD trajectory for the x-angle (O6-C6-C5-O5) in trimannoside 8.

in reasonable agreement with the experimental data, the theoretical values for 3 JH5,H6S were overestimated. The extent to which this is due to approximations inherent in the use of empirical Karplus-type relationships rather than to inaccuracies in the simulation data is unclear. However, the x-angle varies between two staggered rotamers, and a small change in rotamer population may affect the computed J-values considerably. Although the rotamer ratio of 70 : 30 obtained from the MD simulations is in reasonable agreement with the experimental values, it might still be improved by extending the simulation to 100 ns. It is clear that early MD simulations were not performed for sufficient duration to observe these transitions. Lastly, from simulations that include solvent explicitly, it is possible to investigate the role of hydrogen bonding in stabilizing carbohydrate conformation [81]. For example, in 7, an extensive network of internal hydrogen bonds has been observed, characterized by stable inter-residue interactions as well as water-mediated interactions (Fig. 6.20). However, there remains an enigma. Do water-mediated hydrogen bonds influence the conformation, or do they merely occur because the hydroxyl groups are located in a suitable fortuitous 3-D arrangement? Evidence exists that water does influence carbohydrate conformation relative to that which would theoretically exist in the gas phase [81] or in apolar solvents [84]. It appears that water disrupts the internal hydrogen bonds, which would otherwise exert strong influences on the conformation. The weakening of internal hydrogen bonds in water has been used to interpret the conformational preferences of the x-angle in gluco- and galactopyranosides and their 1–6 linked analogs [81]. However, these results alone are not sufficient to directly assess the relative strengths of water-sugar and sugar-sugar hydrogen bonds when they occur in water.

6.6 Conclusions

Fig. 6.20 A schematic representation of the hydrogen bonding in 7. Percentage residency times are indicated for high-occupancy water-

mediated hydrogen bonds (–H2O–) as well as for direct inter-residue hydrogen bonds (–).

6.6

Conclusions

Many experimental NMR parameters which relate to the conformation of an oligosaccharide in solution may be measured. However, achieving a quantitative agreement between these parameters and those computed from a theoretical model remains a challenge. Accurate calculation of parameters such as NOE intensities or scalar coupling constants is difficult, even when the molecule exists in a single well-characterized conformation. Traditional ISPA approaches to computing NOE intensities give at best only qualitative agreement with experiment, and are inappropriate for computing weak NOEs observed only at long mixing times. Deficiencies in empirical relationships between torsion angle and three-bond J-couplings have been frequently noted, and include the prediction of negative rotamer populations and the overestimation of J-coupling values. More quantitative methods exist for computing NOEs, such as matrix-based approaches, and for computing Jcouplings using quantum mechanical calculations, and their application is becoming more common. Nevertheless, the problem becomes considerably more complex when internal motions are present in the molecule. This is frequently the case in oligosaccharides, for which it is necessary to derive the NMR parameters from an ensemble of structures. Both MD and MC methods have been used to generate conformational ensembles for oligosaccharides.

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Advances in computer performance now enable long (> 10 ns) solvated MD simulations to be performed routinely on oligosaccharides. With such long trajectories, computed with suitably accurate force fields, it is possible to determine many of the conformational properties of an oligosaccharide. Practical time limitations still exist for very large systems, such as polysaccharides, or complexes of oligosaccharides and proteins. But, given the continuing growth in computer performance, these limits are decreasing. As longer and longer simulations are reported, more information regarding the timescales of internal motions is becoming available, and it is now evident that simulation times of up to 1 ls may be required in order to achieve statistical convergence. More fundamental issues, relating to the proper treatment of internal motions when computing NMR properties and to weaknesses associated with Karplus-type relationships used to compute J-couplings, still remain a challenge. Developments in the measurement and analysis of residual dipolar couplings may provide a muchneeded additional source of experimental data [85, 86]. To arrive at an accurate overall description of the spatial and temporal properties of an oligosaccharide it is essential to critically compare the simulation to as many diverse experimental results as possible.

6.7

Acknowledgements

We wish to thank B. O. Petersen and J. Ø. Duus, Carlsberg Research Center, Copenhagen, Denmark, for the NMR spectra of compounds 1 and 2.

6.8

References 1 2 3 4 5

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7

The Unique Solution Structure and Immunochemistry of the Candida albicans b1,2-Mannopyranan Cell Wall Antigen Mark Nitz and David R. Bundle

7.1

Introduction

We review here recent progress from our laboratory on studies of the homo-glycan (1 ? 2)-b-mannopyranan, an important antigen located in the cell wall of the yeast, Candida albicans, and a polysaccharide that was predicted some 25 years ago to adopt a unique solution conformation [1]. These predictions are verified, and the compact conformation that results correlates with unusual immunochemical properties that suggest that vaccines against the pathogenic yeast may be constructed from relatively small oligosaccharide fragments conjugated to proteins. Although Candida albicans is ubiquitous in the natural flora of humans, it is also the most common etiologic agent in candidiasis [2]. This infection commonly occurs in immunocompromised patients and those undergoing long term antibiotic treatment [3]. The infection can range in severity from a common mucosal infection to a life-threatening systemic infection. Regular increases in the number of cases of systemic candidiasis have become a major medical problem in hospitals, where C. albicans is now responsible for up to 25% of the nosocomial infections. This increase is associated with increasing drug resistance to available anti-fungal drugs and the difficulty with early detection of C. albicans infections [4]. Considerable effort is now being expended to find new treatments that are effective against this fungal pathogen, and the cell wall oligosaccharides represent one target.

7.2

Candida albicans Cell Wall

The first line of defense for C. albicans is its cell wall, consisting mainly of chitin, glucan and mannan. The chitin and glucan are protective against osmotic stress, allowing the yeast to live in a wide range of environments, inside and outside the host. The mannan portion of the cell wall has received the greatest attention as it is highly immunogenic [5] and has been associated with the adhesion of yeast to different cell types [6, 7]. It is known to cause activation of macrophages [8] and is the mechanism whereby yeasts bind to macrophage membranes [9, 10].

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7 The Unique Solution Structure and Immunochemistry

Fig. 7.1

A portion of Candida albicans N-linked mannan: chain lengths vary.

Suzuki’s group using NMR and mass spectrometry have elucidated the structure of the mannan component of Candida albica [11 a–d]. Less than 10% of the mannan is O-linked, consisting largely of short (1 ? 2)-a and (1 ? 3)-a-d-mannopyranan [12]. The complex N-linked components are composed of extended (1 ? 6)-a-d-mannopyranan backbones containing (1 ? 2)-a-d-mannopyranan branches. Furthermore, (1 ? 2)-b-mannopyranan oligomers are attached through a phosphodiester bridge. The position of attachment of this phosphodiester has yet to be determined (Fig. 7.1). The mannan is heterogeneous and differences in its chain length have been shown to be nutrient and environment dependent [13]. Recently, the mannan has also been shown to exist as a phospholipomannan [14]. This is a new type of eukaryotic glycolipid characterized by the absence of Nacetylglucosamine. The glycolipid contains an eight to eighteen residue (1 ? 2)-bmannan oligomer that is linked via phosphoinositol to a yet to be identified lipid.

7.3

Host Defenses against Fungal Infection

Both humoral and cell-mediated immunity play major roles in host defenses against Candida albicans. While the most serious cases of fungal infections occur in patients with defects in their cellular immunity, the role of antibodies also appears to be crucial in these infections [15]. Indeed, patients with recurring candidiasis seem to lack antibodies against a large portion of the mannan found in the yeast cell wall [16]. Strong evidence pointing to the importance of antibody comes from the observation that murine monoclonal antibodies raised against the C. albicans cell wall extracts were protective against disseminated candidiasis and vaginal candidiasis

7.4 Chemical Synthesis of 1,2-Linked b-Mannopyranose Oligomers

in mouse models [17–19]. Characterization of the specificity of these monoclonal antibodies indicated the epitope to be a portion of the (1 ? 2)-b-mannan polymer found in the phosphomannan [20]. Agglutination studies suggested the epitope was likely to be a (1 ? 2)-b-mannotriose derivative. This is an unusual finding, since the authors found that longer (1 ? 2)-b-mannooligomers were not able to prevent agglutination of antibody-coated latex beads, and especially so since [11 b] had found that longer oligomers predominate on the surface of Candida albicans. (Unpublished data from Cutler‘s laboratory shows that di- and trisaccharide (1 ? 2)-b-mannooligomers are the most abundant species). Given the importance of antibodies against the cell wall (1 ? 2)-b-mannooligomers and their ability to protect mice against infection by C. albicans, we decided to investigate both the solution conformational properties and the relationship to the immunochemistry of (1 ? 2)-b-mannooligomers. Accordingly, a series of these homo-oligomers have been synthesized with the objective of studying their conformational and immunochemical properties as well as their utility as conjugate vaccines.

7.4

Chemical Synthesis of 1,2-Linked b-Mannopyranose Oligomers

The rational synthesis of b-mannopyranosides is a long-standing problem that lacks a general solution despite several novel approaches [21]. The synthesis of a homopolymer containing contiguous b-d-mannopyranosides presents an especially formidable synthetic challenge. We have utilized an approach based upon a ulosyl bromide developed by Lichtenthaler et al., since it offered a versatile method for the generation of 1,2-linked b-mannopyranose oligomers with good selectivity [22–25]. In elaboration of a 1,2-linked oligomer, a ulosyl bromide provides first the corresponding ulopyranoside, which can be reduced to afford directly the selectively protected glycosyl acceptor of the next glycosylation step. Using this approach, structures 1–5 from disaccharide to as large as a hexasaccharide, as well as a me-

Scheme 7.1

The application of ulosyl bromides to generate 1,2-linked b-mannopyranosides.

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tabolically more stable tetrasaccharide 6 containing a terminal thioglycosidic linkage, were synthesized as their propyl glycosides (Scheme 7.1). Amino-terminated aglyconic tethers of the oligosaccharides were also generated and coupled to bovine serum albumin to form neoglycoconjugates. The S-linked tetrasaccharide congener 6 containing a non-reducing terminal thioglycoside linkage was envisaged as a potentially better immunogen for anti-C. albicans vaccine development since the terminal glycosidic linkage would be stable to exo-mannosidases. 7.4.1

Synthesis of the Terminal Reducing Residue

Allyl 3,4,6-tri-O-benzyl-b-d-mannopyranoside (8) could be conveniently synthesized on a large scale (up to 10 g) starting from 3,4,6-tri-O-benzyl-1,2-O-(exo-ethoxyethylidene)-a-d-glucopyranose (7) [26]. Lewis acid-promoted glycosylation in allyl alcohol gave a high yield of a near 1:1 mixture of the expected product 8 and its deacetylated counterpart 9. The allyl-b-d-glucopyranoside 8 was treated under Zemplén deacylation conditions to give the desired crystalline alcohol 9. Oxidation of the glucopyranoside (9) using acetic anhydride and DMSO and reduction with sodium borohydride gave the mannopyranoside (10) in good yield with high selectivity (Scheme 7.2) [27]. 7.4.2

Synthesis of Oligosaccharides

The synthesis of the first 1,2-b-mannosyl linkage was accomplished using conditions similar to those employed by Lichtenthaler et al. [24]. The ulosyl bromide 12 was synthesized in a similar fashion, although the yields for the thermal rear-

Scheme 7.2

Synthesis of reducing terminal allyl glycoside.


Scheme 7.3

Scheme 7.4

The synthesis of benzylated ulosyl bromide.

Synthesis of allyl 2-O-(b-d-mannopyranosyl)-b-d-mannopyranoside.

rangement that converts orthoester 7 to an acetoxyglycal (cf. 11) were approximately 65% (Scheme 7.3). Using silver-exchanged zeolite [28] to promote the glycosylation of 10 by 3,4,6tri-O-benzyl-a-d-arabino-hexopyranos-2-ulosyl bromide (12), disaccharide 13 was obtained in excellent yield after reduction of the uloside product with L-Selectride (Scheme 7.4). No a-manno anomer or gluco epimers were isolated from the reaction mixture. It was necessary to use the sterically hindered reducing agent L-Selectride for this reduction since, in contrast to the monosaccharide, the disaccharide gave epimeric mixtures when sodium borohydride was employed. Introducing subsequent b-mannopyranosyl units proved more difficult, and the conditions employed for disaccharide synthesis failed to yield significant amounts of trisaccharide. Exploration of different activation protocols led to the use of the soluble promoter silver triflate, with 2,6-di-tert-butyl-4-methylpyridine as an acid scavenger and the participating solvent acetonitrile. Participating solvents have been used previously to increase the yield of b-glycosides in the presence of a non-participating group at the 2-position. To date, this approach has not been profitable for the synthesis of b-mannosides, likely because of the steric hindrance that occurs in generating a 1,2-cis linkage [29]. However, the use of ulosyl bromide donors and a participating solvent proved effective for the synthesis of the b-mannosides explored here. The reaction gave the desired trisaccharide in 40–45% yield and 10% yield of the a-gluco epimer together with a significant portion of the 3,4di-O-benzyl-1,6-anhydro-b-d-mannopyranose 16 [23]. The a-gluco epimer likely arose from formation of the a-uloside, which is reduced to the gluco product. It was hypothesized that 16 must form via attack at the anomeric center by O-6, followed by loss of the benzyl group (Scheme 7.5). p-Chlorobenzyl ethers are more stable to acidic hydrolysis than the corresponding benzyl ethers, and thus stabilization of the protecting groups by installing pchlorobenzyl ethers would likely disfavor the formation of this anhydro sugar side product and in turn increase the yield of the target oligosaccharides [30]. The p-

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Scheme 7.5

Synthesis of 1,2-linked b-mannosyl trisaccharide using benzyl protecting groups.

chlorobenzyl-protected donor was synthesized analogously to the previously prepared benzyl-protected ulosyl bromide (Scheme 7.6) [24]. Standard deacylation of the readily available 3,4,6-tri-O-acetyl-(exo-ethoxyethylidene)-a-d-glucopyranose [26 ], followed by Williamson ether synthesis with pchlorobenzyl chloride, gave the p-chlorobenzyl-protected orthoester 17. Subsequent thermal rearrangement in bromobenzene gave a high yield of the acetoxyglycal (18), attesting to the increased stability of the p-chlorobenzyl ethers. Subsequent treatment with N-bromosuccinimide and ethanol in dichloromethane gave the desired ulosyl bromide (19) in adequate purity for glycosylations (Scheme 7.6). Glycosylation of the disaccharide alcohol 13 with this donor (19) in the presence of silver triflate and 2,6-di-tert-butyl-4-methylpyridine in acetonitrile, followed by reduction with L-Selectride, gave a 60–65% yield of the desired trisaccharide (20) along with 15% of the corresponding a-gluco epimer (21), which was easily separated by column chromatography (Scheme 7.5). The p-chlorobenzyl protecting

Scheme 7.6

Preparation of p-chlorobenzyl-protected ulosyl bromide.


groups also imparted superior chromatographic qualities to the trisaccharide (20) than were observed with the benzyl-protected trisaccharide, thereby facilitating purification of such oligosaccharides. The synthesis of tetrasaccharide (22) was accomplished as outlined in Scheme 7.8. Pentasaccharide (23) and hexasaccharide (24) were synthesized under similar conditions, employing pivaloyl nitrile as a participating solvent, silver triflate as a soluble promoter, and a p-chlorobenzyl-protected ulosyl bromide glycosyl donor (19) (Fig. 7.1). Previously, it was found that the use of pivaloyl nitrile as the participating solvent limited attack of the acceptor alcohol on the nitrile carbon of a proposed nitrilium intermediate [31], thereby improving the glycosylation yield. pChlorobenzyl-protected ulosyl bromide (19) was found to give higher glycosylation yields than its benzyl-protected counterpart, likely because of the increased stability of the protecting groups. Formation of the ulosides was accomplished with good selectivity giving an approximate 4:1 b:a mixture in favor of the desired linkage. Separation of the a-anomer was readily accomplished by silica gel chromatography of the protected oligomer. Excellent diastereoselectivity was observed upon reduction of the b-ulopyranoside to the desired b-mannoside with L-Selectride. No b-gluco epimer could be detected by 1H NMR. Heteronuclear one-bond coupling constants were used to unambiguously establish the anomeric configuration of the mannopyransyl residues [32]. The protected oligosaccharides (13, 20, 22–24) were elaborated via photo addition of 2-aminoethanethiol [33] to the allyl glycosides to give the amine-functionalized glycosides (25–28). It was necessary to use long wave (365 nm) UV irradiation to avoid complications with the aromatic protecting groups (Scheme 7.9). Purification of these compounds was difficult, and they were deprotected under dissolving metal conditions to yield the amino-functionalized glycosides (25–28) after purification. The allyl disaccharide (13) could be readily deprotected under standard hydrogenation conditions to give 1, but the allyl glycosides containing pchlorobenzyl protecting groups (20, 22–24) were resistant to hydrogenation. Deprotection of these compounds to their respective propyl glycosides (2–5) required a two-step procedure. The allyl glycoside was first reduced to the propyl glycoside via diimide reduction, and then the protecting groups were removed under dissolving metal conditions (Scheme 7.9).

Scheme 7.7 Synthesis of 1,2-linked b-mannopyranosyl trisaccharide 20 using p-chlorobenzyl protecting groups.

151

152


Scheme 7.8 Synthesis of pentasaccharide 23 and hexasaccharide 24 (1 ? 2)-b-d-mannopyranan oligomers. (a) 2, AgOTf, DtBMP, (CH3)3CCN/CH2Cl2; (b) L-Selectride, THF.

7.4.3

Synthesis of a (1 ? 2)-b-Mannopyranotetrose Terminated by a Thio-glycosidic Linkage

Mannopyranotetrose (6) was synthesized in order to explore the feasibility of using thio-linked glycans as mimics of the parent structures when they are presented to the immune system. Protein conjugates of this compound should exhibit higher metabolic stability to exo-b-mannosidases and therefore make better immunogens. Initial studies with the terminal thioglycosidic linkage indicated that direct displacement with a b-anomeric thiolate on allyl 3,4,6-O-benzyl-2-O-trifluoromethanesulfonyl-b-d-glucopyranoside was not feasible, since only the b-thioglycoside was obtained. This was surprising given the recent success in forming 1-thio-b-mannopyranosides by this method [34]. Thus, the reciprocal approach was undertaken by installing a thiol on the trisaccharide to act as the nucleophile in the displacement of an anomeric leaving group on the glycosyl donor. The previously synthesized ulosyl bromide 19 was chosen as the glycosyl donor in this reaction. The nucleophilic displacement of a 2-chloro sialic acid derivative with sulfur nucleophiles [35], which has shown success, is analogous to displacement of the bromide of uloside 12 or 19, in that both anomeric halide-leaving groups are a to a carbonyl group. Furthermore ulosyl bromides had previously been shown to react with sim-


Scheme 7.9 Deprotection of (1 ? 2)-b-d-mannopyranan oligomers. (a) 2-aminoethanethiol hydrochloride, MeOH/CH2Cl2, hm 365 nm;

(b) Na/NH3, tBuOH, THF; (c) NH2NH2.H2O, EtOH/THF; (d) Pd/C, H2, EtOH.

ple thiols to give 1-thio-b-d-ulosides in high yield [22]. Thus, the trisaccharide 34 was envisaged as the thiol acceptor for this thioglycosylation. It could be synthesized via the glycosylation of disaccharide 13 with the glucosyl donor 29 to give a trisaccharide functionalized as a 4,6-O-benzylidene acetal (30). This protecting group is necessary to lock the 4C1 ring and thereby facilitate displacement at C-2 with a sulfur nucleophile to give access to trisaccharide 33. Furthermore, these compounds would contain the reducing terminal allyl glycoside for elaboration to the amine-functionalized tetrasaccharide or propyl glycoside late in the synthesis (Scheme 7.9). Formation of the trisaccharide 30 was accomplished in good yield from the imidate donor 29 and the disaccharide acceptor 13 using a minimal amount of TMSOTf in dichloromethane at room temperature. The 2-O-acetate of trisaccharide 30 could then be removed using sodium methoxide to give the alcohol 31 in a solution of methanol and THF to ensure the solubility of the hydrophobic starting material. Introduction of the triflate under standard conditions

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Scheme 7.10

Synthesis of (1-thio-b-d-mannopyranosyl)-(1-2)-b-d-mannopyranotriose.

gave the leaving group functionalized trisaccharide 32 necessary for synthesis of thioacetate 33. This reaction was somewhat troublesome, requiring elevated temperatures, and the yields could not be improved by the introduction of crown ether. Removal of the acetate proceeded smoothly to give the thiol 34, which was surprisingly stable to atmospheric oxidation and required no special handling. The thiol was condensed with the ulosyl bromide to give after reduction the desired tetrasaccharide, 35, as well as the a-gluco epimer after reduction. This suggests that some b-ulosyl bromide (19) may have been present in the reaction. It was not visible by NMR spectroscopy of the starting ulosyl bromide but may be formed via halide exchange. The tetrasaccharide was further elaborated under the same conditions as the previously formed 3-(2-aminoethylthio)-propyl glycosides. The thioglycoside did not appear to complicate the photoaddition of the thiol, giving 36 in reasonable

7.5 Molecular Modeling and NMR of (1 ? 2)-b-Mannopyranan Tri-, Tetra- and Pentose

Scheme 7.11

Deprotection of (1-thio-b-d-mannopyranosyl)-(1-2)-b-d-mannopyranotriose.

yield. The allyl glycoside was reduced with a solution of hydrazine hydrate, which forms diimide under atmospheric oxidation, selectively reducing the double bond and giving 37. Dissolving metal conditions efficiently removed the benzyl and pchlorobenzyl protecting groups to give the desired tetrasaccharides 38 and 39 (Scheme 7.11).

7.5

Molecular Modeling and NMR of (1 ? 2)-b-Mannopyranan Tri-, Tetra- and Pentose

In the mid-1970s, the group of Rees used empirical force fields to assign homopolysaccharides to particular conformational families, and the 1,2-linked b-mannopyrans as well as the corresponding b-glucans were identified as a special category of rarely occurring homopolymers. They were predicted to experience steric interactions between remote residues as a result of crumpled conformations that arose because of their linkage position, anomeric conformation and the stereoelectronic requirements of the glycosidic linkage, often termed the exo-anomeric effect. The

155

156


Fig. 7.2

Definitions of glycosidic torsional angles.

predictions have proven to be quite accurate. For example b-glucans occur in certain bacteria as cyclic glucans [36], and both the gluco and manno homopolymers with this linkage type are rare. The definitions of the glycosidic torsional angles used in this chapter are shown in Fig. 7.2 and refer to the }H (H1B-C1B-O1B-C2A) and wH (C1B-O1B-C2A-H2A) dihedral angles. The pyranose residues are labeled alphabetically from the reducing terminus. Subsequently the abbreviations } and w will be used in the place of }H and wH. 7.5.1

Assignment of 1H and 13C Spectra for (1 ? 2)-b-Mannopyranan Tri-, Tetraand Pentose Oligomers

Considering the homo-polymeric nature of these oligosaccharides, it was surprising to find excellent signal dispersion in their 1H NMR spectra. Other carbohydrate-based homopolymers such as kojitetraose [(1 ? 2)-a-glucopyranotetrose] [37], maltoheptose [(1 ? 4)-a-glucopyranotetrose] [38], and (1 ? 2)-a-mannopyranotetrose show extensive overlap in their 1H NMR spectra. Of particular note, Brucella polysaccharide B, a cyclic (1 ? 2)-b-glucopyranose (17–24 residues) exhibits nearly coincident 1H and 13C signals for all the pyranose rings [36]. This suggests that (1 ? 2)-b-mannopyranan oligomers may be more ordered and conformationally distinct than related 1,2-linked homo-oligomers, even for short sequences, and this could influence their biological properties. Unambiguous 1H and 13C chemical shifts for oligosaccharides 1–6 were established by a combination of GCOSY, GTOCSY and HMQC experiments. The most remarkable observation considering the homo-polymeric nature of oligosaccharides 1–5 was the discrete signal dispersion in their 1H NMR spectra, as seen in the TOCSY spectra (Fig. 7.3). The excellent dispersion of 1H signals permits the spin system of each hexose residue of the homo-oligomers to be assigned. While the resonances of protons H-1 to H-4 for each pyranose ring showed excellent dispersion (Tab. 7.1), the H-5 and H-6 resonances exhibited severe overlap (not tabu-

TOCSY NMR spectrum of tetrasaccharide 3.

157

Fig. 7.3


158

7 The Unique Solution Structure and Immunochemistry Tab. 7.1 1H NMR chemical shifts for oligosaccharide glycosides 2–6 and literature data of Suzuki et al. [39] and Strecker et al. [40] (see text) for the corresponding oligosaccharides isolated from C. albicans

Oligosaccharide/ H-1 hexose residue b) This Ref. work a) 39 2 A B C 3 A B C D 4 A B C D E 5 A B C D E F 6 A B C D

H-2 Ref. 40

H-3

This Ref. work a) 39

Ref. 40

H-4


Ref. 40


Ref. 40

4.72 4.91 4.95

5.27 4.98 4.23 4.84 4.91 4.37 4.85 4.95 4.15

4.10 4.16 3.67 4.27 4.41 3.64 4.15 4.15 3.61

3.90 3.67 3.48 3.66 3.67 3.59 3.62 3.26 3.57

3.61 3.50 3.61 3.61 3.57 3.56

4.73 4.89 5.04 4.94

5.27 4.83 4.92 4.91

4.99 4.88 5.04 4.93

4.24 4.40 4.35 4.16

4.11 4.24 4.40 4.15

4.18 4.39 4.38 4.15

3.67 3.68 3.64 3.62

3.90 3.69 3.63 3.61

3.68 3.70 3.64 3.62

3.48 3.50 3.60 3.57

3.59 3.51 3.59 3.57

3.48 3.52 3.60 3.57

4.72 4.89 5.00 5.03 4.95

5.27 4.83 4.91 5.01 4.94

4.99 4.89 5.03 4.92 4.95

4.23 4.34 4.38 4.38 4.15

4.11 4.25 4.39 4.37 4.15

4.18 4.39 4.39 4.41 4.16

3.68 3.67 3.66 3.63 3.62

3.91 3.70 3.66 3.63 3.63

3.69 3.70 3.64 3.69 3.27

3.48 3.49 3.58 3.51 3.56

3.60 3.50 3.50 3.59 3.58

3.47 3.51 3.59 3.50 3.57

4.77 4.90 5.02 5.02 5.06 4.96

5.27 4.83 4.92 4.99 5.03 4.94

4.99 4.89 5.01 5.01 4.94 4.96

4.24 4.34 4.40 4.37 4.40 4.16

4.11 4.25 4.40 4.36 4.37 4.15

4.18 4.39 4.37 4.39 4.41 4.16

3.68 3.68 3.67 3.67 3.65 3.63

3.91 3.70 3.67 3.66 3.64 3.62

3.68 3.71 3.69 3.66 3.67 3.63

3.48 3.50 3.51 3.50 3.59 3.57

3.60 3.51 3.49 3.50 3.59 3.58

3.57 3.50 3.59 3.51 nd 3.48

4.73 4.88 5.17 5.00

N/A N/A 4.24 4.39 3.80 4.10

N/A N/A 3.67 3.67 3.91 3.62

N/A N/A 3.47 3.45 3.25 3.56

N/A N/A

a) data collected in this work. b) Residues labeled alphabetically from reducing terminus.

lated). The groups of Suzuki [39] and Strecker [40] have assigned the 1H and 13C spectra of oligomers as long as seven residues, isolated from the yeast cell wall by hydrolytic procedures. Direct comparisons of the data for the H-1, H-2, H-3, and H-4 resonances are found in Tab. 7.1. These signals were chosen because they have excellent dispersion within all the oligomers analyzed, although severe overlap for the H-5 and H-6’s resonances was observed for all the compounds. The comparison reveals significant discrepancies with the literature data that cannot be easily attributed to any systematic error. It is possible that the isolation procedures differed and the presence of contaminants affects the NMR data. It is well


known that the presence of metal ions, which can be chelated by hydroxyl groups, affects the chemical shift of ring protons and carbon nuclei [41]. Comparison between the synthesized oligosaccharide glycosides 1–5 and isolated oligosaccharides must be done cautiously, as it is to be expected that the reducing terminal sugar assignments would be significantly different, since the naturally isolated material exists as a free hemi-acetal. Their presence in the isolated oligomers cause chemical shift differences and considerable spectral complexity, since both a and b forms of the terminal residue exist and propagate chemical shift changes well beTab. 7.2 Comparison of literature

13

C data of oligosaccharide glycosides 2–5 and literature data of Suzuki et al. [39] and Strecker et al. [40] (see text) for the corresponding oligosaccharides isolated from C. albicans Oligosaccharide/ hexose residue b)

2 A B C 3 A B C D 4 A B C D E 5 A B C D E F 6 A

B C D

C-1

C-2

C-3


Ref. 40


Ref. 40


Ref. 40

100.9 101.9 101.6

92.9 99.9 101.8

94.9 102.3 102.1

79.7 79.0 71.3

79.5 79.5 71.3

80.9 79.4 71.8

73.8 73.1 73.0

70.2 73.1 73.9

73.5 73.4 74.3

101.8 102.0 102.0 101.8

93.0 100.2 102.1 101.9

94.8 102.5 102.4 102.3

80.1 79.9 79.2 71.3

79.8 80.3 79.3 71.3

81.3 80.3 79.6 71.7

72.8 72.8 73.2 73.8

70.1 72.8 73.2 73.9

73.3 73.2 73.6 74.3

100.8 102.1 102.2 101.9 101.8

93.0 100.2 102.3 102.1 101.9

94.8 100.5 102.4 102.7 102.3

80.1 80.1 79.8 79.3 71.3

79.8 80.6 79.9 79.4 71.3

81.4 80.9 80.3 79.8 71.7

nd nd nd nd 73.8

70.1 72.7 72.9 73.2 73.9

nd 73.1 73.6 73.3 74.2

100.8 102.2 102.1 102.1 101.9 101.8

93.0 100.2 102.3 102.2 102.0 101.9

94.9 100.5 100.6 102.4 102.7 102.3

80.0 80.0 80.0 79.9 79.3 71.3

79.8 80.6 80.2 80.0 79.4 71.3

81.3 80.9 80.4 79.8 80.5 71.4

nd nd nd nd nd 73.8

70.1 72.7 72.8 73.0 73.2 73.9

70.4 73.1 73.6 73.4 73.2 74.3

101.8

80.3

102.2 102.0 86.7

79.4 54.3 nd

a) Data collected in this work. b) Residues labeled alphabetically from reducing terminus.

72.9–72.6 72.9–72.6 72.9–72.6

74.7

159

160


yond the terminal reducing hexose residue [39, 40]. Synthetic oligomers by comparison are free of this complicating factor, since the terminal mannose residue is protected as a b-propyl glycoside. The 1H assignments of the internal residues agree more closely with those collected by Strecker et al. [40] than with those of Suzuki et al. [39]. The greatest differences are found in the anomeric signals of the penta- and hexasaccharides. The two literature references have the assignments of H-1C and H-1D reversed, and they are strikingly different to those values found in this study. It is possible that the hemi-acetal of the reducing terminus is affecting these signals, leading to the observed 0.1 ppm difference. This is likely, given the three-dimensional structure of this oligomer which brings these residues close in space. The 13C spectra of the oligosaccharides were assigned from HMQC experiments. The data agree within experimental error with the literature data for the C-1, C-2 and C-3 atoms (Tab. 7.2), given the differences at the reducing terminus. Assignments of the other 13C resonances would require extended acquisition times at the concentrations available from the synthesis. 7.5.2

Analysis of NOE Contacts for (1 ? 2)-b-Mannopyranan Oligomers

The unexpected dispersion of resonances in the spectra of the (1 ? 2)-b-mannopyranosyl oligosaccharides suggested a well-ordered three-dimensional structure for these polymers. To investigate this structure further, NOE data were collected by T-ROESY NMR experiments [42]. The T-ROESY data were quantified for the tri-, tetra-, and pentasaccharides 2–4. Distance references were taken from average intra-residue H1-H5 contacts, set to 2.39 Å based on the distance found in relevant crystal structures [43]. Inter-residue distances were calculated based on the r– 6 relationship between distance and NOE intensity [44]. Inter-proton contacts from the hexasaccharide 5 were not quantified because the NMR spectra of this compound had significant overlap of the important resonances. Spectra for the tetraand pentasaccharides 3 and 4 were obtained at 800 MHz, and numerous ROE contacts between non-contiguous residues were well resolved for the mannopyrans investigated. Inter-residue contacts observed for the tetrasaccharide are shown in Fig. 7.4. All of the interglycosidic contacts (H1/H2) between the contiguous residues are present and easily quantified because of the signal dispersion of the H-1 and H-2 signals. The presence of contacts between H-4A, H-1C and H-2C and between H-4B, H-1D and H-2D, and one contact between H4A and H-1D that spans the first and fourth pyranose rings, are clearly observed. A portion of the T-ROESY spectrum for propyl (1 ? 2)-b-pentamannopyranoside (4) is shown in Fig. 7.5 to illustrate the observed signals between non-contiguous residues. The distance constraints imply a compact repetitive structure in this homopolymer, with similar distances across the glycosidic linkages of all the oligomers (Tab. 7.3). The distances suggest that the structure is not primarily a result of steric interactions between non-contiguous residues but represents a population of low-energy conformations with


Fig. 7.4

Observed interglycosidic NOE contacts in tetrasaccharide 3.

Tab. 7.3 NOE contacts for (1 ? 2)-b-mannopyranosyl tri-, tetra- and pentasaccharides 2–4 (nq:

not quantified because of overlap) Observed NOE contacts a)

Distances calculated (Å)

Contacts across glycosidic linkage H2A-H1B H2B-H1C H2C-H1D H2D-H1E Contacts separated by one residue H4A-H1C H4A-H2C H4B-H1D H4B-H2D H4C-H1E H4C-H2E Contacts separated by two residues H4A-H1D H4B-H1E

2 2.3 2.3 – –

3 2.3 2.2 2.3 –

4 2.2 2.2 nq 2.25

3.3 2.9

3.1 2.8 3.1 2.7

3.2 2.7 3.1 2.7 3.2 2.8

4.1

3.7 4.2

a) Oligomers are labeled alphabetically from the reducing terminus.

similar torsional angles at each glycosidic linkage. If long-range steric interactions were limiting the conformations of oligomers, the shorter oligomers, lacking steric interactions between non-contiguous residues, would be expected to have distances that differ from those of the higher molecular weight counterparts. The presence of multiple NOE contacts between non-contiguous residues is very rare in linear oligosaccharides. Often it is possible to see single interactions between non-contiguous residues in branched oligosacharides, but it is exceptional to see two such well-defined contacts for a linear oligosaccharide. The pres-

161

Fig. 7.5

TROESY NMR spectrum of tetrasaccharide 3 showing long-range ROE cross-peaks between protons of non-contiguous pyranose residues.

162



ence of NOE contacts between residues separated by two pyranose rings is to our knowledge unprecedented, and is indicative of a compact structure. Molecular dynamics simulations provided a model for this unique oligosaccharide. 7.5.3

Molecular Dynamics Simulations

Molecular modeling of the mannopyranans succeeded in generating a credible model of this oligomannan, which provides good agreement with the experimental NOE measurements. Comparisons of the conformational space sampled by the oligosaccharides indicated that the tri-, tetra- and pentasaccharides explore very similar torsional angles across all of their linkages. Molecular dynamics simulations employed the Amber force field modified by Homans et al. for carbohydrates, and the Insight II modelling software to model the (1 ? 2)-b-mannopyranosyl tri-, tetra- and pentasaccharides methyl b-glycosides [45]. The methyl glycosides were chosen to simplify the calculations by locking the terminal residue as the b-anomer while avoiding the extra torsional angles of propyl glycosides. These simulations began with a short, high-temperature molecular dynamics run where the chair conformations of the mannopyranosyl rings were enforced by scaling the torsional energy term by a factor of 7. From this simulation ten structures were generated to provide starting points with random torsional angles about the glycosidic linkages and the exocyclic hydroxymethyl groups. These ten structures were each minimized to a low-energy conformer by a simulated annealing protocol [46]. This involved running stepwise 1 ps molecular dynamics simulations starting at 500 K and cooling to 300 K in 50 K increments, followed by descent in 10 K steps to 10 K and finally to 5 K. Each annealed structure was then minimized further using a steepest gradient method. Comparison of the ten structures generated by this protocol gave insight into the conformational minima of the molecule. The lowest-energy conformation generated, the global minimum, was then used in a 5 ns molecular dynamics simulation at 300 K to provide timeaveraged conformational data for comparison with the collected NMR data. 7.5.4

Results of Trisaccharide Modeling

Ten structures obtained after the simulated annealing protocol converged to a single family of conformations (Fig. 7.6) with glycosidic torsional angles of }1 53.58 ± 18 w1 –0.58 ± 28 and }2 33.58 ± 18 w2 25.18 ± 48. Thus, the simulated annealing protocol converged to the global minimum conformation determined separately by a conjugate gradient search (Fig. 7.6). It is interesting to note that the second glycosidic linkage adopts a significantly different combination of torsional angles than that of the first. This likely results from the need to minimize steric interactions that are potentially severe as a consequence of the vicinal substitution pattern. The outcome is similar to the effects of vicinal branching in more rigid

163

164


Fig. 7.6

Minimum-energy structure for trisaccharide 2, showing selected inter-proton distances.

and branched carbohydrate structures (such as the blood group A and B structures) [47]. From the 5 ns molecular dynamics run for the trisaccharide it was possible to calculate time-averaged inter-proton distances that could be compared to those derived from the ROE spectra (Tab. 7.4) [44]. MD-calculated distances and those extracted from experimental NOE data showed good agreement when compared with the quality of data obtained for other oligosaccharides using this type of simulation [46]. Inspection of all dis-

Tab. 7.4 Comparison of theoretical and experimental distances for trisaccharide 2

ROE contacts a)

Contacts across glycosidic linkage H2A-H1B H2B-H1C Contacts separated by one residue H4A-H1C H4A-H2C

Trisaccharide distances (Å) Observed

Calculated

2.3 2.3

2.5 2.4

3.3 2.9

2.7 3.0

a) Oligomers are labeled alphabetically from the reducing terminus.


Fig. 7.7 Trajectory plot of }H vs wH during a 5 ns molecular dynamics simulation of trisaccharide 2.

tances derived from MD simulations indicated no additional contacts beyond those observed in the NMR data. Analysis of the conformational states explored during the dynamics simulation indicated that the second glycosidic linkage spends a short period of time in the anti-conformation (}*1808), which has an elevated energy (Fig. 7.7). Since experimental data for other oligosaccharides indicate that most oligosaccharides sample this conformation, the observation of its exploration by the b1,2-mannan over the duration of the dynamics run indicates that the simulation samples realistic areas of conformational space and that the dynamics run achieves good conformational averaging. 7.5.5

Results of Tetrasaccharide Modeling

The ten structures obtained after the simulated annealing protocol fell into three categories. One of ten contained the terminal non-reducing sugar in the anti-conformation (w*1808), two of ten contained the terminal reducing sugar in the anti-conformation (w*1808), and the remainder having the lowest-energy conformations fell into a disperse group having similar torsional angles (Tab. 7.5). The results of the simulated annealing protocol starting at high temperature and cooling to 5 K indicate high-energy barriers to transitions between the observed anti-conformations (structures 2, 3 and 10), and the lower energy conformers. It was not possible for terminal sugars in the high-energy anti wells to traverse into the lower-energy syn conformational well during the cooling phase of the simulation. The majority of the conformations generated fell into the same low-energy ensemble of conformations as the global minimum-energy conformation. The lowest-energy conformation, structure 5, used in the 5-nanosecond molecular dynamics simulation, is shown with selected inter-proton distances (Fig. 7.8).

165

166

7 The Unique Solution Structure and Immunochemistry Tab. 7.5 Results of simulated annealing of tetrasaccharide 3

Structure

Relative to- }1 tal energy (kcal/mol)

w1

}2

w2

}3

1 2 (anti) 3 (anti) 4 5 6 7 8 9 10 (anti)

–4.47 –3.25 –1.46 –4.64 –6.45 –4.90 –4.83 –5.74 –5.37 –1.88

–7.6 –176.9 –6.7 –9.5 9.6 0.4 7.7 –7.1 8.2 –178.7

36.1 46.3 71.4 36.9 36.5 43.4 36.6 30.8 37.0 45.2

–3.0 –3.1 57.5 –4.8 –11.5 –1.2 6.9 –5.6 –7.2 –5.0

46.7 51.6 50.3 47.7 47.6 52.6 47.3 47.5 47.1 53.3

54.1 50.2 44.3 53.1 48.2 56.1 53.6 53.1 53.3 49.4

Minimum-energy structure for tetrasaccharide 3 derived from simulated annealing. Selected inter-proton distances show

Fig. 7.8

w3

19.2 27.6 –177.4 19.6 18.2 29.3 –19.8 20.1 20.6 28.6

NOE contacts between H4A of the terminal reducing pyranose residue and protons of residues C and D.

7.5 Molecular Modeling and NMR of (1 ? 2)-b-Mannopyranan Tri-, Tetra- and Pentose Tab. 7.6 Comparison of calculated and experimental NOE-derived distances for tetrasaccharide 3

NOE contacts a)

Contacts across glycosidic linkage H2A-H1B H2B-H1C H2C-H1D Contacts separated by one residue H4A-H1C H4A-H2C H4B-H1D H4B-H2D Contacts separated by two residues H4A-H1D

Inter-proton distances (Å) Observed

Calculated

2.3 2.2 2.3

2.4 2.4 2.5

3.1 2.8 3.1 2.7

2.8 2.7 2.8 3.0

4.1

3.6

a) Residues are labelled alphabetically from the reducing terminus.

No large conformational changes over the duration of the molecular dynamics run performed at 300 K were observed, and similar levels of flexibility were seen for all the torsional angles. The anti-conformation was not sampled for either of the terminal residues, confirming the data found in the annealing simulation of high-energy traverses into these conformations. Calculated time-averaged interproton distances and those derived from NMR experiments showed good agreement (Tab. 7.6). 7.5.6

Results of Pentasaccharide Modeling

Further comparison of the ten structures obtained after the simulated annealing protocol showed that only two families of conformations were observed. The anticonformation was adopted for the glycosidic linkage between residues C and D in one of the ten conformations and was significantly higher in energy than the other nine conformations, all of which fell into a common family (Fig. 7.9). It is interesting to note that even this pentamer does not show any repetition or oscillation in torsional angles that would be expected for a homopolymer. It would likely begin to arise for the hexasaccharide, explaining the overlap observed in the 1 H NMR anomeric signals of residues C and D for this oligomer. Again, the MD-derived time-averaged inter-proton distances compared well with those deduced from the NMR data (Tab. 7.7). During the dynamics run, the oligosaccharide stayed within the range of glycosidic torsional angles represented by the family generated by the simulated annealing.

167

168


Overlay of low-energy conformers generated by application of the simulated annealing protocol to pentasaccharide 4.

Fig. 7.9

7.5.7

Conclusions about Molecular Modeling

As expected, the molecular dynamics predicts reducing and non-reducing termini to be more flexible than the internal residues, but the experimental ROE data do not show significant increases in the inter-residue distances across the terminal glycosidic bonds. It is possible that, despite the increased flexibility, the average distance remains the same. Comparison of the conformation of the minimum-energy structures generated by the simulated annealing protocol also indicates similar torsional angles between the tri-, tetra- and pentasaccharides (Fig. 7.11, s. p. 172). However, the trisaccharide has its terminal non-reducing residue tilted approximately 45 8 compared with the tetra- or pentasaccharides. This is an interesting result in the light of the recent finding that an anti-Candida monoclonal antibody binds the trisac-


Fig. 7.10 }H vs wH trajectory plots for tetrasaccharide 3 and pentasaccharide 4 over a 5 ns

molecular dynamics simulation.

charide, but binds the larger oligomers with greatly reduced affinity. It is possible that this monoclonal antibody is recognizing the trisaccharide in a conformation that is unfavorable for larger oligomers. Given that the modeling adequately represented structures up to the pentasaccharide, it was tempting to build a model of a decasaccharide to help visualize the supermolecular structure of this unique polysaccharide (Fig. 7.12, s. p. 173). This

169

170

7 The Unique Solution Structure and Immunochemistry Tab. 7.7 Comparison of theoretical and experimental NOE-derived distances for pentasaccharide

4 (nq: not quantified because of overlap) ROE contacts a)

Contacts across glycosidic linkage H2A-H1B H2B-H1C H2C-H1D H2D-H1E Contacts separated by one residue H4A-H1C H4A-H2C H4B-H1D H4B-H2D H4C-H1E H4C-H2E Contacts separated by two residues H4A-H1D H4B-H1E

Pentasaccharide distances (Å) Found

Calculated

2.2 2.2 nq 2.3

2.5 2.4 2.4 2.5

3.2 2.7 3.1 2.7 3.2 2.8

2.9 2.7 2.9 2.8 2.8 3.1

3.7 4.2

3.4 3.7

a) Residues are labeled alphabetically from the reducing terminus.

qualitative model shows the obvious helical nature of this polysaccharide. Although the repeating unit is approximately three residues long, the overlap of residues N and N+4 is only approximate because of the flexibility of the glycosidic linkages. In the helix, hydroxyls are oriented out into solution, and there is a hydrophobic core made up of the faces of the mannose rings. Any hypothesis about the importance of this structure to the polysaccharide‘s function must be speculative at this stage, but it is interesting to consider possible implications. The helix hides the glycosidic linkages at its core, perhaps limiting the accessibility to endo-mannosidases. The hydrophobic faces of the rings are also shielded, except for the terminal residues, which likely has implications in the binding of the polymer by antibodies or lectins, where contributions from hydrophobic surfaces are important. 7.5.8

Conformational Analysis of the Thio-tetrasaccharide

Despite their similarity, the substitution of an oxygen atom for a sulfur atom has significant implications for the overall conformation of a glycosidic linkage. The C–S bond is on average 0.4 longer than the C–O bond, but in terms of inter-residue separation this is compensated by a smaller valence angle (C–S–C 1008 compared to C–O–C 1168). The net result is an increased spacing of *0.4 Å spanning the glycosidic linkage. This reduces the steric contacts between residues, generally leading to a more flexible linkage [48]. A number of conformational studies have been carried out on complex thioglycosides. Five disaccharides, containing a sin-


gle thio-glycosidic linkage and a sialyl Lewis-x mimetic containing three thioglycosidic linkages, have been analyzed by a combination of NMR and molecular modeling [49]. Unfortunately, modeling such compounds is hampered by the lack of parameterization of the thioglycosidic linkage in most readily available force fields. It is well known that thioglycoside linkages have a weaker anomeric effect than the corresponding O-glycosides. So, it is likely that the exo-anomeric effect is also weaker [50, 51]. No parameterization is available to describe this constraint, and thus any modeling done up to this point uses parameters developed to model the thio ether without any contribution from the exo-anomeric effect. Nonetheless, the MM2* force field has given excellent results for calculations of populations in low-energy conformations about thioglycosides, and the AMBER force field has been shown to give qualitative results for interpretation of the energy surface and NOE intensities for thiocellobiose [49] and thioFuc(a1-3)GlcNAc. Therefore the AMBER force field was used in these studies. 7.5.9

Analysis of the 1H and 13C NMR Spectra of Propyl b(1-2)-thio-tetramannopyranoside (6)

The 1H NMR spectra were assigned using a combination of gradient-enhanced COSY and TOCSY experiments. As would be expected, the introduction of the sulfur caused upfield shifts of protons separated by two bonds; other protons close in space were also affected because of the anisotropy of the sulfur atom. Inspection of the homonuclear 3J coupling constants for the pyranose ring C indicated a very minimal distortion due to the presence of the sulfur atom, as J2,3 was 4.6 Hz compared to 3.2–3.4 Hz observed for the other residues in the oligomer. The other 3J coupling constants around ring C were comparable to those found in the rings of the O-linked oligomers. The magnitude of coupling constants depends not only on the dihedral angle between the atoms involved but also on the electronegativity of the substituents. Thus, this minor deviation may be due to the presence of a C–S bond and not a distortion of the dihedral angles of the pyranose ring [52]. No obvious perturbations were present in ring D. Unfortunately, because of signal overlap, it was not possible to quantify as many ROE cross-peaks in the thiotetrasaccharide (6) analog as in compound 3, its O-linked counterpart. Nevertheless, the NOE contacts present suggest a similar compact structure. Direct comparison between the native tetrasaccharide 3 and its mimetic 6 is discussed below. 7.5.10

Conformational Analysis of Thio-linked Tetrasaccharide 6

Analysis of the ten structures generated from the simulated annealing protocol suggests a large family of conformational minima all clustered around similar torsional angles (Fig. 7.11). This is expected for the thioglycoside, which should be more flexible. Surprisingly, no structures contained the anti-conformation around the thioglycosidic linkage as has been observed for other thioglycosides [49].

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Fig. 7.11 Overlay of the minimum-energy conformations of the trisaccharide 2 (green), the tetrasaccharide 3 (red), and the pentasaccharide 4 (blue). Ring B of each structure has

been superimposed. The balls indicate the carbon atom of the methyl aglycon used to replace the propyl groups in the theoretical treatment.

Molecular dynamics simulations for the methyl glycoside of 6 indicate that the reducing residue behaves in much the same way as the native O-linked structures; a short foray into a higher energy anti-conformation but a rapid return to the preferred syn-conformation. The second glycosidic linkage is constrained in its mobility to a small region of the energy surface encompassing the families of minimum-energy conformations observed in the simulated annealing protocol. The terminal thioglycosidic linkage shows that two conformations are explored during the simulation at } angles centered around two gauche conformations, 608 and –608 (Fig. 7.13). The conformation about the thioglycosidic linkage that was observed in the simulated annealing protocol is the lower energy of the two (*608). The exo-anomeric effect would favor this conformation, and if the stereo-


Fig. 7.12 Model of a b(1 ? 2)-mannopyranosyl undecasaccharide showing the helical nature of the polymer. The approximate trisac-

charide repeating unit is emphasized by the repeating yellow, green, blue motif.

electronic effect were parameterized in the force field, a greater proportion of the time would be spent in this conformation. Nevertheless, the calculation of the NOE distances from the dynamics run agreed well with those determined experimentally. The calculated H4A-H2C distance, which spans the thioglycosidic linkage, agrees well with the experimental NMR data (Tab. 7.8). 7.5.11

Comparison of the Native Tetrasaccharide with the Thioglycoside Mimetic

The experimentally determined distances for the thioglycoside (6) and for the native tetrasaccharide (3) have been directly compared and found to be very similar. Slightly longer distances are found for the distances spanning the thioglycosidic linkage (H1D-H2C, H2D-H4B), but the differences are small, suggesting no gross differences between the two structures.

173

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Fig. 7.13 Trajectory maps for the thio-linked tetrasaccharide 6 generated by MD calculations.

Tab. 7.8 Comparison of theoretical and experimental ROE distances for compound 6 (nq = not

quantified because of signal overlap but observed) ROE contacts a)


Distances (Å) Found

Calculated

2.2 2.2 2.4

2.4 2.4 2.5

3.2 2.7 nq 2.9

2.9 2.8 2.7 3.2

nq

3.9

a) Residues are labelled alphabetically from the reducing terminus.

7.6 Development of an Anti-Candida albicans Vaccine Tab. 7.9 Comparison of experimental NOE derived distances for compounds 3 and 6 (nq = not quantified because of signal overlap but observed)

ROE contacts

Distances (Å) Native tetrasaccharide Tetrasaccharide mimetic 3 6


2.3 2.2 2.3

2.2 2.2 2.4

3.2 2.7 nq 2.9

3.1 2.8 3.1 2.7

nq

4.1

When three of the lowest-energy structures for each tetrasaccharide (3 and 6) are superimposed it becomes obvious that both compounds sample similar conformational space, but the family of low-energy conformations for the thioglycoside exhibit a wider range of structures (Fig. 7.14). The molecular dynamics runs also suggests a more flexible structure for the thioglycoside mimetic, but only about the thioglycosidic linkage. The other glycosidic linkages explore similar conformational space. Like other thioglycoside mimetics previously investigated, this tetrasaccharide is more flexible than its native counterpart. However, it is less flexible than the other thioglycosides that have been analyzed, as is shown by the absence of any anticonformation about the thioglycosidic linkage during the molecular dynamics simulation.

7.6

Development of an Anti-Candida albicans Vaccine

It has been shown that linking crude cell wall extracts of C. albicans polysaccharides to a protein will produce a vaccine that induces a protective antibody response [17–19]. Analysis of a monoclonal antibody produced against this crude polysaccharide vaccine showed that the recognized epitope was a trisaccharide, (1 ? 2)-b-d-Manp-(1 ? 2)-b-d-Manp-(1 ? 2)-b-d-Man, which is found in the acid labile portion of the cell wall [20]. Although this information is crucial for the development of a vaccine, naturally isolated polysaccharide vaccines are plagued by problems such as heterogeneity, paucity of material and, depending on the meth-

175

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Fig. 7.14 Overlay of the three minimum-energy structures of the O-linked tetrasaccharide 3 (red) and the Slinked tetrasaccharide 6 (blue). Only backbone carbon and oxygen atoms are displayed for reasons of clarity. The sulfur atom is shown in yellow.

od of extraction, the potential for biological contamination, and these problems limit their use in humans. Synthetic carbohydrate vaccines are well defined and overcome these problems. Three factors should be considered when developing a synthetic carbohydratebased vaccine: the size of the carbohydrate, the conjugation chemistry, and the choice of the carrier protein [53]. The size of the carbohydrate should provide a balance between the ease of synthesis and how well it will mimic the natural structure. In the case of bacterial polysaccharides of Chlamydia, which contain the pentasaccharide repeating unit a-Kdop-(2 ? 8)-a-Kdop-(2 ? 4)-a-Kdop-(2 ? 6)-b-d-GlcNAcp-(1 ? 6)-b-d-GlcNAcp(1 ?, it was found that a tetrasaccharide (lacking one b-d-GlcNAc) or the complete pentasaccharide repeating unit was able to generate antibodies which were able to recognize the natural lipopolysaccharide [54]. Thus, despite the fact that the antibody binding site is usually filled by 3 to 4 pyranose rings of a carbohydrate epitope [55–56], it appears necessary to have a larger immunizing oligomer to order the epitope or contact residues as they would be in the native antigen [57]. The (1 ? 2)-b-d-mannan found in the cell wall of Candida albicans is a homopolymer, and, since the synthesis was undertaken prior to modelling studies, it was difficult to speculate as to the repeating secondary structure of this polymer. Consistent with the probable size of the antigenic determinant, inferred from immunochemical data accumulated over the last 40 years [55–57], it was decided that a hexasaccharide and a tetrasaccharide would be synthesized to accurately represent the repeating nature of this polymer. Given the unexpected findings of the conformational analysis reported in the previous chapter, the trisaccharide is the minimum conformational repeating unit. Thus, in order to have the correct conforma-

7.6 Development of an Anti-Candida albicans Vaccine

tion of the repeating unit, it is likely that a hexasaccharide is a good representation of the minimal structure necessary to represent the (1 ? 2)-b-d-mannan. Many ways have been employed to link the oligosaccharide to the protein carrier [58]. With isolated polysaccharides, the free aldehyde of the reducing terminus is often used in a reductive amination reaction with the amines found on the surface of the carrier protein [59]. This destroys the reducing terminal sugar, which is not a major problem with high molecular weight polysaccharides, but is a dubious option with smaller synthetic oligosaccharides. A terminal aldehyde has been introduced in different ways to synthetic oligosaccharides. An allyl group can be subjected to ozonolysis, or a protected aldehyde in the form of an acetal can be incorporated late in the synthesis [60]. Unfortunately, reductive amination can be an inefficient reaction when small amounts of an expensive synthesized carbohydrate are coupled. Other methods have also been introduced such as the introduction of a thiocyanate via reaction of a p-aminophenyl group with thiophosgene followed by in situ coupling to a protein [61]. The use of an acyl azide, formed from reaction of a hydrazide with nitrous acid, allows rapid coupling to lysine amino groups [62]. Thioether chemistry has also been used via introduction of a terminal thiol to the oligosaccharide followed by reaction with a protein onto which a bromoacetate has been installed by reaction with a-bromoacetyl succinimide ester [63]. One of the most efficient protocols developed involves the use of the homo-bifunctional reagent diethyl squarate [64]. Sequential reactions of this reagent with two amines allow reproducible coupling, in high yield and efficiency under mild conditions, with small amounts of oligosaccharide and protein [65]. This was the method chosen for the formation of the glycoconjugates in this study. The choice of protein as a carrier is governed principally by immunological considerations. A protein carrier should be soluble under physiological conditions, PBS pH 7.4, and possess numerous functional groups for conjugation. In order to be immunogenic, the protein should be a heterologous protein (not native to the animal to be immunized), but no consensus has been reached as to the most efficient carrier for generating an immune response [66]. In mice a variety of proteins have been used such as bovine serum albumin (BSA), human serum albumin (HSA), tetanus toxoid (TT), keyhole limpet hemocyanin (KLH), as well as short peptides which do not require processing for display in the MHC complex [67]. In this study tetanus toxoid was chosen as a carrier because it has shown good immune responses in rabbits and mice. It is also well tolerated in humans as it is already used as a vaccine against tetanus and in polysaccharide conjugate vaccines. 7.6.1

Synthesis of C. albicans Conjugate Vaccines

Reaction of the mannopyranoside functionalized glycosides with diethyl squarate in a solution of ethanol and water provided, in high yield, the activated oligosaccharides ready for coupling to protein (Scheme 7.12).

177

178


Scheme 7.12 Synthesis of protein conjugates using diethyl squarate as the homo-bifunctional coupling reagent.

Coupling of the squarate-activated ligands to tetanus toxoid (TT) or bovine serum albumin employed an aqueous borate buffer [25, 65]. Coupling of the oligosaccharides to BSA proceeded with efficiencies of 65–70%. This corresponds to the incorporation of 13–15 ligands with a 20-fold molar excess of activated oligosaccharide. Lower efficiencies were obtained for coupling to tetanus toxoid, as higher incorporations were desired. Efficiencies in the region of 35% were achieved in these reactions. It is possible that the majority of the 106 amino groups of TT were buried in areas of the protein inaccessible to the coupling reagent. No quantitative data are available in the literature for coupling to tenanus toxoid; only estimates of carbohydrate loading generated by size exclusion chromatography have been used in the past [68]. The molecular weights of the protein conjugates were determined by MALDI-TOF spectroscopy. All the conjugates produced had limited polydispersities between one and two conjugations. An unrelated trisaccharide, (1 ? 2)(-a-d-glucopyranosyl)(1 ? 2)-b-d-mannopyranotriose was also conjugated to BSA to serve as a control compound to test the specificity of the immune response. 7.6.2

Immunization of Experimental Animals

New Zealand white rabbits and inbred BALB/c mice were immunized with the tetanus toxoid conjugates, since these strains of rabbit and mice have shown strong immune responses against polysaccharides conjugated to tetanus toxoid [69–70]. 7.6.3

Analysis of Antibody Levels

The titers of antibodies produced in the experimental animals were analyzed by ELISA. The antigen to be tested was adsorbed to a 96-well ELISA plate and the


Scheme 7.13

Preparation of BSA and Tetanus toxoid (TT) conjugates.

plate was washed. To the wells were added serial dilutions of the sera from the immunized animal to be analyzed. After incubation of the plate, unbound antibodies were washed from it. A horseradish peroxidase-conjugated antibody against the antibody to be analyzed was used to quantify the amount of specific antibody bound to the plate. 7.6.4

Antibody Levels in Mice and Rabbits

Mice developed a strong IgM response against the hexasaccharide tetanus toxoid conjugate after two immunizations, as judged by ELISA assay, using the BSA-conjugated hexasaccharide. Weak IgG antibodies were also present after this time. Rabbits showed a strong IgG response after three injections with the tetanus toxoid conjugates. In order to better quantify the specificity of this polyclonal response, titrations of the antibody against all the BSA-conjugated oligosaccharides were undertaken. Surprisingly, it was found that the polyclonal sera recognized all the conjugates with similar affinity. Even the control antigen, a tetrasaccharide conjugate bearing a terminal a-(1 ? 2)-d-glucopyranosyl residue linked to the b1,2mannotriose was well recognized. It was originally envisaged that oligosaccharides conjugated to the heterologous protein, BSA, would distinguish between antibodies that were directed toward the carrier protein of the immunizing antigen and those that were directed against the desired oligosaccharide. However, since squarate coupling chemistry was common to the TT and BSA conjugates, antibodies that recognize this structurally prominent feature may also be detected in the as-

179

180


Fig. 7.15 Titration of rabbit anti-sera against C. albicans mannan antigen coated on ELISA plates. The pooled sera were raised to tetanus

toxoid conjugates, (1 ? 2)-b-d-mannotetrose (50) and (1 ? 2)-b-d-mannohexose (51).

say. If antibodies against the linker are being detected in the assay, this would explain why all the BSA glycoconjugates appear to have the same affinity for the rabbit sera. Based on different titers against neoglycoconjugates 46 and the BSA tetrasaccharide conjugate with an a-linked terminal glucose residue, it was evident that a significant fraction of the antibodies did not bind the control compound. This suggested the presence of antibodies specific for the (1 ? 2)-b-mannosyl oligosaccharides. The possibility was confirmed by screening the rabbit sera against cell wall extracts of C. albicans. These assays showed a high titer of IgG antibody that recognizes the native C. albicans antigen (Fig. 7.15). Both the hexa- and tetrasaccharide TT conjugates raised similar antibody titers. 7.6.5

Binding of Propyl (1 ? 2)-b-mannosides to Monoclonal Antibodies

IgM and IgG monoclonal antibodies, generated by immunization of mice with liposomal extracts of the C. albicans cell wall, are protective against C. albicans challenges in passive transfer experiments [18, 19]. The affinity of these monoclonal antibodies to the synthesized propyl glycosides 1–6 was determined in a competitive ELISA [79]. In this application of the assay, a C. albicans mannan extract was used to coat ELISA plates. The results from this assay are shown as a percentage inhibition, and the concentration of ligand that gives 50% inhibition is quoted as an IC50 value.


The IgM antibody, B6.1, showed a surprisingly high affinity for the di- and trisaccharides when compared with tetrasaccharide 3 and hexasaccharide 5. The inhibitory power of the propyl 1-thio-b-d-mannopyranosyl-b-d-mannopyranotrioside 6 fell between the activity of tri- and tetrasaccharides 2 and 3 (Tab. 7.4). The same panel of oligomannosides with IgG (C3.1) antibody showed a trend in affinities similar to those observed with Mab B6.1. Again di- and trisaccharides had the highest affinities, but were fivefold and twofold higher than for B6.1, while the remaining antigens had a similar affinity (Fig. 7.16b). To the best of our knowledge, the observation of higher affinity for smaller oligomers is unprecedented for antibodies generated to polysaccharide antigens. As a rule, the larger oligomers have higher affinity for the antibodies. Beginning with the pioneering studies of Kabat in which he immunized himself with dextran, the expected trend is to observe oligomer inhibition that increases with oligosaccharide length to a maximum of 5–8 hexose residues [55]. At a certain size, which may vary with the precise pool of antibodies, the inhibition reaches a plateau when expressed on a molar basis. To date, rather unique inhibition patterns have been reported for homo-oligomers of sialic acid, but the increased inhibitory potency correlated with oligomers larger even than 8 residues, in this case reaching a 20-mer [71]. Similar patterns have been observed for hetero-polysaccharide antigens, where sialic acid is presumed to play a critical role in defining a unique bioactive conformation [72]. With the exception of these examples, the consistent theme of oligosaccharide inhibitory activity has followed the Kabat paradigm. It is surprising that the anti-C. albicans IgG and IgM antibodies have very similar specificity and affinity. Statistically one might expect, using a polydisperse antigen such as the extract used to generate these antibodies, that antibodies recognizing differing epitopes would be generated. The finding that both monoclonal antibodies recognize similarly sized epitopes suggests a single immunodominant epitope in the extract of the C. albicans cell wall used for immunization. As these antibodies are known to be protective, the inhibition results also indicate a near ideal situation for the generation of synthetic vaccines. In the development of carbohydrate-based vaccines, the perceived chain length requirement [57] has always been seen as a formidable obstacle to the use of synthetic carbohydrate epitopes. Therefore, to date, commercially approved carbohydrate-based vaccines have only been developed from isolated polysaccharides rather than with defined synthetic structures [73]. However, within the last 3 years chemical synthesis has become sophisticated enough to attempt such tasks [74]. In the case of (1 ? 2)-b-mannopyranans of the yeast cell wall, the size of the epitope recognized by protective antibodies falls within the range of di- to trisaccharides, significantly smaller than the 15–20 sugar residues required to create a practical immunogen for other polysaccharides [57, 73, 74]. Examination of the conformation of the oligosaccharides and a proposed binding mode for the mannopyranans may explain the unexpectedly high affinity of the diand trisaccharides for the monoclonal antibodies. A terminal disaccharide is the epitope for the protective monoclonal antibodies, while elaboration to a trisaccharide gives an inhibitor of similar affinity; further elaboration of the polymer leads to reductions in affinity. Because of the helical nature of this polymer, the fourth manno-

181

Inhibition %


Inhibitor concentration [lM]

Inhibition %

182

Inhibitor concentration [lM] Fig. 7.16 ELISA inhibition data for monoclonal antibodies IgM B6.1 and IgG C3.1. Inhibition by synthetic oligosaccharides 1–3, 5 and 6 of monoclonal antibody binding to C. albicans extract. (n) propyl (1 ? 2)-b-d-mannopyranobioside (1), (s) propyl (1 ? 2)-b-d-mannopyranontrioside (2),

(t) propyl (1-thio-b-d-mannopyranosyl)(1 ?2)-b-D-mannopyranotrioside (6), (^) propyl (1 ? 2)-b-d-mannopyranotetroside (3), (l) propyl (1 ? 2)-b-d-mannopyranohexoside (5). The origin of the flattened binding curve for disaccharide 1 is unknown.

pyranose ring (residue D) comes into close proximity to the reducing residue (residue A). Residue D may then be causing steric interactions with the antigen binding site or a part of the antibody surface adjacent to the site (Fig. 7.17). It has previously been observed that hexoses outside the antibody binding site can be required to adopt higher-energy conformations to avoid steric interactions with the protein surface adjacent to the binding site, consequently binding with lower affinity [75].


Fig. 7.17 Possible steric interactions in the binding sites of antibodies B6.1 and C3.1 that disfavor binding of epitopes larger than trisaccharide. Only backbone carbon and oxygen

atoms are displayed for reasons of clarity. The ball represents the aglyconic carbon attached to the terminal reducing residue.

Steric interactions of this general type can explain the order of the affinity observed for the tetra- (3), thio-linked tetra- (6) and hexasaccharides (5). The terminal thioglycoside of the propyl (1-thio-b-d-mannopyranosyl)-(1 ? 2)-b-d-mannopyranotriose (6) has the most flexible terminal glycosidic linkage (C ? D) when compared with 3 and 5. Thus, residue D of 6 is able to adopt other low-energy conformations about this terminal linkage to avoid unfavorable steric interactions with the protein. The tetrasaccharide 3, which binds with intermediate affinity, has a less flexible fourth residue (D) but it is still able to minimize the steric interactions with the protein by adopting another conformation. Finally, the hexasaccharide 5, which binds with low affinity, has the most rigid fourth residue (D) due to restricted mobility about the C ? D glycosidic linkage enforced by the subsequent residues of the helix. It cannot easily adopt another conformation leading to unresolved steric interactions with the protein and a low affinity inhibitor. If this hypothesis is correct, it suggests that the antibody is either recognizing the reducing terminus of the polysaccharide or very short oligosaccharide sequences. Since the monoclonal antibodies B6.1 (IgM) and C3.1 (IgG) show in vivo protection, the origin of the native epitope that induced the formation of monoclonal antibodies becomes especially pertinent. Short sequences of (1 ? 2)-b-dmannopyranan do exist in the phosphomannan of the yeast. According to one group, trisaccharide and longer polymers generally predominate [76, 77]. However, Cutler’s group report that di- and trisaccharide epitopes may predominate in cell extracts [78]. If the native epitope is a short sequence from the phosphomannan, it is likely that the antibody may accommodate a negative charge from the phosphodiester in the native antigen that links the reducing terminus to the amannan backbone. Inhibitors with this type of structure may bind more tightly to the antibody, although it must be observed that the inhibitor activity falls within typical ranges for oligosaccharide-antibody interactions, implying that the major epitope is presented by the short, neutral homo-oligomers.

183

184


Other (1 ? 2)-b-d-mannopyranose linkages have been found in yeast cell walls. Shibata et al. have proposed that some of the (1 ? 2)-a-d-mannan branches are capped by a (1 ? 2)-b-d-mannobiose residue in serotype A strains of C. albicans [76]. It is possible that an undetermined structure similar to this could be present in serotype B strains used to generate the monoclonal antibodies, and that this structure could constitute the native epitope for these monoclonal antibodies. This seems unlikely given that Cutler et al. found the monoclonal antibodies did not bind the acid stable portion of the C. albicans cell wall, where such structures are proposed to occur [20].

7.7

Conclusions

Further studies are needed to establish the potential of using the conjugates generated in these studies as Candida albicans vaccines. A strong antibody response was generated in rabbits against the tetanus toxoid conjugates, and these antibodies recognize the C. albicans extract. Two monoclonal antibodies (IgM and IgG) previously isolated by the group of Cutler [17–19] have been shown to have higher affinity for smaller (di- and trisaccharides) over larger (tetra- and hexasaccharides) structures. This unexpected result correlates with the compact helical nature of the (1 ? 2)-b-mannan polymer and potential steric interactions with the binding site. This finding implies that a synthetically simple disaccharide or trisaccharide conjugate may be all that is required to generate a protective immune response. Further studies are in progress to isolate a monoclonal antibody to the synthetic neoglycoconjugates synthesized here. It will be interesting to determine whether the specificity of these antibodies is similar to those raised against the natural structure, and whether the level of protection they confer is similar. On the basis of its helical conformation and immunochemical properties, we propose that a small di- or trisaccharide or a suitable analog of the type described here coupled to protein holds strong promise as a conjugate vaccine that will offer protection against C. albicans.

7.8

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48 49

50

D. R. Bundle, J. W. Cherwonogrodzky, M. B. Perry, Infect. Immun. 1988, 56, 1101–1106. V. Pozsgay, J. B. Robbins, Carbohydr. Res. 1995, 277, 51–66. H. Sugiyama, N. Toyohiko, M. Horii, K. Motohashi, J. Sakai, T. Usui, K. Hisamichi, J. Ishiyama, Carbohydr. Res. 2000, 325, 177–182. N. Shibata, K. Hisamichi, H. Kobayashi, S. Suzuki, Arch. Biochem. Biophys. 1993, 302,113–117. C. Faille, J.-M. Wieruszeski, J.-C. Michalski, D. Poulain, G. Strecker, Carbohydr. Res. 1992, 236, 17–27. S. J. Angyal, K. P. Davis, Chem Commun. 1971, 500. T.-L. Hwang, A. J. Shanka, J. Am. Chem. Soc. 1992, 114, 3157–3159. G. A. Jeffrey, R. K. McMullan, S. Takagi, Acta. Crystallogr. Sect. B 1977, 33, 728–737. J. Tropp, J. Chem. Phys. 1980, 72, 6035– 6044. S. W. Homans, Biochemistry 1990, 29, 9110–9118. T. J. Rutherford, D. G. Spackman, P. J. Simpson, S. W. Homans, Glycobiology 1994, 4, 59–68. A. Otter, R. U. Lemieux, R. G. Ball, A. P. Venot, O. Hindsgaul, D. R. Bundle, Eur. J. Biochem. 1999, 259, 295–303. S. Pérez, C. Vergelati, Acta. Crystallogr. 1984, B40, 294–299. a) E. Montero, A. Garcia-Herrero, J. L. Asenso, K. Hirai, S. Ogawa, SantoyoGonzález, J. F. Cañada, J. Jiménez-Barbero, Eur. J. Org. Chem. 2000, 1945–1952; b) B. Aguilera, J. Jiménez-Barbero, A. Fernández-Mayoralas. Carbohydr. Res., 1998, 308, 19–27; c) E. Montero, M. Vallmitjana, J. A. Pérez-Pons, E. Querol, J. Jiménez-Barbero, F. J. Cañada, FEBS. Lett. 1998, 421, 243–248; d) U. Nilsson, R. Johansson, G. Magnusson, Chem. Eur. J. 1996, 2, 295–302; e) A. Geyer, G. Hummel, T. Eisele, S. Reinhardt, R. R. Schmidt, Chem. Eur. J. 1996, 2, 981–988; f) K. Bock, J. Duus, S. Refn, Carbohydr. Res. 1994, 253, 51–61. E. Juaristi, G. Cuevas, Tetrahedron, 1992, 48, 5019–5087.

51 52 53

54

55

56

57

58 59 60 61

62

63

64

65

M. A. Pericas, A. Riera, J. Guilera, Tetrahedron, 1986, 42, 2717–2724 H. Gunter, in NMR Spectroscopy, 1980, John Wiley & Sons, Malta. M. R. Wessels, L. C. Paoletti, H. K. Guttormsen, F. Michon, A. J. D’Ambra, D. L. Kasper, Infect. Immun. 1998, 66, 2186–2192. Y. Fy, M. Baumann, P. Kosma, L. Brade, H. Brade, Infect. Immun. 1992, 60, 1314– 1321. a) E. A. Kabat, Federation Proc. 1962, 21, 694–701; b) E. A. Kabat, J. Immunol. 1966, 97, 1–11; c) E. A. Kabat, in Structural Concepts in Immunology and Immunochemistry, 1976, New York, Holt, Rinehart and Winston. a) D. R. Bundle in H.-J. Gabius and S. Gabius (eds) Glycosciences: Status and Perspectives, Chapman and Hall, Weinheim, 1997, pp. 311–331; b) D. R. Bundle in S. Hecht (ed) Carbohydrates, Oxford University Press Inc., Oxford, 1998 pp. 370–440. a) O. Mäkelä, F. Peterfy, I. G. Outschoorn, A. W. Richter, I. Seppälä, Scand. J. Immunol. 1984, 19, 541–550; b) O. Mäkelä, I. Seppälä, J. Pelkonen, Eur. J. Biochem., 1985, 15, 827–833. C. P. Stowel, Y. C. Lee, Adv. Carbohydr. Chem. Biochem. 1980, 37, 255–281. G. R. Gray, Arch. Biochem. Biophys. 1974, 163, 426–428. J. Zhang, P. Kovac, Tetrahedron Lett. 1998, 39, 1091 C. R. McBroom, C. H. Samanen, I. J. Goldstein, Methods Enzymol. 1972, 28, 212–219. a) R. U. Lemieux, D. R. Bundle, D. A. Baker, J. Am. Chem. Soc. 1975, 97, 4076– 4083; b) B. M. Pinto, D. R. Bundle, Carbohydr. Res. 1983, 124, 313–318. C. C. A. M. Peeters, D. Evenberg, P. Hoogerhout, H. Kayhty, L. Saarinen, C. A. A. van Boeckel, G. A. van der Marel, J. H. van Boon and J. T. Poolman, Infect. Immun. 60, 1992, 1826–1833. L. Tietze, M. Arlt, M. Beller, K. H. Glusenkamp, E. Jahde, M. F. Rawjewsky, Chem. Ber. 1991, 124, 1215–1221. P. Kamath, P. Diedrich, O. Hindsgaul, Glycoconjugate J. 1996, 13, 315– 319.

7.8 References 66 67

68

69

70

71

72

G. T. Hermanson, in Bioconjugate Techniques, 1996, Academic Press, London. J. Alexander, M. F. del Guerci, A. Meawal, L. Qiao, J. Fikes, R. W. Chesnut, J. Paulson, D. R. Bundle, S. DeFreez, A. Sette, J. Immun. 2000, 164, 1626–1633. A. F. M. Verheul, A. K. Braat, J. M. Leenhouts, P. Hoogerhout, J. T. Poolman, H. Snippe, J. Verhoef, Infect. Immun. 1991, 59, 843–851. P. A. Garcia-Ojeda, M. E. Monser, L. J. Rubinstein, H. J. Jennings, K. Stein, Infect. Immun. 2000, 68, 239–246. C. A. Laferriere, R. K. Sood, J.-M. De Muys, F. Michon, H. J. Jennings, Infect. Immun. 1998, 66, 2441–2446. J.-R. Brisson, H. Baumann, A. Imberty, S. Perez, H. J. Jennings, Biochemistry 1992, 31, 4996–5004. M. R. Wessels, A. Muoz, D. L. Kasper, Proc. Natl. Acad. Sci. USA 1987, 84, 9170–9174.

73 74

75 76

77

78 79

V. Pozsgay, Adv. Carbohydr. Chem. Biochem. 1980, 56, 153–199. V. Pozsgay, C. Chu, L. Pannell, J. Wolfe, J. B. Robbins, R. Schneerson, Proc. Natl. Acad. Sci. USA 1999, 96, 5194–5197. M. J. Milton, D. R. Bundle J. Am. Chem. Soc. 1998, 120, 10547–10548. N. Shibata, S. Fukasawa, H. Kobayashi, M. Tojo, T. Yonezu, A. Ambo, Y. Ohkubo, S. Suzuki, Carbohydr. Res. 1989, 187, 239–253. P. A. Trinel, G. Lepage, T. Jouault, G. Strecker, D. Poulain, FEBS Let. 1997, 416, 203–206. T. L. Goins, J. E. Cutler, J. Clin. Microbiol. 2000, 38, 2862–2869. M. Nitz, C.-C. Ling, A. Otter, J. E. Cutler, D. R. Bundle, J. Biol. Chem. 2002, 277, 3440–3446.

187


8

NMR of Sulfated Oligo- and Polysaccharides Miloš Hricovíni, Pedro M. Nieto, and Giangiacomo Torri

8.1

Primary and Secondary Structures

Sulfated derivatives today constitute one of the most intensively studied groups of carbohydrates. The reason for such interest is fairly obvious – the diversity and importance of their biological functions. Sulfated saccharides and proteoglycans, consisting of saccharide chains and proteins, are involved in cell growth and differentiation, lipid metabolism, viral invasion, smooth muscle proliferation, morphogenesis, blood coagulation, angiogenesis and so forth [1–14]. Understanding the molecular details, which would explain why a relatively restricted group of carbohydrates is engaged in such complex biological functions, is currently a sought after issue of structural glycobiology. Many approaches have been undertaken to study biological properties from various points of view, and NMR spectroscopy [15–19] is one of the approaches that is contributing more significantly to a better understanding of the action mechanism at the molecular level. Sulfated derivatives can be prepared by the chemical sulfation of nearly any carbohydrate. They have been synthesized from simple mono- or disaccharides, such as glucose or sucrose, but also from complex oligosaccharides [20, 21]. Many of the chemical modifications made to date have been done on vegetal or bacterial polysaccharides such as cellulose, xylans, dextrans, chitosan, or capsular polysaccharide K5 [3, 10, 21, 22]. However, most have been isolated from various animal sources, especially sulfated polysaccharides with biological activity [10, 14, 22]. Probably the most well-known family of these derivatives is that of the polysaccharides belonging to the group of glycosaminoglycans (formerly mucopolysaccharides) [1, 3, 10, 22–26]. Glycosaminoglycans (GAGs) are structurally complex, linear polysaccharides, made up of alternating uronic acid [glucuronic acid (GlcA) or iduronic acid (IdoA)] and hexosamine [2-amino-2-deoxy-d-glucose (GlcN), 2amino-2-deoxy-d-galactose (GalN)], some parts being O- or N-sulfated (O-SO–3 or N-SO–3 groups). The differences in sulfated GAGs are mainly due the variation in the degree and pattern of sulfation, the configuration of the residues, the types of glycosidic linkages, the presence of acetamido (sulfamido) groups and the chain length. Some sulfated GAGs are: keratan sulfate [-b-Gal-(1 ? 4)-b-GlcNAc-6-S(1 ? 3)-], chondroitin 4-sulfate [-b-GlcA-(1 ? 3)-b-GalNAc-4-S-(1 ? 4)-], chondroitin

189

190

8 NMR of Sulfated Oligo- and Polysaccharides

6-sulfate [-b-GlcA-(1 ? 3)-b-GalNAc-6-S-(1 ? 4)-], dermatan sulfate [-a-IdoA-(1 ? 3)b-GalNAc-4-S-(1 ? 4)-], heparan sulfate and heparin [-a-IdoA-2-S-(1 ? 4)-a-GlcN, 6S-(1 ? 4)-], where S denotes the SO–3 group and Ac denotes the CH3CO group. Furthermore, since these polysaccharides are not homogeneous, there are often other residues in their structures, such as GlcN,3,6-S, GlcA 2-S, GlcNAc, and unsubstituted IdoA residues. It should also be noted that the structural differences between heparin and heparan sulfate are subtle (they are synthesized by different cell types), and quite often the distinction is based either on their core proteins or on their biological activity [6, 10, 14]. 8.1.1

The Effect of SO–3 Groups upon NMR Chemical Shifts and Coupling Constants

The presence of SO–3 groups in the structure of saccharides has a considerable effect on the chemical shift and scalar spin-spin coupling constants in the NMR spectra of these molecules. The electronegativity of the SO–3 group produces a significant deshielding of the chemical shift of the directly bound protons and carbons, the extent of this deshielding depending on the structure of the residue itself as well as on the number of substituents. The overall effect is usually evident in the 1H NMR spectra (Fig. 8.1) [27], which are in most cases better resolved than those for neutral carbohydrates. The effect is notable, especially when more than one sulfate group is introduced into the structure. For example, the chemical shift of all the protons is shifted downfield in 2,3,4,6-sulfated Me b-glucopyranoside [28] with respect to the unsubstituted compound (Tab. 8.1) [29]. Protons linked to carbons bearing sulfates, H-2, H-3 and H-4, showed a change of more than 1 ppm. Protons H-1 and H-5 are also deshielded and their chemical shifts changed 0.4 ppm and 0.68 ppm, respectively, indicating the influence of the SO–3 groups also on protons that are not linked to carbons bearing sulfate groups. Similar effects can also be seen in the 13C spectra (Tab. 8.1). However, b-effects may also have influence on the spectrum. For example, C-2 and C-4 carbons are downfield about 3 ppm and, at the same time, C-1 and C-5 carbons appear upfield. In contrast, the chemical shift of C-3 remains unchanged. Thus, the influence of the sulfate groups can be monitored straightforwardly from the chemical shift variations and, consequently, the sulfation pattern can be determined from the NMR spectra [30]. Also, the spin-spin coupling constants can vary as a function of substitution by SO–3 groups. The couplings greatly depend on the s-character of the r-bond between the nuclei (Fermi contact term). Thus, the three-bond proton-proton coupling constants (3JH-H) in sulfated saccharides can differ from those in neutral saccharides. For example, changes in 3JH-H are evident in sulfated Me a- and Me b-glucopyranosides (Tab. 8.2) [28]. All 3JH-H couplings were found to be smaller (0.2–1.2 Hz) in the 2,3,4,6-sulfated Me b-glucopyranoside than in the unsubstituted compound. In the b-analog, these differences are more significant (up to 4.4 Hz). However, in this latter case, the effect is due not only to variations in spin density but also to the change in conformation of the pyranose ring, for

8.1 Primary and Secondary Structures

500 MHz 1H NMR spectra of synthetic disaccharides GlcA-b-(1 ? 4)-GlcN-SO3a-OMe (A) and GlcA 2-SO3-b-(1 ? 4)-GlcNSO3 -a-OMe (B) in aqueous solution. The effect of substitution by the single sulfate group

is marked not only in the GlcA residue but also in the GlcN-S residue (the tightly coupled spin system is well seen in both residues in A).

Fig. 8.1

Tab. 8.1 The effect of sulfate groups on 1H and 13C chemical shift in methyl b-glucopyranoside (Me b-Glc) in aqueous solution. S denotes the SO–3 group

Atom Me b-Glc b)

1 1

1

3

4

5

6

6'

OMe a)

H C

4.27 3.15 104.0 74.1

3.38 76.8

3.27 70.6

3.36 76.8

3.82 61.8

3.62

3.46 58.1

H C

4.67 4.30 102.1 77.0

4.63 76.7

4.40 73.6

4.04 74.1

4.35 68.7

4.23

3.46 58.1

13

Me b-Glc 2,3,4,6-S c)

2

13

a) Chemical shift of the OMe signal in unsubstituted and substituted compounds was set to equal values. b) Ref. [29]. c) Ref. [28].

which a contribution of non-chair conformations must be taken into account. A large influence of SO–3 groups can be expected on one-bond proton-carbon coupling constants (1JC-H). Indeed, measurements of spin-spin couplings in heparin derivatives showed that 1JC-H can differ by up to 10 Hz in substituted compared with non-substituted compounds [30]. For example, 1JC2-H2 is 148 Hz in the glucosamine residue in the non-substituted polysaccharide: -a-IdoA-(1 ? 4)-a-GlcNH2(1 ? 4)-, and decreases to 138 Hz in the 2-N substituted analog [-a-IdoA-(1 ? 4)-aGlcN-S-(1 ? 4)-]. If two or more sulfate groups are introduced at the same time,

191

192

8 NMR of Sulfated Oligo- and Polysaccharides Tab. 8.2 The effect of sulfate groups on three-bond proton-proton coupling constants in methyl

a-glucopyranoside (Me a-Glc) and in methyl b-glucopyranoside (Me b-Glc) in aqueous solution. S denotes the SO–3 group J1,2

J2,3

J3,4

J4,5

J5,6

J5,6'

J6,6'

Me a-Glc a) Me b-Glc a)

4.0 8.2

10.0 9.6

10.0 9.6

10.0 9.6

2.8 2.4

5.8 6.4

12.8 12.8

Me a-Glc 2,3,4,6-S b) Me b-Glc 2,3,4,6-S b)

3.6 5.7

9.8 5.2

8.8 6.8

– 6.0

– 3.0

– 8.0

– 10.8

a) Ref. [29]. b) Ref. [28].

the 1JC-H variation is less pronounced with respect to non-substituted compounds, and often accompanied by conformational changes in the molecule. Thus, 1JC-H variation is most meaningful when analyzing the effect of a single sulfate, and could be a useful NMR parameter in determining the sulfation pattern in carbohydrate derivatives. 1 H and 13C chemical shifts can also depend greatly on the pH (pD) of the solution because of the presence of carboxylate groups. This is especially true for atoms that are in the vicinity of charged groups, and where changes up to *1 ppm for 1H and *2 ppm for 13C can be detected. The data collected for heparin indicated that the largest downfield shifts were on H-5, H-3 and H-4 (in descending order) in the IdoA 2-S residue, while the largest upfield shifts were detected on H-5 and H-4 protons in the Glc N,6-S residue [31, 32]. C-6 (carboxylate carbon) experienced the largest upfield displacement together with C-3 and C-2 in the IdoA 2-S residue, C-1 in the Glc N,6-S. In contrast, C-5 and C-4 in IdoA 2-S shifted downfield. Similar observations have also been made in other sulfated polysaccharide [33]. 8.1.2

The Effect of SO–3 Groups upon the Structure

The mutual interaction between sulfate and carboxylate groups, both bulky and negatively charged, is also reflected in the 3D structure and dynamics of sulfated carbohydrates in solution. As a result, the polymer chains can adopt an extended, random coil, partly flexible structure [22, 23], but formation of well-defined structures has also been described [26]. The flexibility is due not only to the glycosidic linkages, as in other (neutral) oligo- and polysaccharides, but also to the presence of sulfate groups that can influence the conformation of the pyranose rings. The latter effect is mainly observed in the sulfated IdoA residue [3, 22], and in some cases, in the “oversulfated” glucuronate residue [28]. These changes in both the pyranose ring and the glycosidic linkage conformations, brought about by the presence of SO–3 groups, may have a secondary effect on the values of the chemical shift and coupling constants. Consequently, in substituted compounds, the var-

8.1 Primary and Secondary Structures

iations in the NMR parameters are complex and the interpretation of the NMR data is not always straightforward. Primary and secondary structures have been analyzed in various synthetic and naturally occurring sulfated carbohydrates. Sulfated GAGs were among the first carbohydrates studied by NMR spectroscopy. The structures of heparin, heparan sulfate, chondroitin 4-sulfate, chondroitin 6-sulfate, dermatan sulfate and keratan sulfate have all been analyzed by 1H and 13C NMR spectroscopy [34–46]. The first spectral data allowed the assignment of the anomeric signals, characteristic H-5 resonances in IdoA residues, and confirmed the structure of the main disaccharide units, linkage types, anomeric configuration, and sulfation pattern [34–42]. More detailed studies were later focused on the analysis of minor components in these heterogeneous polysaccharides [40, 43, 47]. These examinations were mainly prompted by the biological properties associated with the less abundant residues of the polysaccharide chains. The NMR analysis of the structure of the heparinpentasaccharide, which corresponds to the binding site of heparin for plasma protein antithrombin, allowed the assignment of the trisulfated glucosamine residue as well as the non-sulfated glucuronic acid moiety [40, 43]. Recent studies have been directed predominantly toward a detailed characterization of the structure of synthetic oligosaccharides [20, 48–50], synthetically modified polysaccharides [21, 30, 51–53], “linkage region” structures [54–56], and those derivatives prepared by the chemical or enzymatic depolymerization of high molecular weight GAGs [57– 65]. Chemical modifications carried out on heparin have enabled the assignment of 1H and 13C chemical shifts as well as the determination of the 3JH-H and 1JC-H couplings. Investigations have shown that the sulfation pattern has a distinct effect upon these NMR parameters, and the shift and coupling variations were large enough to confirm the presence of SO–3 groups in different positions [30, 51]. Similar effects have been observed in dermatan sulfate [66, 67]. For example, the chemical shift in the IdoA residue moved downfield depending on the degree of substitution (Tab. 8.3). The effects were most pronounced on H-2 and H-3, where the difference between the substituted and non-substituted residues was *1 ppm. However, the influence of the sulfated group on the chemical shift of other protons was also relatively strong. The chemical shift of H-1 varied from 4.88 ppm up to 5.23 ppm. Smaller, but still measurable, was the effect upon H-5.

1 H chemical shifts in aqueous solutions of the IdoA protons in dermatan sulfate as a function of sulfation pattern

Tab. 8.3

IdoA a, b) IdoA 2-S a) IdoA 2,3-S a) a) Ref. [66]. b) Ref. [67].

H-1

H-2

H-3

H-4

H-5

4.88 5.16 5.23

3.53 4.17 4.37

3.90 4.23 4.96

4.10 4.06 4.29

4.72 4.85 4.89

193

194


These parameters have been used to analyze the primary and secondary structure of chondroitin 4-sulfate and chondroitin 6-sulfate, a number of synthetic oligosaccharides related to these polymers, and oligosaccharides prepared from their hydrolysis [68–86]. Here, the 6-O-sulfation of the GlcNAc residue in unsaturated disaccharides causes a downfield shift of H-6, H-6' and H-5, regardless of the anomeric configuration [74]. The 2-O-sulfation of the GlcA residue resulted in the downfield shift of H-2. On the other hand, N-sulfation in the GlcN residue caused an upfield shift of the H-2 and H-3 protons. These data allowed the formulation of rules for assigning protons in larger chondroitin-related oligosaccharides [74]. As in other similar polysaccharides, the heterogeneity is due to various sulfation patterns in both chondroitin 4-S and 6-S [68, 77]. NMR analysis has also allowed the characterization, and the existence of structural heterogeneity, of the linkage region of oligosaccharides derived from chondroitin 4-S and 6-S proteoglycans [72, 73, 80]. Keratan sulfates have been divided into two major types according to structural variation: keratan sulfate-I (N-linked to protein, found in cornea) and keratan sulfate-II (O-linked to protein, found in skeletal tissues) [87]. The latter, based on structural differences, has been further subdivided into classes A and B. The A polysaccharides contain fucose and a(2-6)-linked sialic acid residues [88]. The primary and secondary structures of the different keratan sulfates have been studied intensively by NMR [89–98], and the studies of sulfated oligosaccharides, obtained by endo-b-galactosidase treatment, have confirmed the b-configuration of the glycosidic linkages [89]. The latter evidence was based on the analysis of the H-6 and H-6' chemical shifts [90], indicating that the sulfate groups are linked to the C-6 carbons in all residues, except for the reducing-end galactose. It has also been established that there is a high degree of uniformity in the extent of the sulfation in keratan sulfate from shark cartilage [91]. In addition, the 13C spectra of tetrasaccharides derived from bovine articular cartilage keratan sulfate have shown the considerable effect that sulfation has on the carbon chemical shifts [92]. Keratan sulfate isolated from bonefish larvae consists of a disulfated disaccharide alternating with an unsulfated disaccharide in the adjacent N-acetyllactoseamine unit [93]. It is speculated that such a structure might provide an explanation for the ability of bonefish keratan sulfate chains to self-associate into dimers.

8.2

Three-Dimensional Structure

It was recognized long ago that the 3D structure of biomolecules is one of the key phenomena affecting their functions. This is especially true for those that are mediated by intermolecular interactions such as protein-carbohydrate interactions. The conformations of both interacting species, as well as their dynamics in solution, can influence the equilibrium association constants considerably. The analysis of these features has therefore been of marked interest to experimental and theoretical chemists in recent years.

8.2 Three-Dimensional Structure

The determination of 3D structures of sulfated saccharides is usually based on the same approaches as those used for other carbohydrates (see Chapter 6). Both the conformations of the monosaccharide units, as well as the geometry at the glycosidic linkages, have to be determined to obtain the overall picture of molecular structure. Two types of NMR parameters are mostly used in conformation analysis: scalar spin-spin coupling constants and NOEs. Useful data could also be obtained from residual dipolar couplings (see Chapters 2 and 9), although these data have not yet been applied to sulfated carbohydrates. Besides, semi-quantitative data can also be inferred from chemical shifts. 8.2.1

Coupling Constants

In general, three-bond proton-proton (3JH-H) scalar coupling constants are the most commonly used parameters in 3D structure determination, because of their dependence upon the dihedral angle of the bonded atoms (Karplus-type relationship). Experimental 3JH-H values have been determined in all the residues constituting sulfated carbohydrates such as Glc N,6-S, IdoA 2-S, GlcNAc 6-S, GalNAc 4-S and GalNAc 6-S (Tab. 8.4). The vicinal coupling constants in a-Glc N,6-S are comparable in various oligo- and polysaccharides [3, 39, 48, 99]. The 3JH1-H2 values range from 3.6 Hz to 3.8 Hz, whereas the coupling for other intra-ring protons (3JH2-H3, 3JH3-H4 ,3JH4-H5) is large (9–11 Hz). All these values are compatible with the 4C1 chair form of the pyranose ring where the H-1 proton is in the equatorial position and protons H-2, H-3, H-4 and H-5 are in axial positions (Fig. 8.2). The 3JH-H values are in agreement with the 4C1 chair form also in GlcNAc 6-S residues [74], although the 3JH1-H2 couplings differ slightly (about 1–1.5 Hz) with respect to Glc-sulfated residues [39, 48, 99]. The 3JH-H values are comparable regardless of the position of the sulfate (4-S or 6-S) in the sulfated GalNAc residues that

Tab. 8.4 Three-bond proton-proton coupling constants (values in Hz) in sulfated glucopyrano-

side and galactopyranoside residues in various saccharides in aqueous solution Residue

J1,2

J2,3

J3,4

J4,5

Ref.

a-GlcN-S a) a-GlcN, 6-S b) a-GlcN,3,6-S a-GlcNAc 6-S a-GalNAc 4-S a-GalNAc 6-S a-Glc 2,3,4,6-S b-Glc 2,3,4,6-S b-GlcA 2,3,4-S b-GlcA 2,3-S

3.6 3.6 3.5 3.0 3.5 4.0 3.6 5.7 6.4 5.9

10.2 10.3 10.7 11.0 11.0 11.0 9.8 5.2 3.2 –

9.4 9.2 9.1 8.0 2.5 3.0 8.8 6.8 4.0 1.5

9.9 10.0 10.0 9.0 – – – 6.0 2.8 1.5

48 99 99 74 74 74 28 28 28 82

a) Average values in various oligosaccharides. b) Average from different residues in pentasaccharide and polysaccharides.

195

196


The possible ring conformations in the 2-sulfated unsaturated glycosyluronic acid rings (1H2 and 2H1) and in the 2-sulfated

Fig. 8.2

iduronic acid residues (4C1, 1C4 and 2S0) in sulfated saccharides.

also adopt the 4C1 chair form [74]. Quite exceptionally, considerably smaller 3JH-H (Tab. 8.4) have been observed in a few oversulfated synthetic oligosaccharides and synthetically modified polysacharides [28, 61, 82]. The contributions of non-chair conformations (3,0B) had to be taken into account to interpret the experimental data in Glc 2,3,4,6-S [28]. Similarly, the conformational equilibrium in oversulfated glucuronic acid residues (GlcA 2,3,4-S) in disaccharides consists of the 4C1 chair form and the non-chair 3,0B form. The rather complex behavior of the GlcA 2,3-S residue was observed in a chemically modified polysaccharide from chondroitin sulfate [61, 82]. 3JH-H could be interpreted with both chair conformations 4 C1 and 1C4, as well as the skew 2S0 form [82]. A different conformational equilibrium has been determined in 2-sulfated 4,5unsaturated glycosyluronic acid rings (DUA 2-S) (these structures are obtained at the non-reducing end of oligosaccharides by heparinase-mediated cleavage of the polysaccharide) in sulfated carbohydrates. Here, the 3JH-H values were 3JH1-H2 * 3.0 Hz, 3JH2-H3 * 3.0 Hz and 3JH3-H4 * 4.5 Hz [78, 100–102]. The values are consistent with the presence of two half-chair forms in aqueous solution, namely, 1 H2 and 2H1 (Fig. 8.2) [100]. The relatively small 3JH-H values also indicate that the former conformer prevails. The increase in the population of the 2H1 form is observed in desulfated residues (30–60%), depending on the structure of the neighboring sulfated residue in the oligosaccharides [100].

8.2 Three-Dimensional Structure Tab. 8.5 Three-bond proton-proton coupling constants (values in Hz) in the IdoA and IdoA 2-S

residues in various selected saccharides in aqueous solution and the abundance of the 1C4, 4C1 and 2S0 conformers Compound

J1,2

J2,3

J3,4

J4,5

1

1 2 3 4 5 6 7 8 9

1.8 4.9 4.0 1.9 2.5 2.5 4.0 5.2 2.6

3.3 6.9 6.6 3.7 4.5 4.6 7.5 9.8 5.9

3.4 6.4 5.2 3.7 2.8 3.1 3.6 4.1 3.4

2.2 4.2 3.7 2.2 2.2 2.3 3.1 4.0 3.1

90 38 45 87 75 75 35 10 60

C4

2

S0

10 17 26 25 25 65 90 40

4

C1

45 29 13

Ref. 109 114 48 48 115 116 109 113 109

A more complex behavior was found in 2-O-sulfated a-l-iduronic acid (IdoA 2S) residues, which have been subject of a lively debate on their conformational properties [37–39, 46, 48, 49, 103–114]. Tab. 8.5 lists the 3JH-H values for the IdoA 2-S residue in selected compounds. For comparison purposes, selected compounds from the non-sulfated form of a-l-iduronic acid (IdoA) are also presented. The magnitude of proton-proton couplings depends not only on the substitution at position 2 (the presence of the 2-O-sulfate group) of the idopyranose ring (e.g. 1 and 2, 6 and 7), but also on the structure of the neighboring residues. The 3JH4 H values permit the exclusion of the C1 chair form, as they are much smaller than those that would correspond to this conformation (Tab. 8.5, Fig. 8.2). The same argument is valid for the exclusive presence of the 1C4 form, as the larger couplings, mainly 3JH2-H3 and 3JH3-H4, do not correspond to equatorially oriented protons H-2, H-3 and H-4. Only in a very few cases can the NMR experimental

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198


data be interpreted by evaluating the conformational equilibrium of both the 4C1 and 1C4 forms. For example, the magnitude of 3JH-H values can be interpreted by the presence of two chair forms (4C1 : 1C4 about 20 : 80) for disulfated IdoA 2-S (1 ? 4) anMan 6-S (anMan stands for anhydro mannitol) [46, 109]. However, the analysis of 3JH-H values in most sulfated saccharides has shown that other forms must be taken into account as well [104, 107–109]. In the case of a simple monosaccharide, IdoA 2-S, the interpretation requires consideration of two ring forms, 1 C4 and 2S0, with a strong preference for the chair form [108, 109]. Such an equilibrium is in agreement with relatively small 3JH2-H3 and 3JH3-H4 values (H-4 is

8.2 Three-Dimensional Structure 2

3

3

isoclinal in the S0 conformation, and both JH3-H4 and JH4-H5 are relatively small) (Fig. 8.2). In addition, high abundance of the 1C4 form is supported by the presence of 4JH2-H4 (“W” arrangement). On the contrary, the non-sulfated derivative has a more complex conformational equilibrium with nearly equally populated chair forms. The strong influence of the 2-O-sulfate is well documented in the tetrasaccharide 5 and the two pentasaccharides 6 and 7 [99, 109, 115, 116]. In the non-sulfated form, 3JH-H values are relatively small (Tab. 8.5), and the conformational equilibrium is shifted toward the 1C4 form (2S0 : 1C4 * 25 : 75). On the other hand, considerably larger couplings support the prevalence of the 2S0 form in conformational equilibrium in 7 (2S0 : 1C4 * 65 : 35) [109]. Furthermore, in the chemically modified pentasaccharide 8, where one additional sulfate group is introduced, 3JH-H couplings are even larger, and indicate that the conformational equilibrium is shifted nearly completely toward the skew, 2S0 [113]. In heparin, the 3JH-H values differ from the above-mentioned pentasaccharides and agree with the conformational equilibrium of 2S0 : 1C4 * 40 : 60 [109]. Previous detailed computational analyses, together with the extended experimental data, enabled the identification of the conformational equilibrium in various sulfated oligo- and polysaccharides [110]. The data show quite complex conformational equilibriums of the IdoA 2-S residue in oligosaccharides, consisting of either 1C4 and 4C1 or 1 C4 and 2S0 forms, the 1C4 form prevailing in both cases. However, the adjacent units also have a considerable effect on the relative conformer abundance, and the 2 S0 form may become predominant in various oligosaccharides (e.g., 7 and 8). A recent analysis of iduronate ring conformations further indicates that the 1C4 chair form can interchange easily with the 0S2 and 3S1 forms, and the 4C1 form with the 2S0 and 1S3 conformations [112]. The data also suggest that the pseudorotation among these skewed forms is energetically less demanding than for the chair and skewed forms. The above evidence of conformational properties of the sulfated IdoA residue represents an interesting phenomenon in carbohydrate chemistry. Except for the marked effects on the 3D structure, the presence of the 2-SO–3 group in the IdoA 2-S residue influences the dynamics of sulfated saccharides in solution, as well as the biological activity (see Sect. 8.4). Three-bond proton-carbon (3JC-H) and one-bond proton-carbon coupling constants (1JC-H) can provide further insights into 3D structure. 3JC-H can be used to determine the glycosidic linkage conformation [117, 118], though their application to the analysis of sulfated derivatives is rather exceptional. In sucrose octasulfate [119], the experimental 3JC2'-H1 was found comparable with that obtained in 13C-labeled sucrose [120]. This fact, together with experimental NOEs and molecular modeling studies, enabled it to be shown that the 3D structure in aqueous solution is different from that of all the eight conformers observed in the crystalline complex with the acidic fibroblast growth factor [121]. Regarding 1JC-H, both experimental data [111, 122, 123] and theoretical analysis [124–126] have revealed that their magnitudes depend on the molecular geometry. As the oxygen lone pairs orbital interacts with the molecular orbitals localized in the C–H bond, the bond orders change, and consequently the indirect spin-spin couplings vary. Alternatively, this observation can be described by the marked

199

200


changes in the s-character of the C–H bond. Since these effects are very sensitive to molecular geometry, the variation in 1JC-H can be relatively large. The most common evidence of this phenomenon is known from the differences in 1JC-H for a- and b-anomers, where the difference is * 10 Hz, 1JC-H being larger for equatorially oriented C–H bonds [122, 123]. However, other evidence indicates that 1JC-H could have a more general application [115, 124–129]. Recently, a comparison was made of the 1JC-H values in polysaccharides with various sulfation patterns and 1 JC-H in selected compounds (for this see Tab. 8.6) [30, 130]. Considering the IdoA residues, the largest 1JC-H values were obtained in 3-O-sulfated IdoA (10), the smallest in 7. Interestingly, the variations in 1JC-H correspond well with the stereochemistry of the IdoA ring: the 1C4 conformation is the most populated (about 95%) in 10, while the conformational equilibrium is shifted toward the skew form in 7. However, variations at the glycosidic linkages might also influence 1JC-H at both the C-1 and the C-4 positions. For example, the differences in 1JC4-H4 in the glucosamine residues in 10 and 9 (156 Hz versus 149 Hz) suggest a conformational difference at the glycosidic bond. Similar evidence was found in 11 and 9 where the differences also indicate (179 Hz versus 173 Hz) a change at the glycosidic linkage. The above evidence might indicate the possibility of applying 1JC-H to the stereochemical analysis of sulfated carbohydrates, though further studies are needed for more conclusive data. Finally, it should also be noted that experimentally measured 3JC-H values are interpreted through empirical relationships obtained for various types of atom arrays, such as H-C-C-C or H-C-O-C. The precise interpretation of the 3JC-H values should take into consideration not only the influence of the dihedral angles, but also other effects such as bond lengths, bond angles, the electronegativity of neighboring nuclei, and parameters that can change the spin density at the atoms of interest. This is especially important for sulfated saccharides since the charge present at the sulfates (as well as at carboxylates) may influence the magnitude of the spin-spin couplings. As various empirical Karplus-type relationships have

Tab. 8.6 One-bond proton-carbon spin-spin coupling constant (1JC-H, values in Hz) in three differently substituted – (IdoA–GlcN) – sequences a) and pentasaccharide 7 b) and the abundance of the 1C4 and 2S0 conformers in the IdoA residue.

IdoA Sequence

1

10 11 9 7

177 176 173 172

JC1-H1

Glc 1

JC2-H2

C 151 148 145

1

JC3-H3

155 151 149 145

a) Ref. [30]. b) Ref. [130]. c) Could not be measured due to overlap.

1

1

153 153 149 148

175 179 173 175

JC4-H4

JC1-H

1

JC4-H4

156 147 149 C

1

C4

95 85 60 35

2

S0

5 15 40 65


been determined on neutral molecules, care must be taken when interpreting the experimental three-bond couplings in saccharides that bear charged groups.

8.2.2

Nuclear Overhauser Effect (NOE)

The 3D structure of sulfated saccharides may be further analyzed by the comparison of experimental with theoretical NOEs. Both steady-state and transient [one-dimensional (1D) or two-dimensional (2D)] NOE experiments can be utilized, although 2D NOESY (or ROESY) methods have been mainly used in recent years because of better spectral resolution and simple experimental setting. Theoretical NOEs are computed using the appropriate spectral density functions and the corresponding saccharide conformation/s. The latter are obtained by molecular modeling methods (see Chapter 6). The experimental NOEs are then compared with the theoretical data, and the quality of the fit may be estimated from R-factors [131]:

201

202


R

Xh exp Iij smix

i2 Xh i2 exp Iijcalc smix Iij smix

where Iij is the intensity of the calculated (Iijcalc) or experimental (Iijexp) cross-peak between the cross-relaxing protons i and j at a given mixing time (smix). Since NOEs depend upon the interatomic distances of cross-relaxing nuclei, more precisely upon the hr–6 ij i factor (r is the internuclear distance), the 3D structures of saccharides can, in many cases, be determined with satisfactory precision. The application of NOEs in the 3D analysis of rigid, well-defined residues (such as Glc N-S, Glc N,6-S, GalNAc 4-S) has been relatively rare [101, 102]. However, in the case of flexible residues such as IdoA 2-S, NOEs can provide valuable information, especially in polysaccharides where 3JH-H values are not always measurable. The NOE analysis utilizes the fact that the interproton distances differ from each other in three different conformers, namely, 1C4, 2S0 and 4C1 (Fig. 8.2). The most significant difference, between the 1C4 and 2S0 forms, is in the (H-2)-(H-5) distances (*4.0 Å versus *2.4 Å). For instance, in the NOE analysis of IdoA 2-S in 7, the strong (H-2)-(H-5) NOE cross-peak indicates the presence of the skew form [132]. A quantitative analysis based on molecular modeling confirmed the prevalence of the skew form (1C4 : 2S0 * 35 : 65), and the magnitude of the computed (H-2)-(H-5) NOE (–14%) was comparable to the experimental value (–12%) [133]. The pseudorotation of the IdoA residue was also studied in other sulfated oligosaccharides [66, 101, 102, 115, 134] . NOEs (together with 3JH-H) were consistent with the high abundance of the 2S0 conformation in a heparin-derived tetrasaccharide [101]. Both the 1C4 and 2S0 forms are in equilibrium with approximately equal populations in a structurally related hexasaccharide [102]. NOEs and molecular modeling has allowed the interpretation of the conformational equilibrium (the presence of both 1C4 and 2S0 forms) in a few sulfated polysaccharides like heparin [135], dermatan sulfate, and chondroitin 4-sulfate [79]. NOE evaluation in different preparations of dermatan sulfate showed the conformational equilibrium in the IdoA 2-S unit to depend on the sulfation degree [66]. In pig intestine dermatan sulfate, the presence of the skew form was confirmed by 2D NOESY data. However, in the partially as well as in the extensively sulfated polymer, the IdoA 2-S residue exclusively adopted the 1C4 chair form [66]. Intra-residue NOEs have also been applied to characterize the conformation at the (C-5)-(C-6) linkage in sulfated synthetic oligosaccharides [76]. The NOEs between H-4 and H-6 protons in eight synthetic chondroitin sulfate structurally related disaccharides showed that sulfation in positions 4 and 6 has a marked effect on the conformational preference of the sulfonyloxymethyl group in the substituted Gal residue [76]. In the case of the Gal 4-S residues, tg conformers showed a small increase in population, whereas, in the Gal 4,6-S analogs, the population of gt increased as a consequence of the repulsive effect of the two sulfates in positions 4 and 6. A detailed analysis has been performed for a heparin-tetrasacharide (5) and a heparin-hexasaccharide [101, 102]. Experimental NOEs (Figs. 8.3 and 8.4) were interpreted with IRMA (Iterative Relaxation Matrix Approach). Geometries were obtained from restrained energy minimization and molecular dynamics simulations


Two-dimensional phase-sensitive ROESY spectrum of the synthetic tetrasaccharide 5 (GlcN, 6-S-a(1 ? 4)-GlcA-b(1 ? 4)GlcN,3, 6-S-a(1 ? 4)-IdoA-a-OMe) in aqueous Fig. 8.3

Selected cross-sections, from two-dimensional NOESY spectra, along the x2 axis through the anomeric signal in the GlcN,3,6-S residue of the synthetic tetrasaccharide 5 (GlcN, 6-S-a(1 ? 4)-GlcA-b(1 ? 4)-GlcN,3, 6-Sa(1 ? 4)-IdoA-aOMe) in aqueous solution at three different temperatures (reprinted from Ref. [115], with the permission of Blackwell Science). Fig. 8.4

solution at 40 8 C collected with 250 ms mixing time (reprinted from Ref. [115], with the permission of Blackwell Science).

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204


(AMBER force field) with explicit solvent molecules. Similar structures were found at the glycosidic linkages in the derived tetra- and hexasaccharide, except for small differences in the }1, w1 dihedral angles (between the DUA and Glc N,6-S units). The overall conformation also differed slightly from that found for heparin [26]. Furthermore, the computed interatomic distances were compatible with a right-handed sense of the overall conformation. The existence of two different ring forms in the IdoA residue does not affect the overall shape of these oligosaccharides, which corresponds to what has been observed for the 3D structure of 7 [109, 133]. 1D NOEs and ROEs across the glycosidic linkages in chondroitin sulfate-related disaccharides [in b-Gal-(1 ? 4)-b-GlcA] showed that the 6-sulfate group has a stronger influence on the glycosidic bond conformation than the 4-sulfate group. On the other hand, in reverse-type of structures, i.e., b-GlcA-(1 ? 3)-b-Gal, the 4-sulfate group showed an attractive interaction with the carboxylate group in the Gal residue across the glycosidic linkage [76]. This interaction resulted in changes of the glycosidic linkage geometry with respect to the 6-sulfated derivative. However, in general, the interactions between the sulfates and carboxylates were found to be relatively small, suggesting that these interacting charged groups do not necessarily dominate the 3D structure of chondroitin sulfate-related disaccharides. Interglycosidic NOEs have been analyzed in various sulfated polysaccharides [26, 79, 135]. The decasaccharide model of the heparin molecule was obtained with the MM2 force field. Experimental NOEs were then interpreted assuming a non-isotropic overall tumbling (symmetric top model [136]) where both ring forms (1C4 and 2S0) were considered for the IdoA residue [26]. The computed structure, which interprets the experimental NOE satisfactorily, was nearly identical with the solid-state model derived from X-ray analysis [137]. In such models, three sulfate groups form a cluster on one side of the chain, while the other three form a similar cluster on the opposite side. The overall shape can be characterized as a helix, with an overall decasaccharide length of about 50 Å (corresponding to over 4 Å rise per residue). The 3D structure of the helix does not seem to be heavily affected by the pseudorotation of the IdoA residue, as the stereochemistry at the glycosidic linkages is similar in both the 1C4 and 2S0 forms [26, 109]. Further studies on chemically modified sulfated saccharides have shown similarities in the glycosidic linkage conformation of these structurally related polysaccharides, and have revealed that the substitution degree and the position of the sulfate groups have only a limited influence on the conformation of the glycosidic linkage. On the other hand, the sulfation pattern influences the conformational equilibrium in the IdoA residues in sulfated polysaccharides [135]. Alternating pairs of sulfate groups on either side of extended carbohydrate structures have also been described in linear oligomers of keratan sulfate [79, 89]. Experimental NOEs have indicated that chondroitin 4-sulfate might form a 2fold helix in aqueous solution [79]. Furthermore, the monosaccharide residues bearing the carboxylate and acetamide groups are in the cis position with respect to the polymer chain. A twofold helix is also assumed for dermatan sulfate. The NMR analysis further indicated that dermatan sulfate could self-aggregate, which

8.3 Dynamics of Sulfated Saccharides in Solution

is not the case for chondroitin 4-sulfate. This self-aggregation has been explained by different hydrogen bonding systems in the two polymers: intramolecular hydrogen bonds are stronger in chondroitin 4-sulfate, whereas they are much weaker in dermatan sulfate, since axially-oriented OH groups in the 1C4 conformation of the IdoA residue are unable to create hydrogen bonding to neighboring residues. In dermatan sulfate, the weak intramolecular hydrogen bonds free the relevant groups involved in the intermolecular hydrogen bonding system, and thus self-aggregation can occur [79]. 8.2.3

Chemical Shifts

Although chemical shifts are complex by nature, they have been shown to be useful as semiquantitative NMR parameters to determine the 3D structure of various saccharides [125, 139–141]. Several reports have indicated that chemical shift variations can also reflect conformational changes within monosaccharide residues or at the glycosidic linkages in carbohydrates [125, 141–145], including those bearing sulfate groups [30, 76, 111, 115, 135]. It has been speculated that variation in the 13C chemical shift values of anomeric carbons are a consequence of the conformational changes in the IdoA residue in heparin [111]. More detailed analyses in heparin-like oligosaccharides [48], heparin, heparan sulfate, and chemically modified sulfated polysaccharides [135] are in agreement with these observations. The data suggest that upfield 13C chemical shift can be attributed to a greater abundance of the 1C4 chair form. Furthermore, the temperature coefficients of the carbons at the glycosidic linkages are greater than for other carbons in the molecule. This fact [135] agrees with previous observations of distinct temperature coefficients in non-sulfated disaccharides [145]. Chemical shifts of carbons at the glycosidic linkage changed considerably (up to *2 ppm) when the 4- or 6-position (hydroxymethyl group) was sulfated in model disaccharides [76]. A direct effect of sulfates upon remote carbons (at the linkage) was excluded, and the changes interpreted as a function of the glycosidic linkage geometry. Comparison of the reference data for galactose with sulfated derivatives suggests that 1H chemical shifts could also depend on linkage conformation. The downfield shift of protons at the linkage was found to be in agreement with observed variations in conformation [89]. The change in chemical shift of carbons at the glycosidic linkage in tetrasaccharide 5 was also attributed to the conformational change that occurred during the binding process with the plasma protein antithrombin [115]. 8.3

Dynamics of Sulfated Saccharides in Solution

Whereas the 3D structures of molecules describe a static picture in the solid state (X-ray analysis) or in solution (NMR and theoretical analysis, geometries of energy minima corresponding to the lowest energy states), a molecular dynamics

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206


analysis provides information on overall and internal molecular motion and on the corresponding timescales [146, 147]. Knowledge of dynamics in solution is important for its own sake, but for a detailed understanding of intermolecular interactions, such as protein-carbohydrate interactions, the knowledge of such process is a necessity. Ligand-receptor interactions are energetically governed by the free energy change (DG), while the analysis of the 3D structure enables a description of the enthalpic term (DH). Therefore, the entropic contributions must also be determined. There are several examples in the literature where binding cannot be fully explained by static pictures [148–150]. NMR relaxation data and their interpretation can provide knowledge on molecular motion in the liquid state, and describe the rate and amplitude of such motion [151–168]. The motion can range from small-scale fluctuations (up to 10–15o) within an energy well, with frequencies in the order of about 1012 Hz, through internal rotations across the glycosidic linkages at frequencies on the picosecond time scale (*1010 Hz), up to overall motions at frequencies on the pico- to nanosecond timescales or even slower (depending mainly on molecular size and temperature). Present-day NMR instrumentation allows measurements of relaxation parameters using both one-dimensional and two-dimensional methods even in relatively complex molecules. Several theoretical approaches may then enable the derivation of the corresponding motional parameters [146, 169, 170]. In NMR relaxation experiments, the recovery of spin magnetization to its equilibrium, following perturbation by radio-frequency pulses, can be observed. The spin-lattice relaxation rate describes the return of longitudinal magnetization to equilibrium, and the spin-spin relaxation rate describes the return of transversal magnetization. NOEs describe the population changes in the spin state that are brought about by dipole-dipole cross-relaxation. For the 1H–13C spin system (I-S spin system) relaxing by dipole-dipole and chemical shift anisotropy mechanisms, the time dependence of the carbon longitudinal relaxation is [171–173] d=dtSz t

rIS DIz qS qCSA DSz lIS;S 2DIz Sz ;

where D is a deviation from equilibrium. The spin-lattice relaxation rate for qS 1=10D2 JxH

xC 3JxC 6JxH xC :

1 13

C is 2

The term of chemical shift anisotropy can be expressed as qCSA 2=15C2 JxC

3

and the term of cross-correlation is lIS;S C2 D2 6JxC 3 cos2 u

4

1=2

Finally, the cross-relaxation term is rIS 1=10D2 6JxH xC

JxH

xC

5


The expressions for transverse relaxation rates are similar. D is the dipolar coupling constant D l0 =4pcH cC hhrC 3 H i The chemical shift anisotropy constant C is C xC Dr ; where Dr = r||–r^, and r|| and r^ are the parallel and perpendicular components of the chemical shift anisotropy tensor. u is the angle between the principal axis of the cylindrically symmetric chemical shift tensor and the C-H relaxation vector. A correct interpretation of the relaxation data, that includes the choice of the spectral density function, J(x), depends on the nature of the overall and internal motions. A number of models for both isotropic and non-isotropic overall motions have been proposed, with and without the presence of internal motion [169, 174–177]. However, not all these expressions are suitable for a proper analysis of the motional parameters of saccharides in aqueous solution. Too complex models, including those that consider the molecular motion as fully non-isotropic, require an extended set of relaxation data to compute the motional parameters. The presence of internal motion can influence the overall molecular shape (in small molecules, internal motion can contribute to the moment of inertia of the whole molecule), and consequently the molecule may tend to adopt a less ordered shape. In addition, both hydrogen bonds and solvent effects influence molecular structure. Therefore, overall shape is difficult to determine as it is affected by the above phenomena. Thus, the choice of the appropriate spectral density function is not straightforward. For example, in the model-free approach, the assumption is made that internal motion is fast compared with the overall tumbling. In this case, the spectral density functions for an isotropically tumbling molecule can be expressed as [169] JIS x

S2C

H s0 2

1 s0 x

1

S2C

H

s 1 sx2

6

where s0 is the overall correlation time of the molecule, 1/s = 1/s0 + 1/se and se is the effective correlation time characterizing the rate of internal motion. S2C-H is the order parameter that describes the spatial restriction of the internal motion of the C-H relaxation vector. Although the assumption of isotropically tumbling molecules can be correct for molecules of spherical shape (e.g. small molecules; also, in some cases, large proteins can be considered spherical), this is not the case for (sulfated) oligo- and polysaccharides. For these molecules, such an assumption is unlikely to be valid, since molecules of this type usually show an elongated shape. If the molecular shape can be approximated as being axially symmetric (prolate ellipsoid), the spectral density can be expressed in the form [176]

207

208


JIS x S2C

H Jan x

1

S2C

H

s 1 sx2

;

7

where Jan x 0:253 cos2 h 0:75sin4 h

12

sa sb 3 sin2 cos2 h 1 xsa 1 xsb 2 sc

1 xsc 2

and sa s? 1=sb 5=6sb 1=6sjj 1=sc 1=3s? 2=3sjj and s^ = 1/6D^ and s|| = 1/6D||. s|| and s^ are the correlation times for reorientation about the long and short axis, respectively; h is the angle between the C-H relaxation vector and the symmetry axis. In the analysis of proton-proton cross-relaxation rates, fluctuations in interproton distances have also to be considered. In such a case, Jij(x) is Jij x hrij 6 iS2ij Jan x hrij 6 i1

S2ij

s 1 sx2

8

where Sij2 is the order parameter for the H-H relaxation vector and includes both 2 2 the radial (Sij(rad) ) and the angular (Sij(ang) ) components of motional averaging [178, 179]: S2ij

S2ijang S2ijrad

S2ijang

hrij 3 i2 hrij 6 i

:

9

Then, Eq. (8) can be rearranged Jij x hrij 3 i2 S2ijang Jan x hrij 6 i

hrij 3 i2 S2ijang

s 1 sx2

10

Thus, it can be anticipated that the ratio of the relaxation parameters of protons cross-relaxing across time-averaged distances will differ from those cross-relaxing across fixed distances even in an isotropically tumbling molecule [151]. In non-isotropically reorienting molecules, this ratio will be affected by both the motional averaging and the orientation of relaxation vectors with respect to the main axis. If protons are cross-relaxing across fixed distances, Eq. (8) is formally identical with that for an IS spin system [Eq. (7)], and consequently such protons can have


different cross-relaxation rates owing to the various orientations of the relaxation vectors in the molecule [168]. Recently, the dynamics of the heparin-pentasaccharide (pentasaccharide 7), which corresponds to the binding site of heparin for antithrombin, have been analyzed by NMR relaxation measurements at different magnetic fields [168]. Two-dimensional double INEPT methods [170] for measurements of 13C T1 and T2 relaxation times, with and without the suppression of cross-correlation between dipolar and chemical shift anisotropy relaxation mechanisms, were used to determine the relaxation times for carbons in the molecule (Tab. 8.7). Parts of the 2D

Tab. 8.7 13C T1 and T2 relaxation times in pentasaccharide 7 in aqueous solution recorded at 11.7 T. T1 (values in s, column 3) and T2 (values in s, column 4) recorded with suppression of cross-correlation between dipolar and CSA relaxation mechanism. The averaged values of the relaxation times are listed in the last row within the individual residue [168]

Residue

Carbon

13

13

GlcN, 6-S

C-1 C-2 C-3 C-4 C-5

0.29

0.16

a)

a)

0.29 0.28 0.28 0.285 (0.006) 0.25

0.17 0.17 0.17 0.168 (0.005) 0.18

GlcA

GlcN, 3, 6-S

C-1 C-2 C-3 C-4 C-5 C-1 C-2 C-3 C-4 C-5

IdoA 2-S

C-1 C-2 C-3 C-4 C-5

GlcN, 6-S

C-1 C-2 C-3 C-4 C-5

a) Not determined because of overlap.

C T1

C T2

a)

a)

0.26 0.26 0.26 0.258 (0.005) 0.22

0.19 0.18 0.17 0.180 (0.008) 0.16

a)

a)

0.23 0.23 0.23 0.228 (0.005) 0.25 0.25 0.24 0.26 0.24 0.248 (0.008) 0.28

0.17 0.18 0.17 0.170 (0.008) 0.14 0.17 0.17 0.18 0.17 0.166 (0.015) 0.16

a)

a)

0.30 0.30 0.30 0.295 (0.010)

0.18 0.18 0.17 0.173 (0.010)

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210


Contour plots of the ring carbon region of two-dimensional double INEPT spectra of the synthetic pentasaccharide 7 (GlcN, 6-S-a-(1 ? 4)-GlcA-b(1 ? 4)-GlcN,3, 6-Sa(1 ? 4)-IdoA 2-S-a(1 ? 4)-GlcN, 6-S-aOMe) Fig. 8.5

recorded for spin-spin relaxation time measurements with three different lengths of the CPMG pulse train: 6 ms (A), 150 ms (B) and 270 ms (C) (reprinted from Ref. [168], with the permission of Elsevier Science).

spectra are shown in Fig. 8.5. Cross-sections from 2D spectra parallel to the x2 axis through the AM1 signal and the experimental intensities with the best fit are given in Fig. 8.6. The motional parameters have been derived and compared with the experimental data using several motional models. The 13C T1 and T2 relaxation times were found to be inconsistent with the model of an isotropically tumbling molecule. Another support for non-isotropic overall motion of pentasaccharide 7 was found by examining the cross-relaxation rates of protons in the Glc N,3,6-S residue. The cross-relaxation rates between A1*–A2* as well as A2*–A4* (collected at two magnetic field strengths) differed considerably, although they relax across the comparable distances within the rigid residue. Simulation of the relaxation data also showed that the experimental values cannot be interpreted with spectral densities corresponding to an isotropically tumbling molecule [with or without internal motion, Eq. (6)]. A satisfactory agreement was obtained using J(x) for a symmetric top model with internal motion [Eq. (8)]. Tab. 8.8 shows the computed values of s || and s^ (450 ps and 1.6 ns, respectively), the internal motion correlation times (se) for individual residues, and the order parameters for C-

Tab. 8.8 Computed values of the internal motion correlation times (se, ps/rad) and the order parameters (S2C-H) for individual residues in pentasaccharide 7 [168]

Residue

se

GlcN, 6-S GlcA GlcN,3, 6-S IdoA 2-S GlcN, 6-S

31 32 50 28 15

S2C-H (35) (49) (85) (51) (25)

0.72 0.85 0.91 0.83 0.70

(0.10) (0.05) (0.03) (0.08) (0.04)


Cross-sections from the two-dimensional double INEPT spectra of the synthetic pentasaccharide 7 (GlcN, 6-S-a-(1 ? 4)-GlcAb(1 ? 4)-GlcN,3, 6-S-a(1 ? 4)-IdoA 2-Sa(1 ? 4)-GlcN, 6-S-aOMe), parallel to the x2 axis through the anomeric signal in the GlcN,6-S-aOMe residue recorded for spin-lattice relaxation time measurements with six Fig. 8.6

different relaxation delays: 20, 70 120, 200, 300 and 450 ms (A). (B) Experimental T1 and T2 curves for selected signals. Points are the experimental cross-peak intensities, solid lines are the single-exponential fits through the experimental data (reprinted from Ref. [168], with the permission of Elsevier Science).

H relaxation vectors. The computed data show that the order parameters are different for each residue and decrease from the central residue toward both ends of the molecule, indicating that the terminal residues are less restricted in their internal motion. The analysis also showed differences in the S2 values for different relaxation vectors (C-H or Hi-Hj), and that the rate of internal motion is on the picosecond timescale. The diffusion coefficients have been computed in disaccharide DUA-Glc N,6-S in aqueous solution as well as in the presence of the tripeptide GRG [181]. The ratio of computed D|| and D^ was found to be between 0.4 and 0.7 (determined at low temperature, 5 8C). 13C spin-lattice relaxation times and interresidue NOEs, collected at two magnetic field strengths, indicated that the glycosidic linkage is relatively rigid; the values of order parameters determined for the individual C-H vectors vary in the range 0.82–0.89. The analysis also shows that there is little ef-

211

212


fect of the half-chair forms (1H2 and 2H1) of the DUA residue on the diffusion coefficients. In the presence of GRG, the ratio D^/D|| decreased, suggesting that the tripeptide might be oriented along the main axis of the cylindrically symmetric disaccharide molecule. In heparin, 13C T1 data collected at two magnetic fields, and proton cross-relaxation rates determined at 11.7 T, indicated that this polysaccharide could be approximated with the symmetric top model [26]. Di- and dodecasaccharide models were obtained by energy minimization with the MM2 force field, suggesting that heparin could adopt a helical structure. Tab. 8.9 shows the computed values of s || and s^. Since the experiments were carried out at 60 8C, the correlation times are relatively small (s|| = 0.16 ns and s^ = 8 ns). The axial ratio (s^/s||) is about 50, indicating a strong anisotropy of motion for this polymer. The angle between the C-H relaxation vectors and the main axis is in the 60–80 8 interval for seven of the ten vectors. No consideration was given to internal motion. In contrast, for heparin epoxide, a spectral density function for axially symmetric molecules with internal motion was used [Eq. (8)], assuming that the main axis is along the polysaccharide chain spanning the glycosidic oxygens and the C-1 and C-4 carbons [182]. Experimental 13 C T1, T2 and proton cross-relaxation rates were interpreted with the values of the motional parameters listed in Tab. 8.9. The magnitudes of s || and s^ (800 ps and 42 ns, respectively) suggest a strong motional anisotropy for the molecule in aqueous solution. The se (150 ps) value indicates that the rate of internal motion is faster than either of the overall correlation times. A comparison of s || and s^ with those derived for the heparin molecule indicates a difference in the molecular reorientation rate; this is most likely due to the different experimental conditions – temperature and concentration. On the other hand, the axial ratio in both molecules was found to be similar (s^/s|| is about 50), suggesting a close similarity in the molecular shape of heparin and heparin epoxide. A similar type of analysis was also performed in low molecular weight K5 polysaccharide. The relaxation data (13C T1, T2 and 1H–13C NOEs), collected at various magnetic fields strengths (7 T, 11.7 T and 14 T) could be interpreted by the symmetric top model with internal motion [183]. The derived values of s || and s^ (Tab. 8.9) indicated slightly different overall motional properties for the K5 molecule with respect to the previously mentioned sulfated polysaccharides. The axial ratio is smaller (*22), compared with *50, and appears to be in agreement with the smaller size of K5. On the other hand, se (30 ps) and S2 (*0.8) suggest a differTab. 8.9 Computed values of the overall (s||, s^, ns/rad) and internal motion correlation times (se, ps/rad) and the order parameters (S2C-H) for selected molecules

Heparin Heparin epoxide K5 a) Not determined.

s||

s^

se

S2C-H

Ref.

0.16 0.8 0.35

8 42 7.8

a)

a)

0.15 0.03

0.65 0.79

26 182 183

8.4 Interactions with Ions and Proteins

ent extent of internal motion compared with heparin epoxide and also with heparin. This dissimilarity could originate from the structural differences of these molecules: the presence of the structurally well-defined glucuronic acid residue in the K5 molecule could lead to limited internal motion. The analysis also shows the importance of considering the spin-spin relaxation times when deriving s|| and s^ from relaxation data, as the correlation times strongly depend on the low frequencies, J(0) [183]. Although only limited data are currently available on the dynamics of sulfated oligo- and polysaccharides, first conclusions can be formulated on the motional properties of these compounds in solution. It is now evident that the model for isotropic overall motion cannot interpret the experimental NMR relaxation data. The model for a non-isotropically tumbling molecule with axial symmetry and internal motion should be considered. The presence of glucuronic acid in the saccharide structure results in a more rigid structure compared to molecules with 2sulfated iduronic residues. The different data analysis have also shown the importance of evaluating spin-spin relaxation times for the characterization of the motional properties of saccharides. In any case, further studies should be carried out to expand the current knowledge, predominantly on the rate and extent of internal motion.

8.4

Interactions with Ions and Proteins 8.4.1

Interactions with Metal Ions

Although saccharides have many hydroxyl groups that can interact with ions, metal ion binding with neutral carbohydrates is very weak and is influenced by solvation [184]. On the other hand, sulfated saccharides show strong interactions with metal cations, with interesting binding selectivity due to their polyelectrolyte nature [3, 6, 10]. Some GAGs have relatively flexible structures, as a result of the presence of iduronate residues. Together with their negatively charged groups, they represent polysaccharides of a special type that exhibit frequent and extensive interactions with metal ions. This kind of interaction has been found to be essential for some biological activities. For example, the presence of calcium is essential for the anticoagulant and mitogenic activities of GAG [10]. Early NMR studies on GAG-counterion interactions were based mainly on chemical shift data on heparin and chemically modified heparins [185, 186], showing a higher binding affinity for divalent cations than that for monovalent ones. The relative importance of each charged group on binding was assessed using the observed chemical shift variations for different glycosaminoglycan derivatives. The key role of the carboxylate group in the iduronate residue was proposed by comparing chemically modified heparin molecules [185]. Another essential binding group is the glucosamine 2-sulfamino group, as its depletion or substitution by N-

213

214


acetyl groups causes the loss of calcium binding [185]. Interestingly, later studies have revealed that the 2-O-sulfate group in the IdoA 2-S residue is not necessary for calcium binding [186]. The chemical shift variations observed after the addition of Ca2+ ions, with respect to Na+, have been proposed to be a consequence of the existence of conformational changes due to specific binding, though electrostatic effects should not be discarded. The effect of Ca2+ on conformation is manifested by a change in the proton-proton coupling constants for the IdoA residue. There is a shift toward the 1 C4 conformer, the equilibrium shifting from 59 : 41 (1C4 : 2S0) toward 79 : 21 in heparin [110]. The aggregation of side-chains in chondroitin sulfate proteoglycan detected by 23Na relaxation times (in the presence of Ca2+ ) is also a calcium-induced structural change, observed in sulfated saccharides [187]. These conformational changes may be explained by the strict geometrical requirements necessary for metal ion coordination. Although it seems difficult to provide six or seven coordinating groups in an adequate arrangement for sulfated carbohydrates [188], there is a second possible mode of interaction with fewer structural requirements. For these highly charged polyanions, unspecific metalpolyanion interactions can also be considered. The solvated cation is delocalized along the polyanions in this type of interaction, and is termed a territorially bound counterion within the Manning model [189]. Another form of binding is site-specific, where the ion is localized and the coordination sphere is completed. According to the Manning counterion condensation model of binding to polyelectrolytes, territorially bound cations are in a fully hydrated state and are contained within a volume with unrestricted freedom of motion. The binding depends only on the counterion valence and the polyion linear charge density (long-range electrostatics), and is independent of ionic strength. The above model also explains the pH dependence and the loss of binding ability found in chemically modified compounds, as both are the result of reduced linear charge density in the polyelectrolyte [186]. NMR has been one of the techniques used to determine the behavior of glycosaminoglycans as Manning polyelectrolytes. An analysis of NMR spectral parameters, such as chemical shift and T1 and T2 relaxation times, has been used to establish whether a particular counterion is site or territorially bound to the carbohydrate [186, 190, 191]. The analysis of the 23Na T1 relaxation times is based on the observation that Na+ exchange between the bound and free forms is fast in the NMR time scale. Thus, the observed T1o should be a molar fraction of the T1b (bound) and the T1f (free), where the molar fraction of Na+ free is Pf = 1–Pb and 1 1 Pb T1o T1 b

1 T1 f

1 : T1 f

The molar fraction of bound Na+ is Pb = [Na+]b/[Na+]t, where t denotes the total concentration. According to the Manning theory, the concentration of bound cations is proportional to the fraction of heparin charges neutralized, hNa, and to the concentration of anionic sites in the polyion, A; [Na+]b = hNa A


1 hNa A 1 T1o Na t T1b

1 T1f

1 : T1f

Thus, the two-site model predicts that 1/T1o is a linear function of A/[Na+]t, and the values of T1 can be determined for bound and free sodium. Measurements of T1 at various sodium concentrations confirm that the binding of Na+ to heparin is territorial up to a concentration of 0.2 M [190]. The same experiments at different pH values indicate that the fraction of polysaccharide charge neutralized by solvated cations depends on the carboxylate protonation state [191, 192]. While many studies have shown that heparin has sodium and magnesium counterions territorially bound, there is controversy in the case of Ca2+ ions. Although chemical shift variations have been interpreted as diagnostic of site-specific binding [185], the 13C NMR chemical shifts of sodium and calcium heparin salts were interpreted in terms of both cations being non-specifically bound to heparin [186]. This result was in disagreement with the results obtained by other techniques [191, 192]. It was also found that N-desulfated heparin or chondroitin sulfate either does not interact with calcium or the binding constant is too small, indicating a decrease of the polyion linear charge density [186]. The 1H chemical shift of the heparin Na+ salt is similar to that of the Mg2+ salt, but different from those of the Ca2+, Zn2+, and Ln3+ salts. A study based on the 23Na T1 relaxation times of heparin sodium salt with multivalent cations such as Mg2+, Ca2+, Zn2+, and Ln3+ considered the influence of the second cation, either competing in territorial binding or sequestering charges by site binding [190]. The main conclusion of this study was that Na+ and Mg2+ ions are bound territorially, while Ca2+, Zn2+ and Ln3+ are, at least partly, site-bound counterions. Site-specific binding may result in conformational changes, and could explain the range of chemical shift variation. Conformational changes of the internal IdoA residues have been found upon complexation with Ca2+. Since a precise analysis of the binding sites is obscured by the polymeric nature of heparin, studies on smaller heparin fragments have helped to define the cation binding sites. Zn2+ chelation was studied using the heparin disaccharide, a-IdoA-2-S-(1 ? 4)-aGlcNS. A shift was observed in conformational equilibrium of the IdoA residue, together with a decrease in glycosidic linkage flexibility [193, 194]. A binding model was proposed where the carboxylate and the iduronate ring oxygens act as binding sites [193–195]. Similar work on hyaluran disaccharide found small chemical shift changes inconsistent with a simple electrostatic interaction [196]. NMR studies on a synthetic hexasaccharide model of heparin have allowed the observation of individual signals for each residue during Ca2+ titration [197]. Thus, the chemical shift variations corresponding to the protons located in different residues could be detected. The protons in internal residues showed the largest variations. A complex titration profile was also observed, with several equivalence points suggesting specific binding. Further data analyses, together with molecular mechanics and electrostatic potential surface studies, led to the proposal of more complex specific binding sites than suggested previously. These sites are formed by a three-dimensional arrangement of all negatively charged groups in

215

216


Proposed heparin Ca2+ binding site showing the calcium-coordinating atom short distances. A water molecule in apical position would complete a square-bipyramidal coordination sphere. Details taken from the minimized Ca-heparin hexasaccharide complex. Fig. 8.7

the network. Interestingly, one type of these sites is able, along with an additional water molecule, to fulfill calcium cation coordination. Calcium interacts with the glucosamine 2-sulfamido groups, the previous iduronate 2-sulfate, and the carboxylate groups, together with the iduronic ring and the glycosidic oxygen. This square bipyramidal geometry (Fig. 8.7) is often found in calcium-binding proteins, and the participation of an apical water molecule and a nitrogen based ligand is especially frequent. This site is also the one most frequently approached by calcium cations during molecular dynamics simulations, and holds the largest negative surface potential. Therefore, this region has been proposed as the main calcium-binding site in heparin [197]. 8.4.2

Interactions with Proteins

Sulfated saccharides bind to a number of proteins, leading to a variety of biological functions [1–14]. Considerable efforts have been made to understand the molecular details of these biological activities, and it has now been established that negatively charged sulfate groups play a crucial role in weak intermolecular interactions with proteins [3, 6, 10, 14, 23]. The affinity depends significantly on the presence of O- or N-sulfates and on their position within the carbohydrate chain. There is unambiguous evidence that the presence of certain sulfate groups is essential to maintain the biological activity of these carbohydrate derivatives [1, 6, 10, 14]. However, the interaction process is more than a mere neutralization of charged groups. In addition to the ionic interactions, non-ionic forces are often non-negligible. In fact, the effect of hydrogen bonding, water molecules, or hydrophobic interactions can play an important role. Most of the Gibbs free energy (DG) originates from the entropy changes due to the favorable release of bound Na+ or K+ counterions from the ion atmosphere (“polyelectrolyte effect”) [23, 198– 200]. However, there are several examples where the non-ionic contributions to DG can overwhelm the polyelectrolyte effect [201] or be an important part of the DG changes [202, 203].


All NMR parameters can be used to analyze the 3D structure of protein-carbohydrate complexes [15–18, 26, 115, 204–213], though the most commonly used are transferred NOEs [115, 206–213], interpreted with molecular modeling (see Chapter 12) [214–216]. Probably the most studied interaction between sulfated saccharides and proteins is that between heparin and antithrombin III (AT). In fact, heparin has been used for more than 60 years as an anticoagulant, though the structural details of the interaction were revealed only recently. It has now been established that about one third of heparin molecules have a specific pentasaccharide sequence that binds specifically to AT [217–219]. Modeling [216, 220–223] and biochemical studies [224–233] have enabled the characterizing of the binding site [220, 222, 229, 233–236] and the structure of a few oligosaccharides in the bound state [115, 234, 235, 237]. The first NMR study analyzing the effect of AT on the structure of the oligosaccharide was carried out on the synthetic tetrasaccharide 5 [GlcN, 6-S-a(1 ? 4)GlcA-a(1 ? 4)-GlcN,3, 6-S-a(1 ? 4)-IdoA-aOMe], comprising four of the five residues of the active heparin-pentasaccharide [115]. The 3D structure of tetrasaccharide was analyzed in the free state and in the presence of AT. The 1H and 13C chemical shifts, 3JH-H, 1JC-H, as well as transferred NOEs, were monitored as a function of the protein:ligand molar ratio and temperature. Significant changes, due to the presence of protein, were detected in both 1H and 13C chemical shifts. The most pronounced effects were seen for protons H-1, H-2, H-6 and H-6' in the GlcN, 6-S residue and H-1, H-2, H-4 and H-4 in the GlcN,3, 6-S residue (Fig. 8.8). An analysis of the coupling constants indicated that the 1C4 conformer, which is more populated in the free state (1C4 : 2S0 * 75 : 25), is stabilized in the presence of protein. Transferred NOE data, as well as other NMR parameters, suggested changes at the glycosidic linkage between the GlcN, 6-S and the GlcA residues (the change in dihedral angles }1, u1) during the binding process (Fig. 8.9) [115]. The data demonstrated the role of electrostatic effects (due to the interaction of negatively charged sulfates and carboxylates and positively charged amino acid residues) on the structure of the tetrasaccharide. A similar methodology was also used in analyzing the 3D structure of heparinpentasaccharide 7, which represents the binding site of heparin for AT, [GlcN, 6S-a-(1 ? 4)-GlcA-b(1 ? 4)-GlcN,3, 6-S-a(1 ? 4)-IdoA 2-S-a(1 ? 4)-GlcN, 6-S-aOMe] in the complex with the protein [237]. The transferred NOEs were interpreted with full relaxation and conformational exchange matrix analysis using the optimized geometry of heparin-pentasaccharide and 8 amino acids in the binding site (Arg 13, Arg 46, Arg 47, Arg 129, Lys 11, Lys 114, Lys 125 and Asn 45). The comparison of the 3D structures of the pentasaccharide in the free state [}1, u1 (–34 8, –27 8), }2, u2 (47 8, 6 8), }3, u3 (–35 8, –42 8) }4, u4 (43 8, 6 8) ] [133] and in the complex [}1, u1 (–56 8, –60 8), }2, u2 (40 8, 12 8), }3, u3 (–32 8, –43 8) }4, u4 (45 8, 16 8) ] [237] revealed that binding is accompanied by changes at the GlcN, 6-S-a(1 ? 4)GlcA-b linkage and the IdoA 2-S-a(1 ? 4)-GlcN, 6-S linkage. In any case, the changes seem less pronounced than that found for tetrasaccharide 5. The conformations at the glycosidic linkages [}1, u1 (–31 8, –35 8), }2, u2 (41 8, 1 8), }3, u3 (–71 8, –33 8) }4, u4 (44 8, 16 8) ] of a heparin-pentasaccharide analog (bearing extra sulfate

217

218


c a

b Selected regions from 500 MHz 1H NMR spectra of the synthetic tetrasaccharide 5 (GlcN, 6-S-a(1 ? 4)-GlcA-b(1 ? 4)-GlcN,3, 6S-a(1 ? 4)-IdoA-aOMe) in aqueous solution Fig. 8.8

d (A) and in the presence of antithrombin (AT) with two different molar ratios (5: AT) 20 : 1 (B) and 10 : 1 (C) (reprinted from Ref. [115], with the permission of Blackwell Science).

group and methyl groups) obtained in a recent crystal study [235] were found to be comparable, in three out of the four glycosidic linkages, with that of pentasaccharide 7 in the free state [133]. Moreover, the comparison of the bound state NMR conformation of 7 [237] with that of the pentasaccharide analog (X-ray) [235] showed that the geometry of the sugars differs only slightly. This difference might reflect a possible influence of the substituents on the 3D structure of heparin-oligosaccharides in the complex with AT. Furthermore, an analysis of the magnitudes of experimental (H-2)–(H-5) NOEs in the IdoA 2-S residue in 7 showed that this residue adopts the 2S0 conformation in the complex with AT [237]. As the 2-O-sulfate group is not directly involved in the binding process, it appears as a driving force that helps stabilize the 2S0 form of the IdoA 2-S residue in the complex. Such a stereochemical arrangement enables the strong electrostatic interaction between the carboxylate group and the Arg 47 and Lys 114 [235, 237]. Furthermore, the 2S0 form affects


Fig. 8.9 Structure of the synthetic tetrasaccharide 5 (GlcN, 6-Sa(1 ? 4)-GlcA-b(1 ? 4)-GlcN,3, 6-S-a(1 ? 4)-IdoA-aOMe) (AGA*I) in the free state with the following values of the dihedral angles at the glycosidic linkages: }1, u1 (–45 8, –30 8), }2, u2 (42 8, 18 8), }3, u3 (–27 8, –48 8) (A) and in the complex with antithrombin: }1, u1 (39 8, 12 8), }2, u2 (43 8, 14 8), }3, u3 (–27 8, –48 8) (B). (Reprinted from Ref. [115], with the permission of Blackwell Science).

the 3D structure of the reducing end of 7, enhancing interactions among the N-sulfate group of the GlcN,6-S and Arg 46, Arg 47 and Lys 114 (Fig. 8.10). These strong electrostatic interactions are reduced considerably (that with Arg 46 is entirely cancelled) when the 1C4 conformation is adopted, because of the inappropriate stereochemistry of the IdoA2-S-GlcN,6-S OMe part. It thus appears that the skew form of the IdoA 2-S residue plays a crucial role in achieving the complementary 3D structure of heparin-pentasaccharide at the AT binding site [237]. The important biological activity associated with fibroblast growth factors (FGFs) has stimulated the interest in analyzing their interaction with sulfated saccharides [238–240]. Crystallographic studies have enabled a description of the 3D structure of several FGF-saccharide complexes [203, 241, 242]. However, the minimum length of heparin- binding oligosaccharides needed to promote FGF assem-

219

220


bling and enhance binding to tyrosine kinase receptors (FGRFs) is still an open question. A very recent study has shown that even short chains of heparin-derived oligosaccharides may induce dimerization of acidic FGF, provided they meet structural requirements [243]. An 1H NMR study of human acidic FGF (FGF-1) complexed with inositol hexasulfate [244] showed that the 3D structure of the protein is similar to that obtained by crystallographic analysis [245]. The calculated NMR structure indicates that inositol hexasulfate binds to the same residues as sucrose octasulfate [121] except for the interactions with Gln 141, which is substituted by Lys 112. Furthermore, the similarities in the above complexes indicate that the stereospecific requirements for binding sulfated saccharides are not very strict. The receptor region appears to be relatively flexible and able to bind different ligands, supporting the assumption of “induced fit” type interactions. Further analyses have shown that the presence of sulfated saccharides results in a decreased flexibility of the binding site, thus enhancing the stabilization of the protein 3D structure [243, 244]. The complex between a heparin-derived hexasacchar-

Fig. 8.10 Structure of synthetic pentasaccharide 7 (GlcN, 6-S-a-(1 ? 4)-GlcA-b(1 ? 4)GlcN,3, 6-S-a(1 ? 4)-IdoA 2-S-a(1 ? 4)-GlcN, 6-S-aOMe) (AGA*IA) in the complex with an-

tithrombin with following values of the dihedral angles at the glycosidic linkages: }1, u1 (–56 8, –60 8), }2, u2 (40 8, 12 8), }3, u3 (–32 8, –43 8) }4, u4 (45 8, 16 8).


ide and FGF-1 was recently examined by multidimensional NMR methods [246]. The FGF-1 binding site, identified from the chemical shift differences observed for the free and bound state in the HSQC spectra, is located on the flexible region between residues 17–21 and 110–131. It also appears that the binding site is similar to that of basic FGF (FGF-2), and therefore it has been suggested that both FGF-1 and FGF-2 recognize heparin-derived hexasaccharide in a similar manner. 2D double INEPT and HSQC methods were used to analyze the structure and dynamics of FGF-2 in the free state and in the presence of a heparin-tetrasaccharide and heparin-dodecasaccharide [247]. Both sulfated oligosaccharides caused a significant line broadening of the FGF-2 resonances. The line widths of the protein detected in the complex with the longer oligosaccharide were considerably broader than those in the presence of the tetramer. The 15N relaxation data collected for the FGF-2-tetrasaccharide complex showed a large influence of the ligand on the dynamics of the protein. Major changes in the T1 relaxation times were observed for residues 30–152. In addition, there was an increase (values higher than 0.9) in the generalized order parameters throughout the whole molecule, indicating that the tetrasaccharide increases the overall correlation time of the complex. This observation is compatible with the assumption that this oligosaccharide induces the formation of a dimer of two FGF-2 molecules. On the other hand, since the dodecasaccharide had a much greater effect on the dynamics of the protein, it was concluded that a higher order oligomer was formed. It was assumed that the dimer is trans oriented in the presence of the tetrasaccharide, whereas two cis oriented dimers, forming a symmetric tetramer, are assembled in the presence of the dodecasaccharide [247]. In recent years, considerable effort has been made to analyze the structure of complexes among various proteins and sulfated saccharides. Chemical shift variations, observed predominantly in 2D 1H-15N HSQC spectra, have been used to determine the binding regions in platelet factor-4 and growth-related protein-a [248, 249], heparin-binding growth-associated molecule [250], midkine [251], native vitronectin [252], human immunodeficiency protein model [253] and cobra cardiotoxin [254]. In all cases, the interaction of heparin or heparin-derived oligosaccharides had little effect on the tertiary structure of the proteins [248, 249, 252]. Chemical shift variations of hepatocyte growth factor (HGF) resonances, measured in HSQC spectra without and in the presence of sulfated saccharides, have been used to identify the binding region [255]. The largest variations of 1H and 15 N resonances were found in the residues 60–80 that consist of b-2 strand, a-helix and a loop. Experiments with sucrose octasulfate indicate that this sulfated saccharide binds at nearly the same place in HGF as heparin. 15N relaxation data indicate dramatically reduced flexibility of the primary binding site in the N domain due to ligand binding. A more straightforward method to study the aggregation state of the complex is to calculate the apparent size by diffusion coefficients obtained by the pulse field gradient NMR approach. In fact, the dissociation of platelet factor-4 dimers, caused by heparin binding, was determined by this technique [249].

221

222


The above data clearly show that current NMR experiments, together with molecular modeling methods, may enable a detailed analysis of the 3D structure of complexes between sulfated saccharides and proteins in solution. Furthermore, and in contrast with X-ray spectroscopy, NMR relaxation data allow the characterization of the changes in dynamics in both proteins and carbohydrates during the binding process, thus yielding unique information. Such data will unquestionably contribute to our understanding of the mechanism of action of sulfated carbohydrates in living systems.

8.5

References 1

2 3 4 5 6

7 8

9 10 11

12 13 14 15

L. Rodén in: The Biochemistry of Glycoproteins and Proteoglycans. W. J. Lennarz (Ed.), Plenum Publishing, 1980, 491–517. U. Lindahl, M. Höök, Annu. Rev. Biochem. 1978, 47, 385–417. B. Casu, Adv. Carbohydr. Chem. Biochem. 1985, 43, 51–134. M. Höök, L. Kjellen, S. Johansson, Annu. Rev. Biochem. 1984, 53, 847–869. J. T. Gallagher, M. Lyon, W. P. Steward, Biochem. J. 1986, 236, 313–325. D. A. Lane, U. Lindahl (Eds.): Heparin. Chemical and Biological Properties. Clinical Applications. Arnold, London, 1989. T. Toida, H. Toyoda, T. Imanari, Anal. Sci. 1993, 9, 53–58. V. C. Hascall, R. J. Midura, J. M. Sorrell, A. H. Plaas, Adv. Exp. Med. Biol. 1995, 376, 205–216. R. J. Linhardt, R. E. Hileman, Gen. Pharmacol. 1995, 26, 443–451. H. E. Conrad, Heparin-Binding Proteins. Academic Press, San Diego 1998. M. Bernfield, M. Götte, P. W. Park, O. Reizes, M. L. Fitzgerald, J. Lincecum, M. Zako, Annu. Rev. Biochem. 1999, 68, 729–777. B. Mulloy, M. J. Forster, Glycobiology 2000, 10, 1147–1156. R. Sasisekharan, G. Venkataraman, Curr. Opin. Chem. Biol. 2000, 4, 626–631. B. Casu, U. Lindahl, Adv. Carbohydr. Chem. Biochem. 2001, 57, 159-208. L. E. Lerner, in: NMR Spectroscopy and its Application to Biomedical Research. S. Sarkar (Ed.), Elsevier, 1996, 313–344.

16

17

18 19 20

21

22

23 24 25 26 27

28 29

H. van Halbeek, in: Encyclopedia NMR, D. M. Grant, R. K. Harris (Eds.) 1996, J. Wiley, New York, 1107–1137. A. S. Serianni, in: Glycoconjugates, H. J. Allen, E. C. Kisailus (Eds.), M. Dekker, New York, 1992, 71–102. E. F. Hounsell, Adv. Carbohydr. Chem. Biochem. 1994, 50, 311–350. G. Torri, Semin. Thromb. Hemost. 1991, 17, 23–28. C. A. A. van Boeckel, M. Petitou, Angew. Chem. Int. Ed. Engl. 1993, 32, 1671– 1718. B. Casu, A. Naggi, G. Torri, in: Glycoscience- Chemistry and Chemical Biology, J. Thiem (Ed.), Springer Verlag, 2000, 1895–1904. F. A. Ofosu, I. Danishefsky, J. Hirsh (Eds.): Heparin and Related Polysaccharides. New York Acad. Sci., New York, 1989. L. B. Jacques, Semin. Thromb. Hemost. 1991, 17, 1–4. H. Engelberg, Semin. Thromb. Hemost. 1991, 17, 5–8. B. Casu, Semin. Thromb. Hemost. 1991, 17, 9–14. B. Mulloy, M. J. Forster, C. Jones, D. B. Davies, Biochem J. 1993, 293, 849–858. L. Cipolla, F. Nicotra, L. Lay, U. Lindahl, L. Panza, G. Russo, Glycoconjugate J. 1996, 13, 995–1003. H. P. Wessel, S. Bartsch, Carbohydr. Res. 1995, 274, 1–9. K. Bock, Annu. Rep. NMR Spectr. 1984, 13, 1–57.

8.5 References 30

31 32

33

34

35

36

37 38

39

40

41

42 43

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9

Residual Dipolar Couplings: Structure and Dynamics of Glycolipids James H. Prestegard and J. Glushka

9.1

Introduction

The importance of complex carbohydrates as mediators of the interaction of a cell with its environment is well recognized. Less recognized is that the majority of these interactions occur at a membrane surface, and that this surface can have profound effects on the structure and dynamics of the carbohydrates involved. This presents special challenges for the methods we usually use for characterization of the structural and dynamic properties of these molecules, but it also presents special opportunities for application of new methods that have come on the scene in the last ten years. Of primary concern in this chapter are the measurement and analysis of residual dipolar couplings [1, 2]. These couplings provide restraints that depend on orientation rather than distance. The normal to the membrane bilayer naturally presents an oriented frame of reference, and glycolipids, as integral components of many biomembranes, represent a class of molecules where application of these methods might be particularly productive. It is believed that the roles of mammalian glycosphingolipids in antigenicity, adhesion, and signal transduction are related not only to their particular structures, but also to their abilities to cluster into microdomains and form multi-valent structures [3–5]. The relation between individual conformational states, amplitudes and frequencies of motion, and macroscopic aggregation is central to understanding the functions of these molecules in a membrane environment. In this chapter we will attempt to summarize the current state of knowledge about glycolipid structure and dynamics, describe the principles that underlie the contributions residual dipolar couplings can make, outline some of the special challenges associated with application to membrane anchored molecules, and suggest some prospects for the future.

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9 Residual Dipolar Couplings: Structure and Dynamics of Glycolipids

9.2

Glycolipid Structure in Solution

Representative primary structures of some common gangliosides are schematically shown in Fig. 9.1. The degrees of freedom are illustrated as rotations around the glycosidic bonds (}, w angles) for each sugar residue, and around the additional bonds of the ceramide (b1 angle for example). The whole glycolipid can also rotate around the long axis of the ceramide, as well as translate through the lipid bilayer. Our knowledge of the structural and dynamic properties of the carbohydrate moieties found in glycolipids comes mostly from solution NMR studies of released oligosaccharides in deuterated aqueous buffers or intact monomeric glycolipids in organic solvents such as DMSO [6–9]. The general picture that emerges is one in which the individual glycosidic linkages predominantly occupy conformational states predicted by minima in simple energy maps. When energies are close to one another, structures exchange between multiple conformers leading to significant flexibility. This flexibility is often reduced around sterically crowded, multiply substituted, residues. For example, the branched core trisaccharide b-GalNAc[Neu5Ac(2-3)]-(1-4)-b-Gal in GM1 in DMSO is relatively well defined, while the terminal residues can adopt multiple conformations [6]. The flexibility of the Neu5Ac(2-3)Gal linkage decreases when the Gal is substituted at O4 [10].

The primary structure of GM3 and some other common gangliosides, with the ceramide moiety anchored in a lipid bilayer (dotted lines). Related structures are, for ex-

Fig. 9.1

ample, the globosides, which are characterized by lack of Neu5NAc residues and the presence of a-Gal linkages; for example, Gb3 is Gala(1-4)Galb(1-4)Glc-Ceramide.

9.3 Glycolipid Structure in a Membrane Environment

9.3

Glycolipid Structure in a Membrane Environment

There are relatively few examples of structural or dynamic properties of glycolipids having been studied in a native membrane environment. There are good reasons for this. Membrane assemblies are usually large particles with long effective correlation times. In high-resolution NMR, this means broad lines with a concomitant loss of resolution and ability to measure spectral parameters such as nuclear Overhauser effects (NOEs) and vicinal homo- or heteronuclear scalar couplings. Gangliosides can form micelles spontaneously in aqueous buffer, but they are typically of large molecular weight (> 300 kDa) and large hydrodynamic radius [7]. Modifying the lipid portion or mixing with dodecylphosphocholine promotes the formation of smaller spherical micelles (12–16 kDa), providing a phospholipid surface environment suitable for high-resolution work [7]. There are some NOEbased NMR studies of these micellar aggregates which show in general that the conformations of oligosaccharide head groups do not deviate much from those found for solvated monomers [11–13]. Even in the case of a highly carbohydrateenriched micelle made from a modified GM1, the relative orientations and flexibility of the terminal residues were retained, and no effects of neighboring carbohydrates could be detected by the NOE and hydrogen exchange methods used [14]. The anchoring of glycolipids to large micelles can be used to advantage in studying internal motions. For example, a study of GD1a by Poppe et al. [13] exploited the slow tumbling of a micelle to differentiate internal conformational fluctuations of the head group from overall molecular motions. 31P relaxation measurements and natural abundance 13C T1, T1r and NOE data gave overall correlation times of the micelle as 5.1 nanoseconds (ns) and a single correlation time of 2.8 ns for the core GalNAcb(1-4)[Neu5NAc(2-3)]Galb(1-4)Glc tetrasaccharide, the difference suggesting additional rotational or translational motion of the ganglioside within the micelle. The terminal Neu5NAc' (2-6)Gal' fragment, however, was best described by two correlation times, *2.8 and 0.34 ns, because of fast internal motions of these residues. These data agree with the conclusion that there are two allowed conformations consistent with the observed NOEs: an extended structure and an “L-shaped” structure where the terminal residues are more parallel to the membrane surface. Previous X-ray results and molecular mechanics calculations have also shown the existence of both structures [15]. One should point out that in this study, and in a few other more complete descriptions of conformations, the detection of NOEs from hydroxyl protons was critical to the analysis. These protons are normally difficult to observe, except under special conditions such as aprotic solvents [9], low temperature [16], or near micelle surfaces [13, 14].

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9.4

Larger Membrane Assemblies

Larger lipid aggregates are expected to mimic the membrane surface more closely, but the use of standard high-resolution techniques becomes more difficult. The loss of information from scalar couplings and NOEs due to poorly resolved, broad resonances can be a severe problem, and other relaxation or anisotropic phenomena must be considered. Wideline 2H NMR spectroscopy has been successfully used to probe orientation and motions of glycolipids, although it generally requires incorporation of deuterons at several specific locations (see, for example, [17–19]). The possibility of adding information from residual dipolar couplings can be a salvation in these cases. A notable example where this added information has led to specific conclusions about the influence of the membrane environment on head group conformation involves glycolipid mimics produced by adding alkyl chains to a simple sugar [20]. Here the experimentally determined conformation does not agree with predominant population of the global energy minimum as calculated for fully solvated models. The addition of a membrane potential to the force field did, however, produce agreement with experiment. These initial studies were extended to a small set of natural glycolipids including monogalactosyldiacylglycerol, sulfoquinovosyldiacylglycerol, and digalactosyldiacylglycerol [21–23]. In the case of the monoglycosyl lipids the same pattern of an altered conformational preference emerged. In the case of the diglycosyl lipid, the conformational preference of the terminal sugar was not perturbed. This suggests that effects are likely to occur mostly at the sugar juxtaposed to the membrane, and that these effects tend to extend the sugars well away from the surface. It is significant that the above studies used residual dipolar couplings, along with other NMR based data, to reach these conclusions. It suggests that we should look in much more detail at the how this form of NMR data can overcome the limits of relaxation-based measurements, such those that arise from difficulties in observing sufficient NOE constraints and the difficulties in differentiating overall and internal motions from 13C spin-lattice or spin-spin relaxation rates.

9.5

Theory of Residual Dipolar Couplings

Solution NMR spectroscopists are most familiar with the dipole-dipole interaction as a contribution to spin relaxation phenomena and the origin of the distance constraints that come from NOE measurements. As outlined below, and also as discussed in some detail in Chapter 2 of this book, the dipole-dipole interaction actually contains both distance- and angle-dependent terms; both can be a source of structural constraints. This can be seen in Eq. (1) written for the interaction in frequency units for a pair of spin 1/2 nuclei (i, j) of magnetogyric ratios, ci, cj, separated by distance rij along a vector at angle h relative to the magnetic field.

9.5 Theory of Residual Dipolar Couplings

Dres ij

* + l c c h P cos ht i j 2 0 4p 2p2 rij3

1

In the NOE, the angle-dependent part is responsible for modulation of the interaction as a molecule tumbles in solution, but normally it makes no direct contribution to measurable energy differences between spin states because the angular term averages to zero in isotropic solutions. When the angular term does not average to zero, the interaction between a pair of distinguishable spin 1/2 nuclei leads to a splitting of each resonance of magnitude Dres ij . This appears much like a scalar coupling, and in fact simply adds to the scalar coupling contribution to splitting when both contributions are present. In the case of nuclei connected by welldefined bond geometry (two-bond 1H-1H, one-bond 1H-13C, etc), the internuclear distances are known, and the residual dipolar contribution to splitting becomes a simple function of internuclear vector orientation and a rich source of structural data. Conditions that avoid complete averaging of the angular part require the restoration of some level of directional order to molecules as they tumble in solution. Glycolipids are naturally ordered with respect to the bilayer when they insert into lipid membranes, and dispersions of lipid bilayers, in turn, orient when placed in magnetic fields at sufficient densities to form cooperative liquid crystals [24]. Restoring order magnetically depends on the anisotropy of the susceptibility of the assembly; for diamagnetic molecules like lipids, the orientation with the smallest induced opposing magnetic moment has the lowest energy and is preferred. This results in bilayer normals of simple, undoped, lipid bilayer disks being perpendicular to the field. It is also possible to manipulate the anisotropy by adding paramagnetic ions or other molecules with highly anisotropic susceptibilities [25]. Lipid bilayers have also been oriented mechanically by deposition on stacks of glass plates [26, 27]. Use of liquid crystal media for inducing order of dissolved organic molecules has a lot of precedence in the early literature [28]. However, there has also been a recent revival of interest in applications to water-soluble molecules such as proteins, carbohydrates and nucleic acids, because of media composed of disk-like lipid bilayer fragments called bicelles [2, 24, 29, 30]. A distinguishing feature of these latter studies is that they rely on the induction of a very small level of order. This will not be the case for molecules such as intact glycolipids that insert into the bilayers, and special problems in analysis will arise. We will discuss solutions to these problems later, but first we will review in general the treatment of dipolar data. The introduction of small and even moderate levels of order, as opposed to perfect order, has its own inherent analysis complications; in addition to the orientation variables that relate directly to internal structure, the level and anisotropy of order for the entire system of interest have to be treated as variables. The additional variables are conveniently included by rewriting Eq. (1) as follows:

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Dres ij

l c c h X i j 0 Skl cos ak cos al 4p 2p2 rij3 kl

2

Here the angular term has been expressed in terms of nine elements of an order tensor (Sij) and direction cosines relating the internuclear vector to the frame chosen for the system [cos (ak)] [2]. Despite the apparent complexity of the equation, it has only five independent parameters; the direction cosines are dictated by molecular geometry and the order tensor itself is symmetric and traceless. The five independent order tensor elements can alternatively be described in terms of three Euler angles relating the orientation of a molecular fragment to a principle alignment frame and principal and rhombic alignment parameters [30] or in terms of five second-order spherical harmonics. If a sufficient number of independent measurements of dipolar couplings can be made within a semi-rigid fragment, the five parameters can be calculated directly and the three derived Euler angles used to orient fragments into a complete structure. The remaining two variables, which give information on the level and asymmetry of order, give not only information on overall molecular order, but internal order as well. The several connected sugar rings in typical glycolipid head groups are capable of yielding independent order tensor solutions. If the structure is rigid, the overall order and asymmetry parameters will be identical for each ring, but if not, these measures of order will differ. In principle it is possible to convert these differences to measures of internal motion if there are sufficient data to simultaneously determine a reference frame for overall motion [31–33]. Determination of a reference frame can be simplified for glycolipids where the ring closest to the membrane can be assumed to be the most strongly ordered. For example, in one approach, the averaged spherical second-order harmonics are used as variables, and internal contributions to disorder are assigned to oscillations in square wells about a preferred set of } and w angles for each glycosidic bond [20]. The first ring defines the overall order tensor, and, except for 1,6 linkages, each new ring adds four variables to be determined: }, w and the widths of the two wells. There are a number of approaches to extracting the desired angular constraints from a set of dipolar structures. Equation (2) for a set of dipolar couplings can be written in vector/matrix form as follows: 32 3 3 2 cos aij x cos aij x; cos aij x cos aij y; ; ; Sxx Dij 6 Dkl 7 6 cos akl x cos akl x; cos akl x cos akl y; ; ; 76 Sxy 7 76 7 6 7 6 76 Sxz 7 6 7 6 76 7 6 7 6 54 Syz 5 4 5 4 Szz 2

3

This equation can be solved by singular value decomposition [34], as well as by a number of other methods [2, 35]. It is also possible to incorporate experimental couplings in error functions, an approach that is useful when fewer than the five measurements required for a direct solution are available [36].

9.6 Data Collection and Structure of Oligosaccharides from Residual Dipolar Couplings

9.6

Data Collection and Structure of Oligosaccharides from Residual Dipolar Couplings

Although the study of highly oriented, membrane-anchored glycolipids is our ultimate goal, it is useful to first examine some applications of residual dipolar couplings to soluble oligosaccharides. These applications are extremely important for improving our understanding of head group conformation and dynamics, as well as developing experimental and analytical methods. There are now several examples that fall into this class [32, 37–41]. We will discuss a few here; the reader is also referred to Chapter 2 for more discussion. In the glycolipid area, Kiddle and Homans [42] incorporated the dipolar couplings from the Gal residue on a 13C-enriched Neu5NAc-(2-3)-Galb(1-4)Glc trisaccharide derived from the ganglioside GM3, as additional restraints in a simulated annealing calculation. By assuming that the principle axis of symmetry (PAS) of the alignment tensor was along the C7-H7 bond, because of its large negative coupling value, a solution structure was found consistent with previous studies using short range NOEs and heteronuclear coupling constants. Another study by this group [43] localized the binding site of the oligosaccharide portion of the globoside Gb3 onto the B-subunit of the homopentamer of verotoxin 1 with the aid of dipolar coupling data. They measured couplings of the 13C-enriched ligand at increasing protein concentrations, and could then extrapolate to the fully bound state. The alignment tensor frame for the ligand was determined by order matrix analysis, and the PAS of the protein from its axial symmetry [44]. As outlined in the chapter by Martin-Pastor and Bush, these studies on oligosaccharides have shown that many of the methods used to measure scalar couplings can be used or modified for the measurement of dipolar couplings. One must emphasize, as is done in many of the above reports, that multiple couplings per glycosyl residue must be measured to obtain a sufficient number of independent vectors. This typically requires both one-bond and two-bond 1H-13C couplings as well as 1H-1H couplings. Nonetheless, part of the appeal of residual dipolar coupling measurements is the efficiency and simplicity of acquisition. For example, measurement of 13C-1H dipolar couplings of directly bonded pairs in a sugar ring can be based on simple modifications of a constant-time HSQC experiment, such as removing the 180 pulse used for refocusing proton scalar coupling, or introducing a pure (J + D) evolution for part of the indirect evolution period [45]. A spectrum resulting from the latter procedure is illustrated in Fig. 9.2 for the trimannoside core found in all N-linked glycosides, aligned in a bicelle system. These data were taken at natural abundance on a 20 mM sample with an approximately 6 h acquisition. With new cryogenic probes promising to increase sensitivity of NMR spectrometers by a factor of three or four, work with 2 mM samples should be feasible in the future. The dipolar contribution to the splitting is usually extracted by acquiring spectra under both isotropic and oriented conditions, which, in bicelle systems, can be produced by changing the temperature from 25 to 36 8C. The values in the isotropic spectrum are purely scalar coupling (J) (increased by a multiplicative factor resulting from the mode of data acquisition),

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Regions of a constant time, coupling enhanced HSQC spectra of methyl 3,6-di-O(a-mannopyransoyl)-a-mannopyranosyl in dilute bicelle media at 20 (isotropic) and 36 8C

Fig. 9.2

(oriented). The values are a combination of dipolar and scalar couplings scaled by a multiplicative factor. Reproduced from [32].

and the values in the oriented spectrum are a sum of the dipolar and scalar values (J + D). In the example given, the dipolar contributions are relatively small, and it is possible to choose a single evolution time that is optimal for transfer of magnetization from carbon back to protons for observation. As the magnitude of the dipolar contribution increases, as it will for more strongly anchored molecules, choosing a suitable delay for the optimum magnetization transfer will be difficult, and the inherent efficiency of this experiment lost. Fig. 9.3 shows the result of aligning order frames determined for individual rings in the simple trimannoside core of N-glycosides [32]. In this study, the order matrix of each ring was determined by measuring both one- and two-bond 1H-13C couplings as well as 1H-1H couplings reaching an average of ten measurements per ring. Even with this large number of measurements it is important to note that dipolar data are inherently insensitive to axis inversion, resulting in four possible choices for alignment of axes under the best of circumstances [46]. The use of multiple alignment media can lift this degeneracy; in fact, data acquired in both bicelle media and phage media were used in the cited study. For sugar residues connected by short glycosidic bonds, covalent geometry also limits choices of axis systems, as well as restricting translational degrees of freedom.

9.8 Glycolipids Anchored to Membranes The average structure of trimannoside assembled by aligning the order tensor principal axis for each ring (arrows) determined in bicelle media. Adapted from [32].

Fig. 9.3

9.7

Insight into Dynamics

In the above study, only the relationship between rings I and III is well defined. Inconsistencies between structures derived from bicelle data and phage data for the III-II linkage signals the existence of substantial internal motion. As mentioned earlier, comparison of order parameters between structural units in a molecule can provide insight into dynamics. With sufficient data, both axes and amplitudes of motion can be estimated, and motions over a broad range of timescales (pico-seconds to milli-seconds) can be detected. Many reports on dipolar couplings of oligosaccharides have highlighted the detection and characterization of internal flexibility [32, 39, 40, 47]. In the study on the trimannoside core, even the I-II linkage appears to execute significant motion. Order parameters indicate motions about an axis pointing nearly across the glycosidic bond of +/– 25 8. Larger-amplitude motion might be expected from an a-(1-6) linkage, explaining why ring II cannot be aligned so easily.

9.8

Glycolipids Anchored to Membranes

A relatively small amount of work using residual dipolar couplings has been done on intact glycolipids. At first this seems contrary to expectations, since anchoring a carbohydrate head group to an ordered array of lipid bilayers through a lipid moiety should result in higher levels of order and larger, more easily measured dipolar couplings. Measurements prove possible, but large line-widths and the complexity of multiplets make this very difficult. Before discussing specific examples,

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it is important to understand the origin of some of these difficulties. In part, they are due to strong dipolar coupling among the many protons in a typical molecule of interest. These couplings rise from the few Hz expected in weakly aligned samples to thousands of Hz, and become comparable to the separation of proton resonances due to chemical shift differences. Thus, the effects are similar to second order effects in high-resolution spectra in normal solutions. Here, application of radio-frequency pulses no longer results in simple single spin transitions, and precession of magnetization in a static field no longer occurs at frequencies that are simple functions of isolated chemical shift values and scalar couplings. Spectra become very complex, and the well-defined magnetization transfers we rely on to indirectly detect less sensitive nuclei in HSQC spectra no longer occur with normal efficiencies. The effects of strong dipolar coupling are actually not identical to those in highresolution spectra. The full scalar coupling Hamiltonian contains IxIx and IyIy operators, generating terms such as I+I– and I– I+ that mix simple product spin states. Among the more noticeable effects in scalar coupled high-resolution spectra is the observation of a single resonance, as opposed to degenerate doublets for a coupled pair of spins with identical chemical shift. For example, we see only a single line, unaffected by the proton scalar coupling, for a molecule like H2O. In more general cases of N interacting spin 1/2 nuclei with small chemical shift differences, large numbers of forbidden transitions are observed. In the dipolar coupled case, similar operators are included in the full Hamiltonian, but in different proportions, and with specific dependencies on orientation. A pair of spin 1/2 nuclei with identical chemical shifts does not now give a single resonance; they give degenerate doublets, but not with a splitting equal to the dipolar coupling, D. The magnitude of the coupling is not the one given by the expression in equations 1 and 2, but is a factor of 3/2 larger. In one of the first attempts to measure dipolar couplings of carbohydrates, the chemically identical anomeric protons of trehalose were seen as a doublet when incorporated into an aligned bicelle [48]. More general strong coupling effects were treated in detail by spectroscopists working on liquid crystal NMR many years ago, and the effects have been discussed recently [49]. In heteronuclear spectra, the situation is simpler, but strong coupling is still an issue. In Fig. 9.4 we present a simulated 1D carbon spectra [50] at 500 MHz of an anomeric center, in which we have assumed a 200 Hz C1-H1 coupling (150 Hz scalar and 50 Hz dipolar). The scalar H1-H2 coupling is neglected, but we assume a 1000 Hz proton-proton dipolar coupling. Normally we would expect to see a simple doublet split by 200 Hz in the carbon dimension, as in the bottom trace, but, as the chemical shift difference between H1 and H2 approaches zero, additional couplings are seen. When the lines are broad, it is possible to make errors in measuring peak separation and thus coupling magnitude. This is illustrated for the case of Dv = 1500 Hz. More serious are the additional splittings that might be interpreted as direct 1H-13C dipolar couplings, as illustrated with Dv = 500 Hz; this would add incorrect vectors to a structural or dynamic analysis.

9.9 Glycolipid Structure using

13

C Observation

Simulated 1D carbon spectra of a C-H pair with 150 Hz scalar and 50 Hz dipolar coupling. The proton is further coupled to a second proton with 1000 Hz dipolar coupling only, and the difference in chemical shift between the protons is indicated in Hertz.

Fig. 9.4

9.9

Glycolipid Structure using

13

C Observation

While the complexities illustrated in Fig. 9.4 can cause some analysis difficulties, their effects are far less severe than those that would be seen in proton observation. Moreover, there are experimental techniques that allow reduction of the effects. Therefore, direct observation of 13C and use of 13C-13C or 1H-13C couplings have provided most of the residual dipolar data on membrane-anchored glycolipids. For 13C-13C couplings, the fact that the magnetogyric ratio for 13C is one fourth that of 1H, and the chemical shift dispersion is larger, also pushes homonuclear effects nearer the weak coupling limit. The unfortunate part is that isotope enrichment is usually required for direct 13C observation. Nevertheless, several studies of this type have been conducted using synthetic mimics of glycolipids which incorporate 13C and natural glycolipids from algae grown on 13CO2. The first glycolipid work to use 13C residual dipolar coupling extensively used a simple alkyl glucoside synthesized from 90% 13C-enriched glucose [51]. Some deuterium quadrupolar couplings were used to supplement the data, but primarily 13 13 C- C and 1H-13C data were used. The couplings for directly bonded 13C-1H pairs exceeded 3000 Hz, and those for 13C-13C pairs exceeded 300 Hz. Even with the lower magnetogyric ratio of 13C and the increased chemical shift dispersion there were concerns about strong coupling of protons, and homonuclear decoupling sequences (MREV8) were used to minimize the effects. A variety of modified COSY and double quantum 2D experiments were used to facilitate resolution and measurements of couplings. Because the dipolar couplings are so large, the sign of the couplings could not be simply determined. A systematic alteration in composition of bicelles and reduction in temperature to reduce order in the systems was used to extrapolate back to a pure scalar coupling. If the coupling crossed zero prior to the limit, the dipolar contribution was clearly of opposite sign to the scalar coupling. The data col-

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lected eventually led to the development of methods for modeling the effects of the bicelle membrane on the conformation of the head group [52]. The quest for natural glycolipids to which experiments and theoretical analysis were applicable led to the examination of several partially (26%) 13C-labeled lipids isolated from the membranes of algae grown on 13C-enriched CO2 [21, 23]. In addition to 13C-13C dipolar data taken from COSY experiments, these studies employed chemical shift anisotropy (CSA) offsets. This was possible because of the presence of enriched carbonyl sites in the diacylglycerol backbone of these algae lipids. In general, chemical shifts are determined by shielding tensors, not constants. When groups with large, nearly axially symmetric anisotropies, such as a carbonyl group, adopt preferred orientations, chemical shift offsets show the same (3 cos2 h–1) dependence as dipolar couplings. Shifts as large as 5 ppm were observed and used in the subsequent structural analysis. Spin relaxation data on a digalactosyldiacylglycerol also led to the first comparison of spin relaxation order parameters to order parameters derived from residual dipolar data [22]. In this case the two agreed well, but in general one expects somewhat small order parameters from residual dipolar data, because they reflect all motional averaging, as opposed to the contributions of just faster motions. Clearly there would be interest in the application of similar 13C-based techniques to glycolipids of mammalian origin. The first step in this direction was taken by using a novel biosynthetic method [53] to introduce three 13C sites from pyruvate into sialic acid by condensation with N-acetyl-mannosamine. The combination of 13C-13C, 13C-1H, and CSA offsets from the three labeled sites gave sufficient information for a structural analysis of a simple alkyl sialoside [54]. This labeled sialic acid was subsequently incorporated into the ganglioside, GM3, and a structural analysis of this natural glycolipid was attempted [55]. The multiple glycosidic bonds connecting the terminal sialic acid to the ceramide backbone in this case required considerable reliance on modeling to produce a structure, but the outcome provided one of the first pieces of experimental evidence that the headgroups of these lipids extended well away from a membrane surface, where binding to lectins and other carbohydrate-recognizing molecules could be optimized. Direct observation of glycolipid mimics bound to a lectin was also attempted [56]. Some of the uncertainties introduced by multiple glycosidic bonds were later removed by examining constrained tricyclic analogs produced by lactam formation between the sialic carboxyl group and a 2-amino galactose [57]. This molecule mimics a naturally occurring ganglioside GM4 lactone. This work introduced the use of dipolar couplings between 13C and 15N as well as 15N CSA offsets as additional sources of structural information. It also used ECOSY-style effects to determine relative signs of 15N-C1 and 15N-C2 couplings. In the simple 13C-13C COSY experiment used, the 15N spin coupled to both C1 and C2 of the sialic acid was not perturbed, and only the components of the C1-C2 crosspeak that do not involve a spin state change for 15N were preserved. The positive diagonal character of the cross peaks implies that the two couplings are of the same sign. This sign information is extremely valuable in reducing the ambiguities inherent in deducing an average h from an averaged (3 cos2 h–1 ).

9.11 References

9.10

Other Techniques and Future Trends

There have not been large numbers of additional applications of this methodology to glycolipids since the studies in the mid-1990s, despite the growth of interest in the role of glycolipids in processes such as signal transduction. As outlined above, this is in part because of the need for general or site-specific isotope enrichment. Developments in natural or synthetic isotope labeling of glycolipids are to be expected, if only as a by-product of the search for eucaryote expression systems capable of producing glycoproteins [58, 59]. Enzymatic synthesis of oligosaccharides is an established methodology, and there are suitable transferases and synthases currently being studied [60, 61]. Additionally, the detection of natural abundance 13 C will be easier as probe technology continues to improve. Finding sample conditions that retain properties relevant to membranes, as well as NMR experiments that allow for routine collection and analysis of data, will still require new approaches. One promising development is the use of variable angle spinning [62, 63]. Liquid crystals spun slowly at angles other than the magic angle will redefine the liquid crystal director and scale all interactions by an additional (3 cos2 h'–1), where h' is the angle between the field and the new director axis. This gives a generally applicable means of scaling down the size of residual dipolar couplings. It reduces second order effects, and through its ability to manipulate the size of the dipolar contribution it gives a way of extracting signs of dipolar couplings. Only a few applications exist, but bicelles have now been shown to reorient directors under slow spinning [64], and this has been used to scale and determine signs of couplings in a simple myristoylated glycine [65]. As in other areas of biomolecular NMR spectroscopy, the methods from the traditional solid-state and high-resolution liquid specialities are to some degree converging, as biologically interesting “semi-solid” environments are probed. We can look forward to direct experimental data on the conformation and dynamics of glycolipids at membrane surfaces in the future.

9.11

References A. Bax, G. Kontaxis, N. Tjandra, Dipolar couplings in macromolecular structure determination, in Nuclear Magnetic Resonance of Biological Macromolecules, Pt B, 2001, Methods in Enzymology, 339, 127– 174. 2 J. H. Prestegard, H. M. Al-Hashimi, J. R. Tolman, Q. Rev. Biophys. 2000, 33, 371–424. 3 S. V. Evans, C. R. MacKenzie, J. Mol. Recognit. 1999, 12, 155–168. 1

S. Hakamori, Glycoconjugate J. 2000, 17, 143–151. 5 A. H. Merrill, Y. A. Hannun, (Eds.) Sphingolipid metabolism and cell signaling. Methods in Enzymology. 2000, Vol. 311– 312, Academic Press, San Diego. 6 D. Acquotti, L. Poppe, J. Dabrowski, C.-W. von der Lieth, S. Sonnino, G. Tettamanti, J. Am. Chem. Soc. 1990, 112, 7772–7778. 4

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29 30 31

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C. Glaubitz, G. Grobner, A. Watts, Biophys. J. 1998, 74, A296–A296. J. N. Emsley, J. C. Lindon, NMR Spectroscopy Using Liquid Crystal Solvents. 1995, Oxford, Pergamon Press. M. Ottiger, A. Bax, J. Biomol. NMR 1998, 12, 361–372. N. Tjandra, A. Bax, Science 1997, 278, 1111–1114. J. Meiler, J. J. Prompers, W. Peti, C. Griesinger, R. Bruschweiler, J. Am. Chem. Soc. 2001, 123, 6098–6107. F. Tian, H. M. Al-Hashimi, J. L. Craighead, J. H. Prestegard, J. Am. Chem. Soc. 2001, 123, 485–492. J. R. Tolman, H. M. Al-Hashimi, L. E. Kay, J. H. Prestegard, J. Am. Chem. Soc. 2001, 123, 1416–1424. J. A. Losonczi, M. Andrec, M. W. F. Fischer, J. H. Prestegard, J. Magn. Reson. 1999, 138, 334–342. J. Meiler, N. Blomberg, M. Nilges, C. Griesinger, J. Biomol. NMR 2000, 16, 245–252. N. Tjandra, J. Marquardt, G. M. Clore, J. Magn. Reson. 2000, 142, 393–396. C. Landersjo, C. Hoog, A. Maliniak, G. Widmalm, J. Phys. Chem. B 2000, 104, 5618–5624. K. Lycknert, A. Maliniak, G. Widmalm, J. Phys. Chem. A 2001, 105, 5119–5122. M. Martin-Pastor, C. A. Bush, J. Biomol. NMR 2001, 19, 125–139. H. Neubauer, J. Meiler, W. Peti, C. Griesinger, Helv. Chim. Acta 2001, 84, 243–258. T. Rundlof, L. Eriksson, G. Widmalm, Chem.-Eur. J. 2001, 7, 1750–1758. G. R. Kiddle, S. W. Homans, FEBS Lett. 1998, 436, 128–130. G. S. Thompson, H. Shimizu, S. W. Homans, A. Donohue-Rolfe, Biochemistry 2000, 39, 13 153–13 156. P. J. Bolon, H. M. Al-Hashimi, J. H. Prestegard, J. Mol. Biol. 1999, 293, 107– 115. J. R. Tolman, J. H. Prestegard, J. Magn. Reson. Ser. B 1996, 112, 269–274. H. M. Al-Hashimi, H. Valafar, M. Terrell, E. R. Zartler, M. K. Eidsness, J. H. Prestegard, J. Magn. Reson. 2000, 143, 402–406.

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51 52

53

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A. Almond, J. O. Duus, J. Biomol. NMR 2001, 20, 351–363. P. Ram, L. Mazzola, J. H. Prestegard, J. Am. Chem. Soc. 1989, 111, 3176–3182. N. Suryaprakash, Concepts in Magn. Reson. 1998, 10, 167–192. S. A. Smith, T. O. Levante, B. H. Meier, R. R. Ernst, J. Magn. Reson. Ser. A 1994, 106, 75–105. C. R. Sanders, J. H. Prestegard, J. Am. Chem. Soc. 1991, 113, 1987–1996. P. Ram, E. Kim, D. S. Thomson, K. P. Howard, J. H. Prestegard, Biophys. J. 1992, 63, 1530–1535. E. S. Simon, M. D. Bednarski, G. M. Whitesides, J. Am. Chem. Soc. 1988, 110, 7159–7163. Y. Aubin, J. H. Prestegard, Biochemistry 1993, 32, 3422–3428. Y. Aubin, Y. Ito, J. C. Paulson, J. H. Prestegard, Biochemistry 1993, 32, 13 405– 13 413. B. J. Hare, F. Rise, Y. Aubin, J. H. Prestegard, Biochemistry 1994, 33, 10 137– 10 148. B. A. Salvatore, R. Ghose, J. H. Prestegard, J. Am. Chem. Soc. 1996, 118, 4001–4008.

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J. W. Lustbader, S. Birken, S. Pollak, A. Pound, B. T. Chait, U. A. Mirza, S. Ramnarain, R. E. Canfield, J. M. Brown, J. Biomol. NMR 1996, 7, 295– 304. M. S. B. McAlister, B. Davis, M. Pfuhl, P. C. Driscoll, Protein Eng. 1998, 11, 847–853. G. J. Davies, S. J. Charnock, B. Henrissat, Trends Glycosci. Glycotechnol. 2001, 13, 105–120. K. M. Koeller, C. H. Wong, Nature 2001, 409, 232–240. J. Courtieu, J. P. Bayle, B. M. Fung, Prog. Nucl. Magn. Reson. Spectrosc. 1994, 26, 141–169. P. T. F. Williamson, G. Zandomeneghi, B. Bonev, F. J. Barrantes, A. Watts, B. H. Meier, Biophys. J. 2001, 80, 699. G. Zandomeneghi, M. Tomaselli, J. D. van Beek, B. H. Meier, J. Am. Chem. Soc. 2001, 123, 910–913. F. Tian, J. A. Losonczi, M. W. F. Fischer, J. H. Prestegard, J. Biomol. NMR 1999, 15, 145–150.

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10

Activated Sugars Céline Monteiro and Catherine Hervé du Penhoat

10.1

Introduction

Glycosyl esters of nucleoside pyrophosphates, often referred to as sugar nucleotides, are major metabolites in the syntheses of polysaccharides and glycoconjugates. They undergo many types of enzymatic reactions including transformation of the glycosyl group (epimerization, oxidation, reduction), splitting of the pyrophosphate linkage, and transfer of the glycosyl group to an acceptor [1]. The latter class of reactions, which are mediated by glycosyltransferases, proceed with remarkable selectivity as a unique sugar nucleotide (glycosyl donor or activated sugar) is stereoselectively transferred to a specific position of a given glycan or glycoconjugate (glycosyl acceptor). Because of the efficient yields of these processes, glycosyltransferases are now used in several laboratories for the syntheses of complex carbohydrates [2, 3]. Although the reactions involving sugar nucleotides are among the most abundant processes on Earth, they are still very poorly understood. In vivo, glycosyltransferases operate in the presence of a pool of sugar nucleotides and glycosyl acceptors. Divalent metal cations such as Ca2+, Mg2+ or Mn2+ are often necessary for catalytic activity. The high specificity of the reactions suggests that the recognition steps in the formation of both the sugar nucleotide/glycosyltransferase and glycosyl acceptor/glycosyltransferase complexes are of paramount importance. Current efforts to elucidate the mechanisms underlying these reactions have been based on structural investigations of both the enzymes and the sugar nucleotides. Regarding the enzymes, the amino acid sequences for the glycosyltransferases that process sugar nucleotides have been classified into a number of sequence similarity-based families [4], and computational biology has also been used to reveal the conserved DXD motifs [5–8] that are thought to be involved in catalysis [7, 9–11]. Many of these enzymes are membrane proteins (Mw > 30 kDa) and they are not easily crystallized. However, eight crystal structures of glycosyltransferases (a T-phage bglucosyl transferase [12, 13], bovine b(1 ? 4)galactosyltransferase [14], a putative glycosyltransferase from Bacillus subtilis, SpsA [15], rabbit N-acetylglucosaminyltransferase I [16], human b(1 ? 3)glucuronylltransferase I [17], a(1 ? 4)galactosyltransferase from Neisseria meningitidis [18], and bovine a(1 ? 3)galactosyltransferase [19]) have been reported to date. Glycosyltransferase-mediated reactions are extreme-

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ly rapid, and only a few of these enzymes have been obtained as complexes with intact sugar nucleotides [16, 19]. Recent endeavors to unravel the reaction mechanisms using crystal structures are based on the crystallization of complexes containing both donor and acceptor sugar analogs [18]. As concerns the substrate, pioneering work has involved monitoring the effect of chemical modification of the sugar nucleotide functional groups on enzymatic activity (see Fig. 10.1 a). These results have been summarized in a major review by Kochetkov and co-workers [1] in which three types of binding sites were recognized: (i) universally essential sites including the hydroxyl group at C-3'' and the acyl-amido group (CONHCO) of the uracil base, (ii) universally non-essential sites including the double bond of the heterocyclic base and the hydroxyl groups at C2' and C-2'', (iii) specific sites essential for some enzymes and non-essential for others such as the hydroxyl groups at C-4'' and C-6''. The authors postulated the existence of a notable fraction of folded conformations stabilized by three intramolecular hydrogen bonds (O-2···H-O-2', 3-N-H···O-3'', and O-4···H-O-2'', Fig. 10.1 b) to explain the diminished reactivity of certain hydroxyl groups [20]. The existence of folded conformations was also advocated to explain optical rotation data for various sugar nucleotides, including UDP-Glc [21]. The change in optical rotation in going from an aqueous solution of UDP-Glc to an 8 M urea solution of UDP-Glc was interpreted as the reversible dissociation of an ordered to a random conformation. Modeling of nucleotide sugar/metal interactions has been undertaken to afford a basis for understanding the role of the metal ion in nucleotide sugar/metal complexes. The pyrophosphate group has been studied with the ab initio approach [22–26], and force field parameters for both the CHARMM [22] and AMBER [24] molecular mechanics programs have been proposed. Recently, both folded and extended conformations have been revealed by molecular dynamics trajectories in the presence of explicit solvent [27]. Experimental data is crucial for validating the theoretical models of these metabolites interacting with metal ions, and in this context NMR plays a major role. In this chapter, the solution conformations of sugar nucleotides based on NMR spectroscopy have been reviewed. The NMR tools available for determining the conformational preferences of activated sugars are presented in the first section, followed by the results of NMR studies of sugar nucleotides in the presence of mono-, di- and trivalent cations.

10.2

NMR Methods for Conformational Analysis of Sugar Nucleotides 10.2.1

Nomenclature

The atomic numbering and the usual torsion angle labels for UDP-Glc and GDPMan [28] have been indicated in Fig. 10.1 a. Atoms belonging to the nucleotide

10.2 NMR Methods for Conformational Analysis of Sugar Nucleotides

a

Fig. 10.1 (a) Schematic drawing of UDP-Glc and GDP-Man. The protons have been numbered and the torsion angles have been labeled. (b) Folded model proposed by Kochetkov and Shibaev in [1].

b

base, the ribose and the hexose are referred to (i) without additional symbols, (ii) with a single prime ('), and (iii) with a double prime (''), respectively. In keeping with the nomenclature used in the case of nucleoside diphosphates and triphosphates, the phosphorus atoms closest to the ribosyl and glucosyl moieties are referred to as Pa and Pb, respectively. Three different arrangements have been described for the pyrophosphate group, cis-planar eclipsed, staggered and all-trans eclipsed (Fig. 10.2 a). By analogy with the convention adopted for nucleoside pyrophosphates [28], metal chelates of UDP-Glc will be referred to as D-cis, D-trans, K-cis and K-trans (Fig. 10.2 b). The definitions of the dihedral angles are as follows:

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Fig. 10.2 (a) Eclipsed and staggered orientations of the pyrophosphate group. (b) Spatial arrangements of pyrophosphate chelates.


v =H c =H a =H m1 = H U= H

(O-4'-C-1'-N-1-C-2) (O-5'-C-5'-C-4'-C-3') (O-Pa-O-5'-C-5') (O-1''-Pb-O-Pa) (O-5''- C-1''-O-1''-Pb)

d = H (C-5'-C-4'-C-3'-O-3') b = H (Pa-O-5'-C-5'-C-4') m2 = H (Pb-O-Pa-O-5') W = H (C-1''-O-1''-Pb-O-5') x = H (O-5''-C-5''-C-6''-O-6'')

The notations the most commonly used in spectroscopic and crystallographic publications on nucleotides are as follows: syn or cis (* 0 8), trans or anti (* 180 8), ±gauche or ± synclinal (* ± 60 8) and ± anticlinal (± 120 8) [28]. The three preferred orientations of the glucosyl x angle are referred to as gauche-gauche, GG (–60 8), gauche-trans, GT (+60 8) and trans-gauche, TG (+180 8) [29]. The signs of the torsion angles are in agreement with the IUPAC-IUB convention [30]. 10.2.2

Sample Preparation

All of the laboratory equipment and glassware in contact with the sugar nucleotide samples was sterilized to destroy trace amounts of RNase by standing in a 0.1% solution of diethylpyrocarbonate (2 h) followed by autoclaving at 120 8C (1 h). A typical NMR sample was obtained by dissolving 10–20 mg of sugar nucleotide (mono- or disodium salt, Fluka) in 0.5 mL of a 10 mM aqueous (18 MX) solution of phosphate buffer containing 0.1% of EDTA and 1% of TSP (internal reference for the 1H and 13C spectra). This mixture was lyophilized three times against D2O (99.8 %, SDS) and then dissolved in 0.5 mL of D2O (99.96 %, SDS) and sealed in an NMR tube under argon after vacuum removal of dissolved oxygen. EDTA was omitted when divalent cations (CaCl2 · 2 H2O, MgCl2 · 6 H2O, MnCl2 · 4 H2O, Fluka) were added. 10.2.3

NMR Experiments

500 MHz steady-state nuclear Overhauser effects [31] were measured on a Varian Unity plus spectrometer with irradiation times (2.5–10 s) and pulse intervals (* 4–12 s) that ranged from 2–5 times the longest proton T1 (i.e. 2.5 s [37]). 1–2 k scans were recorded with weak irradiation either at the frequency of interest or outside the spectral range, and these FIDs were Fourier transformed with an exponential line-broadening factor of 0.3 Hz in order to reduce noise. 500 MHz homonuclear cross-relaxation rates were measured at 25 8C on a Bruker DRX 500 spectrometer using the 1D DPFGSE-NOESY experiment [32] with seven mixing times between 0.2 and 1.2 s (recycle time 10 s). 1H NMR pulsed-gradient spin-echo experiments (PGSE) were conducted on a Bruker DRX 400 spectrometer at 25 8C. The stimulated spin-echo sequence [33] was used to measure the translational self-diffusion coefficients, as this method proved to be the most reliable in systematic study of the translational diffusion of carbohydrates [34]. The gradient duration (s1) was varied from 1 to 20 ms while keeping its strength fixed at 9.15 G/cm. The intergradient delay (s2)

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was chosen to be as short as possible (* 5 ms) while affording the maximum signal intensity for the shortest s1 value. The translational self-diffusion coefficients have been obtained by fitting the intensities of a selected proton signal in spectra acquired with various lengths of the gradient pulses (8–15 data points) to the Stejskal-Tanner equation with in-house software: M 12M0 expf s2

s1 =T1

2s1 =T2

s1 Gc2 Dt s2

s1 =3g

Several proton signals were monitored in separate experiments to estimate the experimental error in the estimation of Dt, and all experiments were run at least twice. Homo- and heteronuclear spin-lattice relaxation times were measured with the inversion-recovery sequence. The recycle time was greater than 6 ´ T1 and data were collected for 10–20 s values which varied from 5 ms to 2 ´ T1. Proton spinspin relaxation times were obtained with the Carr-Purcell-Meiboom-Gill sequence, and data were collected for roughly 20 spectra with various numbers of echoes (2 ms to 1 s). Heteronuclear NOEs were established by comparing the carbon integrals in composite-pulse decoupled and inverse-gated decoupled 1D spectra acquired with recycle times greater than 6 ´ T1. The integrals of the peaks were fitted to a three- (T1) or two- (T2) parameter exponential function using both spectrometer system software and in-house software, and all relaxation experiments were also run at least twice. 10.2.4

Vicinal Homo- and Heteronuclear Coupling Constants 1

H NMR spectra of sugar nucleotides (Fig. 10.3) can be difficult to analyze because of both overlapping signals and the additional spin-spin couplings to the 31 P nuclei (3JH1'',Pb, 3JH2'',Pb, 4JH4',Pa, 3JH5'a,Pa, and 3JH5'b,Pa). As a result, spectral simulations are often necessary to extract a complete set of coupling constants [35, 36, 37]. The conformation of the pyranosyl ring of sugar nucleotides (i.e. 4C1 for the d-hexose sugars such as UDP-Glc or GDP-Man) is readily determined from the methine proton (H1 to H5) coupling constants using the Karplus equation described by Haasnoot et al. [38]. In the case of the five-membered ribosyl ring, theoretical studies have revealed two major conformational families [39]: C2'-endo (southern conformer) and C3'-endo (northern conformer), which are generally represented on a pseudorotational wheel defined by two parameters, the degree of puckering mmax and the pseudorotation phase angle, P [40]. The 3JH1',H2' and 3 JH3‘,H4' vicinal couplings are the most sensitive to puckering preferences (C2'endo: 8–10 and < 3 Hz for 3JH1',H2' and 3JH3',H4', respectively; C3'-endo: < 2 and 8– 10 Hz for 3JH1',H2' and 3JH3',H4', respectively) [41]. In aqueous solution, the ribose rings of most UDP- and GDP-hexoses display fairly equal populations of C2'-endo and C3'-endo conformers [35]. The x and c angles that define the orientation of the exocyclic -CH2O- groups (x – 3JH5'',H6''a and 3JH5'',H6''b; c – 3JH4',H5'a and 3JH4',H5'b) are well defined by


Fig. 10.3 500 MHz 1H NMR spectra of a 33 mM aqueous solution of UDP-Glc (above) and a 40 mM aqueous solution of GDP-Man

(below) at 25 8C referenced to the residual HOD signal (4.800 ppm).

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homonuclear coupling [38, 42]. As regards the pyrophosphate backbone, Karplustype equations have been developed for the U [43] and b [44, 45] dihedral angles based on heteronuclear coupling to phosphorus (U – 3JH1'',Pb and 3JC2'',Pb; b – 3 JH5'a,Pa, 3JH5'b,Pa, and 3JC4',Pa). Finally, concerning the orientation of the base with respect to the ribose ring, 13C-labeled sugar nucleotides are desirable for characterizing the v dihedral through heteronuclear coupling, 3JC,H (pyrimidines, H-1'-C-1'N-1-13C-6; purines, H-1'-C-1'-N-7-13C-8). Future use of 13C-labeled sugar nucleotides combined with improved parametrization of Karplus equations for both 2JC,X and 3JC,X (X = H, C, P) couplings in 13Clabeled sugars [46] should improve the solution structures of sugar nucleotides based on NMR coupling constant data. However, it is to be noted that four (W, l, m, and a) of the seven torsion angles that define the time-averaged conformation about the pyrophosphate moiety would require both isotope labeling (13C and 17O) and/or the development of reliable Karplus relations for heteronuclear two- (C-OP and P-O-P) and/or three-bond (C-O-P-O and P-O-P-O) couplings. 10.2.5

Hydrodynamic Modeling

Both rotational and translational diffusion coefficients may be used to establish time-averaged molecular volume [47, 48]. Hydrodynamic modeling is performed by fitting the theoretical carbon relaxation data (T1, T2, heteronuclear NOEs) established with a flexible residue approach and typical values of the carbon-proton interatomic distance (1.09 £ rC-H £ 1.11 Å) [49] to the experimental values. For detailed equations, [50–52], see Chapter 1 [Eq. (16)]. Using this methodology (Fig. 10.4), the angles between the various carbon/proton vectors and the axis of the cylinder must be determined. For example, they were estimated with in-house software from the cartesian coordinates of the crystal structure of disodium uridine diphosphoglucose dihydrate [53] after reorienting the molecule about the axis of the principal inertial tensor with CHARMm22 [54]. The optimization routine should systematically evaluate the entire range of physically realistic dynamic parameters to obtain the best fit between theoretical and experimental carbon relaxation data (i.e. for UDP-Glc, 0.5 < S2C-H < 0.9; 50 < se < 200 ps; sc, s^ and s// ± 50% with respect to the values established from hydrodynamic theory). Analytical expressions for the rotational diffusion coefficients, D^r and Dr// have been reported for models of short cylinders [48, 55] with anisotropic ratios, p ³ 2 (p = L/d, where L and d are the length and the diameter of the cylinder, respectively): pg0 L3 D? r =3kT lnp d? 2 A0 pg0 L3 D== r =kT p =1 d==

where A0 = 3.84, d^ = –0.662 + (0.917/p)–(0.050/p2), and d// = (0.677/p)–(0.183/p2).

10.2 NMR Methods for Conformational Analysis of Sugar Nucleotides Fig. 10.4 Molecular dimensions of UDP-Glc obtained from hydrodynamic theory and NMR-defined rotational (translational diffusion) coefficients.

The optimized correlation times, s^ and s//, obtained by fitting the experimental relaxation data are then compared to the Dr values (Dr^ or // = {6s^ or //}–1) for cylinders of various dimensions to establish the time-averaged volume. In a study of the rotational diffusion of UDP-Glc, the considerable spread in the experimental multi-field T1 data (20–33%, measured at 75.13, 100.6 and 125 MHz [37]) for the various methine carbons was successfully modeled with this approach. When the experimental multi-field heteronuclear carbon NOEs in Tab. 10.1 (measured for the same sample) are simulated with a related motional model (se 50 ps, S2C–H 0.7 [37]), good agreement between the experimental and theoretical values is obtained (average deviation, 7%). The exceptions are the base carbons (both local dynamics and the h values may be responsible for the larger deviations, 10–20%). Rotational diffusion is a little slower (i.e. s^ and s// values of 0.24 and 0.12 ns instead of 0.18 and 0.09 ns), as these measurements were performed at a slightly lower temperature (22 8 instead of 25 8, which results in an increase in viscosity). In contrast to the carbon T1 data set, the variations in the theoretical heteronuclear NOEs of the methine carbons are quite small (average variation 6%) and almost fall within the range of experimental error (average error 5%). This fact demonstrates that T1 data are a better probe of molecular dynamics in the case of sugar nucleotides.

255

256

10 Activated Sugars Tab. 10.1 Experimental multi-field (75, 100, and 125 MHz) carbon heteronuclear NOEs of a 33 mM aqueous solution of UDP-Glc in the presence of monovalent cations (Na+ and K+, 2.7 and 0.3 equivalents respectively) at 22 8C

Heteronuclear NOEs, g+1

Carbon

C1'' C2'' C3''+C5'' C4'' C6'' C1' C2' C3' C4' C5' C5 C6

125.7 MHz

100.6 MHz

75.5 MHz

2.54 ± 0.17 2.54 ± 0.08 2.59 ± 0.02 2.65 ± 0.08 2.64 ± 0.10 2.48 ± 0.11 2.61 ± 0.05 2.68 ± 0.08 2.45 ± 0.16 2.45 ± 0.16 2.34 ± 0.16 2.26 ± 0.10

2.73 ± 0.10 2.66 ± 0.01 2.55 ± 0.03 2.61 ± 0.02 2.76 ± 0.05 2.71 ± 0.05 2.69 ± 0.01 2.76 ± 0.01 2.72 ± 0.05 2.72 ± 0.08 2.49 ± 0.02 2.40 ± 0.02

2.79 ± 0.02 2.81 ± 0.01 2.73 ± 0.06 2.61 ± 0.20 2.63 ± 0.12 2.80 ± 0.02 2.63 ± 0.14 2.78 ± 0.01 2.80 ± 0.02 2.72 ± 0.11 2.60 ± 0.01 2.47 ± 0.25

The major problems associated with this approach have been discussed in Section 3.2. Temperature control [49] clearly still represents the major source of error in hydrodynamic modeling), but for molecules the size of sugar nucleotides neglect of cross-correlation (DD/CSA) is undoubtedly also a serious source of error. It would be desirable to measure the carbon relaxation data with pulse sequences that suppress DD/CSA cross-correlation [56, 57]. The translational diffusion coefficients, Dt, of sugar nucleotides have been established recently [34] with the pulsed field gradient spin-echo method [33, 58, 59]. In this work, it has been shown that the gradient strength must be carefully calibrated (with respect to several related compounds of known Dt). Such data have been determined for carbohydrates by optical methods. Moreover, spin-spin relaxation must be taken into account to obtain the most accurate estimations of translational diffusion. Such experiments are very rapid and sensitive (homonuclear 1D spectra) and will undoubtedly find widespread use in the future. The Stokes-Einstein equation has been used to determine the theoretical hydrodynamic radius, r, from Dt as follows (where k is Boltzmann’s constant, T the temperature in K, and g0 is the viscosity of D2O): Dt kT=6p r g0 Expressions for the translation diffusion coefficients, D^t and Dt// have also been reported for models of short cylinders with axial ratios, p ³ 2 (p = L/d, where L and d are the length and the diameter of the cylinder, respectively) [48, 56]: ==

Dt Dt 2D? t =3


4pg0 L D? t =kT lnp c? ==

2pg0 L Dt =kT lnp c== where c^ = 0.839 + (0.185/p) + (0.233/p2), and c// = –0.207 + (0.980/p)–(0.133/p2). Values of the entire range of plausible average hydrodynamic molecular overall dimensions were estimated from Dt with the above equations. In the case of UDPGlc (Na+/K+), fitting of the experimental Dt value gives L and d values of 15.5 and 9.0 Å [34], in excellent agreement with the dimensions established from both Dr (L and d values of 15.2 and 8 Å, respectively [37]) and molecular modeling (see below [27]). A systematic study of the hydrodynamic behavior of carbohydrates as a function of molecular volume has indicated that sugar nucleotides represent the lower limit in size of molecules that obey the Stokes-Einstein relation [34]. Despite their relatively small hydrodynamic volume, a microviscosity correction factor does not appear to be necessary, and the solvent can be treated as a continuous medium characterized by a bulk viscosity [47]. For the comparison of hydrodynamic molecular dimensions of carbohydrates with those from molecular modeling studies, it has been shown that half of the distance between the molecule under study and the first hydration shell should be added to atom-to-atom dimensions of the theoretical model [34]. For instance, * 1.2 Å should be added to the radius of a sphere or cylinder and * 2.3 Å to the length of a cylinder. In the case of disaccharides, this definition has been validated, as the first hydration shell appears to have the same experimental Dt coefficient as that of bulk water [60], indicating that water is not bound as can be the case with proteins. This definition of hydrodynamic dimensions is depicted in Fig. 10.4. 10.2.6

Homonuclear Relaxation Data

Homonuclear relaxation data can probe both the time-averaged structure and minor populations of folded geometries and are thus complementary to the data described in the preceding paragraphs [27]. In the room temperature phase-sensitive 2D NOESY spectra, at 400–500 MHz, of aqueous solutions of sugar nucleotides, the diagonal peaks and the cross-peaks have opposite signs (xsc < 1). The relative values of the nuclear Overhauser effects (NOEs) between the aromatic base proton (H6, pyrimidine bases – uridine and cytosine; H8, purine bases – adenosine or guanosine) and the ribosyl H1', H2' and H3' protons indicate the orientation about the v dihedral [61]. In the case of syn orientation (–90 £ v £ 90, preferred in the case of guanosine), the closest contact is with H1', whereas for the anti orientation (preferred in the case of pyrimidine bases), strong NOEs are observed between the aromatic proton and H2' (C2'-endo, –144 £ v £ 115) and/or H3'(C3'-endo, –180 £ v £ –138). The intraresidue NOEs confirm the ring form of the hexose sugar (strong effects are detected for 1,3-diaxial and 1,2-diequatorial contacts), whereas those of the ribose sugar are more difficult to interpret as they generally reflect the C2'-endo/C3'-endo equilibrium.

257

258

10 Activated Sugars

Back-calculation of NOESY data from suitable ensemble average distance matrices (i.e. a canonical ensemble that reproduces the dihedral angle populations established on the basis of the homo- and heteronuclear coupling constants), using model-free spectral densities to account for internal motion and the dynamic models established previously, gives good agreement for most of the moderate-tostrong NOEs [27]. However, the signal-to-noise ratio (typically ± 0.005 units of normalized intensity for 400–500 MHz spectra obtained with acquisition times of 24– 48 h) is not sufficient for determining borderline NOEs (–0.001 to –0.005) with reasonable accuracy. One-dimensional steady-state [32] and transient NOE [33] experiments have been successfully implemented [25–27] to probe the equilibrium mixture of conformers of UDP-Glc. In Fig. 10.5 a, a series of steady-state NOE difference spectra recorded for a 33 mM aqueous solution of UDP-Glc are displayed (a total of 1–2 k scans/spectrum) along with those recorded with the transient NOE pulse sequence, Fig. 10.5 b (4 k scans/spectrum). Analogous results are obtained with either approach, and these experiments show that it is possible to quantify long-range NOEs in sugar nucleo-

a

Fig. 10.5 (a) Steady-state NOE difference spectra acquired with low-power irradiation of the H2'+H3' signal for various irradiation times (0, 2.5, 5.0, 7.5, and 10 s). The assignments of the proton resonances have been indicated (*, the signal which is sandwiched between the H2' and H4' resonances of UDP-

Glc corresponds to a-glucopyranosyl 1,2 cyclic phosphate, a minor contaminant previously reported [37]). (b) DPFGSE- NOE spectra of UDP-Glc acquired with selective inversion of the H2'+H3' signal and various mixing times (0.2, 0.4, 0.6, 1.0, and 1.2 s).

10.2 NMR Methods for Conformational Analysis of Sugar Nucleotides b

Fig. 10.5 b

tides. One of the main drawbacks to these laboratory-frame NOEs as opposed to transverse rotating-frame NOEs [62] is spin diffusion, but the full relaxation matrix approach takes this into account, and in the case of sugar nucleotides there are no efficient interresidue pathways for indirect effects. Finally, the precision of the data depends on the accuracy of the motional model, and off-resonance approaches [63] that involve determining a correlation for each pair of spins have been recommended to circumvent this problem. The application of such sophisticated pulse sequences to the determination of very weak interactions remains to be demonstrated.

259

260

10 Activated Sugars

10.2.7

Relaxation and Frequency Shifts in the Presence of Paramagnetic Cations

Electron-nuclear relaxation, which is due to interaction of the nuclear spin with the spin of an unpaired electron, may occur by several mechanisms [64]. Many of the early NMR studies of metal-nucleotide structures are based on proton, carbon, or phosphorus differential line-broadening effects [65]. This approach assumes that the electron-nuclear Te2 relaxation is dominated by the dipolar interaction between the nucleus and the unpaired electrons of the metal ion. However, the scalar contribution to Te2, which has no simple distance dependence, may be the dominant mechanism under the chosen conditions. In contrast, the expression for the scalar contribution to Te1 has only a frequency-dependent term, and, since x2s s2e >>1 (xs, electron frequency; se, correlation time for the process), the scalar contribution to Te1 is negligible. As Te1 is determined solely by the dipolar mechanism, it is possible to obtain structural information from the expression by Solomon [66] and Bloembergen [67]: 1 2SS 1c2I c2H h2 3sC1 7sC2 T1 15r 6 1 x2I s2C1 1 x2S s2C2 where S is the spin of the nucleus of interest, cI and cS are the magnetogyric ratios of the nucleus and the electron respectively, r is the distance between the nucleus I and the metal ion and sC is the correlation time for the process as given by the following equation: 1 1 sC1;2 sR 1 sS1;2 sM1

where sR is the rotational correlation time of the metal-nucleotide complex (defined by s^ and s// in the hydrodynamic modeling, but the assumption of an isotropic correlation time is not expected to be an appreciable source of error), sM is the lifetime of the bound state and is assumed to be in the fast exchange region (sM for phosphates lies in the range of 4–6 10–6 s [68, 69]), and for Mn2+, sS (the electron spin relaxation time which can be calculated with the Bloembergen and Morgan equation [70]) is in the range 10–7–10–8 s. Finally, outer sphere relaxation (a mechanism assimilated to the spin-dipolar interaction modulated by translational diffusion) may contribute to Te1, and this can be determined by concentration and temperature dependence studies [64]. The frequency shifts produced in NMR active nuclei as a result of lanthanide ion binding to a specific site on a substrate (lanthanide-induced shifts or LIS) may result from a through-space dipolar interaction (pseudo-contact shift), a direct delocalization of unpaired electron spin density from the metal to the nuclei (contact shift), or from a sum of these two mechanisms. Frequency shifts arising from pseudo-contact origins are related to the average dynamic structure of the lanthanide-substrate complex [71] as follows:

10.3 Monovalent Cations

Dm=m fg 2 b2 JJ 12J

12J 3Dz =60kT 2 3 cos2 h

1=ri3 g

The first term contains magnetic constants characteristic of the lanthanide ion f orbital population (g is the Landé splitting factor, b is the Bohr magneton) and the ligand field term, Dz, while the second contains the desired geometrical information (ri is the distance between nucleus i and the metal ion, and q describes the angle between each metal-nucleus vector and the principal symmetry axis of the ligand field). This simplified equation assumes rapid exchange yielding a complex with effective axial symmetry [72]. It has been pointed out that the use of neutral lanthanide ions as conformational probes can result in significant effects due to secondary binding, as the lack of charge reduces the relative affinity for the negatively charged pyrophosphate moiety which constitutes the primary binding site of sugar nucleotides.

10.3

Monovalent Cations

The molecular conformation in crystalline disodium uridine diphosphoglucose (the only X-ray structure of a sugar nucleotide that has been described) includes the 4C1 form for glucose and C2'-endo puckering for ribose [53]. The orientations of the b, c, and v torsion angles are trans, +gauche and trans, respectively, while the pyrophosphate group adopts the staggered form. Two co-ordination sites are observed for the sodium ions. The first site includes O2'' and a Pb oxygen of one molecule, the two base oxygens of a second molecule, and two co-ordinating waters. The second site contains four glucosyl oxygens (O3'', O4'', O5'', and O6''), O2 of a second molecule and one water ligand. In aqueous solutions containing monovalent cations, NMR studies of UDP-Glc have indicated typical geometries for the various segments (4C1 form for glucose, a 1/1 mixture of C2'-endo/C3'-endo ribose conformers, and an anti orientation of the base) [35–37]. A 90 8 orientation about U and a strong preference (76%) for the trans rotamer of the b dihedral have been proposed from the heteronuclear couplings [37]. The former value falls within the range of privileged orientations (60 8 £ U £ 135 8) reported for the U angle based on theoretical studies [24]. The x and c torsion angles of the exocyclic methylene groups display strong GG (3JH5'',H6''a and 3JH5'',H6''b & 2 and 5 Hz, respectively) and +gauche (3JH4',H5'a and 3 JH4',H5'b & 2.5 and 3 Hz, respectively) populations, respectively. In early work on sugar nucleotides in the presence of monovalent cations [35, 36], experimental evidence for the overall average conformation (extended or folded) was lacking. Recent studies have attempted to obtain this key information for UDP-Glc through hydrodynamic modeling [27, 34, 37] and/or long-range NOEs [25–27, 37] combined with conformational searching. The former approach affords a unified image of overall molecular dimensions (L and d values of 15–16 and 8–9 Å, respectively, see Sect. 10.2) regardless of the experimental phenomenon that is modeled, whether this is rotational (multi-field carbon T1 or NOE

261

262

10 Activated Sugars

data) or translational diffusion. The corresponding average atom-to-atom molecular extension of UDP-Glc reported for 27 ns of molecular dynamics trajectories (nine 3-ns trajectories, initiated with stable geometries displaying different orientations of the torsion angles of the pyrophosphate moiety) in the presence of explicit water and monovalent cations [27] was 14.2 Å (which corresponds to 16.5 Å in terms of hydrodynamic dimension L). Values for the most extended and the most folded conformers were 19 Å (21.3 Å for L) and 9 Å (11.3 Å for L), respectively. On the basis of hydrodynamic modeling it was concluded that UDP-Glc adopts a fairly extended average conformation in the presence of monovalent cations in contrast with the hypothesis of the existence of a unique folded conformer in aqueous solution, as reported in early studies [1, 20, 21]. Although hydrodynamic modeling affords a convincing probe of average structure, it does not offer much insight into the various conformations that are visited by sugar nucleotides in the course of time. Simulations of molecular dynamics trajectories of UDP-Glc in the presence of explicit water and monovalent counterions have suggested that several long range contacts between the glucose and ribose sugars should be detected in homonuclear relaxation experiments [27]. Indeed, monitoring a set of five interresidue interproton distances during nine 3-ns MD trajectories initiated with various starting geometries indicated that the average value for these distances varied from 4.3 to 6.8 Å. The initial low-energy structures for the trajectories were chosen so as to cover a wide range of orientations of both the glucose and uridine moieties, and each one evolved to afford one or two characteristic long range contacts. When theoretical NOEs are calculated for the aforementioned 3-ns MD trajectories, various interresidue contacts (–0.001 to –0.030 units of normalized volume) are predicted that are not observed in the 400 MHz NOESY spectrum [37]. However, considering the typical ranges of signal-to-noise ratio in such spectra (± 0.005) and the fact that NMR experiments necessarily sample an ensemble average of sugar nucleotide conformers, this was not surprising. Long range contacts between the base (H-5 and H-6) and the glucosyl (H-1'' to H-3'') protons were also predicted from ab initio calculations [25, 26]. Both steady-state [25, 26, 37] and transient NOEs [25, 26] have been measured for UDP-Glc to detect the long range interresidue interactions. Such contacts are indeed revealed by the linear buildup of interresidue NOEs in both cases, as shown in the spectra in Fig. 10.5 (steady-state NOE difference spectra above and DPFGSE- NOE spectra below). No single 3-ns MD simulation can simultaneously reproduce the entire experimental set of borderline NOEs, indicating that the ensemble average blend of conformers must necessarily contain many types of slightly folded geometries in equilibrium with more extended ones. As regards GDP-Man, similar conformational preferences have been established on the basis of coupling constant data [35]. Fairly rapid exchange between the H-8 base proton and the deuterated solvent made it very difficult to detect NOEs with the aromatic proton, and the orientation about the v dihedral has not yet been determined. Steady-state NOE difference experiments have been conducted on an aqueous solution of GDP-Man in the presence of monovalent cations, and long range interresidue NOEs were also detected (H-3'/H2'' and H5'a+H5'b/H1'') for

10.4 Divalent Cations

this sugar nucleotide (Tab. 10.2). The translational diffusion coefficient of GDPMan (2.61 ± 0.08 · 10–6 cm2 s–1) is very similar to that of UDP-Glc (2.55 ± 0.04 · 10– 6 cm2 s–1), suggesting a fairly extended average overall conformation for this metabolite in the presence of monovalent cations.

10.4

Divalent Cations

The fraction of molecules in the bound state, the number of binding sites, and the atoms involved in binding for sugar nucleotide/divalent cation complexes will be considered before discussing the geometry of these chelates. Strong interactions are observed for nucleoside di- and triphosphate/divalent metal complexes (UDP/Mg2+, log K & 3 [73]), and it has been demonstrated that the preferred metal ion binding sites for uridine nucleoside di- and triphosphate/metal complexes are the phosphate oxygens [28, 74]. In the case of carbohydrate/metal complexes [75–77], only certain sugar configurations (presenting adjacent axial-equatorial-axial and triaxial hydroxyl groups) lead to significant binding, and for glucose very weak non-specific interactions through pairs of hydroxyl groups would be predicted. In the case of samples of UDP-Glc, comparison of the 1H and 13C NMR chemical shift data acquired in the presence of monovalent cations (Na+, K+) with data acquired in the presence of alkaline earth cations (Ca2+, Mg2+) revealed only very small (Dd < 0.05 ppm) variations in the chemical shifts of the UDP-Glc [37]. In the case of sialic acid, which forms a strong complex with Ca2+ (Kassoc 121 M–1), the calcium-induced diamagnetic shifts for the protons and carbons closest to the cation were 0.316 (H7) and 1.42 (C8) ppm, respectively [78]. It has therefore been concluded that in the presence of alkaline earth cations significant interaction with the UDP-Glc sugar moieties does not occur. In contrast, substantial diamagnetic shifts (Dds) were reported for the 31P signals of UDP-Glc (Pa, 0.25 ppm; Pb, 0.30 ppm) in the presence of 2 equiv. of Mg2+ [37]. When the 31P Dds were plotted as a function of the Mg2+/UDP-Glc ratio, they increased strongly up to a molar ratio of 1 : 1 and more slowly for higher ratios, suggesting the formation of a strong 1 : 1 complex followed by possible weaker binding of additional Mg2+ ions. Comparison of the Dds of the Mg2+/UDP-Glc complex with those reported [79] for Mg2+ chelation of triply-charged geranyl diphosphate (90% of association; 0.68 and 1.58 ppm respectively for the phosphorus a to the terpene, Pa, and the doubly charged Pb) indicated weaker binding for the less-charged Mg2+/ UDP-Glc complex. The diamagnetic shifts of the phosphorus for a sample of UDP-Glc containing an equivalent of Ca2+ were much smaller than those for the Mg2+/UDP-Glc complex [37], in agreement with the weaker chelation of di- and triphosphates by the former cation reported in the literature [73]. Close inspection of the 81 MHz 31P spectra of UDP-Glc as a function of the Mg2+/ UDP-Glc ratio (Fig. 10.6) shows that both the Pa and Pb signals broaden with increasing amounts of Mg2+. Moreover, in the presence of UDP-Glc, a strong increase

263

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10 Activated Sugars

in the 25Mg linewidth was observed when compared to that of an aqueous solution of MgCl2 [37]. In the case of 23Na complexes of crown ethers [80], similar phenomena are usually interpreted in terms of fast quadrupole relaxation due to the lack of cubic symmetry around the quadrupolar ion in the complexed species when compared to the solvated species. Titration of 25Mg linewidths as a function of the Mg2+/UDP-Glc molar ratio revealed a plateau for ratios of < 1. This was followed by a rapid decrease until the ratio was close to 10 and finally much slower narrowing to attain a sixfold decrease for an Mg2+/UDP-Glc molar ratio of 80 [37]. The low signal-to-noise ratio of the spectra recorded for low Mg2+ concentrations made it difficult to accurately estimate the linewidth of the fully-complexed species, limiting the precision of the stability constant determined with this approach [81]. It was surmised that the major species (90%) is the 1 : 1 Mg2+/UDP-Glc complex. Furthermore, line-narrowing was not observed for spectra recorded in a temperature range of 25–80 8C, indicating that the coalescence of free and complexed species occurred at a much lower temperature and that chemical exchange between these species was not contributing significantly to the linewidths. Selective line-broadening experiments (1H, 13C, 31P, etc.) have often been used to reveal the formation of complexes between paramagnetic species and organic molecules [65, 76]. In a comparison of the 1H longitudinal relaxation times for so-

31 P spectra of UDP-Glc recorded under standard conditions (10 mM phosphate buffer in D2O, 0.3 equiv. of K+, 2.7 equiv. of Na+) and in the presence of various molar ratios of Mg2+.

Fig. 10.6 81 MHz

10.4 Divalent Cations 2+

lutions of UDP-Glc containing 0.003 equivalents of Mn and 1 equivalent of Mg2+ the reduction in proton T1 values in the presence of Mn2+ was striking. The shortest proton T1 was observed for H1'' (32 ms) followed by H5'b (45 ms) and H6 (93 ms), indicating that these protons are the closest to the paramagnetic species. These data would be compatible with a complex in which the Mn2+ ion was located roughly between the two phosphate moieties. Similar conclusions were drawn from plots of the methine carbon longitudinal relaxation rates as a function of the Mn2+ concentration, where the largest slope was detected for the glucose anomeric carbon. Finally, in the 31P spectra, severe line broadening was observed for the Pa and the Pb resonances in agreement with complexation of Mn2+ by both Pa and Pb phosphate oxygens. The aforementioned experimental data indicate the formation of a stable 1 : 1 complex in which the divalent cation is coordinated to an oxygen atom of both Pa and Pb in the case of Mg2+ and Mn2+. On the basis of the values of the vicinal couplings [37], it can be assumed that the conformational features of the sugars in the Mg2+/UDP-Glc complex are analogous to those demonstrated for sugar nucleotides in the presence of monovalent cations. The steady-state NOEs for the Mg2+/UDP-Glc chelate are also given in Tab. 10.2, and, although many of the long range interactions are similar to those observed in the presence of monovalent cations, there are several differences. In fact, the interactions between H2'+H3' and H1''–H3'' are slightly stronger and the H2'+H3'/H5'' and H5'a+H5'b/H1'' contacts are much weaker or possibly absent. Finally, hydrodynamic modeling has suggested that the time-averaged conformation of the Mg2+/ UDP-Glc complex is slightly more extended than in the case of Na+ and K+ counterions [34, 37]. The m1 and m2 torsion angles of the pyrophosphate moiety of the disodium salt of UDP-Glc adopt a staggered conformation in the crystal [53]. However, an eclipsed geometry is required to obtain the 2.8 Å distance between the phosphate oxygens displayed in crystal structures where the pyrophosphate group acts as a bidentate ligand. Molecular models of UDP-Glc corresponding to cis (–95 8, 102 8) and trans eclipsed (134 8, 102 8) arrangements of the pyrophosphate moiety (Fig. 10.2 b) were used to summarily explore the conformational space of the pyrophosphate group (W and a torsion angles in 60 8 steps), affording two sets of 36 structures. The other torsion angles (sugar puckering, U, b, c and v) were set to the NMR-defined values and no attempt was made to optimize these structures, as realistic molecular modeling of medium-sized charged molecules such as UDP-Glc with appropriate methods such as molecular dynamics simulations requires both the presence of counterions and explicit solvent. Several of the NOEdefined distances between the sugar moieties in Tab. 10.2 were monitored for these sets of conformers to obtain a rough picture of plausible ranges for these parameters. The average values for these distances for the two sets of structures are collected in Tab. 10.3. It can be seen that all the long range NOEs would be expected for the cis eclipsed arrangements, whereas only the H5'a+H5'b/H1'' contact is predicted for the trans eclipsed conformers. In both cases, certain geometries (the ranges of W

265

266

10 Activated Sugars Tab. 10.2 Experimental 500 MHz long range steady-state NOEs of sugar nucleotides measured at 25 8C for the following samples: (a) a 33 mM aqueous solution of UDP-Glc in the presence of monovalent cations (Na+ and K+, 2.7 and 0.3 equivalents respectively), (b) a 33 mM solution of UDP-Glc in the presence of 1 equivalent of MgCl2, and (c) a 40 mM solution of GDP-Man in the presence of monovalent cations (Na+ and K+, 1.25 and 0.13 equivalents respectively)

Sample

Irradiation Long range steady-state NOEs time (s) Irradiated spin(s)/detected spin(s) (%) H2'+H3'/ H2'+H3'/ H2'+H3'/ H2'+H3'/ H5'a+H5'b/ H3''+H6''/ H1'' H2'' H3'' H5'' H1'' H5

UDP-Glc a) M+

2.5 5 7.5 10

0.4 0.5 0.5 0.75

e 0.4 0.6 0.85

0.6 0.6 0.85 0.95

e 0.35 0.6 0.8

0.6 0.75 0.8 0.9

UDP-Glc b) M2+

2.5 5 7.5 10

0.45 0.55 0.95 1.35

0.75 0.85 1.0 1.1

0.7 0.85 1.3 1.35

0 0 0 0

e e e e

GDP-Man c) M+

2.5 5 7.5 10

a) b) c) d)

e 0.5 0.5 0.85

e 0.85 1.0 1.15

0.3 d) 0.65 d)

Na+ and K+, 2.7 and 0.3 equivalents respectively. Mg2+, 1 equivalent. Na+ and K+, 2.7 and 0.3 equivalents respectively. only H-3' was irradiated in the case of GDP-Man.

Tab. 10.3 Average interproton distance data for sets of uridine diphosphoglucose structures with the pyrophosphate moiety in either the trans-eclipsed (m1 134 8, m2 102 8) or cis-eclipsed (m1 –95 8, m2 102 8) arrangements. Conformers were obtained by varying W and a dihedrals in 60 8 steps while maintaining the NMR-defined values of the other torsions (U, x, b, c, and v).

Average interproton distances (Å) UDP-Glc Structure Cis-eclipsed a) C2'-endo

H2'/H1'' H3'/H1''

H2'/H2'' H3'/H2''

H2'/H3'' H3'/H3''

H2'/H5'' H3'/H5''

H5'a/H1'' H5'b/H1''

6.1 5.2 6.0 5.6

6.4 5.3 6.4 5.7

6.1 4.9 6.0 5.3

6.3 5.1 6.5 5.7

5.3 5.5 5.1 5.3

Trans-eclipsed a) C2'-endo 8.3 7.1 C3'-endo 9.1 8.2

10.3 9.1 11.5 9.7

9.7 8.5 11.9 10.0

9.1 7.9 10.8 9.0

5.3 5.9 6.0 6.1

C3'-endo

a) This set includes –608 <W < 1208 and all values of a except 0 and 120 8.

10.6 Perspectives

and a are indicated in the footnote) have been excluded as they do not correspond to stable structures in the theoretical investigation [24]. Severe steric conflicts are observed for the excluded conformers in the case of the cis eclipsed arrangements (interproton distances 6.0 Å). The overall molecular extension of the cis eclipsed complexes (very folded) is not compatible with the hydrodynamic modeling, which points to an extended time-averaged structure as has been demonstrated for the trans eclipsed arrangements [37]. However, rapid exchange between these two families of conformers with a smaller equilibrium population of the cis eclipsed family could account for all the experimental observations.

10.5

Trivalent Cations

Aqueous solutions of UDP-Glc have also been investigated with the lanthanide-induced shift (LIS) technique to determine the overall conformation [82]. The neutral, water-soluble nitrilotriacetate chelates, Ln(NTA)/UDP-Glc (Ln = Pr, Tb, Dy, Er, Yb), proved to be the most satisfactory, as bare ions rapidly hydrolyzed the sugar nucleotide. As was the case for the divalent cations, the primary binding site for these neutral lanthanide chelates is the pyrophosphate moiety. The smallest lanthanides appeared to have the most specific affinity for the pyrophosphate group, in agreement with the stronger binding of Mg2+ to UDP-Glc as compared to Ca2+. Secondary binding to the uracil carbonyl groups also occurred, and the largest ions showed the greatest affinity for these secondary sites. This effect was overcome by extrapolating the observed shift ratios to zero lanthanide ion concentration. The extrapolated shift ratios were relatively constant for the entire series of lanthanides, indicating that the solution conformation of UDP-Glc was insensitive to the metal size. Quantitative analysis of the LIS was interpreted in terms of the extended average conformation that is displayed in Fig. 10.7. The shift cone defined by the term (3 cos2h–1) has been indicated and translates the signs of the experimental shift ratios. The principal symmetry axis from which h is measured is assumed to pass through the central oxygen of the pyrophosphate moiety.

10.6

Perspectives

Divalent cations such as Mg2+ or Mn2+ are necessary for the catalytic activity of many of the enzymes that metabolize sugar nucleotides during the biosynthesis of polysaccharides and glyco-conjugates. Understanding their role in these processes has been a major goal in structural studies. Conformational analysis of sugar nucleotides in the presence of various cations has been undertaken, to reveal

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Fig. 10.7 Schematic illustration of the relative orientation of the lanthanide nitrilotriacetate/UDP-Glc complex indicating approximate positions of the carbons relative to the shift cone defined by 3 cos2h–1. The principal symmetry axis from which h is measured is assumed to pass through the central oxygen of the pyrophosphate moiety, with permission, ref. 82.

a possible preorganization of the sugar nucleotide by the cation prior to the formation of a glycosyl donor/glycosyl transferase complex. Because of the topology of sugar nucleotides it has been a major endeavor to assess the overall conformation and, in particular, the relative positions of the hexose and ribose sugars. NMR structural determination based on the measurement of residual dipolar coupling in liquid crystalline medium is a very promising field of research [83]. This approach would appear to be particularly well suited to the study of sugar nucleotides, as global conformational features can be obtained without recourse to an uninterrupted scalar coupling or NOE pathway. However, sugar nucleotides are very reactive molecules, and maintaining a stable sample for a reasonable length of time requires careful control of pH and ionic species present in solution [1]. As charged molecules seem prone to interact with the liquid crystalline medium, the major challenge will undoubtedly be to find a suitable medium for obtaining weak alignment of sugar nucleotides (see Chapter 9). Comparison of the NMR data of free sugar nucleotides (K+ and Na+) with those of chelated species (Mg2+ or Mn2+) suggests that (i) the preferred binding sites of the metal ions are the pyrophophate oxygens, (ii) a 1 : 1 complex is formed in aqueous solution, (iii) the major form of the complex corresponds to a trans eclipsed arrangement of the pyrophosphate linkage, and (iv) a significant population of cis eclipsed forms exists in solution in the absence of enzyme. Formation of either cis or trans eclipsed chelates creates two chiral centers at Pa and Pb and positions the various functional groups susceptible to engaging in stabilizing interactions with enzymes. When the conformational features of divalent cation/sugar nucleotide complexes are compared to those of the first crystallographic structures of UDP-Glc/glycosyltransferase complexes, it appears that the minor population (cis eclipsed arrangement of the pyrophosphate linkage) is recognized by the enzymes.

10.7 References

10.7

References 1

2 3

4

5

6

7 8 9

10

11

12

13

14 15 16

17

18

N. K. Kochetkov, V. N. Shibaev, Adv. Carbohydr. Chem. Biochem. 1973, 28, 307– 397. M. M. Palcic, O. Hindsgaul, Trends Glycosci. Glycotechnol. 1996, 8, 37–49. S. David, Chimie moléculaire et supramoléculaire des sucres, CNRS Editions, Paris 1995; pp 169–176. J. A. Campbell, G. J. Davies, V. Bulone, B. Henrissat, Biochem. J. 1997, 326, 929–942. C. Breton, E. Bettler, D. H. Joziasse, R. A. Geremia, A. Imberty, J. Biochem. 1998, 123, 1000–1009. K. Shibayama, S. Ohsuka, T. Tanaka, Y. Arakawa, M. Ohta, J. Bacteriol. 1998, 180, 5313–5318. C. A. Wiggens, S. Munro, Proc. Natl. Acad. Sci. USA 1998, 95, 7945–7950. C. Breton, A. Imberty, Curr. Opin. Struct. Biol. 1999, 9, 563–571. C. Busch, F. Hofmann, J. Selzer, S. Munro, D. Jeckel, K. Aktories, J. Biol. Chem. 1998, 273, 19566–19572. K. Shibayama, S. Ohsuka, K. Sato, K. Yokayama, T. Horii, M. Ohta, FEMS. Microbiol. Lett. 1999, 174, 105–109. N. Hodson, G. Griffiths, N. Cook, M. Pourhossein, E. Gottfridson, T. Lind, K. Lidholt, I. S. Roberts, J. Biol. Chem. 2000, 275, 27311–27315. A. Vrielink, W. Rüger, H. P. C Driessen, P. S. Freemont, EMBO J. 1994, 13, 3413–3422. S. Moréra, A. Imberty, U. Aschke-Sonnenbron, W. Rüger, P. S. Freemont, J. Mol Biol. 1999, 292, 717–730. L. N. Gastinel, C. Cambillau, Y. Bourne, EMBO J. 1999, 18, 3546–3557. S. J. Charnock, G. J. Davies, Biochemistry 1999, 38, 6380–6385. U. M. Ünligil, S. Zhou, S. Yuwaraj, M. Sarkar, H. Schachter, J. M. Rini, EMBO J. 2000, 19, 5269–5280. L. C. Pedersen, K. Tsuchida, H. Kitagawa, K. Sugahara, T. A. Darden, M. Negishi, J. Biol. Chem. 2000, 275, 34580– 34585. K. Persson, H. D. Ly, M. Dieckelmann, W. W. Wakarchuk, S. G. Withers, N. C.

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J. Strynadka, Nat. Struct. Biol. 2001, 8, 166–175. L. N. Gastinel, C. Bignon, A. K. Misra, O. Hindsgaul, J. H. Shaper, D. H. Joziasse, EMBO J. 2001, 20, 638–649. E. I. Budowsky, T. N. Drushinina, G. I. Eliseeva, N. D. Gabrielyan, N. K. Kochetkov, M. A. Novikova, V. N. Shibaev, G. L. Zhdanov, Biochim. Biophys. Acta 1966, 122, 213–224. S. Hirano, Biochem. Biophys. Res. Commun. 1971, 43, 1219–1222. J. J. Pavelites, J. Gao, P. A. Bash, A. D. Mackerell, J. Comput. Chem. 1997, 18, 221–239. I. Tvaroska, I. André, J. P. Carver, J. Phys. Chem. 1999, 103, 2560–2569. P. Petrova, J. Koca, A. Imberty, J. Am. Chem. Soc. 1999, 121, 5535–5547. K. B. Kim, E. C. Behrman, E. J. Behrman, Nucleotides & Nucleosides 1999, 18, 1055–1056. K. B. Kim, E. C. Behrman, C. E. Cottrell, E. J. Behrman, J. Chem. Soc., Perkin Trans. 2 2000, 677–682. P. Petrova, C. Monteiro, C. Hervé du Penhoat, J. Koca, A. Imberty, Biopolymers 2001, 58, 617–635. W. Saenger, Principles of Nucleic Acid Structure, Springer-Verlag, 1984, New York; pp. 201–219. R. H. Marchessault, S. Pérez, Biopolymers 1979, 18, 2369–2374. IUPAC-IUB. Arch. Biochem. Biophys. 1971, 145, 405. D. Neuhaus and M. Williamson in The Nuclear Overhauser Effect in Structural and Conformational Analysis VCH, 1989, Weinheim. K. Stott, J. Stonehouse, J. Keeler, T.-L. Hwang, A. J. Shaka, J. Am. Chem. Soc. 1995, 117, 4199–4200. J. E. Tanner, J. Chem. Phys. 1965, 52, 2523–2526 C. Monteiro, C. Hervé du Penhoat, J. Phys. Chem. A 2001, 105, 9827–9833. C. H. Lee, R. H. Sarma, Biochemistry 1976, 15, 697-704. J. V. O’Connor, H. A. Nunez, R. Barker, Biochemistry 1979, 18, 500–507.

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C. Monteiro, S. Neyret, J. Leforestier, C. Hervé du Penhoat, Carbohydr. Res. 2000, 329, 141–155. C. A. G. Haasnoot, F. A. A. M. de Leeuw, C. Altona, Tetrahedron 1980, 36, 2783– 2792. H. P. M. de Leeuw, C. A. G. Haasnoot, C. Altona, Isr. J. Chem. 1980, 20, 108–126. C. Altona, M. Sundaralingam, J. Am. Chem. Soc. 1972, 94, 8205–8212. G. Varani, I. Tinoco, Quart. Rev. Biophys. 1991, 24, 479–532. K. Bock, J. O. Duus, J. Carbohydr. Chem. 1994, 13, 513–543. M. M. W. Mooren, S. S. Wijmenga, G. A. van der Marel, J. H. van Boom, C.W. Hilbers, Nucl. Acids Res. 1994, 22, 2658– 2666. F. E. Hrusha, D. J. Wood, R. J. Mynott, R. H. Sarma, FEBS Lett. 1973, 31, 153– 155. D. J. Wood, F. E. Hrusha, R. J. Mynott, R. H. Sarma, Can. J. Chem. 1973, 51, 2571–2577. T. C. Church, I. Carmichael, A. S. Serianni, J. Am. Chem. Soc. 1997, 119, 8946–8964. R. T. Boeré, R. G. Kidd, Annu. Rep. NMR Spectrosc. 1982, 13, 319–385. J. G. de la Torre, V. A. Bloomfield, Quart. Rev. Biophys. 1981, 14, 81–139. D. C. McCain, J. L. Markley, J. Am. Chem. Soc. 1986, 108, 4259–4264. G. Lipari, A. Szabo, J. Am. Chem. Soc. 1982, 104, 4546–4559. D. E. Woessner, J. Chem. Phys. 1962, 37, 647–654. F. Heatley, Annu. Rep. NMR. Spectrosc. 1986, 17, 179–230. Y. Sugawara, H. Iwasaki, Acta Cryst 1984, C40, 389–393. B. Brooks, R. Bruccoleri, B. Olafson, D. States, S. Swaminathan, M. Karplus, J. Comput. Chem. 1983, 4, 187–217. M. M. Tirado, M. M.; J. G. de la Torre, J. G. J. Chem. Phys. 1979, 73, 1986–1993. L. E. Kay, L. K. Nicholson, F. Delaglio, A. Bax, D. A. Torchia, J. Magn. Reson. 1992, 97, 359–375. A G. Palmer, N. J. Skelton, W. J. Chazin, P. E. Wright, M. Rance, Mol. Phys. 1992, 75, 699–711.

58 59 60

61

62 63 64 65 66 67 68

69

70 71 72 73

74 75 76 77

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79 80

P. Stilbs, Progr. NMR Spectrosc. 1987, 19, 1–45. C. S. Johnson Progr. NMR Spectrosc. 1999, 34, 203–256. S. B. Engelsen, C. Monteiro, C. Hervé du Penhoat, S. Pérez, Biophys. Chem. 2001, 93, 103–127. G. Varani, F. Aboul-ela, F. H.-T. Allain, Progr. NMR Spectrosc. 1996, 29, 51– 127. T.-L. Hwang, A. J. Shaka, J. Am. Chem. Soc. 1992, 114, 3157–3159. H. Desvaux, P. Berthault, Progr. NMR Spectrosc. 1999, 35, 295–340. G. C. Levy, J. J. Dechter, J. Kowalewski J. Am. Chem. Soc. 1978, 100, 2308–2314. G. C. Levy, J. J. Dechter, J. Am. Chem. Soc., 1980, 102, 6191–6196. I. Solomon, Phys. Rev. 1955, 99, 559. N. Bloembergen, J. Chem. Phys. 1957, 27, 572. H. Sternlicht, R. G. Shulman, E. W. Anderson, J. Chem. Phys. 1965, 43, 3123. F. F. Brown, I. D. Campbell, R. Henson, C. W. J. Hirst, R. E. Richards, Eur. J. Biochem. 1973, 38, 54. N. Bloembergen, L.O. Morgan, J. Chem. Phys. 1961, 34, 842. B. Bleaney, J. Magn. Reson. 1972, 8, 91. W. Horrocks, J. Am. Chem. Soc. 1974, 96, 3024. A. T. Tu, M. J. Heller, Metal ions in Biological Systems, Vol. 1 Simple Complexes, Helmut Sigel (Ed), Marcel Dekker, 1974, New York; pp 1–116. E. Walaas, Acta Chem. Scand. 1958, 12, 528–536. S. J. Angyal, Adv. Carbohydr. Chem. Biochem. 1989, 47, 1–43. K. Dill, R. D. Carter, Adv. Carbohydr. Chem. Biochem. 1989, 47, 125–166. D. M. Whitfield, S. Stojkovski, B. Sarkar, Coordination Chemistry Reviews 1993, 122, 171–225. L. W. Jaques, E. B. Brown, J. M. Barrett, W. S. Brey, W. Weltner, J. Biol. Chem. 1977, 252, 4533–4538. D. I. Ito, S. Izumi, T. Hirata, T. Suga, J. Chem. Soc. Perkin I 1992, 37–39. G. W. Buchanan, Progr. NMR Spectrosc. 1999, 34, 327–377.

10.7 References 81

M.-D. Tsai, T. Drakenberg, E. Thulin, S. Forsén, Biochemistry 1987, 26, 3635– 3643.

R. E. London, A. D. Sherry, Biochemistry 1978, 17, 3662–3666. 83 N. Tjandra, Structure 1999, 7, 205–211. 82

271


Part C Interactions of Carbohydrates with Biomolecules Investigated by NMR Techniques and Applications


11

NMR Analysis of Carbohydrate – Carbohydrate Interactions Armin Geyer

11.1

Introduction

Leukocytes and other migrating cells present a complex language of glycoconjugates to communicate with their environment [1]. On their journeys through our bodies they selectively adhere to various other cell types or to the extracellular matrix. The glycoconjugates are involved in the decision on adhesion or repulsion between the cells. The glycocalix forms the front line of cell-cell recognition. Transient yet selective ligand-receptor recognition leads to movement under a controlled speed and direction, the fine-tuning of velocity being steered by gradually multiplying weak singular interactions to tighter polyvalent contacts [2]. Hakomori described the glycosphingolipid-based cell-adhesion and repulsion [3]. This cell-recognition process does not involve proteins, thus making the homotype binding between oligosaccharides of the cell membrane fundamentally different from other cell-recognition processes. The weakness of carbohydrate–carbohydrate interactions does not mean that these are of minor biological importance compared with other high affinity complexations. Transience is an asset of this biological recognition event, not a liability [4]. Soon after the protein-independent cell-adhesion was described, the question of structural details was approached by NMR spectroscopy [5]. Unexpectedly, the carbohydrates showed no calcium affinity in the NMR titrations. The oligosaccharides had been investigated in isotropic solution without their ceramide aglyca and consequently without the orientating effect of an underlying membrane. Lacking such preorganization, no homophilic recognition was observed between the carbohydrates. On a different scale, the hooks of a zipper or of a Velcro fastener need tethering to a supporting material to constructively interact with the other surface. Obviously, the binding is absent in an “isotropic” mixture of hooks and loops which are not supported by a scaffold. Can we expect to observe carbohydrate – carbohydrate interactions in isotropic solution? Preorganization as a requirement of the carbohydrate-carbohydrate interaction became obvious with the identification of glycosphingolipid microdomains [6]. In the beginning dismissed as isolation artifacts, microdomains and membrane rafts are now widely accepted, and numerous studies are currently investigating their composition and diffusion properties or

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even observing them directly by atomic force microscopy [7]. Yet the molecular surfaces of the cooperative carbohydrate–carbohydrate binding which stabilizes the microdomains remain the subject of speculation. The average diameters of microdomains are in the region of 20 nm, and aggregates of such size cannot be studied directly by high-resolution NMR. A second obstacle for solution NMR is the necessity for pre-orienting the carbohydrates at a phase barrier – the membrane – or on a self-organizing synthetic scaffold [8]. Ultra-low affinities of the individual carbohydrate–carbohydrate interactions combined with high off-rates of complexation, fast exchange on the NMR time scale, and the averaging of resonance signal sets make up the third group of problems. Finally, the conformations and relative orientations of monomers within homophilic complexes are more difficult to analyze by NMR than those within heterophilic complexes, which yield separate NMR resonance signals. On the other hand, only NMR spectroscopy can directly observe a complex in solution, analyzing the complementary molecular surfaces of the interacting species. Quantification of average interproton distances from NOE data identifies hydrophobic contact sites. Together with 3J couplings, chemical shifts, and relaxation data, the relative orientation of interacting species can be studied in solution. Based on the knowledge of the contact sites between glycosphingolipids, the overall structure of microdomains will be better understood. The dominating theme of this chapter is the NMR analysis of homophilic interactions between carbohydrates and the development of strategies to analyze weak binding and cooperative effects on membranes.

11.2

Membrane Models for High-Resolution NMR

Synthetic membrane models like micelles and liposomes can mimic the dense packing of sugar head groups on biological membranes. Tumbling rates decrease with increasing sizes of the membrane fragments, and excessive line-broadening is one consequence. Wideline 2H NMR spectra of selectively deuterium-labeled gangliosides on liposomes formed from 1-palmitoyl-2-oleoyl phosphatidylcholine were acquired [9]. Micellar aggregates of natural glycosphingolipids are too large for NMR analysis [10]. High-resolution spectra are obtained from glycolipids on micelle-forming synthetic detergents like sodium dodecylsulfate (SDS-D25) [11]. Uncharged micelles of similar size are obtained from dodecylphosphatidylcholine (DPC-D38). This environment leads to a line-broadening of less than 3 Hz for the carbohydrate chains of micelle-anchored glycolipids. Carbohydrate-enriched micelles are obtained from (semi-)synthetic glycolipids bearing only one lipid chain [12]. Specific carbohydrate – carbohydrate interactions have not yet been observed in the micellar environment; a reason for this could be the highly curved nature of the micelle surface. Planar phospholipid bilayer fragments, so-called bicelles, with diameters between 10 and 100 nm, are obtained from dimyristoyl phosphatidylcholine and var-

11.3 Carbohydrate – Carbohydrate Affinities

Fig. 11.1 Glycosphingolipids perform an axially symmetric rotation about the bilayer normal. Tilting and precession about this axis result in a cone-shaped overall movement, the ceramide primary alcohol group acting as a flexible joint between carbohydrate moiety and the membrane. Common structural features of the Lewis glycosphingolipids are a single lactose unit (black hexagons) to which at least one Gal-GlcNAc disaccharide (gray hexagons) is bound. The dimeric Lewis anti-

gens bear at the most three Fuc units (white hexagons), which stabilize a secondary structure. Oligosaccharide backbones of alternating b(1-3), b(1-4) glycosidic bonds of the GalGlcNAc disaccharide units (left, LeX and LeY series) form extended average conformations, while backbones of only b(1-3) glycosidic bonds (right, Lea and Leb series) result in bent structures which consequently rotate in a wider cone (Details in [16]).

ious detergents in the magnetic field of the NMR spectrometer [13]. The alkyl chains of the glycolipids can insert into the bilayers, but the resulting severe linebroadening effects restrict conformational analyses to 13C-labeled glycolipids [14]. Furthermore, such liquid crystalline membrane models tolerate only minor amounts of glycolipids, high dilution of carbohydrates being one plausible reason for the absence of carbohydrate–carbohydrate interactions in these membrane models. Nevertheless, several complex gangliosides were investigated, and possible influences of the membranes on the carbohydrate head groups were analyzed. Although the membrane environment restricts the accessible conformational space of the carbohydrate head group, specific interactions of sialic acids or other sugars with the membrane surface were not observed [15]. The orientation of the sugars toward the solvent can be visualized in the form of a rotation cone of the carbohydrate head group (Fig. 11.1 [16]). Detailed structural analysis of membrane-anchored amphiphiles will profit from further developments of highly solvated membrane models for NMR studies.

11.3

Carbohydrate – Carbohydrate Affinities

The affinities between uncharged carbohydrates are generally weak [17]. A 0.1 M solution of methyl-b-d-ribopyranoside leads to a 13C NMR chemical shift variation of Dd = + 0.15 ppm for the anomeric carbons of b-cyclodextrin, too small to quanti-

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fy the ratio of free to complexed ligand at various titration steps [18]. A stronger signal response is required to quantify weak binding affinities. Other sensitive NMR parameters like paramagnetic shifts, diffusion rates, or transfer NOEs can be measured. General NMR aspects of weak complexation have been discussed by Gemmecker [19]. Although several metal complexes of mono- and disaccharides are known [20], there is no metal mediated di- or even oligomerization of simple sugars. Protic organic solvents increase the metal ion affinities of sugars, and, by this, emphasize the structure dependence of complexation. Yet, weak complexes still require a large excess of metal ions, which then occupy secondary binding sites and render the separation of selective complexation from non-specific binding by NMR more difficult. The suspected interaction sites of the LewisX (LeX) pentasaccharide (Galb1-4[Fuca1-3]GlcNacb1-3Galb1-4Glcb1-O, where Gal = d-galactose, Fuc = l-fucose, GlcNAc = d-N-acetylglucosamine, Glc = d-glucose) were studied by Henry et al. in organic solvents [21]. The metal-binding sites were identified with moderate precision by distance triangulation methods in the vicinity of Fuc and lactose, but a homotype carbohydrate–carbohydrate binding was not observed.

11.4

LewisX Glycosphingolipids

A large fraction of the cell-surface glycosphingolipids present LeX as the terminal trisaccharide unit [22]. Draber showed that calcium-dependent homophilic recognition between LeX-LeX sphingolipids on intact cells was neutralized only by soluble LeX, but not by other sugars or membrane component [23]. Thus, the carbohydrate head group mediated the interaction, and the composition of the ceramide membrane anchor – controlling the phase transition temperature – is of minor relevance. The branched LeX trisaccharide (Galb1-4[Fuca1-3]GlcNacb1-O) is stabilized by hydrophobic stacking between the a-side of Fuc and the b-side of Gal. This welldefined solution conformation, with only very little averaging about the glycosidic torsions, made LeX an attractive NMR target [24]. The LeX pentasaccharide with an additional lactose unit is the smallest Lewis glycosphingolipid found on cellular surfaces. Fatty acids and sphingosine of varying chain lengths are found in the aglyconic ceramides. Microheterogeneity is also observed for the carbohydrate head group, and effective coupling and protecting strategies are necessary to make homogeneous glycosphingolipids and derivatives accessible for NMR studies [25]. The LeX-LeX interaction is shown schematically in Fig. 11.2 a. As mentioned above, there is no calcium complexation between LeX tri- or pentasaccharides in solution (Fig. 11.2 b). The equilibrium is far on the side of the uncomplexed monomers. Phase barriers are, in principle, no problem for solution NMR, but the addition of calcium ions to liposome-anchored LeX glycolipids leads to immediate precipitation. The formation of microdomains requires a dynamic equilib-

11.4 LewisX Glycosphingolipids

Fig. 11.2 (a) Schematic representation of a X

membrane-anchored Le pentasaccharide in equilibrium with a glycosphingolipid microdomain as postulated to occur on cellular membranes. Microdomains are in dynamic equilibrium with the monomeric sphingolipids. The cone model in Fig. 11.1 is valid for monomeric sphingolipids; their mobility is restricted within the microdomains. (b) The orientating effect of the membrane is absent in

an isotropic solution of LeX trisaccharides. The calcium ion complexation is disfavored and the equilibrium shifts to the left. (c) Only weak binding is observed for synthetic glycolipids consisting of an LeX trisaccharide linked to an SDS micelle by a triethylene spacer (Details in [27]). (d) Two LeX trisaccharides linked by an adequate spacer are thought to bind calcium ions strongly enough to make the complex accessible for NMR studies.

rium between free and complexed carbohydrates within one sample. This can be managed by a mixture of soluble LeX and membrane-anchored LeX glycolipids (Fig. 11.2 c [26]). The soluble LeX shows a small but detectable membrane affinity to liposomes which are decorated with LeX glycolipids. Soluble LeX binds transiently to the membrane, and consequently its average molecular tumbling rate slows down. As a result, NOESY cross signals with higher positive values (more negative NOE) are observed. The strong correlation between NOE intensity and tumbling rate in the region of sign inversion of the NOE leads to a detectable experimental signal even for a carbohydrate–carbohydrate affinity in the M–1 region. The LeX trisaccharide was identified as the minimal structural unit for the homophilic interaction, but no structural details are obtained with this method.

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11.5

Covalent Tethering of LeX Units [27]

If, in the case of the glycosphingolipids, the job of the membrane is confined to the preorganization of the carbohydrate head groups, a covalent spacer between the supposed recognition domains should effectively mimic this arrangement. Two trisaccharides binding one calcium ion is a reasonable assumption about stochiometry for the bulky sugars involved. The complex formation should be more favorable, with the equilibrium shifting to the right (Fig. 11.2 d). The synthetic model restricts the number of interacting oligosaccharide moieties. An NMR analysis then can identify the relative orientations of the trisaccharide units in the complex to define the complementary molecular surfaces within the homophilic interaction. The GlcNAc primary hydroxyl groups of the LeX methyl glycoside 1 are connected via a methylene group in the bis-trisaccharide 2. 2 retains sufficient relative

" H NMR spectra of 2 between 0 and 15.1 equivalents of calcium chloride in methanolD4. Considerable chemical shift variations are observed in the NMR titration. For Fig. 11.3

1

example, the exocyclic methylene protons of GlcNAc migrate in opposite directions. 2c-H, 3c-H, and 1c-H form a higher order spin system.

11.5 Covalent Tethering of LeX Units [27]

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Fig. 11.4 The 1H NMR chemical shifts [Hz] of 1 (top) and of 2 (below) in methanol are plotted against the amount of calcium chloride added. Only non-specific calcium binding is observed for 1, the resonance signals gradually migrating to lower fields (higher ppm). The large chemical shift variation with only a few equivalents of calcium chloride is due to a structural change of 2. Both, high-field and

low-field shifts are thus observed. Calcium complexation causes a high-field shift for 1cH which is inverted at higher calcium levels because of the non-selective binding of calcium to 2. Therefore, all curves – except for the solvent resonance – show a double exponential dependence on the calcium concentration.

mobility of the two trisaccharide units to permit either parallel or antiparallel dimerization. The bis-lactoside 4 served as a model for non-specific binding of calcium [28]. The NMR titrations of sugars 1–4 and calcium chloride were performed in methanol. The 1H NMR spectra of 2 with increasing calcium concentration are shown in Fig. 11.3. The 1H resonance signals were assigned, and sev-


Fig. 11.5 Scatchard plots of 1 (&), 2 (n), 3 (*) and 4 (l). The fraction of complexed carbohydrate (m) is plotted against the ratio of m/I (I = concentration of uncomplexed calcium ions). The affinity constant Ka [M–1]is obtained from the y-axis by linear extrapolation to m = 0. Only compound 2 yields a straight line with an affinity constant of Ka = 55 M–1.

Secondary binding sites are populated at high concentrations of calcium ions, and a reduced slope is observed at m > 0.7. Weak affinities below Ka = 10 M–1 are slightly overestimated because full complexation (m = 1) is not reached without secondary effects playing a dominant role.

eral well-separated signals could be used for the quantification of the calciumbinding affinity of 2. A plot of the chemical shifts in Hz of three selected resonances and the solvent methanol against the equivalents of calcium chloride added shows the strong calcium dependence (Fig. 11.4). Only for 2, a large chemical shift variation with only a few equivalents of calcium ions is observed. The affinity constant is defined by the ratio of complex to free components [Eq. (1), where ROH is the sugar]. Ka

ROH Ca2 ROH Ca2

m

ROH Ca2 ROH Ca2 ROH

1

The bound fraction (m was determined between 0% and 100%, and Eq. (2) was then analyzed graphically. m

Ca2 Ka Ca2 1

m Ka Ca2

mKa

2

The binding affinities Ka were determined from Scatchard plots (Fig. 11.5) [29]. The abscissa shows the bound fraction (m), and the ordinate shows the ratio of

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free calcium to the bound fraction m. The affinity constant is obtained by linear extrapolation to zero complexation (m = 0). The higher the determined value at the ordinate, the better the binding. Only 2 shows a straight line with cooperative calcium binding of both trisaccharide moieties. The affinity constant is approximately the product of the monomeric affinity constants, equivalent to the summation of monomeric free energies of binding.


Fig. 11.7 Solution conformation of the calcium complex of 2. Top: Ten snapshots from a molecular dynamics simulation including ROEderived distance restraints. The rotational mobility about the covalent tether was not restricted, and the experimental NOEs were included as weak additional restraints. The exocyclic torsion of GlcNAc (a and a') populates the gauche-trans rotamer in a and the gauchegauche rotamer in a'. The methylene spacer linking the two GlcNAc units is shown in green.

Rings a and a' are coplanar and assume a cross-shaped relative orientation. Both trisaccharide moieties are in fast conformational exchange, and the molecular dynamics simulation visualizes only one of the exchanging identical conformations. Bottom: The position of the calcium ion is tentatively assigned at the hydrophilic contact site of the trisaccharide moieties in the averaged conformation of 2. SCHAKAL (E. Keller, University of Freiburg, Germany).

3 Fig. 11.6 Compensated ROESY (600 MHz, 4 kHz spin lock, 200 ms mixing time, CD3OD, 300 K) of 2 in the presence of 15 equivalents of calcium chloride. Rotating frame NOEs, which are only visible in the presence of calcium chloride, are indicated by gray boxes. Other cross signals than those indicated do not change their intensities relative to the ROESY of 2 without calcium chloride. The cross signal intensities correspond to average interproton distances of between 1.8 and 4 Å. The chair conformation of pyranose rings is

characterized by the 3JH,H coupling constants. Several intraglycosidic NOEs, like Fuc-H4 to H4, served as calibration distances. Important for the relative spatial orientations of the pyranosidic rings are the transglycosidic NOEs between CH groups flanking the glycosidic bond: here, for example, the one from Fuc-H1 to GlcNAc-H3. The most predictive NOEs are between proton pairs separated by many bonds but close in space, so-called longrange NOEs, for example Fuc-H5 to Gal-H2.

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The affinity is strong enough to become detectable in water with Ka = 8 M–1. No enhancement was observed for lactosides 3 and 4: they show no cooperative binding of calcium ions. A large excess of calcium was used to determine the end points of titration. Non-specific calcium binding dominates above 20 equivalents of calcium chloride, visible as a kink in the Scatchard plot of 2. Based on this complex of moderate calcium affinity, the actual goal of this NMR investigation was approached: the identification of the relative orientation of two interacting LeX oligosaccharides. The structural differences between free and complexed 2 were studied by rotating-frame NOESY-spectra [30]. Under the experimental conditions – short mixing time of 200 ms – the volume integral of each cross signal correlates to a single interproton distance (two-spin approximation). The offsetcorrected cross peak intensities are then calibrated according to the r–6-dependence of the NOE with the assumption of isotropic tumbling of 2 (Fig. 11.6) [31]. Fixed intraglycosidic ROEs served as reference ROEs. Without calcium ions, 2 exhibits the same NOE intensities as those detected for the monomeric LeX-trisaccharide 1. Thus, the methylene spacer allows independent mobility of the trisac-

Fig. 11.8 Two LeX pentasaccharides (lactoses are shown with white pyranose rings and LeX trisaccharides are shown with filled hexagons) are sketched with the relative orientation of the LeX trisaccharide headgroups as determined in the calcium ion complex of 2. The Y shapes symbolize the branched LeX pentasaccharides shown on the left; arrows point to-

wards the membrane surface. Trans-homophilic contacts between glycolipids on different membranes and cis-homophilic contacts between glycolipids on the same membrane can aggregate to polyvalent cell-cell contacts. Both types of LeX dimers are formed via a single molecular surface.

11.6 References

charide units. In the presence of calcium ions, additional ROEs are observed (boxes in Fig. 11.6). For example, an ROE between H2 of the GlcNAc and the H2 of Gal is evident. These new short interproton distances identify hydrophobic contacts between the two LeX-trisaccharide moieties in fast exchange. The average interglycosidic distances were included as restraints in a molecular dynamics simulation. They are in agreement with a single structure characterized by a stacking interaction between the two LeX moieties. The two trisaccharides lie on top of each other and are approximately rotated by 908 against each other, resulting in a crossed relative orientation (Fig. 11.7). A cation binding site is formed by a hydrophilic pocket which is surrounded by the Fuc-2O, Fuc-3O, and Gal-6O together with Gal-2O and Gal-3O of the second trisaccharide moiety. From the cross-shaped relative orientation of the trisaccharide units, a crossshaped relative orientation of pairs of LeX-sphingolipids on the cell membrane was proposed. Fig. 11.8 shows how glycolipids can interact to stabilize a cell-cell contact. The cross-shaped dimerization allows for cis-homophilic and for transhomophilic binding without resorting to different recognition phenomena. Thus, one complementary molecular surface is sufficient to stabilize side-by-side contacts within the same membrane and additionally the head-to-head contacts between glycolipids from different membranes. A principle which is discussed for other cell-adhesion molecules, too [32]. Although it is potentially difficult to extrapolate conclusions beyond the environment where the experiments were carried out, NMR spectroscopy identifies a selfcomplementary molecular surface of the LeX antigen. The synthetic models of natural glycoconjugates can mimic the weak homophilic interactions, which are expected to occur in a similar way at cellular surfaces. NMR spectroscopy yields detailed structural information about the conformational aspects of cellular interactions.

11.6

References (a) R. A. Dwek, Chem. Rev. 1996, 96, 683– 720; (b) A. Varki, R. Cummings, J. Esko, H. Freeze, G. Hart, J. Marth (Eds.), Essentials of Glycobiology, Cold Spring Harbor Laboratory Press, New York, 1999. 2 M. Mammen, S.-K. Choi, G. M. Whitesides, Angew. Chem. 1998, 110, 2908– 2953; Angew. Chem. Int. Ed. Engl. 1998, 37, 2754–2794. 3 (a) I. Eggens, B. Fenderson, T. Toyokuni, B. Dean, M. Stroud, S. Hakomori, J. Biol. Chem. 1989, 264, 9476–9484; (b) N. Kojima, B. A. Fenderson, M. R. Stroud, R. I. Goldberg, R. Habermann, 1

T. Toyokuni, S. Hakomori, Glycoconj. J. 1994, 11, 238–248; (c) S. Hakomori, K. Handa, K. Iwabuchi, S. Yamamura, A. Prinetti, Glycobiology 1998, 8, xi–xix. 4 (a) S. Hakomori, Cancer Res. 1996, 56, 5309–5318; (b) N. V. Bovin in: Glycosciences: Status and Perspectives, H.-J. Gabius, S. Gabius (Eds.), Chapman & Hall, Weinheim 1997, 277–289; (c) K. Matsuura, H. Kitakouji, N. Sawada, H. Ishida, M. Kiso, K. Kitajima, K. Kobayashi, J. Am. Chem. Soc. 2000, 122, 7406–7407.

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J. K. Beattie, M. T. Kelso, Aust. J. Chem. 1981, 34, 2563–2568; S. J. Angyal, Adv. Carbohydr. Chem. Biochem. 1989, 47, 1– 43. B. Henry, H. Desvaux, M. Pristchepa, P. Berthault, Y.-M. Zhang, J.-M. Mallet, J. Esnault, P. Sinay¨, Carbohydr. Res. 1999, 315, 48–62. F. W. Symington, D. L. Hedges, S. Hakomori, J. Immunol., 1985, 134, 25–34. M. Boubelik, D. Floryk, J. Bohata, L. Draberova, J. Macak, F. Smid, P. Draber, Glycobiology 1998, 8, 139–146. (a) R. U. Lemieux, Chem. Soc. Rev. 1989, 18, 347; (b) Y. Ichikawa, Y.-C. Lin, D. P. Dumas, G.-J. Shen, E. Garcia-Junceda, M. A. Williams, R. Bayer, C. Ketcham, L. E. Walker, J. C. Paulson, C.-H. Wong, J. Am. Chem. Soc. 1992, 114, 9283; (c) P. Berthault, N. Birlirakis, G. Rubinstein, P. Sinay¨, H. Desfaux, J. Biomol. NMR 1996, 8, 23–35. Y. D. Vankar, R. R. Schmidt, Chem. Soc. Rev. 2000, 29, 201–216. A. Geyer, C. Gege, R. R. Schmidt, Angew. Chem. 1999, 111, 1569–1571; Angew. Chem. Int. Ed. Engl. 1999, 38, 1466–1468. A. Geyer, C. Gege, R. R. Schmidt, Angew. Chem. 2000, 112, 3382–3385, Angew. Chem. Int. Ed. Engl. 2000, 39, 3246–3249. Synthesis of 1, 2, 3, and 4: C. Gege, R. R. Schmidt, Carbohydr. Res. 2002, 337, 1089–1094. R. P. Junghans, Immunology Today 1999, 20, 401–406. (a) A. A. Bothner-By, R. L. Stephens, J. Lee, C. D. Warren, R. W. Jeanloz, J. Am. Chem. Soc. 1984, 106, 811–813; (b) A. Bax, D. G. Davis, J. Magn. Reson. 1985, 63, 207–213; (c) C. Griesinger, R. R. Ernst, J. Magn. Reson. 1987, 75, 261– 271. A. Kumar, G. Wagner, R. R. Ernst, K. Wüthrich, J. Am. Chem. Soc. 1981, 103, 3654–3658. C. Kasper, H. Rasmussen, J. S. Kastrup, S. Ikemizu, E. Y. Jones, V. Berezin, E. Bock, I. K. Larsen, Nat. Struct. Biol. 1999, 7, 389–393.


12

TR-NOE Experiments to Study Carbohydrate-Protein Interactions Jesus Jiménez-Barbero and Thomas Peters

12.1

Introduction

The recognition of oligosaccharides and glycoconjugates by enzymes, antibodies, and lectins is a topic of major interest [1]. It is believed that knowledge of the three-dimensional structure of carbohydrate-protein complexes will significantly assist in the design of new carbohydrate-based therapeutic agents [2]. Current developments in experimental techniques and instrumentation for the structural analysis of biological macromolecules have provided access to detailed information on the three-dimensional structure of several protein-carbohydrate complexes [3]. These structural data are complemented by thermodynamic data obtained from titration microcalorimetry, which allows one to distinguish between enthalpic and entropic contributions to carbohydrate-protein interactions [4]. Binding of carbohydrates to protein receptors is characterized by hydrogen bonding, van der Waals interactions, and stacking of hydrophobic sugar faces against aromatic and aliphatic amino acid side chains [5]. In some cases, salt bridges are also present. The comparative importance of apolar interactions (van der Waals and stacking) and polar interactions (hydrogen bonds and salt bridges) depends on the individual protein and the carbohydrate ligand, and remains a topic of current scientific discussion [6]. It has been recognized that water plays an important role in assisting the formation of specific carbohydrate-protein complexes, and present research attempts to identify and understand the molecular mechanisms by which water mediates carbohydrate-protein recognition [7]. Water molecules are often located in the binding pocket or at the surface of the protein to provide additional specific interactions, which help to stabilize the complex and to achieve higher selectivity for a particular carbohydrate ligand [8]. In addition, different metal ions have been shown to be of crucial importance for the formation of a variety of protein-carbohydrate complexes. For instance, calcium and manganese ions are encountered in some legume lectins, while the animal C-lectins are also calcium-dependent [9]. For the function of most glycosyltransferases the presence of manganese ions is essential because the metal ion specifically interacts with the activated sugar such as UDP-Galactose [10].

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In contrast to enzymes and to some antibodies, lectins bind monosaccharides rather weakly, and therefore they employ different strategies for enhancing both the specificity and the affinity of their interactions for more complex glycostructures [11]. Thus, by using different lectin subsites and/or subunits it is possible to obtain these enhancements, since, in this manner, several contacts between a given lectin and the carbohydrate may take place. Also, an increased affinity for oligosaccharides may result from clustering of individual binding sites in lectin oligomers [12]. The large size of carbohydrate-binding proteins (lectins, antibodies and enzymes) has long prevented direct studies by means of NMR. With the advent of new spectroscopic techniques considerable progress has been possible in this area of structural biology [13]. Carbohydrates also exhibit dynamic fluctuations, and therefore NMR measurements may well offer insights not only into the conformation of bound oligosaccharides but also into molecular motions on different time scales [14]. Thus, using NMR it is possible to deduce the specificity and the affinity of binding, e.g. by determining association constants and equilibrium thermodynamic parameters from titration experiments [15]. The relationship between NOEs and proton-proton distances is well established [16] and can be utilized for structural analysis at different levels of precision, with the full matrix relaxation analysis offering the most precise approach [16 b]. The full relaxation matrix approach has been extended to the calculation of TR-NOEs [16c], also taking into account distances between ligand and protein protons and incorporating the exchange kinetics of complex formation. NOE intensities are sensitive to conformer populations, and often a limited number of key NOEs is sufficient to estimate the distribution of conformers in free solution. By comparison with respective TRNOEs in the carbohydrate-protein complex, conclusions about the protein-bound conformation, i.e. the bioactive conformation of the carbohydrate ligand, can be obtained. Since many questions concerning protein-carbohydrate interactions are associated with the conformational behavior of the carbohydrates, we will focus in this chapter on a general way to decode the three-dimensional structure of a bound carbohydrate through TR-NOESY experiments.

12.2

The TR-NOE Experiment

It is obvious that knowledge about the bioactive conformation of a carbohydrate presents considerable implications for rational drug design [17]. The transferred nuclear Overhauser enhancement (TR-NOE), as pioneered by Bothner-By and later by Feeney and coworkers [18] and by Clore and Gronenborn [19] permits us to assess protein-bound oligosaccharides, i.e. their bioactive conformations. As in a standard NOESY, this experiment provides information about protons that are close in space, and it is therefore used to deduce conformational information. The TR-NOESY is performed with the standard NOESY pulse sequence, but is applied

12.2 The TR-NOE Experiment

to a protein-ligand mixture which represents a system in dynamic exchange. The ligand is present in excess over the protein, and TR-NOEs are observed on the signals of the free ligand. In general, for bound ligands which exchange with the free state at a fast rate on the relaxation time scale, transferred (TR-NOE) experiments provide a valuable instrument to determine the conformation of the bound ligand. In complexes involving large molecules, cross-relaxation rates of the bound state (rB), which depend on the respective interproton distances, the spectrometer frequency, and on the correlation time of the complex, are opposite in sign to those of the free state (rF) and produce negative NOEs. Therefore, the existence of binding may be easily deduced from visual inspection, since NOEs for small molecules are positive (Fig. 12.1). The conditions for the applicability of the TR-NOE experiment are well defined, depending critically on the dissociation rate of the protein-sugar complex and the molar fractions of free and protein-bound sugar: PROTEIN SUGARexcess $ PROTEINSUGAR Ka

PROTEIN SUGAR PROTEIN SUGAR

1 2

pb rB > pf rF

3

rB

4

k

1

where Ka is the association constant, pb and pf are the fractions of bound and free sugar ligand, and rB and rF are the cross-relaxation rates for the bound and the free ligand, respectively. k–1 is the off-rate constant. From condition (4) it is seen that the exchange reaction has to be fast on the relaxation time scale. Because of the relatively low values of cross-relaxation rates in diamagnetic systems (< 10 s–1), the fast exchange case usually holds, and the experiment is applicable. Under these conditions, and as an approximation, it can be stated that robs pb rB pf rF

5

The conditions required to monitor TR-NOEs are often satisfied by sugar-protein complexes [20]. This favorable situation is due to several reasons. Protein-carbohydrate interactions are usually weak, leading to fast exchange between the free and the bound states of the ligand. The perturbations of the conformational equilibrium of a given oligosaccharide upon binding to a protein are reflected by the TRNOEs. Apart from the simplified analysis described above, it is possible to perform a quantitative analysis of the build up of TR-NOEs of the ligand protons in the presence of chemical exchange. A full relaxation matrix approach is applied, with a relaxation matrix comprising the properties of the free and bound states of the ligand. The full relaxation matrix is a function of the correlation times and of the interproton distances of the corresponding state. Additionally, a kinetic matrix

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defines the exchange process, which includes the molar fractions of free and bound ligand and the exchange rates between states. The diagonal and off-diagonal elements of the relaxation matrix are affected by these exchange contributions. In this manner, a quantitative analysis of the observable cross-relaxation rates and their translation into accurate inter-proton distances for the bound state may be performed [21]. Therefore, the experimental TR-NOE cross-peak volumes can be translated into distances. Utilizing a qualitative approach, the isolated spin pair approximation may be used, accompanied by additional experiments which are able to distinguish or abolish artifacts such as spin diffusion effects (see below). If possible, a full relaxation matrix may be applied. This requires knowledge of the dissociation constant Kd and the dissociation rate constant k–1 [Eq. (4)]. If protein protons are included, a 3D model for the protein, preferably from NMR or X-ray structural analysis, has to be available too. 3D models of the ligand are available from molecular modeling using force fields that are parametrized for carbohydrates. Usually, the bioactive conformation is close to the global or a local energy minimum. A comparison of theoretical and experimental TR-NOEs then allows one to validate the bound conformation. As indicated above, protons of the protein-binding pocket also contribute to the TR-NOEs via intermolecular relaxation. This is the main reason for spin diffusion to occur, which leads to false inter-proton distances for the bound ligand. The explicit inclusion of protein protons into the calculation in theory leads to a better fit between experimental and theoretical data. In practice, many factors lead to a much more complicated situation, and expectations of generating more “precise” structures using such a high-level approach should not be too high. Intermolecular (protein-sugar) TR-NOEs or titration NMR data can help to identify the type of amino acid (and ideally its location in the peptide sequence) that participates in contacts with the bound glycostructure. Calculations with and without protein protons included can clarify their potential role for the analysis of the bioactive conformation of the carbohydrate ligand. For the calculation of TR-NOEs, an average correlation time (sc) is usually used, and this can be estimated from the average molecular weight of the complex (sc = ca. 10–12 ´ MW). Also, sc may be obtained in a semiquantitative manner from ratios between T1 values (or ratios of experimental cross-relaxation rates) of selected protons at two magnetic fields, or from T1/T2 ratios at a given magnetic field. 12.2.1

Experimental Aspects Sample Preparation and Experimental Set-up Usually, 0.4–0.5 mL of a 0.05–1 mM solution of receptor protein (lectin, enzyme, antibody) is used in TR-NOESY experiments. The ligand is typically present in 5to 100-fold molar excess over the concentration of binding sites. The ligand/protein ratio chosen depends on the kinetics of the exchange reaction and on the binding affinity. Preferably, two or three molar ratios should be tested. Since for 12.2.1.1


carbohydrates only the non-exchangeable HC protons are usually studied, the NH protons in the protein may be exchanged with D2O, and the samples are dissolved in phosphate buffer or deuterated Tris buffer in D2O. Exhaustive exchange of residual NH protons of the protein is achieved through repeated lyophilization after suspension in D2O. This, of course, requires that the protein remains active under these conditions. In general, dialysis or ultrafiltration techniques have to be applied. The experiments can also be performed in H2O, but then pulse sequences, such as WATERGATE, to remove the intense H2O signal have to be used, e.g. as implemented in the NOESY-WATERGATE experiment [22]. All components should also be passed through a micro-column containing Chelex to remove traces of paramagnetic ions. EDTA can also be helpful, providing that the binding ability of the protein in not calcium-dependent. In a first step, separate 1H NMR spectra of the protein and ligand are recorded. Then, a sample of the protein is titrated using a concentrated stock solution of the ligand. The reverse procedure, using a stock solution of the protein, is also possible, but not very practical for a variety of reasons [23]. To assess binding independently from the observation of TR-NOEs, chemical shift perturbations upon complexation of a ligand with a protein may be monitored. Likewise, changes in linewidths serve as indicators for ligand binding [24]. Recently, it was found that saturation transfer difference (STD) experiments provide a very robust and fast technology to assess a variety of characteristics of ligand binding [25, 17 c]. STD experiments also provide a tool to determine binding constants. In a qualitative manner, off-rate constants koff can be estimated from the dependence of the linewidth on the ligand/protein ratio [26]. Other non-NMR methods can be used to independently measure both, koff (e.g. surface plasmon resonance) [27] and the binding constant (e.g. microcalorimetry) [28]. As stated above, the independent determination of these parameters may allow a more detailed interpretation of TR-NOE data. TR-NOESY experiments are usually performed at different mixing times and ligand/protein ratios. Therefore, several days are typically required to obtain the data. For each ligand/protein ratio, and as in the regular 2D-NOESY, a minimum number of FIDs (at least 128) have to be recorded to achieve the desired digital resolution in f1, which can be further expanded using linear prediction algorithms. The number of scans is dictated by the amount of material available and by the sensitivity of the NMR instrument. The relaxation delay is usually between 2 and 5 s. Depending on the size of the protein, mixing times between 25 and 500 ms are used to obtain TR-NOE build-up curves. The initial slope of the TR-NOE curves is less affected by spin diffusion and is therefore used for an analysis of the data without taking into account protein protons. Auto- and cross-peak intensities are calculated from the volume integrals or from individual 1D slices of the 2D dataset using commercial software packages. Cross-relaxation rates may be estimated from the initial slopes of the time-dependent NOEs, from the cross-peak to auto-peak intensity ratios at a given mixing time, or by fitting the data obtained at different mixing times to a double exponential equation [29].

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The activity and/or binding ability of the protein should be determined before and after the TR-NOE experiments. In principle, data collected after a significant loss of binding specificity should not be used, since the binding site topology and thus the conformation of the bound ligand may change. The instrument to be used depends on various factors, obviously including accessibility to a high-field instrument and the complexity of the spectrum of the ligand with potential overlap between key protons. The solubility of the components also plays an important role, as well as the amount of material available for the measurements. For disaccharides a spectrometer operating at 400 MHz may be sufficient. The sensitivity of the experiment (and the cross-relaxation rates between protons) increases at higher magnetic fields. The availability of highest-field magnets and especially the implementation of cryo-probes will permit TR-NOE experiments to be performed with very small amounts of material. For instance, cryo-probes will allow protein amounts in the nmol range to be used. The assumption of positive cross peaks for the free ligand and negative ones for the bound ligand is not always valid. For ligands of the size of a pentasaccharide and above, the NOESY cross peaks will start to be negative already at 500 MHz and a temperature of 295 K. For larger oligosaccharides, or at lower temperatures, or at stronger fields, the free ligand will show negative cross peaks. Thus, the contribution of the free ligand should be taken into consideration, and an analysis using an extended full relaxation matrix with exchange is recommended. 12.2.2

Variations in the Regular 2D Sequence 1D Experiments For ligands that do not show overlap of key protons, 1D-NOE experiments can also be performed using either saturation of a given proton or selective inversion (see Chapter 4). In all cases, sufficient time should be given during individual scans (ca. 5 T1). For the saturation experiments, the irradiation time is usually between 0.1 and 1 s. The major drawback of the method is due to its intrinsic low sensitivity and to the possibility of additional saturation of hidden protein resonances. This saturation may be transferred to ligand protons, thus leading to a misinterpretation of the data. Transient experiments are preferable, following careful calibration of the selective inversion pulses and a realistic choice of the mixing time, considering that a substantial amount of relaxation occurs during the relatively long (tens of ms) inversion pulse. Especially if pulsed field gradients are used to enhance the selectivity of excitation, sensitivity has to sacrified, because during the delays relaxation of the signals occurs. The duration of the experiment will depend on the number of scans required for the adequate signal-to-noise ratio. 12.2.2.1


3D Experiments When heavy overlapping takes place, information on the key TR-NOEs can be obtained by extending the NMR data to a third dimension. Both homo- and heteronuclear 3D methods have been applied [30a, 30b, 31]. Provided that the oligosaccharide can be obtained 13C-labeled, isotope-filtered or edited experiments become possible. For instance, the bioactive conformation of a completely 13C-labeled Sialyl LeX tetrasaccharide bound to E-selectin has been determined through HMQC-NOESY experiments [31]. In this case, the experimental data were interpreted by using an extended full relaxation matrix approach with exchange. 12.2.2.2

12.2.3

How to Solve Experimental Complications Suppression of the Protein Envelope The TR-NOE experiment has complications, one of them being the presence of the protein protons in the spectrum. Depending on the size of the protein, these protons may provide either a very broad signal as background or relatively sharp lines due to the most flexible side chains. The fact that T2 relaxation times of the ligand protons are much longer than those of the receptor allow relaxation filtering modules to be implemented and to simplify the spectra by selectively removing peaks originating from the protein. Both T2- [32] and T1q-filters [33] have been proposed for this purpose. T2-filters may be applied with success when the T2 of the protein is comparable to or shorter than the lifetime of the ligand in the bound state. T1q filters are usually more efficient in suppressing the protein signals and are applicable when the ligand exchange rate is faster than the relaxation rates of the ligand protons. In addition, the conservation of the coherence during the exchange under the spin-lock pulse used in the T1q-filter is an additional advantage of this scheme. In particular, the T1q-filter is applied as a short (5–10 ms) spin-lock pulse with medium size intensity (4–8 kHz) immediately after the first 90 8 pulse of the TR-NOESY sequence. The phase of the spin-lock pulse is shifted 90 8 with respect to the hard 90 8 pulse. 12.2.3.1

Presence of Spin Diffusion Possibly the major complication is the potential presence of spin diffusion effects, which are typical for large molecules [34]. In this case, apart from direct enhancements between protons close in space, other spins may mediate the exchange of magnetization, thus producing negative cross peaks between protons far apart in the macromolecule. These peaks have the same sign as those coming from direct enhancements and cannot be easily distinguished. Thus, in TR-NOE experiments, protein- or intra-ligand-mediated indirect TR-NOE effects may lead to a false conformation for the bound ligand. Since the cross relaxation of the bound ligand depends on the correlation time of the macromolecular receptor, TR-NOE cross peaks are negative (same sign as diagonal peaks). Unfortunately, under these con12.2.3.2

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ditions, cross peaks originating from spin diffusion are also negative, making “true” and “false” enhancements impossible to distinguish. As indicated above, it is possible to take spin diffusion into account by using a quantitative analysis based on the extended full relaxation matrix approach. However, the flexibility of carbohydrate ligands, different correlation times for proton-pairs located in different regions of the ligand and many other factors lead to severe complications using this high-level approach.

Identification of Spin Diffusion by TR-ROESY As an example of interference of spin diffusion with the analysis of TR-NOE data, in one of the first reported TR-NOE experiments applied to carbohydrates the conformation of a fluorinated disaccharide Gal-b-(1 ? 6)-Gal-b-OMe bound to a monoclonal antibody was analyzed. On the basis of TR-NOEs it was concluded that the disaccharide underwent major conformational changes around the glycosidic linkage when bound to the antibody [32]. However, the re-evaluation of this problem by the same authors, using rotating frame Overhauser (TR-ROESY) experiments, demonstrated that the key TR-NOEs reported were mediated by protein protons [35]. In TR-ROESY, as in the regular ROESY experiment [36–38], direct cross peaks are always positive, that is, they show the opposite sign relative to the diagonal signals. Spin diffusion via one relay proton leads to negative cross peaks that can easily be distinguished from direct interactions. In TR-ROESY experiments, usually more than one relay proton from the protein binding site is involved, leading to cancellation of the respective cross peak. Therefore, if a cross peak is observed in the TR-NOESY spectrum and no cross peak appears in the TR-ROESY spectrum, it can be concluded that the cross peak in the TR-NOESY originated from spin diffusion. One important information is lost in TR-ROESY experiments: bound and free ligands both give positive signals, and therefore the experiment can only in combination with TRNOESY distinguish between ligands that bind and those that do not bind to a protein. Thus, TR-ROESY complements TR-NOESY, providing conformational information, which is less contaminated by spin-diffusion-type artifacts (Fig. 12.1). Most of the TR-NOE analysis uses a combination of TR-NOESY/TR-ROESY data. From the experimental point of view the experiment can be performed by using a constant-phase spin-lock period for mixing (50–500 ms) or using the T-ROESY scheme [39], in which phase-alternated 180 8 pulses are employed. The T-ROESY sequence effectively suppresses the Hartmann-Hahn effects frequently found in ROESY spectra [37, 38] of glycostructures, for which little chemical shift differences occur between J-coupled protons. However, proton pairs in T-ROESY crossrelax in a tilted frame, somewhere midway between the longitudinal and transverse frames, so that the experimental cross relaxation is averaged between rnoe and rroe. Since for the bound state they are opposite in sign, they partially cancel each other, thus leading to a weaker signal-to-noise ratio than regular ROESY [40]. It should be noted that spin diffusion processes and direct dipolar interactions may occur simultaneously, leading to a partial or total cancellation of the positive 12.2.3.3


Fig. 12.1 Schematic representation of NOESY, TR-NOESY and TR-ROESY for a small molecule. Positive cross peaks are observed in the free state. Negative cross peaks are evident in the bound state, but spin diffusion

(three-spin) effects may contaminate the information. The use of TR-ROESY may help to differentiate between direct NOEs (positive) and three-spin effects (negative). See text for further explanation.

(direct dipolar) and negative (spin diffusion) contributions. In principle, these points may be addressed quantitatively, using the extended full relaxation matrix with exchange described above. However, other experimental schemes have been proposed to detect the interference of spin diffusion pathways.

Suppression of Spin Diffusion via MINSY One possibility is the use of the simple MINSY experiment [41], which allows one to selectively switch off relaxation pathways during the mixing time of the TRNOESY experiment by selectively saturating a spin or group of spins that are assumed to be responsible for the spin diffusion process. From the experimental point of view, low power irradiation at a given frequency is employed during the mixing time. This feature can be easily implemented in the 2D or 1D transient versions of the TR-NOESY. 12.2.3.4

Suppression of Spin Diffusion via QUIET-NOESY Probably the most careful way of detecting spin diffusion is through the use of the QUIET-versions [42] of the NOESY (or off-resonance ROESY) experiments [43]. In this case, pairs or groups of spins, which are expected to give mutual TR-NOEs, are inverted with a double or multiple selective shaped 180 8 pulse at the middle 12.2.3.5

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of the mixing period. This inversion leads to the total cancellation of all dipolar magnetization transfers except of those that are due to the direct interactions between the spins of interest (those inverted). The method is robust to eliminate spin diffusion, and the only minor drawback resides in the necessity of performing several experiments and in the constant attenuation of the intensities due to the unavoidable loss of magnetization during the band-selective inversion pulse. Artifacts can arise when protein protons, which are responsible for the spin diffusion pathway, are inverted simultaneously with the ligand protons under investigation. 12.2.4

Experimental Protocol for TR-NOE Experiments

First, choose the conditions of pH, temperature, and magnet(s) that will be used for the experiments, depending on accessibility and stability of the biomolecules. If possible, perform independent measurements of binding affinity and kinetics (koff) of the binding reaction. 1. Prepare a solution of the protein (ca. 0.05–1 mM) and transfer it to the NMR tube. 2. Prepare a concentrated solution of the ligand (ca. 0.1–5 mM). 3. Titrate the protein with the ligand solution and follow perturbations in chemical shifts and linewidths, and, if required, perform saturation transfer difference experiments (1–2 s saturation time) to unambiguously detect binding (be aware that saturation transfer difference spectra give best results if a ligand-to-protein ratio of ca. 100:1 or more is approached). 4. Preferably, choose two or three ligand/protein molar ratios (between 10 : 1 and 100 : 1) which can be useful to perform the experiments. Linewidths should not be too large, but still negative peaks should be observed in TR-NOESY experiments. Be ready to prepare samples for each ligand/protein ratio. Decide whether T2 or T1q filters have to be used to suppress the protein background. 5. Estimate T1 (and T2 if possible) of one or several protons of the ligand. These measurements are useful to set the recycling delay and to estimate the average correlation time. If possible, perform these measurements at two magnetic fields. 6. For each ligand/protein molar ratio, perform a series of TR-NOESY experiments (at least two) with mixing times between 50 and 500 ms. If possible, perform the measurements at two magnetic fields. 7. Perform also additional TR-ROESY (mixing times between 100 and 400 ms) and/or TR-QUIET-NOESY experiments (mixing times between 100 and 500 ms). In this latter case, the target regions to be selectively inverted have to be chosen in advance, depending on the results of the TR-NOESY and TRROESY experiments. 8. Analyze the cross-peak intensities by measuring volumes or by integrating 1D slices from the 2D spectra for each ligand/protein ratio. Get estimates of cross-relaxation rates.


9. Translate the cross-relaxation rates into distances from the initial slopes of the TR-NOE curves. Consider the information of the TR-ROESY/QUIET-TRNOESY experiments. In a first step, use the relaxation information of an intra-residue proton pair as internal reference. If possible, use one intra-residue proton pair of each moiety involved at each glycosidic linkage as a reference for estimating the distances across the glycosidic linkage. 10. Perform molecular mechanics, dynamics or Monte Carlo calculations to generate potential bound conformations of the ligand. Inspect the proton-proton interresidue distances from the calculations and compare them to those experimentally estimated. At this step, it may be helpful to perform restrained molecular mechanics, dynamics or Monte Carlo calculations to fit the experimental distances. In cases where more than one conformation can be bound, ensemble averages of conformers have to be considered. 11. For each, ligand/protein ratio, use an extended full relaxation matrix with exchange for the obtained conformer(s) to estimate cross-relaxation rates, and compare them to those obtained experimentally. At this point sc, the association constant, and koff should be known. Repeat the matrix calculations with different values of these parameters to validate the values. If possible, compare them to values obtained by independent experimental techniques. 12. Inspect visually the obtained conformers, and calculate the free energy difference with respect to the global minima. 13. Try to validate the results by NMR (look for protein-ligand intermolecular TRNOEs), or modeling (docking to a protein 3D structure obtained by homology building or by X-ray). As an example, see the description of the binding of Kdo-containing disaccharides to two monoclonal antibodies [44, 45]. 12.2.5

Applications and Examples

Different studies focused on the structural events that mediate the molecular recognition processes between proteins and carbohydrates employing lectin-, antibody-, and enzyme-type receptors [46]. Specific comparisons of the differential binding of natural and modified analogs have also been reported [47]. We will describe some of the key examples, while, for more detailed information on specific cases, the reader may consult the references specified in Tab. 12.1, in which other cases of sugar-protein interactions studied by TR-NOE are presented. Several examples are also presented in Chapters 4 and 8 in this book.

Recognition of the Global Minimum Conformation Although there is no general rule, in many cases protein binding sites are well preorganized to recognize the global minimum energy conformation of a saccharide. 12.2.5.1

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12 TR-NOE Experiments to Study Carbohydrate-Protein Interactions Tab. 12.1 Selected examples of applications of TR-NOE to the study of protein-carbohydrate interactions. Other examples are described in detail in the text. Theoretical analysis [83] and applications to the analysis of mixtures [89] and discrimination of epitopes [91] have also been reported

Protein

Carbohydrate

Reference

Dolichos biflorus Dolichos biflorus Strep 9 antibody Lentil lectin Glucoamylase Verotoxin Maclura pomifera agglutinin Viscumin and galectin-1 Glucosidase 3'-Phosphotransferase Chorionic gonadotropin Fibronectin Endoglucanase Antibody Fv fragment Antithrombin Hevein domains Aurelia aurantia agglutinnin Wheat germ agglutinnin

Blood group A Forssman pentasaccharide Branched trisaccharide Sucrose Maltoside heteroanalogs Globoside T-antigen disaccharide Galactobiosides S-cellobiose Aminoglycosides N-glycan chain Heparin Cellooligosaccharides Estrone-3-glucuronide Heparin tetrasaccharide Chitooligosaccharides Carba fucosides S-chitobioside

71 71 72 73 74, 75 76, 81 77 78, 80 79 82, 92 84 85 86, 87 88 90 93–99 100 101

The first TR-NOE study in the carbohydrate field used one-dimensional transferred NOE (1D-TR-NOE) experiments to study the binding of methyl b-lactoside to the B chain of the toxic galactose-binding lectin ricin. Prestegard and coworkers [48] used a selectively deuterated substrate to show that that only minor changes in the conformation of free methyl b-lactoside occurred upon binding to ricin-B. Two years later [49], the same group studied the ricin-B-bound conformation of flexible melibiose [Gal-a(1 ? 6)-Glc], demonstrating that only one of the two solution conformations of melibiose was selected by the lectin, thus causing a shift in the solution equilibrium. Docking studies indicated that the protein excluded binding of certain ligand conformations on the basis of steric interactions between the polypeptide and the Glc moiety of the sugar. Later, the conformational changes that occur when methyl a-lactoside-Gal-b(1 ? 4)-GlcaOMe- bound to ricinB chain were studied [50]. The observed data indicated that the protein caused a slight conformational variation in the glycosidic torsion angles of methyl a-lactoside, although the recognized conformer was still within the lowest energy region. Molecular modeling using molecular dynamics, minimization, and docking of the disaccharide within the binding site of ricin B permitted the proposal of a mode of binding in which both van der Waals contacts and hydrogen bonding contribute to the stability of the complex. As with ricin/lactose, there are other cases in which there are no major variations in the conformational behavior of the oligosaccharide upon protein binding.


This is, for instance, the case for galectins, for which always syn-conformers (} 50–60 8, w 0 8) are recognized, as demonstrated in the binding of Galb(1 ? 2)Galb-(1 ? R) to the galectin of chicken liver [51], and for the binding of Galb-(1 ? 3)Glc, Galb-(1 ? 2)Xyl, Galb-(1 ? 3)Xyl, and Galb-(1 ? 4)Xyl to bovine heart galectin-1 [52].

Simultaneous Recognition of Different Conformations However, there are also cases in which the protein does not select a single conformer. Aleuria aurantia agglutinin (AAA) simultaneously recognizes different conformations of Fuc-a(1 ? 6)-GlcNAcb-(1 ? OMe) [53]. This disaccharide, which is fairly flexible when free in solution, appears to remain, to a certain extent, flexible around the glycosidic linkage within the lectin-binding site. An analogous case has been reported for the complex between methyl b-allolactoside (Galb(1 ? 6)Glcb-OMe) and ricin B [50]. In this case, different conformations around the }, w, and x glycosidic bonds of methyl b-allolactoside are recognized by the lectin. In fact, for this complex, only the TR-NOESY cross-peaks corresponding to the protons of the galactose residue were negative, as expected for a molecule in the slow motion regime. In contrast, the corresponding cross peaks for the glucose residue were ca. zero, as expected for a molecule with motional properties practically independent of the overall motion of the protein. 12.2.5.2

Protein-induced Conformational Selections Carbohydrate-binding or -processing proteins may select just one of the conformers present in the conformational equilibrium for the free state. One of the paradigmatic cases relates to the sialyl LewisX (sLeX, [aNeuNAc-(2 ? 3) b-Gal(1 ? 4)aFuc(1 ? 3)]Glc) oligosaccharide interacting with selectins. The LewisX tetrasaccharide exists in solution as an equilibrium of several conformations, which are mainly characterized by the orientations of the N-acetyl-neuraminic acid residue [54]. Using spin-locked filtered TR-NOESY experiments and Metropolis Monte Carlo calculations [55], the bioactive conformation of sLeX bound to E-selectin was identified. The most relevant conclusion is that E-selectin exclusively complexes a conformation of sialyl LewisX from the conformational equilibrium in aqueous solution in which the sialic acid shows an orientation defined by (}/w ca. –76/6), already reported to be present in free solution. On the other hand, the orientation of the fucose residue (}/w ca. 38/26) differs from that preferred in aqueous solution. This work clarified previous discussions on the conformational changes of sLeX upon binding to E-selectin [56]. The conformation of sLeX bound to E-selectin was also compared to that recognized by P- and L-selectin [57]. It was demonstrated that the bound conformation of the branched LeX trisaccharide was similar to the conformation of the free ligand. However, E- and P-selectin recognize a different conformation around the sialic acid glycosidic linkage than L-selectin. Molecular motions of an extended oligosaccharide within the binding site may produce a variation of the cross-peak intensities for the different monosaccharide 12.2.5.3

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entities that compose the glycostructure. As stated above for the ricin-B/ Galb(1 ? 6)Glcb-OMe case [50], negative and positive (or almost zero) cross peaks may coexist, provided that the binding site only accommodates one or two of the residues and the remote residues do not show any contact with the protein. Obviously, in this case, the individual residues of the glycostructure in the bound state possess different correlation times. These effective correlation times will be larger for residues close to the protein and will decrease according to the length of saccharide chain. In such cases, the sign of the cross peaks may depend on the ligand/protein ratio (of course, they also depend on koff). For instance, at very high ligand/protein ratio (50/1–100/1), with a major molar fraction of the free state, probably only those residues that are tightly bound to the protein (and that indeed are affected by the large correlation time of the macromolecule) may show negative cross peaks. Under these conditions, the remote residues far from the protein binding site will probably show either positive, or zero, or very weak negative cross peaks (effective correlation time corresponding to a relatively fast motion). At intermediate ratios (20/1–40/1), the remote residues may start to show negative cross peaks also, since the amount of free ligand is now much smaller. However, those residues close to the binding site may feel “too much” of the protein, their correlation time being also very large, and they therefore show very broad and weak TR-NOESY crosspeaks due to the very efficient relaxation in the bound state. At low ligand/protein ratios, the cross peaks for the residues in close contact with the protein may completely disappear. Such observations became evident in the NMR analysis of a complex of a lectin from Dolichos biflorus and the Forssman pentasaccharide GalNAca-(1 ? 3)GalNAcb-(1 ? 3)Gala-(1 ? 4)Galb-(1 ? 4)Glc [58]. In this case, the combined TRNOESY/TR-ROESY analysis revealed close contacts between the non-reducing disaccharide moiety of the carbohydrate and the lectin binding site. Using a protocol of recording experiments at different lectin:sugar ratios, the authors deduced two distinct classes of NOE cross peaks which reflected the size of the carbohydrate epitope and thus also of the binding pocket of the lectin. In order to detect contacts between the protein and the carbohydrate chain, T2-filtered TR-NOESY spectra were performed which allowed one to detect NOEs between the terminal disaccharide fragment and protein protons, most likely belonging to Leu residues, in agreement with the previously reported molecular modeling study of the complex.

Protein-induced Conformational Variations Several cases of major protein-induced conformational changes have been reported (Tab. 12.1). Bundle and coworkers have presented TR-NOESY evidence of recognition of anti-type conformation, usually populated below 10% for regular oligosaccharides [59]. They also showed that a branched trisaccharide (a-Galp(1 ? 2)[aAbep(1 ? 3)]-Manp-1 ? OMe), related to the antigenic determinant of a Salmonella polysaccharide, undergoes an antibody-induced conformational shift about one glycosidic linkage (Gal-Man) [60]. Conformational variation between free and bound states also occurs for sucrose octasulfate when interacting with the acidic fibroblast 12.2.5.4


growth factor. In this case, strong electrostatic interactions between guest and host may be the dominant factor for the deformation of the sugar [61].

12.2.5.5 Use of Structurally Modified Carbohydrate Analogs

Obviously, not only natural ligands, but also structurally-modified oligosaccharides may be used as lectin ligands or as inhibitors of carbohydrate-processing enzymes, and thus these analogs may be employed to deduce enzymatic mechanisms. Moreover, conformational differences between free and protein-bound natural carbohydrates and synthetic analogs may also be assessed by TR-NOE experiments. As a particular case, it has been demonstrated that C-lactose, a non-hydrolyzable lactose analog, is selected by ricin-B [62], a toxic galactose-binding lectin, by a hydrolytic enzyme, E. coli b-galactosidase [63] and by bovine heart galectin-1 [64] in three distinct conformations: anti-w, anti-U, and syn-U, respectively. A protocol based on TR-NOESY experiments assisted by docking methods was carried out. The conformational study of C-lactose in the free state showed that the exoanomeric conformation around the C-glycosidic bond was adopted. However, the conformation around the aglyconic bond was rather different from that of the natural compound [65]. For O-lactose [66], ca. 90% of the population was located around the so-called minimum syn, }/w 54/18, and ca. 10% of population around minimum anti, }/w, 36/180. C-lactose was shown to exhibit much higher flexibility than its O-analog, and three conformational regions (syn, anti and gauche– gauche) were significantly populated in solution (Fig. 12.2). Regarding the C-lactose recognition by galectin-1 [64], the comparison between the NOESY/ROESY spectra of C-lactose recorded in the absence and in the presence of galectin-1 showed the disappearance of the key NOEs for the anti-W and the anti-U geometries. In contrast, the observed interresidue NOEs indicated that the bound conformation belonged to the exo-syn-U, syn-W family. Moreover, competitive TR-NOE experiments were performed in such a way that methyl-b-lactoside was added to the NMR tube containing C-lactose/galectin-1. It was observed that the cross peaks corresponding to the C-analog changed their sign to positive, while those pertaining to lactose appeared as negative, indicating that both ligands approach to the same binding sites and that the affinity for lactose is higher than for the C-analog. Using an MD/docking protocol, it was possible to show that major interactions take place between the galectin and the galactose moiety. Nevertheless, the Glc residue was also involved in the binding: the complexes highly favored the syn-U, syn-W conformer, since only in this case it is possible that three hydrogen bonds, involving O-3 of the remote Glc residue, are formed: two with Glu-71 and one with Arg-48. These additional interactions are no longer possible for the other conformational families. In contrast, the comparison between the NOESY and ROESY spectra of C-lactose, recorded in the absence and in the presence of ricin-B [62], indicated that conformers having syn-W or anti-U, were not bound. In this case, the experimental results indicated that ricin-B selects different conformers of C-lactose, (anti-W), and its O-analog,

303

304


Fig. 12.2 Schematic representation of the three possible low-energy conformers for b(1 ? 4) linked disaccharides. Relevant NOEs are indicated.

(syn-W). It was also demonstrated that both ligands compete for the same binding sites of the lectin and that the affinity constant of C-lactose is smaller than that of its O-analog. After a docking protocol, because of the lack of major contacts between the remote Glc residue and the lectin, it seems that the ricin-B binding site is accommodated to always select the global minimum conformation of the glycoligand.


Passing to enzymes, it was also demonstrated by TR-NOESY experiments [63] that E. coli b-galactosidase can even bind the high energy exo-anti-U, syn-W conformer of C-lactose (destabilized in 9 kJ/mol with respect to the global minimum in free solution). In this case, the NOESY spectra of C-lactose recorded in the presence of the enzyme showed the disappearance of the exclusive NOES for the global and secondary energy minima, anti-W anti syn-U/syn-W. In turn, the H4/H2' NOE, which displayed weak intensity for the free ligand (absent for lactose itself), was now the strongest interresidual one in the spectrum. Also, the observed NOEs for the methylene protons indicated that the bound conformation belonged to the highenergy exo-anti-U, syn-W family. In this case, the fact that the binding of C-lactose was active site selective was shown by competitive TR-NOE experiments which were also performed by adding a known competitive inhibitor, namely isopropyl thiogalactoside (IPTG) to an NMR tube containing C-lactose and the enzyme. It was observed that the TR-NOE signals of C-lactose disappear at equimolar concentrations of IPTG with concomitant appearance of strong negative NOEs for IPTG. Docking experiments indeed showed that the global minimum conformations of either C- or O-lactose are not allowed within the binding site. Only the distorted exo-anti-U, syn-W conformation fits into the deep binding site without severe steric conflicts, in agreement with the experimental NMR results. In this case, the authors have speculated that the recognition of this high-energy conformation of C-lactose could have implications for the catalytic mechanism, lowering the energy barrier necessary for hydrolysis. Recent results have also demonstrated that the anti-U conformer of S-lactose (with a thio-interglycosidic linkage) is also bound, and that therefore the recognition of the high energy conformer of C-lactose is not an artifact due to the presence of the CH2-group [67]. In this context, it is worth pointing out that TR-NOESY experiments can also be used to detect conformational distortions in sugars, different from rotations around the glycosidic or C5-C6 torsions. For instance, distorted chair conformations of the galactose moiety of lactose, 2'-deoxy lactose, and allolactose are not bound by the E537Q mutant of that E. coli b-galactosidase [67]. This enzyme conservative mutant lacks the nucleophile; it is catalytically inactive and therefore can be used for TR-NOE experiments: the ligand is not hydrolyzed during the course of the experiment, as with the wild-type enzyme. In this case, the Gal- H-1/H-3 and Gal-H-1/H-5 TR-NOE cross peaks, which define the galactose moiety, are very weak, in contrast to the expectations for a regular 4C1 chair. They are ten times weaker than the equivalent cross peaks for the corresponding Glc-residues, independently of the ligand/protein ratio (from 20 : 1 to 80 : 1). According to the full relaxation matrix calculations, the average H-1'/H3' and H-1'/H-5' distances in the galactose chairs of the O-lactose analogs 5 is ca. 2.9-3.0 Å, far from the average 2.45 Å for a regular 4C1 chair, thus indicating a significant distortion of the pyranose ring. Normal distances were estimated for the H-3'/H-5' cross peaks, providing evidence that the distortion caused by the E537Q enzyme is focused on the anomeric region of the pyranose ring. The geometry is probably a flattened chair form with the C5-O5-C1-C2 torsion angle adopting a

305

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value of ca. –25 8 instead of the regular one of –60/–65 8. These experimental results lead to important conclusions: that E. coli b-galactosidase (WT or E537Q) always selects a high energy conformer of its bound O-glycoside or C-, S-glycomimetic, and that this recognition takes place before the catalytic reaction itself has started. For the C- and S-analogs the high-energy conformer is produced upon rotation around the glycosidic }-angle, while for the O-glycosides distortion of the chair is produced by the enzyme. Nevertheless, the three-dimensional shape of both types of conformers is fairly similar, with the aglycon adopting almost the same spatial orientation with respect to the glycon Gal moiety. Indeed, molecular modeling studies indicate that both types of conformers (distorted-U or distortedchair) may be bound without significant distortion of the enzyme binding site [65].

Other Developments TR-NOESY experiments have also been applied to the identification and characterization of biologically active molecules from a mixture [68]. As already stated above, the sign of transferred NOEs is opposite to that of NOEs of small molecules that do not bind to a protein, and thus an unequivocal and fast identification of molecules with binding properties is possible. This technique has been extended by the more versatile and robust STD experiment [25, 17]. 12.2.5.6

12.2.6

Perspectives

The use of TR-NOESY experiments is useful to gain information on the conformational features of the bound state in a number of molecular recognition processes in which carbohydrates are involved. Comparison with TR-ROESY and/or QUIETTR-NOESY experiments should also be performed to detect spin diffusion effects. Future access to 13C-labeled molecules may expand the range of applicability to more complex systems. Nevertheless, to deduce the conformation of the bound state, other experiments have been recently described which are independent of NOEs. The molecular alignment in a strong magnetic field induced by the use of dilute crystalline liquid media (see Chapters 2 and 9) has been applied to deduce the orientation of oligosaccharides within protein-binding sites. Other NMR experiments, which are based on the transfer of cross correlation (see Chapter 5) may be used to deduce the bound conformation of biomolecules [69, 70], since they contain information about angles between atomic vectors in different sides of the molecule. However, the experiments will be useful provided that the ligands are labeled with stable isotopes (i.e. 13C). The application of these methodologies to glycostructures gives access to new information about bound conformations, and this can be used in the design of a better rational inhibitor.

12.3 References

12.3

References 1

2

3 4 5

6 7 8

9

10 11

12

13 14 15 16

H. J. Gabius, S. Gabius (Eds.), Glycosciences: Status and Perspectives. Chapman & Hall, London, 1997. H. Rüdiger, H.-C. Siebert, D. Solís, J. Jiménez-Barbero, A. Romero, C.-W. õ, H.-J. von der Lieth, T. Díaz-Maurin Gabius, Curr. Med. Chem. 2000, 7, 389– 416. H. Lis, N. Sharon, Chem. Rev. 1998, 98, 637–674. E. Toone, Curr. Opin. Struct. Biol. 1994, 4, 719–728. R. Loris, T. Hamelryck, J. Bouckaert, L. Wyns, Biochim. Biophys. Acta. 1998, 1383, 9–36. R. A. Dwek, Chem. Rev. 1996, 96, 683– 720. R. U. Lemieux, Acc. Chem. Res. 1996, 29, 373–380. (a) J. M. Rini, Y. D. Lobsanov, Curr. Opin. Struct. Biol. 1999, 9, 578–584. (b) W. I. Weis, K. Drickamer, Annu. Rev. Biochem. 1996, 65, 441–473. (c) N. K. Vyas, Curr. Opinion Struct. Biol. 1991, 1, 732–740. (a) D. N. Moothoo, J. Naismith, Glycobiology 1998, 8, 173–181. (b) K. Drickamer, Curr. Opin. Struct. Biol. 1999, 9, 585–590. U. M. Unligil, J. M. Rini, Curr. Opin. Struct. Biol. 2000, 10, 510–517. E. J. Gordon, J. E. Gestwicki, L. E. Strong, L. L. Kiessling, Chem. Biol. 2000, 7, 9–16. (a) C. S. Wright, J. Biol. Chem. 1992, 267, 14345–52. (b) P. I. Kitov, J. M. Sadowska, G. Mulvey, G. D. Armstrong, H. Ling, N. S. Pannu, R. J. Read, D. R. Bundle, Nature, 2000, 403, 669–672. J. O. Duus, C. H. Gotfredsen, K. Bock, Chem. Rev. 2000, 100, 4589–4614. A. Poveda, J. Jiménez-Barbero, Chem. Soc. Rev. 1998, 27, 133–143. K. A. Kronis, J. P. Carver, Biochemistry, 1985, 24, 826–833. (a) D. Neuhaus, M. P. Williamson, The Nuclear Overhauser Effect in Structural and Conformational Analysis, Wiley-VCH, 2000. (b) R. Stolarski, W. Egan, T. L.

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22 23

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