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Topics in Current Chemistry Recently Published and Forthcoming Volumes
NMR of Proteins and Small Biomolecules Volume Editor: Guang Zhu Vol. 326, 2012 Molecular Imprinting Volume Editor: Karsten Haupt Vol. 325, 2012 Activity-Based Protein Profiling Volume Editor: Stephan A. Sieber Vol. 324, 2012 Beauty in Chemistry Volume Editor: Luigi Fabbrizzi Vol. 323, 2012 Constitutional Dynamic Chemistry Volume Editor: Mihail Barboiu Vol. 322, 2012 EPR Spectroscopy Volume Editors: Malte Drescher, Gunnar Jeschke Vol. 321, 2012 Radicals in Synthesis III Volume Editors: Markus R. Heinrich, Andreas Gansa¨uer Vol. 320, 2012 Chemistry of Nanocontainers Volume Editors: Markus Albrecht, F. Ekkehardt Hahn Vol. 319, 2012 Liquid Crystals: Materials Design and Self-Assembly Volume Editor: Carsten Tschierske Vol. 318, 2012 Fragment-Based Drug Discovery and X-Ray Crystallography Volume Editors: Thomas G. Davies, Marko Hyvo¨nen Vol. 317, 2012
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NMR of Proteins and Small Biomolecules
Volume Editor: Guang Zhu
With Contributions by K. Chen N.K. Goto R. Ishima H. Li R. Powers J. Qin T. Qureshi J.L. Stark H. Sun K.H. Sze N. Tjandra H.S. Tse O. Vinogradova Q. Wu X. Zhao G. Zhu
Editor Prof. Dr. Guang Zhu Department of Biochemistry The Hong Kong University of Science and Technology Clear Water Bay Kowloon, Hong Kong China
ISSN 0340-1022 e-ISSN 1436-5049 ISBN 978-3-642-28916-3 e-ISBN 978-3-642-28917-0 DOI 10.1007/978-3-642-28917-0 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2012935239 # Springer-Verlag Berlin Heidelberg 2012 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Volume Editor Prof. Dr. Guang Zhu Department of Biochemistry The Hong Kong University of Science and Technology Clear Water Bay Kowloon, Hong Kong China
Editorial Board Prof. Dr. Kendall N. Houk
Prof. Dr. Steven V. Ley
University of California Department of Chemistry and Biochemistry 405 Hilgard Avenue Los Angeles, CA 90024-1589, USA
[email protected] University Chemical Laboratory Lensfield Road Cambridge CB2 1EW Great Britain
[email protected] Prof. Dr. Christopher A. Hunter
Prof. Dr. Massimo Olivucci
Department of Chemistry University of Sheffield Sheffield S3 7HF, United Kingdom
[email protected] Universita` di Siena Dipartimento di Chimica Via A De Gasperi 2 53100 Siena, Italy
[email protected] Prof. Michael J. Krische University of Texas at Austin Chemistry & Biochemistry Department 1 University Station A5300 Austin TX, 78712-0165, USA
[email protected] Prof. Dr. Joachim Thiem Institut fu¨r Organische Chemie Universita¨t Hamburg Martin-Luther-King-Platz 6 20146 Hamburg, Germany
[email protected] Prof. Dr. Jean-Marie Lehn
Prof. Dr. Margherita Venturi
ISIS 8, alle´e Gaspard Monge BP 70028 67083 Strasbourg Cedex, France
[email protected] Dipartimento di Chimica Universita` di Bologna via Selmi 2 40126 Bologna, Italy
[email protected] vi
Editorial Board
Prof. Dr. Pierre Vogel
Prof. Dr. Henry Wong
Laboratory of Glycochemistry and Asymmetric Synthesis EPFL – Ecole polytechnique fe´derale de Lausanne EPFL SB ISIC LGSA BCH 5307 (Bat.BCH) 1015 Lausanne, Switzerland
[email protected] The Chinese University of Hong Kong University Science Centre Department of Chemistry Shatin, New Territories
[email protected] Prof. Dr. Chi-Huey Wong Professor of Chemistry, Scripps Research Institute President of Academia Sinica Academia Sinica 128 Academia Road Section 2, Nankang Taipei 115 Taiwan
[email protected] Prof. Dr. Hisashi Yamamoto Arthur Holly Compton Distinguished Professor Department of Chemistry The University of Chicago 5735 South Ellis Avenue Chicago, IL 60637 773-702-5059 USA
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Thus each review within the volume critically surveys one aspect of that topic and places it within the context of the volume as a whole. The most significant developments of the last 5–10 years are presented, using selected examples to illustrate the principles discussed. A description of the laboratory procedures involved is often useful to the reader. The coverage is not exhaustive in data, but rather conceptual, concentrating on the methodological thinking that will allow the nonspecialist reader to understand the information presented. Discussion of possible future research directions in the area is welcome. Review articles for the individual volumes are invited by the volume editors. In references Topics in Current Chemistry is abbreviated Top Curr Chem and is cited as a journal. Impact Factor 2010: 2.067; Section “Chemistry, Multidisciplinary”: Rank 44 of 144
Preface
Nuclear Magnetic Resonance (NMR) is one of only a few scientific techniques that have been widely applied in many different areas such as physics, chemistry, biology and medicine. Today, NMR plays a crucial role in structure-function studies of organic and inorganic compounds and of large biomolecules, particularly proteins and DNA. In medicine it is one of the most important imaging techniques available to physicians and it also has extensive applications in pharmaceutical research. In this special issue of NMR of Proteins and Small Biomolecules, review chapters cover a wide-range of topics on some of the latest developments in NMR techniques and their applications. A review of recent developments in structure-based drug discovery begins this volume by showing how combining 1D and 2D NMR techniques with molecular docking can efficiently screen and identify novel “druggable” leads. The success of such an approach relies on the selection of worthwhile therapeutic targets; presumably proteins that are critical in particular diseases. In that context, studying protein-ligand interactions with NMR techniques that have unique powers for the study of weak protein-ligand interactions, as described in chapter 2, followed by the use of residual dipolar coupling approaches, reviewed in chapter 3, may be essential. Chapter 4 is dedicated to the study paramagnetic metalloproteins, giving an overview of paramagnetic NMR and 13C directly detected protonless NMR spectroscopy. Since NMR is especially powerful for the study of proteins dynamics, more recent developments in transverse relaxation dispersion experiments, which have extended the range of NMR relaxation studies to the milli-micro second timescale, are illustrated in chapter 5. Solid and liquid state NMR techniques for studying membrane proteins represent another “hot” area of contemporary research. Chapters 6 and 7 systematically describe these approaches. This volume concludes with chapter 8, a review of the considerable sensitivity enhancement attainable in magnetic resonance spectroscopic imaging (MRSI) through the use of dynamic nuclear polarization transfer. This non-invasive technique can be applied to the measurement of metabolites in vivo to allow early diagnosis and assessment of diseases in personalized medicine.
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I hope that the reviews of these unique topics in NMR techniques and their applications as presented in this volume NMR of Proteins and Small Biomolecules are informative and fun to read; and I thank all the authors who made this project possible. Hong Kong
Guang Zhu
Contents
Application of NMR and Molecular Docking in Structure-Based Drug Discovery . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Jaime L. Stark and Robert Powers NMR as a Unique Tool in Assessment and Complex Determination of Weak Protein–Protein Interactions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 Olga Vinogradova and Jun Qin The Use of Residual Dipolar Coupling in Studying Proteins by NMR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Kang Chen and Nico Tjandra NMR Studies of Metalloproteins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Hongyan Li and Hongzhe Sun Recent Developments in 15N NMR Relaxation Studies that Probe Protein Backbone Dynamics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Rieko Ishima Contemporary Methods in Structure Determination of Membrane Proteins by Solution NMR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123 Tabussom Qureshi and Natalie K. Goto Protein Structure Determination by Solid-State NMR . . . . . . . . . . . . . . . . . . . . 187 Xin Zhao Dynamic Nuclear Polarization: New Methodology and Applications . . . . 215 Kong Hung Sze, Qinglin Wu, Ho Sum Tse, and Guang Zhu Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
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Top Curr Chem (2012) 326: 1–34 DOI: 10.1007/128_2011_213 # Springer-Verlag Berlin-Heidelberg 2011 Published online: 14 September 2011
Application of NMR and Molecular Docking in Structure-Based Drug Discovery Jaime L. Stark and Robert Powers
Abstract Drug discovery is a complex and costly endeavor, where few drugs that reach the clinical testing phase make it to market. High-throughput screening (HTS) is the primary method used by the pharmaceutical industry to identify initial lead compounds. Unfortunately, HTS has a high failure rate and is not particularly efficient at identifying viable drug leads. These shortcomings have encouraged the development of alternative methods to drive the drug discovery process. Specifically, nuclear magnetic resonance (NMR) spectroscopy and molecular docking are routinely being employed as important components of drug discovery research. Molecular docking provides an extremely rapid way to evaluate likely binders from a large chemical library with minimal cost. NMR ligand-affinity screens can directly detect a protein-ligand interaction, can measure a corresponding dissociation constant, and can reliably identify the ligand binding site and generate a co-structure. Furthermore, NMR ligand affinity screens and molecular docking are perfectly complementary techniques, where the combination of the two has the potential to improve the efficiency and success rate of drug discovery. This review will highlight the use of NMR ligand affinity screens and molecular docking in drug discovery and describe recent examples where the two techniques were combined to identify new and effective therapeutic drugs. Keywords Drug discovery, FAST-NMR, In silico screening, Ligand affinity screens, Molecular docking, Nuclear magnetic resonance, Virtual screening
J.L. Stark and R. Powers (*) Department of Chemistry, University of Nebraska – Lincoln, 722 Hamilton Hall, Lincoln, NE 68588-0304, USA e-mail:
[email protected] 2
J.L. Stark and R. Powers
Contents 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 NMR Ligand Affinity Screens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Ligand-Based NMR Screens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Target-Based NMR Screens . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Molecular Docking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1 Docking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2 Scoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3 Protein Flexibility . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4 Virtual Screening and Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Combining Molecular Docking with NMR Ligand Affinity Screens . . . . . . . . . . . . . . . . . . . . . . 4.1 Identification of New Therapeutic Targets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2 Rapid Protein–Ligand Structure Determination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Lead Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2 4 4 6 7 8 10 13 14 17 18 20 23 26 26
1 Introduction The completion of the human genome project [1] coupled with an increase in R&D investments was widely anticipated to be the cornerstone of personalized medicine with a corresponding explosion in new pharmaceutical drugs targeting a range of diseases. Nearly a decade later, the rate at which new drugs enter clinical development and reach the market has declined dramatically despite the influx of novel therapeutic targets and R&D investments. In the past 5 years the number of new molecular entities (NMEs) receiving FDA approval has decreased by 50% from the previous 5 years [2]. There are several reasons for this decline, but most stem from the fact that drug discovery is a complex and costly endeavor. Approximately 80–90% of drugs that reach the clinical testing phase fail to make it to market [3, 4]. Efforts to reduce costs often lead pharmaceutical companies to invest their time and money in proven therapies, like “best-in-class” drugs, instead of “firstin-class” drugs that target new mechanisms of action or diseases. As a result, many diseases are “orphaned” and lack any therapeutic compounds in the discovery pipeline. Addressing these issues will require fundamental changes to create a more efficient drug discovery process. The enormous costs and high failure rates inherent to the pharmaceutical industry are clearly contributing factors to the declining number and diversity of new therapeutics. Efforts that minimize costs without restricting research endeavors will evidently benefit the development of drugs for various human diseases. The availability of hundreds of whole-genome sequences for numerous organisms provides an invaluable data set for drug research [1, 5, 6]. Identifying a novel “druggable” protein target is a critical first step for a successful and efficient drug discovery effort. Unfortunately, bioinformatics analysis alone does not generally provide enough information to justify embarking upon an expensive drug discovery program [7, 8]. Instead, knowing the three dimensional structure of a protein greatly
Application of NMR and Molecular Docking in Structure-Based Drug Discovery
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enhances the value of the bioinformatics analysis. Protein structures often provide insights into the molecular basis of the protein’s biological function and its relationship to a particular disease. A protein structure also provides detailed information on the sequence and structural characteristics that govern ligand binding interactions. Building a drug discovery effort based on structural information promises to help in the identification of novel therapeutic targets, in the discovery of new lead compounds, and in the optimization of drug-like properties to improve efficacy and safety. Currently, the drug discovery process within the pharmaceutical industry employs high-throughput screening (HTS) as the primary method for identifying lead compounds. However, the high false positive rate [9–12] combined with a significant cost in time and money has encouraged the development of alternative methods to drive the drug discovery process [13, 14]. Nuclear magnetic resonance (NMR) spectroscopy is uniquely qualified to assist in making the drug discovery process more efficient [15, 16]. NMR is useful for several reasons: (1) it directly detects the interaction between the ligand and protein using a variety of techniques, (2) samples are typically analyzed under native conditions, (3) hundreds of samples can be analyzed per day, and (4) information on the binding site and binding affinity can be readily obtained. These features allow NMR to be an effective tool at multiple steps in the drug discovery pathway, which includes verifying HTS and virtual screening hits [15, 17–19], screening fragment-based libraries [15, 20–22], optimizing lead compounds [15, 17, 23, 24], evaluating ADME-toxicology [25–27], and identifying and validating therapeutic targets [28, 29]. Nevertheless, there are still intrinsic costs to maintaining an NMR instrument, screening a compound library, and producing significant quantities of a protein. One way to significantly reduce experimental costs is to utilize in silico methodologies to supplement the lead identification and optimization steps of the drug discovery process [30]. Molecular docking is a computational tool that predicts the binding site location and conformation of a compound when bound to a protein [30–32]. This approach has been found to be fairly successful in redocking compounds into previously solved protein–ligand co-structures [33], where more than 70% of the redocked ˚ root mean squared deviation (RMSD) of the actual ligand ligands reside within 2 A pose. During the prediction of protein–ligand co-structures, molecular docking programs calculate a binding score that allows for the selection of the best ligand pose. The binding score is typically based on a combination of geometric and energetic functions (bond lengths, dihedral angles, van der Waals forces, Lennard-Jones and electrostatic interactions, etc.) in conjunction with empirical functions unique to each specific docking program [34–39]. A large variety of docking programs are available that include AutoDock [40], DOCK [41], FlexX [42], Glide [43], HADDOCK [44], and LUDI [45, 46]. Binding energies are also routinely used to rank different ligands from a compound library after being docked to a protein target. The virtual or in silico screening of a library composed of thousands of theoretical compounds can be accomplished in a day with minimal cost [47–49]. Thus, a virtual screen can significantly accelerate the hit identification and optimization process while
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reducing the amount of experimental effort. However, a virtual screen does have significant limitations that prevent it from completely replacing traditional HTS [50–52]. These limitations include inaccurate scoring functions, use of rigid proteins, and simplified solvation models. In essence, a virtual screen only increases the likelihood that a predicted ligand actually binds the protein target, experimental verification is essential. Despite the individual drawbacks, NMR ligand affinity screens and molecular docking are complementary techniques. This review will highlight the use of NMR ligand affinity screens and molecular docking in drug discovery and describe recent examples where the combination of the two techniques provides a powerful approach to identify new and effective therapeutic drugs.
2 NMR Ligand Affinity Screens NMR ligand affinity screening is a versatile technique that is useful for multiple stages of the drug discovery process [15, 17, 22, 53]. This versatility arises from the ability of NMR to directly detect protein–ligand binding based on changes in several NMR parameters. A binding event is detected by the relative differences between the protein or ligand NMR spectrum in the bound and unbound states. However, the specific type of information obtained about the binding process depends on whether a ligand-based or target-based NMR experiment is used.
2.1
Ligand-Based NMR Screens
Ligand-based NMR screens typically monitor the NMR spectrum of a ligand under free and bound conditions. Distinguishing between a free ligand and a protein–ligand complex is generally based on the large molecular weight difference that affects several NMR parameters. Small molecular weight molecules have slow relaxation rates (R2), negative NOE cross-peaks, and large translational diffusion coefficients (Dt). If a protein–ligand binding event occurs, the ligand adopts the properties of the larger molecular-weight protein, increasing R2, producing positive NOE cross-peaks, and decreasing Dt, all of which can be observed by NMR [54]. Most ligand-based NMR screens use one-dimensional (1D) 1H-NMR experiments to monitor these changes, which provide significant benefits for a highthroughput screen. 1D NMR experiments are typically fast (2–5 min) and routinely use mixtures without the need to deconvolute [55]. The deconvolution of mixtures is avoided by ensuring that NMR ligand peaks do not overlap in the NMR spectrum (Fig. 1). The application of mixtures allows for hundreds to thousands of compounds to be screened in a single day. Another advantage of ligand-based NMR methods is the minimal amount of protein required (10 min) due to the additional dimension and the need to collect a reference spectrum for the ligandfree protein. Also, the protein needs to be 15N and/or 13C isotopically labeled. Importantly, 2D1H-13C/15N HSQC/TROSY NMR experiments provide additional information about the ligand binding site. A binding ligand often results in the observation of CSPs of the resonances in a 2D1H-15N- or 1H-13C-HSQC spectrum (Fig. 2a). These CSPs are usually caused by a change in the chemical environment for residues proximal to the bound ligand or residues undergoing ligand-induced conformational changes. The availability of the protein structure and the NMR sequence assignments (correlation of an NMR resonance with a specific amino acid residue) allows for the CSPs to be mapped onto a three-dimensional (3D) representation of the protein’s surface. A cluster of residues on the protein surface with observed CSPs often identifies the ligandbinding site. The ligand binding affinity or KD is also routinely determined from CSPs measured from a series of 2D 1H-13C/15N HSQC/TROSY NMR experiments. The magnitude of the CSPs at varying ligand concentrations is correlated to the KD for the protein–ligand complex using the following equation [74, 75]: qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðKD þ ½ L þ ½PÞ ðKD þ ½ L þ ½PÞ2 ð4½ L½PÞ ; (1) CSPobs ¼ CSPmax 2½P where [P] is the protein concentration, [L] is the ligand concentration, CSPmax is the maximum CSP observed for a fully bound protein, and CSPobs is the observed CSP at a particular ligand concentration. A least squares fit of (1) to the experimental CSP data is used to calculate a KD (Fig. 2b). As previously mentioned, since target-based screens require the use of multidimensional NMR experiments, data collection is significantly longer relative to ligand-based NMR screens. Also target-based screens require higher protein concentrations (>50 mM compared to 1,000,000 compounds), which are screened using automated, biological assays intended to monitor a specific response or biological effect [136]. Unfortunately, HTS is extremely inefficient due to the high cost of developing, maintaining, and screening such large libraries of compounds. Furthermore, the random search for an effective drug in the vastness of chemical space (~1060 compounds) [137] is almost guaranteed to fail. Thus, HTS hit rates are typically very low, where 10 4 M), on the other hand, are less well understood. This could be attributed in part to the technical difficulties encountered during attempts to characterize them directly in vitro or in vivo. The other reason relates to a common prejudice that wPPIs might not be found in living cells, especially considering low (
