Computer-Assisted Structure Elucidation

Computer-Assisted Structure Elucidation Dennis H. Smith, Publication Date: June 1, 1977 | doi: 10.1021/bk-1977-0054.fw0...

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Computer-Assisted Structure Elucidation Dennis H. Smith,

Publication Date: June 1, 1977 | doi: 10.1021/bk-1977-0054.fw001

Stanford

University

EDITOR

School of

Medicine

A symposium sponsored by the Division of Chemical Information at the 173rd Meeting of the American Chemical Society, New Orleans, La., March 23, 1977

ACS SYMPOSIUM SERIES

AMERICAN CHEMICAL SOCIETY WASHINGTON, D. C. 1977

54


Library of Congress CIP Data Computer-assisted structure elucidation. (ACS symposium series; 54 ISSN 0097-6156) Bibliography: p. Includes index. 1. Chemical structure—Data processing—Congresses. I. Smith, Dennis H . , 1942. II. American Chemical Society. Division of Chemical Information. III. Series: American Chemical Society. ACS symposim series; 54. QD471.C594 ISBN 0-8412-0384-9

543'.08 ACSMC8

77-24427 54 1-151

Copyright © 1977 American Chemical Society All Rights Reserved. No part of this book may be reproduced or transmitted in any form or by any means—graphic, electronic, including photocopying, recording, taping, or information storage and retrieval systems—without written permission from the American Chemical Society. PRINTED IN T H E U N I T E D STATES O F AMERICA

ACS Symposium Series


Robert F. Gould, Editor

Advisory

Board

D o n a l d G . Crosby Jeremiah P. Freeman E. Desmond Goddard Robert A . Hofstader J o h n L. Margrave N i n a I. M c C l e l l a n d J o h n B. Pfeiffer Joseph V . Rodricks Alan

C. Sartorelli

Raymond B . Seymour Roy L. W h i s t l e r Aaron W o l d


FOREWORD T h e A C S S Y M P O S I U M SERIES was f o u n d e d i n 1 9 7 4 to

provide

a m e d i u m for p u b l i s h i n g s y m p o s i a q u i c k l y i n b o o k f o r m .

The

f o r m a t of the SERIES p a r a l l e l s that of its predecessor, A D V A N C E S IN CHEMISTRY

SERIES, except that i n o r d e r to save t i m e

the

p a p e r s are n o t typeset b u t are r e p r o d u c e d as t h e y are s u b m i t t e d b y the authors i n c a m e r a - r e a d y

form.

A s a further

means of s a v i n g t i m e , the papers are not e d i t e d or r e v i e w e d except b y the s y m p o s i u m c h a i r m a n , w h o b e c o m e s e d i t o r t h e book.

P a p e r s p u b l i s h e d i n the A C S S Y M P O S I U M

of

SERIES

are o r i g i n a l c o n t r i b u t i o n s not p u b l i s h e d e l s e w h e r e i n w h o l e or major p a r t a n d i n c l u d e reports of r e s e a r c h as w e l l as r e v i e w s since s y m p o s i a m a y e m b r a c e b o t h types of p r e s e n t a t i o n .

PREFACE "Elucidation

of

u n k n o w n m o l e c u l a r structures o c c u p i e s

a

significant

a m o u n t of the chemist's t i m e i n m a n y areas of c h e m i c a l research. A v a r i e t y of p h y s i c a l a n d c h e m i c a l m e t h o d s are a v a i l a b l e to assist i n this task.

Suitably programmed

d i g i t a l c o m p u t e r s are a d d i t i o n a l tools

w h i c h c a n h e l p to solve s t r u c t u r a l p r o b l e m s .

If u s e d i n t e l l i g e n t l y , the

s p e e d a n d thoroughness of t h e c o m p u t e r c a n b e a p o w e r f u l asset to t h e Publication Date: June 1, 1977 | doi: 10.1021/bk-1977-0054.pr001

c h e m i s t , b o t h i n d e c r e a s i n g t i m e r e q u i r e d for analysis a n d i n e n s u r i n g that a l l p l a u s i b l e alternatives h a v e b e e n c o n s i d e r e d .

(Computers play a

c r i t i c a l role i n x-ray c r y s t a l l o g r a p h i c t e c h n i q u e s also.

However,

such

t e c h n i q u e s w e r e not a d d r e s s e d i n this s y m p o s i u m . ) T h i s s y m p o s i u m w a s h e l d at a t i m e w h e n : (1) M o s t o r g a n i z a t i o n s i n v o l v e d i n c h e m i c a l r e s e a r c h h a v e a v a i l a b l e c o m p u t e r systems to h a n d l e m a n y phases of a c q u i r i n g a n d r e d u c i n g experimental data (2) Some of t h e earliest m e t h o d s u s i n g c o m p u t e r s to assist i n struct u r e e l u c i d a t i o n , e.g., l i b r a r y s e a r c h t e c h n i q u e s , are w i d e l y a v a i l a b l e a n d are i n c o r p o r a t e d i n t o c o m m e r c i a l systems (3) C o m p u t e r n e t w o r k i n g is m a k i n g m o r e recent p r o b l e m - s o l v i n g p r o g r a m s a v a i l a b l e to m a n y chemists at r e l a t i v e l y l o w cost These developments

have placed powerful

computer

systems

i n the

l a b o r a t o r y for r o u t i n e w o r k a n d , b y resource s h a r i n g v i a n e t w o r k i n g , h a v e r e d u c e d t h e l a g t i m e for a p p l i c a t i o n of n e w c o m p u t e r t e c h n i q u e s to days or w e e k s r a t h e r t h a n m o n t h s or years. T h e p a r t i c i p a n t s i n this s y m p o s i u m are u s i n g c o m p u t e r s i n several different

ways

to h e l p solve u n k n o w n structures.

Methodologies

cussed i n c l u d e l i b r a r y s e a r c h t e c h n i q u e s , a u t o m a t e d

interpretation

disof

d a t a , p a t t e r n r e c o g n i t i o n , s t r u c t u r e generation, a n d r a n k i n g of c a n d i d a t e structures b a s e d o n p r e d i c t i o n of s p e c t r o s c o p i c or c h e m i c a l b e h a v i o r .

It

is s t r i k i n g to see a c o n v e r g e n c e of ideas a n d t e c h n i q u e s i n these s e e m i n g l y diverse m e t h o d s .

If one v i e w s s t r u c t u r e e l u c i d a t i o n as a t r a n s f o r m a t i o n

of d a t a ( a n d representations of other i n f o r m a t i o n a b o u t a n u n k n o w n ) i n t o representations of m o l e c u l a r s t r u c t u r e w h i c h are p o t e n t i a l solutions, t h e n the reasons for the c o n v e r g e n c e are o b v i o u s .

T h e c o m p u t e r is a

p o w e r f u l a i d e i n c a r r y i n g out these transformations. I express m y sincere t h a n k s to M o r t o n M u n k for his h e l p f u l s u g gestions i n a r r a n g i n g the s y m p o s i u m a n d for c h a i r i n g a p o r t i o n of the vii

p r o g r a m . T h e officers of the D i v i s i o n of C h e m i c a l I n f o r m a t i o n ,

especially

C y n t h i a O ' D o n a h u e , w e r e m o s t h e l p f u l i n assisting m y efforts. S t a n f o r d U n i v e r s i t y S c h o o l of M e d i c i n e Stanford, Calif.

Publication Date: June 1, 1977 | doi: 10.1021/bk-1977-0054.pr001

M a y 3 1 , 1977

viii

DENNIS

H.

SMITH

1 Computer-Assisted Structure Identification of U n k n o w n Mass Spectra

Publication Date: June 1, 1977 | doi: 10.1021/bk-1977-0054.ch001

R. VENKATARAGHAVAN, H. E. DAYRINGER, G. M. PESYNA, B. L. ATWATER, I. K. MUN, M. M. CONE, and F. W. McLAFFERTY Department of Chemistry, Cornell University, Ithaca, NY 14853

Mass spectrometry has become a routine technique for structure identification in a number of applications (1). Gas chromatograph/mass spectrometer/computer (GC/MS/COM) systems capable of producing a mass spectrum every second are commercially available (2). Voluminous amounts of data are generated with such systems using subnanogram amounts of sample. For full utilization of this highly specific information it is essential to employ computer techniques. Such computer-aided structure identification from mass spectrometric data has taken two distinct directions (3). The first utilizes "retrieval" systems which compare the unknown data to a library of reference spectra to report compounds with a high degree of similarity. A number of techniques have been employed for the retrieval approach (3). The second approach involves interpretive schemes that attempt to identify part or all of the unknown structure from correlations of mass spectral fragmentation behavior. Pattern recognition (4) and artificial intelligence (5) are examples of such schemes that have been employed for interpreting mass spectral data of specific classes of compounds. We will describe here a retrieval Probability Based Matching (PBM) system (6, 7) and an interpretive Self-Training Interpretive and Retrieval System (STIRS) (8 -11)developed for the analysis of low resolution mass spectra. Both these systems are available on a computer network (TYMNET) from an IBM-370/168 computer system at Cornell University to outside users. Probability Based Matching System It has been shown that to increase the relevancy of information retrieved from a library of data it is essential to attach proper weighting to the contents of the system (12). The PBM system employs a probability weighting to both the mass and abundance data (6, 7) • The abundance values are weighted according to a log normal distribution (13) and the masses are given a uniqueness value based on their occurrence probability 1


2

COMPUTER-ASSISTED STRUCTURE ELUCIDATION

i n a m a s s s p e c t r a l d a t a b a s e of 1 8 , 8 0 6 different c o m p o u n d s (14). The P B M s y s t e m a l s o u s e s a r e v e r s e s e a r c h s t r a t e g y , i n d e p e n d e n t l y p r o p o s e d b y A b r a m s o n (15), w h i c h i s v a l u a b l e i n i d e n t i f y i n g components of a m i x t u r e . This t e c h n i q u e demands that the p e a k s of the r e f e r e n c e s p e c t r u m be p r e s e n t i n the u n k n o w n , but not that a l l p e a k s of the u n k n o w n be p r e s e n t i n the r e f e r e n c e . The d e g r e e of m a t c h of the r e f e r e n c e to the u n k n o w n i s i n d i c a t e d w i t h a c o n fidence i n d e x K, b a s e d on the s t a t i s t i c a l p r o b a b i l i t y that this degree of m a t c h o c c u r r e d by c o i n c i d e n c e ; d e t a i l s of the method h a v e b e e n d e s c r i b e d e l s e w h e r e (6, 7 ) . A s t a t i s t i c a l e v a l u a t i o n of P B M ' s performance w a s made u s i n g " u n k n o w n " m a s s s p e c t r a , for e a c h of w h i c h at l e a s t one other s p e c t r u m of the same compound w a s present i n the d a t a b a s e . L o w a n d h i g h m o l e c u l a r w e i g h t s e t s , e a c h of ~ 4 0 0 u n k n o w n s p e c t r a r e m o v e d at r a n d o m from the d a t a b a s e , w e r e r u n t h r o u g h the P B M s y s t e m , and the r e s u l t s evaluated u s i n g r e c a l l and r e l i a b i l i t y as measures of performance. R e c a l l (RC) i s d e f i n e d a s the number of r e l e v a n t s p e c t r a a c t u a l l y r e t r i e v e d and r e l i a b i l i t y (RL) i s t h e p r o p o r t i o n o f r e t r i e v e d s p e c t r a w h i c h a r e a c t u a l l y relevant. In a d d i t i o n to t h e s e terms i t i s d e s i r a b l e to e x p r e s s the performance of automated s y s t e m s i n terms of f a l s e p o s i t i v e s (FP), the p r o p o r t i o n of s p e c t r a p r e d i c t e d i n c o r r e c t l y (16). R

C

=

:

c

/

V (

I

c

P

(2)

V

+

FP = I / P f

(1)

c

(3)

f

where I = number of c o r r e c t p r e d i c t i o n s , P = t o t a l p o s s i b l e n u m b e r o f c o r r e c t p r e d i c t i o n s , If = n u m b e r o f f a l s e p r e d i c t i o n s , and P = t o t a l p o s s i b l e number of f a l s e p r e d i c t i o n s . At the 50% r e c a l l l e v e l the r e l i a b i l i t i e s for the l o w and h i g h m o l e c u l a r w e i g h t sets w e r e 65% and 4 2 % , counting as correct only predicted s t r u c tures w h i c h are i d e n t i c a l to the u n k n o w n . I n v a r i a b l y r e t r i e v a l s y s t e m s p r e d i c t s i m i l a r s t r u c t u r e s i n a d d i t i o n to the i d e n t i c a l s t r u c t u r e . In the e v a l u a t i o n of P B M r e s u l t s four c l a s s e s of s i m i l a r i t y w e r e d e f i n e d : I, i d e n t i c a l c o m p o u n d or s t e r e o i s o m e r ; I I , c l a s s I o r a r i n g p o s i t i o n i s o m e r ; I I I , c l a s s II o r a h o m o l o g ; I V , c l a s s III o r a n i s o m e r o f c l a s s III c o m p o u n d f o r m e d b y m o v i n g o n l y o n e c a r b o n a t o m . It w a s f o u n d t h a t w h e n c l a s s IV t y p e c o m pounds were a c c e p t e d as correct predictions the r e l i a b i l i t y of the s y s t e m i n c r e a s e d to 95% at the same r e c a l l l e v e l . R e c e n t l y , i t has b e e n found that the performance of P B M for the i d e n t i f i c a t i o n of c o m p o n e n t s i n a m i x t u r e c a n be e n h a n c e d (17) b y i n c o r p o r a t i n g a s p e c t r u m s u b t r a c t i o n p r o c e d u r e s i m i l a r t o the one p r o p o s e d b y H i t e s a n d B i e m a n n (18). The method subtracts the reference compound matched by P B M w i t h the h i g h e s t c o n f i d e n c e i n d e x (or a n y o t h e r i n t h e l i s t o f p r e d i c t e d s p e c t r a ) f r o m t h e unknown spectrum and matches the r e s i d u a l peaks against the c

f

c

1.

VENKATARAGHAVAN E T A L .

Structure

of Unknown

Mass Spectra

3

reference f i l e b y P B M . This operation i s p a r t i c u l a r l y v a l u a b l e for identifying a minor component m i s s e d by the reverse search proc e d u r e w h e n there i s s u b s t a n t i a l o v e r l a p i n the s p e c t r a of the major and minor c o m p o n e n t , or w h e n amount of the latter f a l l s o u t s i d e the l i m i t s set for " p e r c e n t c o m p o n e n t " or " p e r c e n t c o n tamination" #


Self-Training Interpretive and Retrieval

System

The STIRS s y s t e m i s a n i n t e r p r e t i v e s c h e m e t h a t t r a i n s i t s e l f for the i d e n t i f i c a t i o n of different s t r u c t u r a l features i n a n u n k n o w n b y u t i l i z i n g s p e c i f i c c l a s s e s o f m a s s s p e c t r a l d a t a (8). Table I shows the fifteen data c l a s s e s u s e d ; although these have b e e n s e l e c t e d for t h e i r s t r u c t u r a l s i g n i f i c a n c e , there are no p r e d e s i g n a t e d c o r r e l a t i o n s of s p e c i f i c s p e c t r a l d a t a w i t h c o r r e s ponding s t r u c t u r e s . For e a c h unknown spectrum the system matches its data i n each c l a s s against the corresponding c l a s s d a t a of a l l r e f e r e n c e s p e c t r a a n d c o m p u t e s a m a t c h f a c t o r (MF) i n d i c a t i n g the degree of s i m i l a r i t y . In e a c h data c l a s s the fifteen r e f e r e n c e c o m p o u n d s o f h i g h e s t M F v a l u e s a r e s a v e d . If a p a r t i c u l a r substructure(s) i s found i n a s i g n i f i c a n t p r o p o r t i o n of t h e s e c o m p o u n d s , its p r e s e n c e i n the u n k n o w n i s p r o b a b l e . A b s e n c e of a s u b s t r u c t u r e i s not p r e d i c t e d , as the m a s s s p e c t r a l features of one s u b s t r u c t u r e c a n be made n e g l i g i b l e by the p r e s e n c e of a more p o w e r f u l f r a g m e n t a t i o n - d i r e c t i n g g r o u p . The d a t a b a s e for the s y s t e m i n c l u d e s i n f o r m a t i o n from 2 9 , 4 6 8 different o r g a n i c compounds containing the common elements H , C , N , O, F, S i , P, S, C I , B r , a n d / o r I. A l l s t r u c t u r e s of t h e s e c o m p o u n d s h a v e b e e n c o d e d i n W i s w e s s e r L i n e N o t a t i o n (WLN) to f a c i l i t a t e c o m puter h a n d l i n g of s t r u c t u r e d a t a . To u t i l i z e t h e i n f o r m a t i o n p r o v i d e d b y t h e STIRS s y s t e m , the r e s u l t s for e a c h d a t a c l a s s are e x a m i n e d and the common s t r u c t u r a l features i d e n t i f i e d . To a i d t h i s p r o c e s s , i n a r e c e n t l y i m p l e m e n t e d s y s t e m (9), t h e c o m p u t e r e x a m i n e s t h e d a t a for t h e p r e s e n c e of 179 f r e q u e n t l y f o u n d s u b s t r u c t u r e s (19). The p r o b a b i l i t y for the p r e s e n c e i n the u n k n o w n of e a c h s u b s t r u c t u r e i s predicted u s i n g a random drawing m o d e l . Knowing the frequency of o c c u r r e n c e of a s p e c i f i c s u b s t r u c t u r e i n the f i l e , t h i s m e t h o d i n d i c a t e s the p r o b a b i l i t y that the p r e d i c t i o n of its p r e s e n c e i n the u n k n o w n o c c u r r e d at r a n d o m . From t h i s p r o b a b i l i t y the c o n f i d e n c e for e a c h p r e d i c t i o n i s c a l c u l a t e d . For e x a m p l e , i n the STIRS d a t a b a s e t h e p h e n y l s u b s t r u c t u r e i s f o u n d to b e p r e s e n t i n 28% of the c o m p o u n d s . S t a t i s t i c a l l y on the a v e r a g e t h i s s u b s t r u c t u r e w o u l d o c c u r i n 4 o f a n y 15 c o m p o u n d s i n t h e d a t a b a s e , i n c l u d i n g t h e t o p 15 c o m p o u n d s s e l e c t e d i n a S T I R S d a t a c l a s s . O n t h e o t h e r h a n d i f p h e n y l i s f o u n d i n 10 o f t h e 15 c o m p o u n d s , the probability that this occurred by chance i s only 1 i n 113, so that the confidence i n the p h e n y l p r e d i c t i o n i s >99%, or a f a l s e p o s i t i v e s v a l u e of < 1 % .

4


Table I.

M a s s S p e c t r a l D a t a C l a s s e s U s e d i n STIRS


Data Class

D e s c r i p t i o n , maximum number of p e a k s

I

Ion Series

(14 a m u s e p a r a t i o n )

2-4

Characteristic ions

250)

5C

Five

16-20, 30-38, 44-51, 59-65,72-76

6C

Five

26-28, 39-42, 52-56, 62-70, 80-84

7, 8

II

S e c o n d a r y n e u t r a l l o s s e s from most abundant o d d - m a s s (MF7) and e v e n - m a s s (MF8) l o s s O v e r a l l match factors

11.0

MF11.1 + MF11.2

11.1

2A + 2B + 3A + 3B + 4A + 4B

11.2

5A + 5 B + 6A

175)


1.


Structure

of Unknown

Mass Spectra

5

The s y s t e m h a s b e e n e x t e n s i v e l y t e s t e d for e a c h of the 179 s u b s t r u c t u r e s b y s e l e c t i n g 373 c o m p o u n d s a t r a n d o m from t h e d a t a b a s e (every 50th compound i n the Registry data) (20). If the d a t a s e t d i d n o t c o n t a i n a t l e a s t 30 c o m p o u n d s w i t h a p a r t i c u l a r s u b s t r u c t u r e , the required a d d i t i o n a l compounds were s e l e c t e d at r a n d o m t h a t c o n t a i n e d t h e s u b s t r u c t u r e . I f f e w e r t h a n 30 c o m pounds w i t h a g i v e n substructure w e r e a v a i l a b l e , a l l of them were selected. System performance i n each data c l a s s was evaluated by computing r e c a l l and r e l i a b i l i t y terms for e a c h s u b s t r u c t u r e . In contrast to equation 2 , the r e l i a b i l i t y term i n this c a s e i n c l u d e d a f a l s e p o s i t i v e factor, b e i n g set equal to RC/(RC + FP), s u c h that the v a l u e s reflect the s y s t e m performance averaged for c o m pounds c o n t a i n i n g and not c o n t a i n i n g the s u b s t r u c t u r e . This r e l i a b i l i t y term l e d to s u b s t a n t i a l c o n f u s i o n , s o that w e n o w f e e l that i t i s better to report performance of the s y s t e m i n terms of r e c a l l and f a l s e p o s i t i v e s (16), as d i s c u s s e d for P B M (equations 1 and 3). A n a l y s i s of the d a t a s h o w s that a l t h o u g h i n d i v i d u a l d a t a c l a s s e s are g o o d for s p e c i f i c s u b s t r u c t u r e i d e n t i f i c a t i o n , the b e s t p e r f o r m a n c e i s f o u n d i n t h e o v e r a l l m a t c h f a c t o r ( T a b l e I) r e s u l t s . T h i s i s due to the fact t h a t the o v e r a l l m a t c h factor d a t a c o m b i n e s the i n f o r m a t i o n d e r i v e d from the i n d i v i d u a l d a t a c l a s s e s . The overall match factor, M F 1 1 . 0 , w h i c h combines ion series, c h a r a c t e r i s t i c i o n s , and neutral l o s s data has been found to g i v e the most r e l i a b l e information on the different substructure p o s s i b i l i t i e s i n a n u n k n o w n c o m p o u n d . F o r t h e 179 s u b s t r u c t u r e s t e s t e d , t h e M F 1 1 . 0 g a v e a r e c a l l of 4 9 % a t 1.9% f a l s e p o s i t i v e l e v e l . A number of improvements have b e e n made to the c h a r a c t e r i s t i c i o n d a t a c l a s s e s (10) a n d t h e p r i m a r y n e u t r a l l o s s e s ( 1 1 ) ; the o v e r a l l m a t c h factors M F 1 1 . 1 and M F 1 1 . 2 h a v e b e e n found to g i v e a n a v e r a g e r e c a l l of 47% and 3 2 . 1 % , r e s p e c t i v e l y , at-H0-C H -C H N 0 R00C-C H ~C0-0-*-C H RC0NH-C H -C0-0-CH 6

4

e

2

4

3

4

6

3

2

6

3

2

e

7

e

6

3

4

e

4

e

3

3

2

3

4

3

3

4

3

3

6

3

4

3

4

2

5

4

4

4

e

4

6

2

4

e

4

e

4

6

3

4

11 10 9 10 20

p-H0-C H -C0—0-C H p-H0-C H -C0-0-fl-C Hg />~H0-C H -C0—0-CH m—H0-C H -C0-0-CH tf-H0-C H -C0-CH /fj-H0-C H ~C0-e0-CH )-R m-H0-C H -C0-CH p -H0-C«H -C0-CH /n-H0-C«H -*C0-0H)C0R 7?-R-0—C H -CO-OH 6

4

4

73+ 72+ 72+ 71+ 61**+

Data class 3B:/»/* 89-158

7

5

4

6

37 46 45 50

% Component 53% 64% 53% 38%

24% 26% 29% 30%

spectrum subtracted, residual spectrum run o n

Isopropylbenzene Isopropylbenzene Isopropylbenzene I s opropy lb en zen e 1 -Methyl-2 -ethylbenzene

50-

9

Mass Spectra

P B M R e s u l t s o n U n k n o w n a n d R e s i d u a l Spectra from

Compound

lOO-i

of Unknown

3

s

7

6

34% 34% 34% 43% 36%

77% 91% 83% 72% 74%

Oata class 5: losses of 0-64 C4H3O-CO—0— n — CjH C H 0-C0-0-5 — C H C H NH-CO-O - * - C H R0C H - CO - 0 - n — C H HSCH -C0-0-/» - C H C H -C0-0-5-C3H CH -C0—0-CH NR CH — S-n—C H C0-0-CH 4

6

3

5

6

4

7

S

7

s

2

6

S

5

3

2

s

3

4

3

Neutral Losses STIRS

results for the mass spectrum

of n-propyl

7

2

Data class 5 "(neutral losses)"

1.

7

7

m/e

Figure

7

3

p-hydroxybenzoate

7


10

COMPUTER-ASSISTED STRUCTURE

ELUCIDATION

w h e n a r e f e r e n c e s p e c t r u m of t h i s c o m p o u n d , n - p r o p y l jD-hydroxyb e n z o a t e , w a s not i n the data b a s e . R e s u l t s f o r t h r e e o f t h e 15 d a t a c l a s s e s i l l u s t r a t e t h e " s e l f - t r a i n i n g " feature b y w h i c h STIRS i n d i c a t e s structural features of the u n k n o w n . D a t a c l a s s 2 A u t i l i z e s the l a r g e s t p e a k s i n t h e l o w m a s s r e g i o n of t h e s p e c t r u m (m/e 6 - 8 8 ) ; t h e s e f r a g m e n t i o n s a r e m o r e o f t e n f o r m e d b y s e c o n d ary r e a c t i o n s of h i g h e r energy r e q u i r e m e n t s , and so are i n d i c a t i v e of g r o s s , rather t h a n s p e c i f i c , s t r u c t u r a l f e a t u r e s . Thus a l l of the s p e c t r a found of h i g h e s t M F 2 A v a l u e s c o n t a i n e d a p h e n y l group, although the phenyl rings i n these compounds c o n t a i n a rather w i d e v a r i e t y of s u b s t i t u e n t s . The e x p e r i e n c e d m a s s s p e c t r o m e t r i s t p r o b a b l y w o u l d h a v e i n f e r r e d the p r e s e n c e of p h e n y l f r o m t h e " a r o m a t i c i o n s e r i e s " i n t h i s r e g i o n ; h o w e v e r , STIRS w a s not t r a i n e d s p e c i f i c a l l y to r e c o g n i z e t h e s e f e a t u r e s , but i n s t e a d i n d i c a t e d the p r e s e n c e of p h e n y l by f i n d i n g that s u c h c o m p o u n d s matched these data the most c l o s e l y . D a t a c l a s s 3B c o v e r s a h i g h e r m a s s r a n g e , w h o s e f r a g ment p e a k s s h o u l d be i n d i c a t i v e of more s p e c i f i c s t r u c t u r a l features. A g a i n a l l c o m p o u n d s of h i g h e s t M F 3 B v a l u e s c o n t a i n the p h e n y l g r o u p , but a l m o s t a l l of t h e m a l s o c o n t a i n a n a r y l h y d r o x y g r o u p (not ortho) a n d a c a r b o n y l . N o t e t h a t t h e l a t t e r i s contained i n carboxyl, ester, and keto functionalities; because STIRS i s d e s i g n e d t o p r o v i d e p o s i t i v e i n f o r m a t i o n , d a t a c l a s s 3B thus i n d i c a t e s the p r e s e n c e of H O - p h e n y l - C O - . D a t a c l a s s 5 employs " n e u t r a l l o s s " information, the differences i n mass b e t w e e n the observed fragment i o n and the m o l e c u l a r i o n , w h i c h i n t h i s c a s e i s a s s u m e d to b e m/e 1 8 0 . C l e a v a g e of the m o l e c u l a r i o n g i v e s two fragments, o n l y one of w h i c h holds the p o s i t i v e c h a r g e , and thus the n e u t r a l l o s t g e n e r a l l y c o n t a i n s the more e l e c t r o n e g a t i v e f u n c t i o n a l i t i e s . Illustrating t h i s , w h e n the m a s s e s r e p r e s e n t i n g the most common neutral l o s s e s of t h i s u n k n o w n w e r e matched a g a i n s t the w h o l e r e f e r e n c e f i l e , the h i g h e s t M F 5 v a l u e s w e r e found to be m a i n l y p r o p y l esters. To r e i t e r a t e , STIRS w a s not p r e p r o g r a m m e d to r e c o g n i z e p r o p y l e s t e r s f r o m t h e i r c o m m o n l o s s e s o f 4 1 , 4 2 , a n d 59 m a s s u n i t s ; STIRS i n e f f e c t t r a i n s i t s e l f to r e c o g n i z e t h e p r o p y l e s t e r f u n c t i o n a l i t y by f i n d i n g that t h e s e d a t a of the u n k n o w n w e r e matched best by propyl esters i n the f i l e . Note a l s o that the c o m pounds found by M F 5 d i d not c o n t a i n a p a r t i c u l a r l y s i g n i f i c a n t n u m b e r of p h e n y l g r o u p s ; t h e d i f f e r e n t d a t a c l a s s e s of STIRS h a v e been s e l e c t e d to be s e n s i t i v e to different f u n c t i o n a l i t i e s . STIRS h a s b e e n d e s i g n e d a s a n a i d to t h e i n t e r p r e t e r ; i f t h e i n t e r p r e t e r n o w a d d s up t h e m a s s of d i - s u b s t i t u t e d p h e n y l (76), h y d r o x y l (17), a n d p r o p y l e s t e r (87), he c a n n o t e t h a t t h e s u m c o r r e s p o n d s to the s u p p o s e d m o l e c u l a r w e i g h t , 1 8 0 , i n d i c a t i n g that a l l of the f u n c t i o n a l i t i e s of the u n k n o w n m o l e c u l e h a v e been i d e n t i f i e d by these three d a t a c l a s s e s of STIRS. STIRS: U n k n o w n Terpene. The m a s s s p e c t r u m of l2p-acetoxysandaracopimar-15-en-8p-, l l a - d i o l was examined

by


1.


Structure

of Unknown

Mass

Spectra

11

STIRS, o m i t t i n g a l l s p e c t r a of t h i s c o m p o u n d from the r e f e r e n c e file. The n i n e s t r u c t u r e s of h i g h e s t " o v e r a l l m a t c h f a c t o r " (MF11.0) v a l u e s are shown i n Figure 2. If t h e i d e n t i t y o f t h i s m o l e c u l e h a d b e e n t o t a l l y u n k n o w n to the i n t e r p r e t e r , t h e s e M F 1 1 . 0 s e l e c t i o n s s h o u l d h a v e i n d i c a t e d at l e a s t the g e n e r a l s t r u c t u r a l features of the m o l e c u l e to the interpreter. Thus a l l of the c o m p o u n d s of F i g u r e 2 h a v e e i t h e r three or four fused rings and a l l have the three f u s e d s i x membered r i n g s t h a t are a c t u a l l y p r e s e n t i n the u n k n o w n . The four t r i c y c l i c compounds c l o s e l y r e s e m b l e the correct structure i n h a v i n g m e t h y l g r o u p s i n t h e 4 , 4 , 1 0 , a n d 13 p o s i t i o n s , hydroxy at 8, and v i n y l at 1 3 . N o t e that three of the steroids contain a 5-hydroxy group, w h i c h c a n be v i e w e d as corresponding to the correct 8-hydroxy p o s i t i o n by " f l i p p i n g " the s t r u c t u r e s , w i t h their a c e t o x y groups then at l e a s t present i n the r i n g c o r r e s p o n d i n g to t h e r i n g c o n t a i n i n g t h e a c e t o x y group i n t h e u n k n o w n . The p r e s e n c e of h y d r o x y l a n d a c e t o x y g r o u p s are i n d i c a t e d b y the f a c t that e i g h t of the n i n e c o m p o u n d s c o n t a i n h y d r o x y l s a n d s e v e n c o n t a i n a c e t o x y g r o u p s ; o n l y t w o c o n t a i n more t h a n one h y d r o x y l g r o u p , w h i l e none c o n t a i n more t h a n one a c e t o x y . H o w e v e r , the compound does g i v e a m o l e c u l a r i o n , so that it s h o u l d be p o s s i b l e for the i n t e r p r e t e r to i n f e r c o r r e c t l y t h a t the u n k n o w n c o n t a i n s one acetoxy and two h y d r o x y l groups after d e d u c i n g the t r i c y c l i c s y s tem w i t h the other s u b s t i t u e n t s . A l s o , the steroid s e l e c t e d as the seventh compound has a 4 - g e m - d i m e t h y l group. For this u n k n o w n t h u s STIRS c a n g i v e f a i r c o n f i d e n c e i n a l l of t h e s t r u c t u r e a s s i g n m e n t s e x c e p t the p o s i t i o n of the a c e t o x y a n d one of the h y d r o x y g r o u p s ; there i s e v e n s o m e i n d i c a t i o n of t h e i r p o s i t i o n s , as i n the majority of s e l e c t e d s t r u c t u r e s of F i g u r e 2 t h e s e s u b stituents are o n the exterior r i n g b e a r i n g the bridgehead h y d r o x y l . P B M / S T I R S E x a m i n a t i o n of U n k n o w n S p e c t r a of F a t t y A c i d E s t e r s . In a n e a r l y c l a s s i c c a s e of n a t u r a l p r o d u c t s t r u c t u r e d e t e r m i n a t i o n b y m a s s s p e c t r o m e t r y (25) a c o m p o u n d i s o l a t e d a s the m e t h y l e s t e r from butterfat w a s i d e n t i f i e d to be m e t h y l 3 , 7 , 1 1 , 1 5 - t e t r a m e t h y l h e x a d e c a n o i c a c i d . T h e o r i g i n a l p u b l i s h e d (25) s p e c t r u m (omitted from the r e f e r e n c e file) w a s r u n t h r o u g h P B M a n d STIRS to g i v e the r e s u l t s s h o w n i n T a b l e I V . P B M c o r r e c t l y i d e n t i f i e d the compound as methyl p h y t a n o a t e , r e t r i e v i n g the two r e f e r e n c e s p e c t r a of t h i s compound i n the P B M reference file; note that the third s e l e c t i o n is a much p o o r e r m a t c h . The s u b s t r u c t u r e s i d e n t i f i e d b y STIRS M F 1 1 . 0 a n d 1 1 . 1 are c o r r e c t , although the a c e t a t e substructure i n d i c a t e d by M F 1 1 . 2 is not (Table IV). The b e s t - m a t c h i n g c o m p o u n d s found b y STIRS M F 1 1 . 0 a r e a l l m e t h y l e s t e r s of l o n g - c h a i n f a t t y a c i d s , and a l l but one has a methyl group i n the three p o s i t i o n . The p o s i t i o n s of the other m e t h y l groups w e r e not found b y STIRS, c o n s i s t e n t w i t h the rather s m a l l effect of s u c h methyl groups on the mass s p e c t r a .

COMPUTER-ASSISTED

OAc

STRUCTURE

ELUCIDATION

12/3 — Acetoxysandaracopimar— l 5 - e n - 8 / 3 , Ha — diol


(spectrum

MF

Figure

II.0

Best

2. Best-matching STIRS examination

not in file)

Matches:

compounds and their MF11.0 values found in the of 12j3-acetoxysandaracopimar-15-en-8p,li<x-diol

1.


Table IV.

Structure

Phytanic Acid Methyl Ester M e t h y l Phytanoate Isopropylidene batyl alcohol


13

Mass Spectra

U n k n o w n B u t t e r f a t M e t h y l E s t e r (not i n f i l e )

PBM;

STIRS:

of Unknown

Overall Match

MF11.0

K

AK

101+ 98+ 57**

0 2 4 3

14

COMPUTER-ASSISTED S T R U C T U R E

ELUCIDATION

As a further t e s t of t h e s e n s i t i v i t y of STIRS a n d P B M for s u c h structural d i f f e r e n c e s , the s p e c t r u m of m e t h y l 1 0 - m e t h y l nonadecanoate was run as an unknown without removing its s p e c trum from the r e f e r e n c e f i l e . Table V s h o w s , as e x p e c t e d , that Table V. file)

U n k n o w n , M e t h y l 10-methylnonadecanoate (spectrum i n

PBM:


Methyl 10-methylnonadecanoate Methyl n-eicosanoate Methyl 16-methylheptadecanoate Methyl 14-methylhexadecanoate

K

AK

159+ 102+ 84** 83***

0 10 28 29

STIRS, M F 1 1 . 0 :

- E o - , Methyl Methyl Methyl Methyl Methyl Methyl Methyl Methyl Methyl

-OCH

10-methylnonadecanoate 10-D-methyloctadecanoate 11-methylnonadecanoate n-docosanoate n-tricosanoate 17-methyloctadecanoate 16-methylheptadecanoate 13-methylpentadecanoate 15-methylhexadecanoate

3

919 844 774 749 745 734 733 733 72 6

t h i s s p e c t r u m i s t h e n r e t r i e v e d as the b e s t m a t c h for b o t h P B M a n d M F 1 1 . 0 of S T I R S . N o t e t h a t b o t h t h e P B M a n d STIRS r u n s h a v e r e t r i e v e d l o n g - c h a i n fatty a c i d methyl e s t e r s , most of w h i c h c o n t a i n a s i n g l e m e t h y l group s u b s t i t u t e d far from the ester f u n c t i o n a l i t y . L o c a t i n g t h e p o s i t i o n w i t h c o n f i d e n c e b y STIRS w o u l d r e q u i r e that the r e f e r e n c e f i l e c o n t a i n s a s u b s t a n t i a l number of s u c h 1 0 - m e t h y l d e r i v a t i v e s , as w e l l as that the e x a c t p o s i t i o n of the m e t h y l group p r o d u c e s s u b s t a n t i a l d i f f e r e n c e s i n the m a s s spectral behavior. The M S f r a g m e n t a t i o n - d i r e c t i n g c a p a b i l i t y of the c a r b o n y l group i s w e l l k n o w n , and i t s p o s i t i o n i n an a l k y l c h a i n s h o u l d have a m u c h greater effect o n the mass s p e c t r u m t h a n a m e t h y l g r o u p . T a b l e VI s h o w s the r e s u l t s of the P B M / S T I R S e x a m i n a t i o n of the m a s s s p e c t r u m of m e t h y l 3 - o x o n o n a d e c a n o a t e as a n u n k n o w n . N o w t h e f i v e b e s t m a t c h e s r e t r i e v e d b y STIRS M F 1 1 . 0 are a l l m e t h y l esters of l o n g - c h a i n fatty a c i d s w i t h a c a r b o n y l group i n the three p o s i t i o n .

1.


Table VI. file)

Structure

Unknown, Methyl

of Unknown

3-oxononadecanoate

PBM: Methyl 3-oxononadecanoate

15

Mass Spectra

(spectrum i n

K

AK

138+

0


STIRS, M F 1 1 . 0 :

Methyl Methyl Methyl Methyl Methyl

3-oxononadecanoate 3-oxoheptadecanoate 3-oxooctadecanoate 3-oxotetracosanoate 3-oxopentadecanoate

878 837 817 785 655

As a f i n a l e x a m p l e , the r e s u l t s of e x a m i n i n g the m a s s spectrum of g l y c e r y l t r i d o d e c a n o a t e as a n u n k n o w n are s h o w n i n Table VII. Although the unknown spectrum was not i n the f i l e , Table VII.

Unknown G l y c e r y l Tridodecanoate

PBM:

K

AK

120* 29***+

0 88

Glyceryl tridodecanoate Vinyl dodecanoate

(not i n f i l e )

STIRS, M F 1 1 . 0 : Glyceryl tridodecanoate Glyceryl tritetradecanoate G l y c e r y l - 2 - l a u r a t e - l , 3-distearate N-trifluoroacetyl-N-dodecyldodecanamide Glyceryl trioctadecanoate L - l ,2-dilauroylglycerylphosphoroylcholine G l y c e r y l - l - p a l m i t a t e - 2 , 3-distearate G l y c e r y l - 2 - l a u r a t e - l , 3-dipalmitate 1- S t e a r o - 2 , 3 - d i m y r i s t i n 2- Stearo-l, 3-diacetin Glyceryl trioctadecanoin G l y c e r o l - l , 3 - d i octadecanoate G l y c e r y l - 2 - m y r i s t a t e - l , 3-distearate

725 596 5 82 5 82 57 3 5 67 560 552 551 547 5 43 542 535

16

COMPUTER-ASSISTED STRUCTURE

ELUCIDATION


P B M r e t r i e v e d another s p e c t r u m of t h i s c o m p o u n d as a n e x c e l l e n t m a t c h , w i t h K and A K v a l u e s far s u p e r i o r to that of the o n l y other r e t r i e v e d s p e c t r u m , that of v i n y l d o d e c a n o a t e . The b e s t - m a t c h i n g c o m p o u n d s r e t r i e v e d b y STTRS M F 1 1 . 0 w e r e , w i t h o n l y o n e e x c e p t i o n , a l l g l y c e r y l esters c o n t a i n i n g fatty a c i d r e s i d u e s . The d o d e c a n o a t e (lauric) a c i d m o i e t y i s found i n f i v e of the eight b e s t matching c o m p o u n d s , w h i c h s h o u l d at l e a s t provide some help to the interpreter. P r a c t i c a l U s e of P B M a n d STTRS. O u r m a i n i n c e n t i v e of making these s y s t e m s a v a i l a b l e on the C o r n e l l computer o v e r the T Y M N E T s y s t e m (23) w a s t o g a i n f e e d b a c k o n t h e i r a p p l i c a t i o n t o r e a l u n k n o w n s . The authors w o u l d e s p e c i a l l y a p p r e c i a t e r e c e i v i n g s p e c t r a o n w h i c h P B M or STIRS a p p a r e n t l y d i d not g i v e s a t i s f a c t o r y r e s u l t s . It h a s b e e n o u r e x p e r i e n c e t h a t t h e b e s t w a y t o u n d e r s t a n d the u t i l i t y , a n d the s h o r t c o m i n g s , of P B M as a r e t r i e v a l s y s t e m , a n d of STIRS a s a n i n t e r p r e t i v e s y s t e m , i s to r u n s p e c t r a of compounds of d i r e c t i n t e r e s t to the p a r t i c u l a r u s e r . Because STIRS h a s b e e n d e s i g n e d a s a n a i d t o t h e i n t e r p r e t e r , t h e i n t e r preter s k n o w l e d g e of (and i n t e r e s t in) t h e s a m p l e a n d i t s c h e m i s try s h o u l d m a x i m i z e the i n f o r m a t i o n w h i c h c a n be g a i n e d from e x a m i n a t i o n of t h e STIRS r e s u l t s . U s i n g t h e s e r e s u l t s e f f i c i e n t l y does require experience. S u g g e s t i o n s a s to b e t t e r u s e of t h e s e r e s u l t s , or i m p r o v e m e n t s t o e i t h e r t h e P B M or STIRS s y s t e m , w i l l be welcomed by the authors. 1

Literature Cited 1. Waller, G. R., "Biochemical Applications of Mass Spectrometry", Wiley-Interscience, New York, 1972. 2. McFadden, W. H., "Techniques of Combined Gas Chromatography/Mass Spectrometry", Wiley-Interscience, New York, 1973. 3. Pesyna, G. M. and McLafferty, F. W., in "Determination of Organic Structures by Physical Methods", pp. 91-155, Nachod, F. C., Zuckerman, J. J., and Randall, E. W., Eds., Vol. 6, Academic Press, New York, 1976. 4. Isenhour, T. L., Kowalski, B. R., and Jurs, P. C., Critical Review Anal. Chem., (1974), 4, 1. 5. Smith, D. H., Buchanan, B. G., Engelmore, R. S., Adlercreutz, H., and Djerassi, C., J. Am. Chem. Soc., (1973), 95, 6087. 6. McLafferty, F. W., Hertel, R. H., and Villwock, R. D., Org. Mass Spectrom., (1974), 9, 690. 7. Pesyna, G. M., Venkataraghavan, R., Dayringer, H. E., and McLafferty, F. W., Anal. Chem., (1976), 48, 1362. 8. Kwok, K.-S., Venkataraghavan, R., and McLafferty, F. W., J. Am. Chem. Soc., (1973), 95, 4185.


I.

VENKATARAGHAVAN ET A L .

Structure

of Unknown

Mass Spectra

17

9. Dayringer, H. E., Pesyna, G. M., Venkataraghavan, R., and McLafferty, F. W., Org. Mass Spectrom., (1976), 11, 529. 10. Dayringer, H. E. and McLafferty, F. W., Org. Mass Spectrom., (1976), 11, 543. 11. Dayringer, H. E. and McLafferty, F. W., Org. Mass Spectrom., (1976), 11, 895. 12. Salton, G., "Automatic Information Organization and Retrieval", McGraw-Hill, New York, 1968. 13. Grotch, S. L., 17th Annual Conference on Mass Spectrometry, Dallas, May, 1969, p 459. 14. Pesyna, G. M., McLafferty, F. W., Venkataraghavan, R., and Dayringer, H. E., Anal. Chem., (1975), 47, 1161. 15. Abramson, F. P., Anal. Chem., (1975), 47, 45. 16. McLafferty, F. W., Anal. Chem., accepted. 17. Atwater, B. L., McLafferty, F. W., and Venkataraghavan, R., in preparation. 18. Hites, R. A. and Biemann, K., Adv. Mass Spectrom., (1968), 4, 37. 19. "ISI Chemical Substructure Dictionary", Institute for Scientific Information, Philadelphia, Pennsylvania, September, 1974. 20. Stenhagen, E., Abrahamsson, S., and McLafferty, F. W., "Registry of Mass Spectral Data", Wiley-Interscience, New York, 1974. 21. McLafferty, F. W., "Mass Spectral Correlations", Advances in Chemistry Series No. 40, American Chemical Society, Washington, 1963. 22. Cone, M. M., Venkataraghavan, R., and McLafferty, F. W., J. Am. Chem. Soc., submitted. 23. Office of Computer Services, Cornell University, Ithaca, New York 14853. 24. Brenner, L. and Suffet, I. H., Environ. Sci. Health, Part A, in press. 25. Ryhage, R. and Stenhagen, E., in "Mass Spectrometry of Organic Ions", p. 417, McLafferty, F. W., Ed., Academic Press, New York, 1963. Acknowledgment We are grateful to Professor I. H. Suffet of Drexel University for helpful discussions concerning the application of PBM and STIRS to actual problems, to the National Institutes of Health (grant 16609) and to the Environmental Protection Agency (grant R804509) for financial support of this work, and to the National Science Foundation for partial funding of the DEC PDP-11/45 computer used in this research.

2 Identification of the Components of Complex Mixtures by

GC-MS

J. E. BILLER, W. C. HERLIHY, and K. BIEMANN


Department of Chemistry, Massachusetts Institute of Technology, Cambridge,MA02139

It has been well-known for many years that Gas Chromatography-Mass Spectrometry is a powerful tool for the qualitative identification of the components of complex mixtures. It has also been well-established that the computer is neededinall aspects of this process beginning with the initial acquisition of the data from the laboratory instrument, the processing and "crunching" of the data, and presentation of the data to the human interpreter. In recent years, techniques to improve and enhance the data, as well as the many methods of interpretation and identification have also fallen almost totally into the province of the computer. Our laboratory has been intimately involved in the development and use of many of these techniques. Our needs are somewhat unique in the very large number of chemical problems from very diverse sources which require identifications or structure determinations. We currently acquire and analyze approximately one-half million spectra a year from such varied sources as drugs in body fluids, geochemical extracts, metabolism studies, organic synthetic studies, and many others. We have even had to extend the capability of our data enhancement and interpretive algorithms and routines to the analysis of spectra returned from the GC-MS instruments in the two Viking landers on the surface of Mars (1). The need to analyze and interpret such a large volume of data has many implications. The most important requirement is a fully automated system capable of maximum performance and efficiency from end-to-end. This means that the GC-MS instrumentation must produce the best quality data possible under the fast scan conditions necessary for reasonable resolution of complex mixtures. The man-machine interface must be simple and human-engineered to limit the probability of operator error; the computer-instrument interfaces (both data and control) have to be accurate and highly reliable. The basic processing of the data must be efficient, fast, economical and complete, and the presentation of such vast amounts of information must be accomplished 18


2.

BILLER ET AL.

Components

of Complex

Mixtures

by GC-MS

19

i n an e q u a l l y e f f i c i e n t , yet convenient form. Perhaps most imp o r t a n t l y (and c e r t a i n l y of the g r e a t e s t c o m p l e x i t y ) , the computer must be able to purge the s p e c t r a of background and other unavoidable i n t e r f e r e n c e s so t h a t i t can r e l i a b l y i n t e r p r e t the s p e c t r a to accomplish the primary task of the i d e n t i f i c a t i o n of the components of i n t e r e s t . In a d d i t i o n , the r o u t i n e analyses of such l a r g e amounts of data r e q u i r e p r a c t i c a l approaches to the design of r o u t i n e s to both enhance and i n t e r p r e t s p e c t r a . Very elegant and timeconsuming algorithms which improve the r e s u l t s by some s m a l l f r a c t i o n a l margin towards p e r f e c t i o n at the expense of e i t h e r l a r g e computer power or time are o b v i o u s l y not u s e f u l or a p p r o p r i a t e . In a s i m i l a r way, the approach to the p r e s e n t a t i o n of the data i n such huge q u a n t i t i e s n e c e s s a r i l y precludes impressive but imp r a c t i c a l i n t e r a c t i v e graphic systems which r e q u i r e i n o r d i n a t e amounts of both human and computer time. We f e e l that we have developed a p r a c t i c a l system a b l e to meet a l l of these needs. We would l i k e to b r i e f l y d e s c r i b e how t h i s has been accomplished, and i n a d d i t i o n , d e s c r i b e a new and powerful technique f o r the automated and i n t e l l i g e n t i d e n t i f i c a t i o n of o l i g o p e p t i d e s i n complex mixtures i n support of our work on p r o t e i n sequencing. A Comprehensive System f o r the A n a l y s i s of Complex M i x t u r e s As mentioned above, the f i r s t necessary component i n a balanced system f o r the i d e n t i f i c a t i o n of the c o n s t i t u e n t s of a complex mixture i s the source of the data. The GC-MS instrument must be designed and optimized f o r f a s t , continuous a c q u i s i t i o n of data over the e n t i r e GC a n a l y s i s . The scan f u n c t i o n must be accurate and r e p r o d u c i b l e , the data must be acquired w i t h h i g h s e n s i t i v i t y , low e l e c t r o n i c n o i s e , and wide dynamic range to accomodate the l a r g e c o n c e n t r a t i o n d i f f e r e n c e s common i n complex organic mixtures. This i s accomplished i n our l a b o r a t o r y on a h i g h l y modified H i t a c h i RMU-6L Mass Spectrometer i n t e r f a c e d to a P e r k i n Elmer 990 Gas Chromatograph v i a a Watson-Biemann f r i t t e d g l a s s separator (2). Almost a l l of the RMU-6L e l e c t r o n i c s have been replaced w i t h r e l i a b l e s o l i d - s t a t e c i r c u i t r y , and the magnet i s c o n t r o l l e d d i g i t a l l y to produce a f a s t , r e p r o d u c i b l e scan. The output of a s o l i d - s t a t e electrometer i s d i g i t i z e d at three separate g a i n l e v e l s to achieve a very accurate s i g n a l w i t h l a r g e dynamic range, high s i g n a l - t o - n o i s e r a t i o , and h i g h s e n s i t i v i t y (3). The system i s diagrammed i n F i g u r e 1. The data processing i n c l u d e s the normal m a s s - i n t e n s i t y r e d u c t i o n , and i n a d d i t i o n , the r o u t i n e generation of a l l mass chromatograms (3,4). To p r i n t or p l o t t h i s amount of i n f o r m a t i o n i n the conventional ways f o r even a s i n g l e sample would be very time-consuming and d i f f i c u l t . To s o l v e the data p r e s e n t a t i o n problem, a l l s p e c t r a and mass chromatograms are d i r e c t l y micro-

GAS

SCANNER UNIT

OPERATOR DIGITAL SCAN CONTROL/DISPLAY CONTROLLER CONSOLE

HITACHI RMU-6L ELECTRONICS CONSOLE

• SAMPLE-

CHROMATOGRAPH

t

Figure 1.

AUXILIARY PROCESSING UNIT

DIGITAL INPUT / OUTPUT

system

1800 DACS Basic GC-MS

IBM

1802 CPU

1851 MULTIPLEXER

configuration

ANALOG TO DIGITAL CONVERTER CORE MEMORY (32 K)

DATA CHANNEL CONTROLS (DMA)

DIGITAL SIGNAL CONDITIONING CONTROL AUXILIARY DIFFERENTIAL AMR, LOGIC AND FILTER, S/H AMR, PROG. PULSE MULTIPLEXER -GAIN ADJUSTMENT GENERATOR i J

ANALOG FM MAGNETIC TAPE

ELECR0N MULTIPLIER ELECTROMETER AMPLIFIER

MASS SPECTROMETER


TYPEWRITER

CARD READER AND PUNCH

LINE PRINTER

PLOTTER

DISKS (3)

DIGITAL TAPES (2)

CRT DISPLAY

s

bo o


2.

BILLER E T A L .

Components

of Complex

Mixtures

by

GC-MS

21

f i l m e d (5.,6). Thus, a l l of the i n f o r m a t i o n produced i n the course of the experiment i s permanently a v a i l a b l e t o the user independently of the computer. This approach i s very economical and more i m p o r t a n t l y , very e f f i c i e n t w i t h respect t o human and computer time and resources. To prepare the data f o r the s e v e r a l automated i n t e r p r e t i v e techniques a v a i l a b l e ( i n c l u d i n g both l i b r a r y searching and s e v e r a l more i n t e l l i g e n t and s p e c i a l i z e d i n t e r p r e t i v e a l g o r i t h m s f o r s p e c i f i c c l a s s e s of compounds), the technique of r e c o n s t r u c t i o n of the s p e c t r a was developed and i s being c o n s t a n t l y improved i n t h i s l a b o r a t o r y . Since t h i s technique has been described p r e v i o u s l y (_7), a b r i e f review of the concept w i l l be s u f f i c i e n t . S p e c t r a l data from a GC-MS a n a l y s i s i s acquired c o n t i n u a l l y , and a t a constant r a t e . Thus, the normal two dimensional view of the data and i t s i n f o r m a t i o n content (mass and i n t e n s i t y ) can be expanded t o three dimensions to i n c l u d e the time element. Components only p a r t i a l l y r e s o l v e d by the gas chromatograph w i l l normally show separate maxima i n the mass chromatograms characteri s t i c of those components a t the times t h e i r i n d i v i d u a l conc e n t r a t i o n s a r e g r e a t e s t . An enhanced s e t of s p e c t r a i s generated by performing a f u l l peak p r o f i l e a n a l y s i s on the e n t i r e mass chromatogram f o r every m/e value and then r e c o n s t r u c t i n g s p e c t r a at each scan by assembling only those m/e values which maximize at that scan. These r e c o n s t r u c t e d s p e c t r a a r e p r a c t i c a l l y f r e e of the c o n t r i b u t i o n s of unresolved companion substances, t a i l i n g f r a c t i o n s , column b l e e d , and other sources of i n t e r f e r e n c e . The Mass-Resolved Gas Chromatogram (the e q u i v a l e n t of a T o t a l I o n i z a t i o n P l o t generated from t h i s new s e t of r e c o n s t r u c t e d data) i s generated and the e n t i r e s e t of data i s m i c r o f i l m e d . The Mass-Resolved Gas Chromatogram i s now a w e l l - r e s o l v e d i n d i c a t i o n of the number, l o c a t i o n , and r e l a t i v e i n t e n s i t y of each of the components i n the mixture. The r e c o n s t r u c t e d s p e c t r a a r e r e l a t i v e l y f r e e of i n t e r f e r ences which o f t e n make the c o r r e c t i d e n t i f i c a t i o n of the v a r i o u s components more d i f f i c u l t i f not i m p o s s i b l e . Automated i d e n t i f i c a t i o n techniques such as l i b r a r y searching and others such as the a l g o r i t h m f o r the i n t e r p r e t a t i o n of peptide mixtures d e s c r i b e d below a r e g r e a t l y f a c i l i t a t e d , and the r e s u l t a n t r e l i a b i l i t y g r e a t l y improved. An I n t e r p r e t i v e A l g o r i t h m f o r Complex Peptide M i x t u r e s The determination of the amino a c i d sequence of p o l y peptides i s of great i n t e r e s t and has been shown to be amenable to a n a l y s i s by gas chromatography-mass spectrometry ( 8 ) . I n order to c l a r i f y the ensuing d i s c u s s i o n of an a l g o r i t h m to automate the i n t e r p r e t a t i o n of o l i g o p e p t i d e mass s p e c t r a , the peptide sequencing s t r a t e g y used i n t h i s l a b o r a t o r y w i l l be b r i e f l y d e s c r i b e d . A p o l y p e p t i d e , such as Subunit I of the sweet p r o t e i n M o n e l l i n ( 9 ) , i s p a r t i a l l y hydrolyzed w i t h weak


22

COMPUTER-ASSISTED S T R U C T U R E E L U C I D A T I O N

a c i d or enzymes to produce a complex mixture of d i - to pentapeptides. These peptides are d e r i v a t i z e d to enhance t h e i r v o l a t i l i t y (10) (Figure 2 ) , and i n j e c t e d i n t o a gas chromatograph-mass spectrometer system which r e s u l t s i n 200-300 mass s p e c t r a of the 15-50 o l i g o p e p t i d e s i n the mixture. One must now l o c a t e and i d e n t i f y a l l of these o l i g o p e p t i d e s and f i n a l l y reassemble them to determine the sequence of the o r i g i n a l p o l y peptide. Since the manual i d e n t i f i c a t i o n of a l l the components of these complex mixtures i s a time-consuming and d i f f i c u l t task, an automated procedure was needed. Searching the unknown s p e c t r a against a l i b r a r y of standard s p e c t r a i s not f e a s i b l e s i n c e a l i b r a r y of a l l p o s s i b l e d i - to pentapeptides would c o n t a i n approximately 3.4 m i l l i o n s p e c t r a . An i n t e r p r e t i v e a l g o r i t h m i s f e a s i b l e , however, s i n c e the p o l y aminoalcohol d e r i v a t i v e s (Figure 2) used i n t h i s l a b o r a t o r y d i s p l a y p r e d i c t a b l e fragmentation p a t t e r n s . By examining a l a r g e number of standard peptide s p e c t r a we have found that d i peptides always e x h i b i t an i n t e n s e Z l i o n ; t r i - to pentapeptides always show a prominent A2 i o n , and t e t r a - and pentapeptides always e x h i b i t an i n t e n s e A3 i o n . In a d d i t i o n to these fragment a t i o n r u l e s , the a l g o r i t h m makes use of the amino a c i d composition of the o r i g i n a l p o l y p e p t i d e , and the r e t e n t i o n index f o r each scan which i s c a l c u l a t e d by a p r e v i o u s l y described method (11). A l s o , as has been p r e v i o u s l y shown, (12) we can c a l c u l a t e the expected r e t e n t i o n index f o r any o l i g o p e p t i d e which i s a f u n c t i o n of i t s composition, but r e l a t i v e l y independent of the amino a c i d sequence. Based on t h i s i n f o r m a t i o n the a l g o r i t h m shown i n Table I was developed. I t should be noted that f o r the e n t r i e s i n the peptide l i s t i n steps 1 and 3, the order of the amino a c i d s i s not s i g n i f i c a n t . Thus, a l l t e t r a p e p t i d e s which have the composition (A,B2,C) w i l l be represented by a s i n g l e entry. In steps 4-7, however, the order of the amino a c i d s i n s p e c i f i c , so that these steps r e f e r to sequences and not j u s t combinations of amino a c i d s . Steps 1 and 3 are f i l t e r s based on the amino a c i d composition of the o r i g i n a l polypeptide and the r e t e n t i o n index of the unknown s p e c t r a . Step 4 i s a f i l t e r based on the r e l i a b l e A2 i o n ( Z l f o r d i p e p t i d e s ) . S i m i l a r l y , step 6 i s a f i l t e r based on the known presence of an A3 i o n i n the s p e c t r a of t e t r a - and pentapeptides. For the h y p o t h e t i c a l example shown i n Table I an A2 i o n i s assumed to have been found f o r the p a r t i a l sequences AB.. and BA.., and an A3 i o n i s assumed to have been found only f o r the sequences ABBC and BABC. The c a l c u l a t i o n i n step 7 i s complex and w i l l be presented i n d e t a i l elsewhere (13). I t should be noted that c o r r e c t i d e n t i f i c a t i o n of an unknown spectrum i s not dependent on the presence of a molecular i o n , nor any s p e c i f i c sequence i o n (except the r e l i a b l e A2, A3, and Z l as described above). This a l g o r i t h m was t e s t e d on the data from the a n a l y s i s of a mixture of o l i g o p e p t i d e s generated i n an a c i d h y d r o l y s i s e x p e r i -

BILLER ET A L .

Components

of Complex

Mixtures

by

GC-MS

o

Q

i 0

1

14. Oppm

l^ppm.

The a s t e r i s k d e n o t e s t h e atom f o r which the shift is p r e d i c t e d . The p r e d i c t i o n i s g i v e n i n ppm down f i e l d from TMS. The important s u b s t r u c t u r a l arrangements given i n the r u l e are actually constructed by t h e program from a language of features supplied by t h e user. Molecular structure elucidation i s accomplished

60


by o b s e r v i n g a t o t a l s h i f t and f i n d i n g t h e r u l e s which are possible explanations f o r the shift. The rules selected postulate p a r t i a l substructures w h i c h m i g h t be i n the m o l e c u l e . These s u b s t r u c t u r e s are assembled to construct the f i n a l molecule. A description of the rule formation and structure elucidation programs a p p l i e d t o t h e p a r a f f i n s and a c y c l i c a m i n e s i s g i v e n i n the f o l l o w i n g s e c t i o n s . We b e l i e v e t h e a l g o r i t h m s u s e d are g e n e r a l enough to t r e a t w i d e l y d i f f e r e n t c l a s s e s of compounds. Rules generated for decalins, methyldecalins and h y d r o x y - s t e r o i d s a r e shown i n the third section.


Empirical

Rule

Formation

Rule G e n e r a t i o n . The r u l e g e n e r a t i o n p r o g r a m (.2.) must be s u p p l i e d a training set of known s t r u c t u r e s with t h e i r assigned spectra. A set of p r i m i t i v e terms which w i l l form the l a n g u a g e o f atom f e a t u r e s used to d e s c r i b e t h e a t o m s and b o n d s ( a t o m t y p e , number o f nonhydrogen neighbors, orientation of substituents, e t c . ) m u s t a l s o be supplied. These terms are combined to c o n s t r u c t s t r u c t u r a l fragments which imply a total shift. The chemist also sets two parameters which regulate the generality of the rules generated. MINIMUM-EXAMPLES is a parameter which s p e c i f i e s the minimum number o f d a t a p o i n t s w h i c h a r u l e must e x p l a i n w i t h i n the t r a i n i n g s e t . The o t h e r p a r a m e t e r , MAXIMUMRANGE, s p e c i f i e s t h e maximum a l l o w a b l e s h i f t range f o r a rule. I f the c h e m i s t wants o n l y the most g e n e r a l t r e n d s i n the d a t a he c a n require a larger number o f examples with moderately s i z e d s h i f t ranges. The f o r m a t o f t h e r u l e s g e n e r a t e d i s substructure

implies^

13

Q

s

h

i

f

t

r a n

ge.

I f the s u b s t r u c t u r e to the l e f t of the arrow w i t h i n some m o l e c u l e t h e n there i s a s h i f t range g i v e n to the r i g h t of the arrow. The i n T a b l e I was g e n e r a t e d on a c o m b i n e d s e t a m i n e s and p a r a f f i n s .

i s present w i t h i n the r u l e shown of a c y c l i c

5.

S C H W E N Z E R AND

MITCHELL

Table

C

NMR

I

Rule

13

61

Rules

Form

1 >

5-4-3-2-7

44.7ppm

^

g(3)$

44.9ppm

8


Node

1,5,7,8 2 3 4

Atom Type C C C C

Number o f n o n - h y d r o g e n Neighbors 5^

4 2 2

For the s u b s t r u c t u r e shown i n Table I w i t h the c o r r e s p o n d i n g atom f e a t u r e s f o r atom t y p e and number o f n o n - h y d r o g e n n e i g h b o r s atom number 3 w i l l h a v e a C-13 shift in the range 4 4 . 7 p p m to 4 4 . 9 p p m d o w n f i e l d from TMS. The r u l e search procedure i s shown i n Figure 1 . The search begins with the general seed rule C->-oo^g ^ oo ( w h e r e C may be any c a r b o n atom w i t h any atom prSperties and is the observed s h i f t ) and proceeds to expand t h i s r u l e by a d d i n g new a t o m s and atom f e a t u r e s t o t h e s u b s t r u c t u r e w h i c h w i l l n a r r o w t h e p r e d i c t e d range of s h i f t s . The s e e d r u l e i n Figure 1 is expanded by considering a l l possible v a l u e s of "number of n e i g h b o r s " of the central carbon. Each resulting level 1 s u b s t r u c t u r e i s expanded i n level 2 by adding either an "atom type" or "number of neighbors" s p e c i f i c a t i o n to e a c h atom one bond away from the c e n t r a l carbon. At each step o n l y a single atom f e a t u r e from the user s u p p l i e d list i s added. Each s u b s t r u c t u r e g e n e r a t e d i s a s s o c i a t e d w i t h a range o f C-13 s h i f t s . This range i s determined by s e a r c h i n g for o c c u r r e n c e s of the s u b s t r u c t u r e w i t h i n the t r a i n i n g set molecules. The s h i f t range associated w i t h the substructure i s the range of a l l occurrences of the s u b s t r u c t u r e i n the t r a i n i n g s e t . Each s u b s t r u c t u r e g e n e r a t e d i n the r u l e search i s e v a l u a t e d i n terms of the a s s o c i a t e d s h i f t range. If the shift range i s narrower than the range of the p a r e n t r u l e t h e n the added s p e c i f i c a t i o n i s considered to be u s e f u l and t h e search continues from the new substructure, o t h e r w i s e the path i s terminated. The

62

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C*-^-oo^S ^oo c


LEVEL I: SPECIFICATION^ OF NEIGHBORS

(paths to other descendents)

C*-*8.I^S 66.9<S(^68.0

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UNIQUE STRUCTURE

EXPERIMENTAL DESIGN AND EXECUTION

Figure

1.

"Manual"

structure

elucidation

MOLECULAR FORMULA

COMPATIBLE

STRUCTURES

CHEMICAL DATA f AUTOMATED INTERPRETER/

Figure

2.

CASE

network

TRUNCATED LIST OF STRUCTURES


7.

SHELLEY

ET

AL.

Interactive

Structure

Elucidation

95

as c o n t a i n i n g a c a r b o x y l i c a c i d f u n c t i o n a l i t y . Simil a r i n i t i a l s e t s o f g u i d e l i n e s must be e s t a b l i s h e d f o r a l l other f u n c t i o n a l i t i e s . Next the program i s t e s t e d on some i n f r a r e d s p e c t r a . Anytime the program makes an e r r o n e o u s i n t e r p r e t a t i o n , i t i s n e c e s s a r y t o a l t e r the g u i d e l i n e s t o c o r r e c t the m i s t a k e . As l o n g as a c h e m i s t can do a b e t t e r j o b o f i n t e r p r e t i n g a spectrum than the program, then the program can be a l t e r e d by u s i n g t h i s new i n f o r m a t i o n so t h a t i t w i l l do a b e t t e r j o b o f i n t e r p r e t a t i o n i n the f u t u r e . T h i s a b i l i t y t o a l t e r the program t o c o r r e c t m i s t a k e s i s a major advantage o f a r t i f i c i a l i n t e l l i g e n c e programming. As w i t h o t h e r components o f CASE, the i n f r a r e d i n t e r preter i s continually evolving. The c o m p u t e r - d e r i v e d a n a l y s i s o f t h e i n f r a r e d spectrum can be reviewed by the c h e m i s t p r i o r t o a u t o m a t i c e n c o d i n g , or t h e c h e m i s t can be bypassed, w i t h t h e a u t o m a t i c a l l y encoded f u n c t i o n a l group i n f o r m a t i o n b e i n g s e n t d i r e c t l y t o the m o l e c u l e assembler. The development o f programs f o r the automated i n t e r p r e t a t i o n of other spectroscopic information i s a t an e a r l i e r s t a g e . A preliminary investigation u s i n g p a t t e r n r e c o g n i t i o n t e c h n i q u e s t o a i d i n the i n t e r p r e t a t i o n o f 13c-NMR s p e c t r a has y i e l d e d promising results. A t the p r e s e n t t i m e , much o f the r e maining i n t e r p r e t a t i o n of s p e c t r a l data i s chemistderived. CASE a l s o i n c o r p o r a t e s programs f o r the automated i n t e r p r e t a t i o n of chemical information. As an example, CASE a c c e p t s t h e number o f moles o f p e r i o d a t e consumed by a compound and uses the i n f o r m a t i o n t o c o n s t r a i n t h e m o l e c u l e assembler. Thus, o n l y m o l e c u l e s c o n s i s t e n t w i t h the p e r i o d a t e i n f o r m a t i o n a r e assembled. The m o l e c u l e assembler a c c e p t s b o t h the computerd e r i v e d and u s e r - d e r i v e d s t r u c t u r a l i n f o r m a t i o n , and, g i v e n the m o l e c u l a r f o r m u l a , c o n s t r u c t s a l l s t r u c t u r a l isomers c o m p a t i b l e w i t h the i n p u t . A nonredundant l i s t i n g o f the c o m p a t i b l e m o l e c u l e s i s p r e s e n t e d t o the c h e m i s t i n the c o n v e n t i o n a l s t r u c t u r a l language. The l i s t o f c o m p a t i b l e m o l e c u l e s u s u a l l y can be f u r t h e r t r u n c a t e d by comparing c e r t a i n p r e d i c t e d s p e c t r o s c o p i c p r o p e r t i e s f o r each m o l e c u l e c o n s t r u c t e d w i t h the o b s e r v e d s p e c t r o s c o p i c p r o p e r t i e s o f the unknown. The t a s k s o f p r e d i c t i n g , comparing, and r a n k i n g are a s s i g n e d t o the spectrum s i m u l a t o r . These programs a r e a l s o a t an e a r l y s t a g e of development. One o p e r a t i o n a l component c a l l e d PEAK w i l l be i l l u s trated later. G i v e n a m o l e c u l a r s t r u c t u r e , PEAK p r e d i c t s the number o f s i g n a l s e x p e c t e d i n the l^C-NMR spectrum.


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The m o l e c u l e assembler ( F i g u r e 3) i s unique i n approach and i n i t s s i m p l e s t form was d e s i g n e d t o expand e x h a u s t i v e l y the c o n v e n t i o n a l p a r t i a l s t r u c t u r e i n t o a l l s t r u c t u r a l isomers c o n s i s t e n t w i t h i t . The a l g o r i t h m on which the assembler i s based i s r e c u r s i v e . By c o n c e n t r a t i n g more on p a r t i a l s t r u c t u r e e x p a n s i o n than on m o l e c u l a r f o r m u l a e x p a n s i o n , g r e a t e r compactness and e f f i c i e n c y were a c h i e v e d . From the s t a r t i t was r e c o g n i z e d t h a t a b r o a d l y a p p l i c a b l e m o l e c u l e assembler must be c a p a b l e o f u t i l i z i n g more i n f o r m a t i o n than j u s t the c o n v e n t i o n a l p a r t i a l s t r u c t u r e , because the c h e m i s t g e n e r a l l y has more i n f o r m a t i o n than can be e x p r e s s e d by the conventional p a r t i a l structure. Thus, i n F i g u r e 3 the term " p a r t i a l s t r u c t u r e " i s used i n a b r o a d e r c o n t e x t . The p a r t i a l s t r u c t u r e i n c l u d e s the m o l e c u l a r f o r m u l a and c o m p u t e r - d e r i v e d and/ o r c h e m i s t - d e r i v e d s t r u c t u r a l fragments. Atoms i n t h e s e fragments must not d u p l i c a t e one a n o t h e r ; t h a t i s , t h e fragments must be n o n o v e r l a p p i n g . The p a r t i a l s t r u c t u r e a l s o i n c l u d e s supplementary i n f o r m a t i o n t h a t cannot be e x p r e s s e d i n terms o f n o n o v e r l a p p i n g s t r u c t u r a l fragments. Communication w i t h CASE i s a c h i e v e d by means t h a t mimic the n a t u r a l language o f the c h e m i s t . The molecu l a r f o r m u l a i s i n p u t i n s t a n d a r d format. The v e r s a t i l e l i n e a r code d e s i g n e d f o r s t r u c t u r a l fragment i n p u t i s i l l u s t r a t e d i n F i g u r e 4. Thus, l i n e s 1, 3, 5, 7 and 9 r e p r e s e n t r e s p e c t i v e l y , a 1 - h y d r o x y e t h y l group w i t h a s i n g l e r e s i d u a l v a l e n c e a t the 1 - p o s i t i o n , a c a r b o n y l group w i t h d o u b l y d e f i c i e n t carbon atom, a c a r b o n y l group j o i n e d t o oxygen w i t h v a l e n c e d e f i c i e n c i e s a t carbon and s i n g l e bonded oxygen, a c a r b o x y l group and a c y c l o h e x a n e r i n g w i t h each c a r b o n atom doubly valence d e f i c i e n t . In the l a t t e r example, note t h a t r i n g d e s i g n a t i o n i s a c h i e v e d by l a b e l i n g one carbon atom w i t h a number (1 i n t h i s case) and f o r m i n g a bond between a carbon f i v e atoms removed and t h e label. The l i n e a r code may be f u r t h e r e l a b o r a t e d by a d d i n g atom and fragment tags t o d e s c r i b e t h e l o c a l environment o f atoms i n a s t r u c t u r a l fragment w i t h o u t c o n c e r n f o r o v e r l a p p i n g atoms. F o r example, the v a l e n c e d e f i c i e n t carbon atom o f the 1 - h y d r o x y e t h y l group i s r e q u i r e d t o bond t o a methine c a r b o n by the a d d i t i o n o f t h e atom t a g ( l i n e 2 ) . S i n c e the i n f o r m a t i o n i s p r o v i d e d by means of t h e t a g , the c h e m i s t need not be concerned whether t h a t methine c a r b o n d u p l i c a t e s a s i m i l a r group i n a n o t h e r s t r u c t u r a l fragment.

7.

SHELLEY E T AL.

Interactive

Structure

97

Elucidation

MOLECULAR FORMULA NONREDUNDANT LIST OF COMPATIBLE STRUCTURES


STRUCTURAL FRAGMENTS

SUPPLEMENTARY INFORMATION

Figure

3.

Molecule

assembler

1. CH3-CH-0H

2. CH -CH-0H 3

3. 0=C L

0 = C

MOLECULAR FORMULA

5. 0 = C-0 6. 0 = C-0 7. 0 = C-OH

STRUCTURAL FRAGMENTS

8. 0 = C-OH 9. 1:C-C-C-C-C-C-1 10. 1:C-C-C-C-C-C-1 MULTIPLE BONDS RINGS SUBSTRUCTURE CONTROL AUTOMATED CHEMICAL CONSTRAINTS AUTOMATED SPECTROSCOPIC CONSTRAINTS^

Figure

4.

SUPPLEMENTARY INFORMATION

Constraints

PARTIAL STRUCTURE


98


Statement 4 r e s t r i c t s the environment o f t h e c a r b o n y l c a r b o n atom w i t h t h r e e atom t a g s : p r o h i b i t s i t s p r e s e n c e as p a r t o f a 3-5 membered r i n g , i . e . , t h e c a r b o n y l group i s u n s t r a i n e d (R f o r r i n g , 03 f o r minimum r i n g s i z e , 05 f o r maximum r i n g s i z e , 0 f o r minimum number o f s u c h r i n g s , 0 f o r maximum number o f such r i n g s ) , and and r e q u i r e t h e c a r b o n y l t o be f l a n k e d by a methine and a methylene group, respectively. Statement 6 s p e c i f i e s a five-membered lactone w i t h u n s a t u r a t i o n c o n j u g a t e d t o t h e a l c o h o l oxygen. The environment o f t h e c a r b o n y l c a r b o n atom i s d i s c l o s e d by t h r e e atom t a g s : r e q u i r e s t h a t i t j o i n t o c a r b o n , d e s i g n a t e s t h a t i t must be p a r t o f a five-membered r i n g (the absence o f minimum and maximum v a l u e s f o r t h e number o f such groups i n f e r s a minimum o f 1) and p r e c l u d e s t h e p r e s e n c e o f a , 3 u n s a t u r a t i o n t o t h a t c a r b o n atom (= i s t h e double bond symbol, 0 f o r minimum number o f d o u b l e bonds, 0 f o r maximum number). The two atom t a g s f o r the a l c o h o l oxygen r e q u i r e t h a t i t bond t o c a r b o n () and the p r e s e n c e o f a , 3 - u n s a t u r a t i o n (). Statement 8 r e p r e s e n t s a c a r b o x y l i c a c i d f u n c t i o n t h a t cannot b e a r a , 3 - u n s a t u r a t i o n . The symbol i s a fragment t a g t h a t i n s t r u c t s t h e program t o f o r b i d the f o r m a t i o n o f i n t e r n a l bonds i n a fragment. Thus, because o f statement 10, no m o l e c u l a r s t r u c t u r e s cont a i n i n g m u l t i p l e bonds o r b r i d g e s i n t h e c y c l o h e x a n e r i n g w i l l be assembled. Some s t r u c t u r a l i n f o r m a t i o n i s n o t s p e c i f i c t o atoms or fragments and must be t r e a t e d s e p a r a t e l y . Thus, M u l t i p l e Bonds d e s i g n a t e s the number, e i t h e r e x a c t o r a range, and k i n d s o f m u l t i p l e bonds a l l o w e d ; Rings p e r m i t s t h e same c o n t r o l o v e r r i n g s . Substruct u r e C o n t r o l can be used t o r e q u i r e t h e p r e s e n c e o r absence o f any s p e c i f i e d s t r u c t u r a l fragment u s i n g t h e same l i n e a r code d e s c r i b e d . Automated C h e m i c a l and S p e c t r o s c o p i c C o n s t r a i n t s i n s t r u c t the m o l e c u l e assemb l e r to generate only those s t r u c t u r e s c o n s i s t e n t with the a p p l i e d c o n s t r a i n t s . F o r example, the a p p l i e d c o n s t r a i n t may be t h e number o f moles o f p e r i o d a t e t h a t an unknown compound consumes o r the number o f s i g n a l s i n t h e -^C-NMR spectrum o f t h e unknown. These a p p l i c a t i o n s w i l l be i l l u s t r a t e d l a t e r . The i n f o r m a t i o n c o n t a i n e d i n " p a r t i a l s t r u c t u r e " ( F i g u r e 3) i s used i n a way t h a t maximizes t h e e f f i c i e n c y o f the molecule assembler. The g o a l i s t o p r e c l u d e the assembly o f an i n v a l i d m o l e c u l e r a t h e r t h a n r e j e c t i t a f t e r assembly. Thus, i n most c a s e s , atom and fragment t a g s , and supplementary i n f o r m a t i o n


7.

SHELLEY E T A L .

Interactive

Structure

Elucidation

99

c o n s t r a i n the assembly p r o c e s s . In o t h e r c a s e s , retrospective searching i s required. The m o l e c u l e assembler i s c o n s t r a i n e d i n o t h e r ways as w e l l . 1. A u s e r - d e f i n e d l i b r a r y o f h i g h l y s t r a i n e d o r c h e m i c a l l y u n s t a b l e m o e i t i e s c o n s t r a i n s the assembly o f m o l e c u l e s c o n t a i n i n g t h e s e s t r u c t u r a l f e a t u r e s , £•£•/ a c y c l o p r o p a n o n e r i n g . 2. The assembly o f d u p l i c a t e s t r u c t u r e s i s minimized. A number o f t e c h n i q u e s a r e i n c o r p o r a t e d i n t o the program t o e l i m i n a t e duplicates prospectively. The most i m p o r t a n t t e c h n i q u e i n v o l v e s the p e r c e p t i o n o f t o p o l o g i c a l symmetry (11) a t each s t e p o f t h e assembly p r o c e s s . In t h i s way, o n l y one member o f a group o f t o p o l o g i c a l l y e q u i v a l e n t v a l e n c e - d e f i c i e n t atoms i s p e r m i t t e d t o i n i t i a t e bond f o r m a t i o n . In s p i t e o f t h e h e u r i s t i c s used, t h e t o t a l e x c l u s i o n o f d u p l i c a t e s cannot always be a s s u r e d . Those d u p l i c a t e s s t i l l formed can be e l i m i n a t e d retrospectively. A newly d e s i g n e d and h i g h l y e f f i c i e n t c a n o n i c a l naming a l g o r i t h m performs t h i s r e m a i n i n g t a s k . The a l g o r i t h m a l s o r e c o g n i z e s resonance forms and i n c l u d e s o n l y one member on t h e l i s t o f v a l i d s t r u c t u r e s . Applications In t h e d i s c u s s i o n o f a p p l i c a t i o n s , our purpose i s t o p r o v i d e an o v e r v i e w o f the system network, i t s i n t e r a c t i v e n a t u r e , and i t s scope. CASE was o r i g i n a l l y d e v e l o p e d on r e a l w o r l d problems under s t u d y i n our own l a b o r a t o r y and i n a c o u p l e o f o t h e r n a t u r a l products l a b o r a t o r i e s . In more r e c e n t y e a r s "simul a t e d " r e a l w o r l d problems, t h a t i s , problems t a k e n from t h e c h e m i c a l l i t e r a t u r e , have a l s o p l a y e d an important r o l e . Such problems, a l t h o u g h a d m i t t e d l y somewhat c o n t r i v e d , p r o v i d e d the n e c e s s a r y b r e a d t h o r depth e x a c t l y when needed i n t h e program development and t e s t i n g . S p e c i f i c k i n d s o f problem s i t u a t i o n s a r e d i f f i c u l t t o produce on demand w i t h slower moving r e a l w o r l d s t r u c t u r e problems. F a u l k n e r e t a l . (_12) r e c e n t l y i s o l a t e d a h a l o g e nated monoterpene from a sea hare and r e p o r t e d t h e s t r u c t u r e (A). The assignment was made i n p a r t on the c h e m i c a l and s p e c t r o s c o p i c d a t a r e p o r t e d i n the paper and i n p a r t by analogy t o a r e l a t e d known compound. The s t r u c t u r a l i n f o r m a t i o n d e r i v e d from the c h e m i c a l and s p e c t r o s c o p i c d a t a i s shown i n the I/O p r i n t o u t o f

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STRUCTURE

ELUCIDATION

the i n i t i a l run o f t h e problem ( F i g u r e 5 ) . The mol e c u l a r f o r m u l a i s i n p u t as C 1 0 H 1 3 B 2 X 3 , where X, a s t a n d a r d h a l o g e n symbol, i s CI i n t h i s problem, and B i s u s e r - d e f i n e d as B r . S i n c e B i s n o t a s t a n d a r d mol e c u l a r f o r m u l a symbol, t h e computer asks t h e u s e r t o s p e c i f y i t s v a l e n c e . Next the n o n o v e r l a p p i n g f r a g ments are l i s t e d . In o r d e r they a r e : an a l l y l c h l o r i d e fragment w i t h a l l carbon atoms h a v i n g r e s i d u a l v a l e n c e , a v i n y l bromide u n i t , a bromomethylene u n i t , and two CH groups each a t t a c h e d t o a q u a t e r n a r y carbon. The s t r u c t u r e c o n s t r a i n i n g d e v i c e , S u b s t r u c t u r e C o n t r o l , i s used t o l i m i t t h e number o f CH groups t o t h e known v a l u e o f 2. A t t h i s p o i n t we a r e ready t o s t a r t the m o l e c u l e assembler. S i n c e we have no e s t i m a t e on t h e t o t a l number o f s t r u c t u r a l isomers c o n s i s t e n t w i t h t h i s i n p u t , we s e t some a r b i t r a r y l i m i t on m o l e c u l e assembly, 20 i n t h i s c a s e , t o make c e r t a i n t h a t the problem s t r a t e g y i s i n d e e d sound b e f o r e g i v i n g f r e e r e i n t o t h e m o l e c u l e assembler. The f i r s t 20 s t r u c t u r e s were examined and we found t h a t we c o u l d e a s i l y c o n s t r a i n the m o l e c u l e assembler w i t h 2 a d d i t i o n a l p i e c e s o f i n f o r m a t i o n because we saw a c o n j u g a t e d d i e n e i n some s t r u c t u r e s and a gem-dimethyl group i n some s t r u c t u r e s . One o f the a u t h o r s o f t h e paper, Dr. I r e l a n d , i n d i c a t e d the a v a i l a b i l i t y o f e v i d e n c e , not i n t h e paper, to e x c l u d e a c o n j u g a t e d d i e n e . In a d d i t i o n , the geminal methyl groups s h o u l d have been e x c l u d e d by us based on the p u b l i s h e d PMR i n f o r m a t i o n . These two c o n s t r a i n t s were added by c a l l i n g Substructure C o n t r o l (Figure 6). Sixteen structures were g e n e r a t e d . Of the 16, 8 had geminal c h l o r i n e atoms. I r e l a n d b e l i e v e d t h e s e s t r u c t u r e s t o be unl i k e l y on t h e b a s i s o f i n d i r e c t c h e m i c a l e v i d e n c e . The r e m a i n i n g 8 c a n d i d a t e s c o u l d be pruned t o 4 s t r u c t u r e s on t h e b a s i s o f some o f t h e mass s p e c t r o s c o p i c data. The s t r u c t u r e a s s i g n e d (A) i s one o f the f o u r . 3


3

In our own s t r u c t u r e work on the a n t i b i o t i c a c t i n o b o l i n (_5 ) , which i s a compound u n r e l a t e d i n s t r u c t u r a l type t o known a n t i b i o t i c s , an e a r l i e r v e r s i o n o f CASE was used. The s t r u c t u r e study was i n i t i a t e d by an e x a m i n a t i o n o f a d e g r a d a t i o n p r o d u c t ,

SHELLEY E T AL.

Interactive

Structure

Elucidation


T I T L E J FAULKNER J0Cv41. v2461 (1976) • E N T E R T H E MAXIMUM NUMBER OF S T R U C T U R E S TU B E G E N E R A T E D J MOLECULAR FORMULA• C 1 0 H 1 3 B 2 X 3 WHAT I S T H E V A L E N C E OF A B ATOM? t 1 FRAGMENT ( S ) t CH-CH-CH--X FRAGMENT(S)• CH«CH-B FRAGMENT(S)i CH2-B F R A G M E N T ( S ) : CH3 CH3 FRAGMENT(S): ? C O N S T R A I N T ( S ) J SUBSTR FRAGMENT(S): CH3 5 MINIMUM• 2 MAXIMUM: 2 CONSTRAINTS) : y COMMAND: G E N E R A T E

20

STRUCTURE'S G E N E R A T E D Figure

5

T I T L E J FAULKNER JOC.41*2461(1976)• M 0 L E C U L A R F 0 R MIJ I... A I C :l. 0 H 1.3 B 2 X 3 WHAT I S T H E V A L E N C E OF A B ATOM? S 1. F R A G M E N T ( S ) : CH=CH-CH-X F R A G M E N T ( S ) : CH=CH~B FRAGMENT(S)t CH2-B F R A G M E N T ( S ) J CH3 C H 3 < C H 0 > FRAGMENT(S ) : ? CONSTRAINT< S ) J SUBSTR FRAGMENT(S)J CH3 t MINIMUM: 2 MAXIMUM: 2 C O N S T R A I N T ( S ) : SUBSTR F R A G M E N T ( S ) : C=C - C=C ? MINIMUM: o MAXIMUM: o C O N S T R A I N T ( S ) : SUBSTR FRAGMENT(S): CH3-C-CH3 v MINIMUM: o MAXIMUM: o CONSTRAINT(S): y COMMAND: G E N E R A T E

1.6 S T R U C T U R E S G E N E R A T E D Figure 6


102


ELUCIDATION

actinobolamine (B), c o n t a i n i n g 9 o f the o r i g i n a l 13 c a r b o n atoms ( 2_ ) . T h a t problem has been r e r u n on the c u r r e n t v e r s i o n o f CASE. The IR i n t e r p r e t e r program r e p o r t s the p r e s e n c e o f a l c o h o l and ketone w i t h h i g h c o n f i d e n c e l e v e l s , 4 and 3 ( F i g u r e 7 ) . Subclass information, with c o n f i dence l e v e l s o f 2, i s o f i n s u f f i c i e n t c e r t a i n t y f o r use by t h e m o l e c u l e assembler. The same i s t r u e o f o t h e r major c l a s s e s o f f u n c t i o n a l groups l i s t e d . Note t h a t the program c o n s i d e r s o n l y f u n c t i o n a l groups c o n s i s t e n t w i t h the m o l e c u l a r f o r m u l a . In a d d i t i o n , atoms o f f u n c t i o n a l groups r e c e i v i n g a c o n f i d e n c e l e v e l o f 4 a r e a u t o m a t i c a l l y s u b t r a c t e d from the m o l e c u l a r formula and a r e not c o n s i d e r e d f u r t h e r . The I/O p r i n t o u t shown i n F i g u r e 8 i n c l u d e s u n s t r a i n e d ketone c a r b o n y l , i . e . , not p a r t o f a 3-5 membered r i n g , f l a n k e d by a C b e a r i n g f o u r r e a d i l y exchangeable p r o t o n s , a secondary h y d r o x y l group, a secondary amine a t t a c h e d t o two d i f f e r e n t methine c a r b o n s , and a 1 - h y d r o x y e t h y l group. The M u l t i p l e Bond C o n s t r a i n t s DOUBLE and TRIPLE p r e c l u d e the g e n e r a t i o n o f double and t r i p l e bonds. Substructure C o n t r o l r e s t r i c t s assembly o f k e t a l and a m i n a l l i n k a g e s , and a l s o t h e number o f CH groups t o one. The consumption o f two moles o f p e r i o d a t e by a c t i n o bolamine i s i m p o r t a n t s t r u c t u r a l i n f o r m a t i o n , the s i g n i f i c a n c e o f which i s a u t o m a t i c a l l y c o n s i d e r e d by c a l l i n g PERIODATE and g i v i n g t h e molar u p t a k e . This i n f o r m a t i o n c o n s t r a i n s t h e m o l e c u l e assembler i t s e l f ; the s e a r c h f o r c o m p a t i b i l i t y i s not done r e t r o s p e c tively. CASE produced f i v e s t r u c t u r e s c o n s i s t e n t w i t h the a v a i l a b l e e v i d e n c e ( F i g u r e 9 ) . Armed w i t h the a s s u r ance t h a t no v a l i d s t r u c t u r e had been o v e r l o o k e d , an examination of these f i v e s t r u c t u r e s provided i n v a l u a b l e g u i d a n c e i n the d e s i g n o f the minimum number o f experiments t o a s s i g n the s t r u c t u r e o f a c t i n o b o l a m i n e correctly. A l l o f the e x p e r i m e n t s were s p e c t r o s c o p i c i n n a t u r e and l e d t o the c o r r e c t s t r u c t u r e (B). 3

OH

CHOH CH

3

(B)

7.

Interactive

SHELLEY E T AL.

Structure

Elucidation

H30 C13H20N206

•

C9H15N03

AC T I N O B O L I N

ACTINOBOLAMINE


IR INTERPRETER OUTPUT

EACH C L A S S HAS A CONFIDENCE L E V E L OF 0-4• 4 •••• D E F I N I T E L Y PRESENT 3 - HIGH P R O B A B I L I T Y 2 - MEDIUM P R O B A B I L I T Y 1 - LOW P R O B A B I L I T Y 0 ™ D E F I N I T E L Y ABSENT

CLASS 1 • ALCOHOL-

SUBCLASSES •--

4

2, PRIMARY 4 |

6. KETONE 8* LACTAM-

~

- 3

••-

2

10 • CARBAMATE -

3-A f B-A ' >B' ~

7. SATURATED

- -

9. 5 MEMBER W/0

2 1 1 . PRIMARY

2 2 2 . SATURATED

2 4 . ETHER 2 7 . ACETAL 2 8 . KETAL

— —

—

2

5* SEC• I N RING

- 2

NH-~

2

2 16* TERTIARY

17. C=C(NON~AROMATIC) 2 1 8 . CHR=CR2 19. METHYL— --- 2 2 0 . GEM DIMETHYL

2 3 . PYRROLE

•—

1

2 15* SECONDARY

2 1 . NITRO GROUP

3* 2-A9B-

- 2 1 2 . SECONDARY

1 3 , TERTIARY 14* AMINE-

-—

2

- 1. 1 2

2 1 2 5 . SATURATED - 1

1 2 6 . UNSATURATED-

1. Figure

7

104



T I T L E: A C T I N 0 B 0 L AMINE MOLECULAR FORMULA * C 9 H 1 5 N 1 0 3 0=C < R 0 3 0 5 0 0 > < c I-1222 > FRAGMENT(S) FRAGMENT(S) 0H NLKCILI 2 2 > FRAGMENT(S) F R A G M E N T ( S ) :CH3-CH--0H FRAGMENT(S)J 9 C O N S T R A I N T ( S ) : DOUBLE CONSTRAINTS) : TRIPLE C O N S T R A I N T S ) : SUBSTR F R A G M E N T ( S ) : O-C-0 9 MINIMUM: 0 MAXIMUM: o JBSTR CONSTRAINT(S) 0~C -N 9 FRAGMENTS) MINIMUM: 0 MAXIMUM: o C O N S T R A I N T S ) : SUBSTR F R A G M E N T S ) : CH3 9 MINIMUM: i MAXIMUM: I PERIODATE CONSTRAINTS) CONSTRAINTS) t 5 COMMAND: G E N E R A T E

Figure

8

5 STRUCTURES

GENERATED

QH

Figure

9.

Program

CASE-draw,

Arizona

State University,

actinobolamine

7.

SHELLEY E T

AL.

Interactive

Structure

C o r o n a t i n e i s a t o x i n produced by a m i c r o o r g a n i s m of the Pseudomonas genus. I t s s t r u c t u r e was r e p o r t e d e a r l y t h i s y e a r (13). A d e g r a d a t i o n p r o d u c t , c o r o n a f a c i c a c i d , p l a y e d a key r o l e , and a l t h o u g h some chemi c a l and s p e c t r o s c o p i c d a t a and t h e i r s t r u c t u r a l s i g n i f i c a n c e a r e r e p o r t e d i n the paper, the f i n a l d e t e r m i n a t i o n o f the d e g r a d a t i o n p r o d u c t was by x - r a y . We d e c i d e d t o see how c l o s e t o the a c t u a l s t r u c t u r e the r e p o r t e d c h e m i c a l and s p e c t r o s c o p i c i n f o r m a t i o n would have taken the a u t h o r s . The computer i n p u t i s shown i n F i g u r e 10. Coronafacic acid i s C i 2 H i 0 . I t contains a c y c l o p e n t a n o n e r i n g w i t h t h r e e r e a d i l y exchangeable hydrogen atoms, an u n s t r a i n e d a , $ - u n s a t u r a t e d c a r b o x y l i c a c i d moeity and an e t h y l group t h a t i s not p a r t o f a p r o p y l group. There a r e no a d d i t i o n a l m u l t i p l e bonds and o n l y a s i n g l e methyl group. CASE assembled 88 s t r u c t u r e s , t h u s , the c h e m i c a l and s p e c t r o s c o p i c e v i d e n c e b r o u g h t the a u t h o r s t o w i t h i n 88 s t r u c t u r e s o f the c o r r e c t one. One l a s t s i m p l e , but i n f o r m a t i v e example i l l u s t r a t e s one a p p l i c a t i o n o f the spectrum s i m u l a t o r ( F i g u r e 11). The monoterpene c i n e o l e , C i o H i 0 , was r e c e n t l y examined by l^C-NMR. o f f - r e s o n a n c e and broad-band p r o t o n d e c o u p l e d s p e c t r a r e v e a l q u a t e r n a r y carbon b e a r i n g e t h e r oxygen, a t l e a s t one methine carbon, two methylene carbons and two methyl c a r b o n s , and no u n s a t u r a t e d c a r b o n s . The 1 C-NMR e v i d e n c e i s c o m p a t i b l e w i t h 458 s t r u c t u r a l isomers a c c o r d i n g t o CASE. I f PEAK i s c a l l e d ( F i g u r e 12), the number o f CNMR s i g n a l s expected f o r each o f the 458 compounds i s predicted. Those s t r u c t u r e s not c o n f o r m i n g t o the observed number, 7 i n t h i s c a s e , are r e j e c t e d . In t h i s way the l i s t o f 458 s t r u c t u r e s i s pruned t o 38. Of the 38 s t r u c t u r e s , o n l y 5 conform t o the i s o p r e n e r u l e . Peak p r e d i c t i o n i s based on m o l e c u l a r t o p o l o g y , b u t the d e t e r m i n a t i o n o f c l a s s e q u i v a l e n c e i n t h i s case c o n s i d e r s o n l y n e i g h b o r i n g atoms no more than t h r e e bonds removed. S i n c e a p e r f e c t match between p r e d i c t i o n and o b s e r v a t i o n cannot be expected f o r each and e v e r y s t r u c t u r e examined by PEAK, the p r u n i n g s t e p of PEAK can compare the a c t u a l number of observed s i g n a l s t o a range o f p r e d i c t e d v a l u e s , g e n e r a l l y the a c t u a l number p l u s o r minus one. Thus, i f PEAK i s s e t a t 7 w i t h a range o f p l u s o r minus one, the l i s t o f 458 s t r u c t u r e s i s reduced t o 144. Of the 144, o n l y 19 comply w i t h the i s o p r e n e r u l e . 6


105

Elucidation

3

8

3

1 J

computer-assisted structure elucidation

T I T L E : CORONAFACIC ACID M O L E C U L A R FORMULA: C 1 2 H 1 A 0 3 FRAGMENT S ) : 1:C(=0)-CH-C~C-CH2-1 FRAGMENT ( S ) •* C H < R 0 3 0 5 0 0 X H 0 0 > = C < H 0 0 > - C < = 0 ) -OH FRAGMENT(S)t CH3-CH2 FRAGMENTS) : $ C O N S T R A I N T S ) : DOUBLE 0 0 C O N S T R A I N T S ) : SUBSTR FRAGMENT(S)* CH3 i MINIMUM: 1 MAXIMUM: i CONSTRAINTS) * 9 COMMAND: G E N E R A T E


8 8 STRUCTURES GENERATED Figure 10

T I T L E : CINEOLE MOLECULAR FORMULA: C1.OH 1 S01 F R A G M E N T S ) : C 0-C F R A G M E N T ( S ) J CH FRAGMENT < S ) * CH2 CH2 F R A G M E N T S ) * CH3 CH3 v C O N S T R A I N T ( S ) : DOUBLE 0 0 CONSTRAINTS): TRIPLE 0 0 CONSTRAINT(S)J * COMMAND: G E N E R A T E

Figure

11

458 S T R U C T U R E S G E N E R A T E D

T I T L E : CINEOLE M O L E C U L A R FORMULA: C10H1B01. F R A G M E N T ( S ) : C-0-C F R A G M E N T ( S ) J CH FRAGMENT ( S ) : CH2 CH2 COMMAND: G E N E R A T E

Figure

12

38

STRUCTURES GENERATED

7.

SHELLEY E T A L .

Interactive

Structure

Elucidation

107

Summary In summary CASE i s a h i g h l y i n t e r a c t i v e network o f computer programs f o r r e l i a b l y and e f f i c i e n t l y a s s i s t i n g the chemist i n t h e c o n v e r s i o n o f chemical and s p e c t r o s c o p i c d a t a t o m o l e c u l a r s t r u c t u r e . Comm u n i c a t i o n i s i n t h e c o n v e n t i o n a l language o f t h e c h e m i s t and program e x e c u t i o n i s s u f f i c i e n t l y r a p i d to make problem s o l v i n g a h i g h l y c o n v e r s a t i o n a l p r o cess. CASE i s d e s i g n e d t o grow and expand, and we a r e c o n f i d e n t i t w i l l be more p o w e r f u l tomorrow than i t i s today.


Literature 1.

2. 3.

4. 5.

6. 7. 8. 9. 10. 11. 12. 13.

Cited

S t e v e n s , C a l v i n L., Taylor, K . G r a n t , Munk, Morton E., M a r s h a l l , W. S., Noll, K l a u s , Shah, G . D., Shah, L . G . and U z u , K., J. Med. Chem. (1965), 8, 1. Munk, Morton E., Sodano, C h a r l e s S . , McLean, Robert L. and Haskell, Theodore H., J. Am. Chem. Soc. (1967), 89, 4158. Munk, Morton E., N e l s o n , Denny B., A n t o s z , F r e d e r i c k J., H e r a l d , Jr., D e l b e r t L . and H a s k e l l , Theodore H., J. Am. Chem. S o c . (1968), 90, 1087. N e l s o n , D. B., Munk, M. E., Gash, K . B . and H e r a l d , Jr., D. L., J. O r g . Chem. (1969), 34, 3800. A n t o s z , F . J., N e l s o n , D. B., H e r a l d , Jr., D. L. and Munk, M. E., J. Am. Chem. S o c . (1970), 92, 4933. N e l s o n , D. B . and Munk, M. E., J. O r g . Chem. (1970), 35, 3832. N e l s o n , D. B . and Munk, M. E., J. O r g . Chem. (1971), 36, 3456. Bognar, R . , Sztaricskai, F., Munk, M. E. and Tamas, J., J. O r g . Chem. (1974), 39, 2971. Woodruff, H . B . and Munk, M. E., J. O r g . Chem. (1977), 42, 0000. Woodruff, H . B . and Munk, M. E., Anal. Chim. A c t a / Computer T e c h n i q u e s and O p t i m i z a t i o n , i n p r e s s . S h e l l e y , C . A . and Munk, M. E., J. Chem. I n f . Comput. Sci. (1977), 17, 0000. Ireland, C., Stallard, M. O., F a u l k n e r , D. J., Finer, J. and C l a r d y , J., J. O r g . Chem. (1976), 41, 2461. Ichihara, A., Shiraishi, K., S a t o , H., Sakamura, S., N i s h i y a m a , K., S a k a i , R . , F u r u s a k i , A . and Matsumoto, T., J. Amer. Chem. S o c . (1977), 99, 636.

8 C H E M I C S : A Computer Program System for Structure Elucidation of Organic Compounds TOHRU YAMASAKI, HIDETSUGU ABE, YOSHIHIRO KUDO, and SHIN-ICHI SASAKI


Miyagi University of Education, Aoba, Sendai 980 Japan

There have been many articles concerned with computer programs for structure elucidation of organic compounds by analyzing chemical spectra. The methodologies and the techniques employed for this purpose can be classified into two categories, one i s the identification of unknown compounds by the retrieval method of f i l e d spectra (1,2) i s carried out and the other is the generation of structural formula based on the analytical results of spectral data and other chemical evidence (3,4,5). As reported previously, our integrated computer system for structure elucidation of organic compounds named CHEMICS stands mainly on the latter methodology (6). IR and H NMR spectral data of an organic compound are analyzed and plausible structural formula consistent with the analytical results are generated. Since generation of correct structure i s the major premise of this system, rather ample allowance for elucidation of partial structures is made during data analysis. Thus, an excessive number of candidate structures (informational homologues) are generated upon occasion. In order to prevent this undesirable situation, two different strategies are considered to be practical. They are; 1) Application of the f i l e retrieval method as a complement to the data analysis, and 2) introduction of other kinds of information sources and/or improvement of the spectral data analysis more precisely. The former solution has been already actualized as CHEMICS-F as shown in Fig. 1 (7). For the latter strategy, several t r i a l s have been made at our laboratory, for example, quantitative analysis of IR spectra(£0 , spectral simulation of NMR( 1

108

YAMASAKI

ET AL.

Structure


/

of Organic

M o l . F o r m . , NMR, IR, MS, UV

DATA FILE

SEARCH

Match ing Resul

Compounds

/

/

Plausible

109

/

ANALYSIS

'components'

STRUCTURE

GENERATOR

Candidate

Structure

/

/

Matching Result

/

OUTPUT

/

Figure

1.

Plausible Structure

Block diagram of CHEMICS-F.

/

Dashed arrow means off-line

routine.

110

COMPUTER-ASSISTED

STRUCTURE

ELUCIDATION

ALACON)(9), a n a l y s i s o f n u c l e a r double resonance d a t a (1H{1H}, NMDR)(10) and p r e d i c t i o n o f NMR s p e c t r a ( 11) . In t h i s paper we d e s c r i b e i n c o r p o r a t i o n o f NMR s p e c t r a l a n a l y s i s i n t o CHEMICS t o extend i t s capabilities. General

feature of 13Q NMR s p e c t r a l

data

analysis

R e c e n t l y , 13C NMR s p e c t r o s c o p y has been e f f e c t i v e l y employed f o r s t r u c t u r e e l u c i d a t i o n o f o r g a n i c compounds. Here we i n t e n d t o i n t r o d u c e t h e s p e c t r a l d a t a as a new i n f o r m a t i o n s o u r c e because o f i t s gene r a l l y a p p l i c a b l e nature. The e n t i r e system i s shown i n F i g . 2. The program f o r a n a l y s i s o f C NMR s p e c t r a ( ASSINC) i s composed o f t h e f o l l o w i n g f o u r elements as shown i n F i g . 2. a) DATA INPUT b) PRIMARY ANALYSIS c) SECONDARY ANALYSIS d) CHEMICAL SHIFT TABLE The i d e a o f ASSINC i s much t h e same as t h a t o f 1'H NMR d a t a a n a l y s i s o f t h e system CHEMICS (ASSIN) (6), i n which knowledge o b t a i n e d by a n a l y z i n g s p e c t r a l d a t a o f unknown compounds i s r e p r e s e n t e d as a group o f subs t r u c t u r e s named 'components . A c c o r d i n g t o t h i s i d e a , 189 k i n d s o f 'components' a r e p r e v i o u s l y d e f i n e d f o r the ASSINC as shown (part i a l l y ) i n T a b l e I , i n s t e a d o f t h e 179 'components' f o r the former e d i t i o n . Each 'component' i s d e f i n e d by i t s a d j a c e n t atoms and/or f u n c t i o n a l groups bonded with i t .


l 3

1

DATA INPUT. Input d a t a f o r 13c NMR d a t a a n a l y s i s c o n s i s t o f p o s i t i o n s and i n t e n s i t i e s o f e v e r y s i g n a l and t h e i r m u l t i p l i c i t i e s . We use the example o f s t r u c t u r e 1, C9H14O, whose spectrum i s shown i n F i g . 3. Both c a r d and paper t a p e image d a t a a r e O^x^vy acceptable. Even i f the m u l t i p l i c i t i e s T j a r e n o t a v a i l a b l e , the ASSINC can a n a l y z e t h e r e s t o f t h e d a t a and w i l l o f f e r u s a b l e I answers f o r s u c c e s s i v e r o u t i n e s . But i n such a c a s e , some a m b i g u i t i e s c o u l d not be 1 avoidable. PRIMARY ANALYSIS. The b l o c k diagram o f the p r i m a r y a n a l y s i s r o u t i n e i s shown i n F i g . 2. As shown i n this f i g u r e , i t c o n s i s t s o f two major p a r t s . One i s a l l o c a t i o n o f carbons t o each s p e c t r a l s i g n a l and t h e o t h e r i s e x a m i n a t i o n o f t h e p r e s e n c e o f 'components'.

8.

YAMASAKI E T A L .

Structure

of Organic

Data

111

Compounds

analysis

IR,

lH

NMR

!3c

NMR

Spectrum

off-resonance

/

multiplicity

>

primary


Allocation

Selection

||

of

of

carbon

'components'

Making

set

of

by

analysis

atoms

chemical

shift

table

'components

secondary

analysis

Structure

Figure

NO

POSITION(ppm)

2.

Flow

chart of C

INTENSITY

13

generation

NMR

spectral

data

analysis

MULTIPLICITY

1

24.4

1679

Q

2

28.3

4549

Q

3

33.5

895

4

45.2

2380

5

50.8

2119

6

125.4

2494

7

159.9

1084

199.2

861

S T T D S S

Figure

3.

C

13

NMR data of pound 1

com-


112


A l l o c a t i o n o f c a r b o n s . The f i r s t s t e p o f t h e p r i m a r y a n a l y s i s i s t h e a l l o c a t i o n o f t h e p r o p e r number o f carbons t o each s i g n a l . However, i t must be emphasized t h a t t h e p r o c e s s i s n o t aimed a t o b t a i n i n g the e x p l i c i t s o l u t i o n f o r a l l c a s e s , b u t g a t h e r i n g as much u s e f u l i n f o r m a t i o n as p o s s i b l e . I t i s well known t h a t s i g n a l i n t e n s i t i e s a r e n o t always p r o p o r t i o n a l t o t h e carbon numbers c o n t r i b u t e d t o t h e s i g n a l s i n 13Q NMR s p e c t r a , m a i n l y because o f t h e p r e s ence o f n u c l e a r Overhauser e f f e c t ( N O E ) ( 1 2 ) . However, i t can be assumed t h e s i g n a l i n t e n s i t i e s o f p r o t o n a t e d carbons a r e p r o p o r t i o n a l t o the amount o f carbons because o f t h e i r almost complete enhancement a c c o r d i n g to t h e NOE. The a l l o c a t i o n o f carbon numbers i s based on t h i s assumption. The b l o c k diagram o f t h e r o u t i n e f o r t h e a l l o c a t i o n o f carbons i s shown i n F i g . 4. By u t i l i z i n g t h e m u l t i p l i c i t y d a t a , the i n p u t s i g n a l s a r e c l a s s i f i e d i n t o two c a t e g o r i e s , namely, s i g n a l s a s s i g n e d t o p r o t o n a t e d carbons and t h o s e which are a s s i g n e d t o n o n - p r o t o n a t e d c a r b o n s . Allocation of carbons f o r t h e s i g n a l s i s performed s e p a r a t e l y f o r each c a t e g o r y . At f i r s t , t h e a l l o c a t i o n i s t r i e d f o r s i g n a l s assigned t o protonated carbons. Then t h e amount o f carbons (AOC) c o r r e s p o n d e d t o t h i s c a t e g o r y i s l i m i t e d i n t h e range o f R^ t o R2 d e f i n e d by e q u a t i o n ( 1 ) . , , , , w h o l e c a r b o n numbers^ V of the molecule )

(

1

/number o f s i g n a l s \ f _ \ V p r o t o n a t e d carbon / n Q n

(1) 2

_/number o f s i g n a l s a s s i g n e d \ ^ t o p r o t o n a t e d carbons /

A f t e r e s t i m a t i o n o f t h e AOC, t h e number o f carbons f o r v a l u e o f each s i g n a l (CNS) i s e v a l u a t e d by means of t h e e q u a t i o n (2) and a s e t o f t h e CNS v a l u e s i s o b t a i n e d w i t h r e s p e c t t o each AOC v a l u e . However, i f any one o f t h e CNS v a l u e i n t h e s e t i s g r e a t e r than 0.3 and l e s s than 0.7, t h e s e t i s abandoned t o a v o i d an error. AOS CNSi = I N T i / I

(INT) j * AOC

CNSi: carbon number a l l o c a t e d t o s i g n a l " i " INTi: i n t e n s i t y of signal " i " AOC : amount o f c o r r e s p o n d i n g carbons

(2)

YAMASAKI E T AL.

Structure

of Organic

c

D for evaluation for

of

AOC

protonated

of

CNS

estimation

of

CNS

to

category

range

calculation sets


Compounds

e a c h AOC

sets

for

evaluat ion

non-protonated

category

o f AOC

c o r r e s ponded

to

p r o t o r a t e d AOC

i estimat ion

Figure

4.

of

CNS

Procedure for the allocation to each signal

of

carbons

114

COMPUTER-ASSISTED


AOS

: amount o f c o r r e s p o n d i n g

STRUCTURE

ELUCIDATION

signals

The a l l o c a t i o n p r o c e s s f o r t h e s i g n a l s a s s i g n e d t o n o n - p r o t o n a t e d carbon i s t h e f o l l o w i n g s t e p . At t h i s s t a g e , t h e AOC v a l u e i s e s t i m a t e d i n t h e b a s i s o f r e m a i n i n g carbons which a r e n o t consumed a t p r e c e e d i n g stage. As t h e r e s u l t o f s o l v i n g t h e e q u a t i o n (2) , the s e t s o f CNS v a l u e s w h i c h c o r r e s p o n d t o non-protona t e d carbons a r e o b t a i n e d . Here, i t i s assumed t h a t the weakest i n t e n s i t y o f t h e s i g n a l i s s h a r e d w i t h a u n i t number(1,2,3,...) o f c a r b o n s . Consequently, a l l o c a t e d numbers, namely, a s e t o f e n t i r e CNS i s a c q u i r e d f o r each i n p u t s i g n a l . I f t h e r e i s more than one s o l u t i o n f o r t h i s problem, any one o f them c o u l d be chosen as a c o r r e c t s e t o f a l l o c a t e d numbers t o t h e signals. The a p p l i c a t i o n o f t h e p r o c e d u r e t o t h e spectrum o f compound 1 i s d e s c r i b e d below. The i n p u t s i g n a l s shown i n F i g . 3 a r e c a l s s i f i e d i n t o e i t h e r p r o t o n a t e d o r n o n - p r o t o n a t e d c a t e g o r y where s i g n a l s number 1,2,4, 5 and 6 a r e grouped i n t o t h e former and 3,7 and 8 a r e grouped i n t o t h e l a t t e r . Through t h e p r o c e d u r e o f p r o t o n a t e d c a t e g o r y t h e AOC i s a p p r a i s e d as 5 and 6 because i s c a l c u l a t e d as 6 ( 9 - 3 ) and R2 i s e q u a l t o 5. The c o r r e s p o n d i n g s e t s o f t h e CNS a r e shown below where each i n t e g e r v a l u e e n c l o s e d by p a r e n t h e s i s i s a l l o c a t e d number o f c a r b o n s . signal number

1

2

4

5

6

A0C=5

0.63 (*)

1.72 (2)

0.90 (1)

0.80 (1)

0.94 (1)

AOC=6

0.76 (1)

2.06 (2)

1.08 (1)

0.96 (1)

1.13 (1)

S i n c e i t i s i m p o s s i b l e t o a l l o c a t e carbons t o s i g n a l number 1 a t t h e f i r s t s e t , t h i s s e t i s abandoned. T h e r e f o r e o n l y one s o l u t i o n i s d e r i v e d from the case where t h e AOC i s e q u a l t o 6. A t the f o l l o w i n g s t a g e , t h e AOC f o r n o n - p r o t o n a t e d c a t e g o r y i s f i x ed t o 3, and so each r e s i d u a l s i g n a l must be a l l o c a t e d t o one carbon i n d i v i d u a l l y . The f i n a l r e s u l t o f a l l o c a t e d number i s as f o l l o w s : signal number allocated number

1 1

2 2

3 1

4 1

5 1

6 1

7 1

8 1

8.

YAMASAKI

ET AL.

Structure

of Organic

Compounds

115 1

E x a m i n a t i o n o f t h e p r e s e n c e o f 'components . Now we have c o n f i r m e d two k i n d s o f i n f o r m a t i o n about a g i v e n C NMR s p e c t r a l d a t a . They a r e t h e amount o f carbons a s s i g n e d t o each s i g n a l and n a t u r e o f carbons (protonated o r non-protonated). By c o n s i d e r i n g t h e i n f o r m a t i o n , t h e p o s s i b l e p r e s e n c e o f each 'component' i s examined and t h o s e which a r e i n c o n s i s t e n t w i t h t h e i n f o r m a t i o n a r e abandoned. The p r e s e n c e o f each 'components' i s judged t o be a p p r o p r i a t e by i t s c h e m i c a l s h i f t range ( r e f e r t o T a b l e I ) , i n o t h e r words, i f t h e r e a r e no s i g n a l s w i t h i n a c h e m i c a l s h i f t range c o r r e s p o n d i n g t o a 'component', i t i s judged t o be n o t p r e s e n t i n a sample compound. As shown i n F i g . 5, twenty-nine components s u r v i v e for compound 1., through t h e p r i m a r y a n a l y s i s . The r e s u l t o f t h e p r i m a r y a n a l y s i s i s r e p r e s e n t e d by the m a t r i x named NM m a t r i x , i n which each row i s c o r r e sponding t o a s u r v i v e d 'component' and each column t o each s i g n a l o f t h e g i v e n 13c NMR spectrum. Each mat r i x element i n d i c a t e s maximum number o f t h e carbons f o r 'component' a s s i g n e d t o t h e c o r r e s p o n d i n g s i g n a l . Those elements w i t h v a l u e -1 i n d i c a t e c o r r e s p o n d i n g 'components' were n o t a s s i g n e d t o t h e s i g n a l s .


1 3

SECONDARY ANALYSIS. A t t h e f i r s t s t e p o f t h i s r o u t i n e , a s e t o f 'components' which i s c o n s i s t e n t w i t h t h e m o l e c u l a r f o r m u l a i s s e l e c t e d from s u r v i v e d 'components'. One o f t h e f i v e s e t s which was f i n a l l y g e n e r a t e d f o r compound 1_ i s shown i n F i g . 6. As d e s c r i b e d b e f o r e , each o f t h e s i g n a l s i s t r e a t e d as i f i t were independent o f t h e o t h e r s and the 'components' which can be a s s i g n e d t o a t l e a s t one s i g n a l s u r v i v e w i t h o u t any f u r t h e r e x a m i n a t i o n a t t h e primary a n a l y s i s . However, i t i s n e c e s s a r y t o examine whether t h e s e t i s c o n s i s t e n t w i t h t h e g i v e n spectrum o r n o t , i n o t h e r words, each o f a l l 'components' o f t h e s e t s h o u l d be c o n f i r m e d whether they a r e f u l l y consistent w i t h t h e i n p u t spectrum w i t h n e i t h e r excess n o r d e f i ciency. To make t h i s e x a m i n a t i o n , t h e s e l e c t i v e NM m a t r i x i s made f o r t h e s e t by e x t r a c t i n g t h e rows c o r r e s p o n d i n g t o s e l e c t e d 'components' from NM mateix shown i n F i g . 5. T h i s s e l e c t i v e m a t r i x i s shown i n F i g . 6. As shown i n F i g . 7 , t h i s m a t r i x N i s c o n v e r t e d i n t o another m a t r i x X by s u b s t i t u t i n g t h e p o s i t i v e elements by v a r i a b l e s ( x ^ j ) and t h e n e g a t i v e elements by z e r o s . A s e t o f simultaneous l i n e a r equations i s made from X and two c o n s t n a t v e c t o r s C and D, r e p r e -



NO

CMP

SUB/STRUCTURE

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29

10 11 12 14 17 33 38 40 106 107 108 109 118 143 144 145 146 153 172 173 174 175 177 182 184 185 186 187 188

GEM-DI M E T H Y L - ( D ) GEM-DI M E T H Y L - ( T ) GEM-DI M E T H Y L - ( C ) CH3-CO(Y) (T) CH3-COCH3(D) CH3COCD) CH3CO(C) -CH2(C)(K) -CH2(C)(D) -CH2(C)(T) -CH2(C)(C) -CH= :C= < 0 L E F I N > =C= =C= FURAN(O) -0-CO(C)(D) -CO(C)(T) -CO(C)(C)

NM

o=c= Y Y C C C C

(0) (C) (Y) (K) (D) (T) (C)

c

SAMPLE

MATRIX

1 1 1 1 1 1 1 1 -1 -1 -1 -1 -1 -1 -1 -1

2 2 2 2 2 2 -1 2 -1 -1 -1 -1 -1 -1 -1 -1

-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

-1 -1 -1 -1 -1 -1 -1 -1 1 1 1 1 -1 -1 -1 -1

-1 -1 -1 -1 -1 -1 -1 -1 1 1 1 1 -1 -1 -1 -1

-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1 -1

-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 -1 -1

-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1

-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

-1 -1 -1 -1 -1 -1 1 1 1 1 1

-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

-1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1

-1 -1 -1 -1 1 1 -1 -1 -1 -1 -1

1 1 1 1 -1 -1 -1 -1 -1 -1 -1

X

1 J O B END

Figure

5.

Survived

components

of compound analysis

1 through

C

13

NMR

data

8.

YAMASAKI E T A L .

Structure

of Organic

number 1

12

GEM-DIMETHYL-

(C)

2

33

CH 3

number

of

of

selective

carbons

'components'

117

Compounds

2#

NM m a t r

-1

-

(D)

-1

-

1

3

106

-CH -

(C)(K)

4

107

-CH -

(C)(D)

5

118

-CH=

-1

6

143

-C=

-1

-

7

172

-CO-

(C)(D)

-1

-

8

188

-c-

(C)

-1

-

1

1

2

2

1

( 1 2

-

1

allocation


Only methyl

carbon

Figure

f

is

considered

Selective

6.

components

1

2 -1 -1 -1 -1 -1 -1 >

1

2 -1 -1 -1 -1 -1 -1

-1 -1 -1

1

1 -1 -1 -1

-1 -1 -1

1

1 -1 -1 -1

-1 -1 -1 -1 -1

-1 -1 -1 -1 -1 -1

s

1 -1

a

)

a

n

1

1

1

1

1

1

1 )

d:

( 1

of

1

0 0 0 0 0 0

0 0 0 0 0 0 X 0 0 0 0 0 0 83 0

0 0 0 0\ 0 0 0 0 0 0 0 X 0 0 0 0 0 0 0 0 67 0 0 0 0 78 0 0 0 0 )

2

1

1

x:

0 0 0 0 0 0

1

group

for the fifth set of compound

1 -1 -1 -1 -1

1

( 2

gem-dimethyl

1 -1 -1

-1 -1 -1 -1 -1 -1 -1 -1 -1

in

1

number

carbons #

1

X

1

X

X

1

1

1 )

d

N' X' O D mean s e l e c t i v e NM m a t r i x , s e l e c t i v e NM m a t r i x r e p l a c e d by XJLj, m o d i f i e d 'component' v e c t o r a n d a l l o c a t i o n v e c t o r , r e s p e c t i v e l y .

r x •i = c ^ b)

I

•

X

representation o f simultaneous v e c t o r having e i g h t elements.

Figure

7.

Representation

of

=

D

linear

equations

simultaneous linear pound 1

equations

where I means u n i t row

for

the

fifth

set of

com-


118

COMPUTER-ASSISTED

STRUCTURE

ELUCIDATION

s e n t i n g carbon numbers i n t h e 'components' and a l l o c a t e d carbon numbers, r e s p e c t i v e l y . The number o f e q u a t i o n s i s t h e number o f 'components' i n t h e s e t plus that of the s i g n a l s . The e q u a t i o n s have a r e s t r i c t i o n , t h a t t h e v a r i a b l e x^- s h o u l d n o t exceed t h e range between z e r o and t h e v a l u e o f the c o r r e s p o n d i n g s e l e c t i v e m a t r i x element. To s o l v e t h e s e s i m u l t a n e o u s e q u a t i o n s i s t h e major function of t h i s routine. When no s o l u t i o n i s o b t a i n e d , the s e t i s judged t o be i n a p p r o p r i a t e one, and when a s o l u t i o n i s g i v e n , the s e t i s s e n t t o t h e f o l l o w i n g r o u t i n e (the s t r u c ture generator). At the f i n a l stage o f the s p e c t r a l a n a l y s i s , f i v e s e t s o f components which a r e g e n e r a t e d from twentyn i n e components a r e s e l e c t e d as p l a u s i b l e ones f o r compound 1. F i v e s e t s a r e shown as f o l l o w s , numera l i n p a r e n t h e s i s e x p r e s s e s number o f t h e component; NO.

1

10 (1), 38 (1), 107 (1), 109 (1), 118 (1), 143 (1), 189 (1)

NO.

2

10 (1), 40 (1), 106 (1), 107(1), 118 (1), 143(1), 189 (1)

NO.

3

12 (1), 38(1), 107 (2), 118(1), 143 (1), 189 (1),

NO.

4

10 (1), 33 (1), 106 (1), 109 (1), 118 (1), 143 (1), 172 (1), 189(1)

NO.

5

12 (1), 33 (1), 106 (1), 107 (1), 118 (1), 143 (1), 172 (1), 189 (1)

The o v e r a l l p r o c e s s t h a t 189 components a r e r e duced i n t o 29 by means o f t h e e x a m i n a t i o n o f m o l e c u l a r f o r m u l a f o l l o w e d by t h e s u c c e s s i v e a n a l y s e s o f IR, 1H NMR and C NMR i s shown i n F i g . 8. In f i g . 8, num e r a l s 10 8, 105, 59 and 29 i n p a r e n t h e s e s i n d i c a t e t h e amounts o f s u r v i v e d components by s u c c e s s i v e restrict i o n s o f m o l e c u l a r f o r m u l a , IR, J-H NMR and 13c NMR, respectively. Only f i v e s e t s o f components u n c o n t r a d i c t o r y w i t h m o l e c u l a r f o r m u l a and g i v e n NMR spectrum a r e p i c k e d up from t h e s e twelve components. Finally, the s t r u c t u r e generator(L3) i s a p p l i e d t o generate the s t r u c t u r e s from each s e t o f components so t h a t 3, 1, 2, 3 and 3 s t r u c t u r e ( s ) produced f o r s e t s , 1, 2, 3, 4 and 5. These s t r u c t u r e s a r e shown i n F i g . 9 as i n f o r m a t i o n a l homologues f o r t h e i n p u t m o l e c u l a r f o r m u l a and c h e m i c a l s p e c t r a . The u n d e r l i n e d one i s t h e s t r u c t u r e o f t h e compound 1. 1 3

PREPARATION OF CHEMICAL SHIFT TABLE. A c h e m i c a l s h i f t ranges f o r a s i g n a l o f a 'component' was d e t e r mined f o r the a n a l y s i s d e s c r i b e d i n the previous

YAMASAKI E T A L .

Structure

of

Organic

119

Compounds

189 COMPONENTS Molecular Formula ( C

9

H

1 4

^

0 )

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 21 22 23 24 25 27 29 30 31 32 33 34 38 39 40 41 42 43 44 45 46 49 52 53 55 57 58 59 60 61 67 71 76 79 80 82 84 85 86 87 88 90 92 93 99 100 101 102 104 105 106 107 108 109 110 113 114 115 116 117 118 126 127 136 137 138 139 140 141 142 143 144 145 146 153 165 172 173 174 175 176 177 182 183 184 185 186 187 188 (108)


IR S p e c t r a l Data 1 2 3 4 5 6 7 8 9 10 11 12 13 22 23 24 25 27 29 30 31 32 33 34 38 39 49 52 53 55 57 58 59 60 61 67 71 76 79 90 92 93 99 100 101 102 104 105 106 107 108 109 137 138 139 140 141 142 143 144 145 146 153 165 172 184 185 186 187 188 (105)

14 40 80 110 173

15 16 17 18 19 21 41 42 43 44 45 46 82 84 85 86 87 88 114 115 116 117 118 136 174 175 176 177 182 183

iH NMR S p e c t r a l Data 7 9 10 11 12 13 14 15 16 17 18 33 34 38 39 40 41 43 44 45 46 67 71 76 79 80 85 86 87 88 104 106 107 108 109 116 117 118 141 142 143 144 145 146 153 165 172 173 174 175 176 177 182 183 184 185 186 187 188 (59) 1 3

C NMR S p e c t r a l Data

5»»

10 11 12 14 17 33 38 40 106 107 108 109 118 143 144 145 146 153 172 173 174 175 177 182 184 185 186187 188 (29)

selected 'components' 10 12 33 38 40 106 107 109 118 143 172 189

generated structures

set o f • components' #2 #4 #3

#1 1 0 0 1 0 0 1 1 1 1 0 1

( Figure

8.

Feature

1 0 0 0 1 1 1 0 1 1 0 1

0 1 0 1 0 0 2 0 1 1 0 1

1 0 1 0 0 1 0 1 1 1 1 1

0 1 1 0 0 1 1 0 1 1 1 1

1

2

3

3

1

3

#5

1 1 )

of reducing the number of components analyses of compound 1

through

consecutive

120

COMPUTER-ASSISTED

STRUCTURE

ELUCIDATION

s e c t i o n i n t h e f o l l o w i n g way. The components which c o n t a i n carbon atoms a r e 177 o u t o f e n t i r e 189. F o r t h o s e 'components , t h e i r c h e m i c a l s h i f t v a l u e s i n v a r i o u s k i n d s o f compounds were c o l l e c t e d from s e v e r a l s o u r c e s ( 1 4 , 1 5 , 1 6 ) . The c o l l e c t e d d a t a f o r 'component no.25 o f m e t h y l c a r b o n s , as an example, a r e shown i n F i g . 10. By u s i n g t h e s e d a t a , the c h e m i c a l s h i f t range f o r t h e 'component' i s o b t a i n e d as f o l l o w s . 1

1

1

1

i.


ii.

An assumed r e g i o n o f the mean v a l u e ( y ) i s c a l c u l a t e d by means o f common s t a t i s t i c a l procedure. An a r b i t r a r y v a l u e up.

(y')

i n the r e g i o n i s p i c k e d

iii.

The s t a n d a r d d e v i a t i o n ( a ) lated.

iv.

Whether a l l t h e c o l l e c t e d d a t a f o r the 'component' a r e w i t h i n t h e range between TT' - 3 a t o I T ' + 3 a i s examined.

v.

y~' i s c a l c u -

f o r the

I f n o t , the TT' i s updated and p r o c e d u r e s i i i and i v a r e r e p e a t e d , i f i t i s , the v a l u e s I T ' - 3 a and y ' + 3 a a r e determined as the upper and lower l i m i t s o f the s h i f t o f the 'component' r e spectively. -

The assumed r e g i o n o f mean v a l u e o f component 25 was c a l c u l a t e d as 19.15 - 24.48ppm based on v a r i o u s k i n d s o f d a t a s o u r c e s as shown i n F i g . 10. Here, an a p p a r e n t mean v a l u e o f t h e s e c o l l e c t e d d a t a i s 21.8ppm and t h i s i s an i n i t i a l v a l u e o f y"' . Some d a t a o f samples a r e o f t e n o u t o f the normal G a u s s i a n d i s t r i b u t i o n , t h e r e f o r e s t a n d a r d d e v i a t i o n has t o be c o n s i d e r e d s e p a r a t e l y i n h i g h e r magnetic f i e l d ( a ) and lower magnetic f i e l d ( C L ) compared w i t h y ' , f o r d e t e r m i n a t i o n o f the s t a n d a r d d e v i a t i o n f o r y . The y ' i s renewed by ' f l i p - f l o p ' u n t i l l y ' - 3 a and y* + 3 a can i n c l u d e the whole sampling d a t a . In case o f component 25, mean v a l u e i s f i n a l l y found o u t t o be 21.4ppm, when a =2.05 and a =1.39. The upper and lower l i m i t s o f the s h i f t determined a c c o r d i n g t o t h i s manner i s 15.21 - 25.53ppm which i s r e g i s t e r e d i n T a b l e I. T h i s p r o c e d u r e i s a p p l i e d t o a l l 'components' and the c h e m i c a l s h i f t t a b l e i s o b t a i n e d as shown i n T a b l e I. H

1

H

R

Result and

The

1

L

L

Discussion

r e s u l t o b t a i n e d f o r twenty two

compounds by


8.

YAMASAKI E T A L .

Structure

of Organic

121

Compounds

obtained shift

chemical

range

assumed r e g i o n ^

mean

of

value

-

"

CH

> ( C ) 3

iteration sample

•

mean

I

15.0

Figure

1 '

10.

' —

1

— I —

1

20.0

Estimation

—

1

—

1

—

1

—

1

—

1

—

1

1—

t i m e s = 46

amount

value

=

21.4

1

25.0

chemical

of C NMR chemical shift range of component 13

= 32

shift

#25

122

COMPUTER-ASSISTED

Table I


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 #

ELUCIDATION

Components and t h e i r appearance range of T3c NMR chemical

NO

STRUCTURE

shift

COMPONENT TERT-BUTYLTERT-BUTYLTERT-BUTYLTERT-BUTYLTERT-BUTYLTERT-BUTYLGEM-DIMETHYLGEM-DIMETHYLGEM-DIMETHYLGEM-DIMETHYLGEM-DIMETHYLGEM-DIMETHYLCH3-COCH3-COCH3-COCH3-COCH3-COCH3-COISO-PROPYLISO-PROPYLISO-PROPYLISO-PROPYLISO-PROPYLISO-PROPYLISO-PROPYLCH30CH30CH30CH30CH30CH30CH3CH3CH3CH3C0CH3C0CH3COCH3COCH3COCH3CO-

SHIFT (0># (Y) (K) (D) (T) (C) CO) (Y) (K) CD) (T) (C) (0) (Y) (K) (D) (T) (C) (0) (A) (Y) CIO CD) CT) CO CO) CY) CK) CD) CT) CO CY) CD) CT) CO) CY) CO CD) CT) CO

RANGE (ppm)

26,02 *«•* 31.13 24.47 * * * * 33,57 2 5 . 4 8 *•»» 3 4 , 0 4 2 8 . 2 3 * * * * 36.78 25.48 **** 34.04 23.65 * * « * 32.97 27.42 * * * * 32.95 10.72 36.27 36.27 10.12 14.72 36.27 36.27 10,12 6.80 * * * * 3 2 . 6 1 4,58 * * * * 3 2 . 0 1 4 . 5 8 *#•* 3 2 , 0 1 5.25 ***» 1 5 . 5 0 10.43 21.53 4.58 32.01 9.92 12.97 25.83 15.09 16.63 25.83 25.45 20.95 15,09 **** 23.87 16.33 25.83 15.09 25.83 15.21 25.53 52.88 61.61 54.59 57,92 50.34 52.53 56.68 * * « * 61.51 52.88 61.51 60.60 49.95 7.26 26.10 7.06 • ••• 3 3 . 0 8 -2.49 **** 8.49 19.81 * * * * 23.39 22.95 31.79 22,95 33.92 22.22 28,15 8.49 -2,49 2 0 . 8 0 #*»» 3 0 . 0 1

means t h e a d j a c e n t atom o r f u n c t i o n a l g r o u p , t h e y a r e , s a t u r a t e d oxygen (O), a r o m a t i c c a r b o n ( Y ) , c a r b o n y l carbon(K), o l e f i n i c carbon(D), a c e t y l e n i c carbon(T), and s a t u r a t e d c a r b o n ( C ) , r e s p e c t i v e l y .

8.

YAMASAKI E T A L . Table


no. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 *1 22

II

Structure

Results obtained f o r

a-Methyltetrahydrofuran p-Quinone 2-Methylpentane 3-Methylpentane 2,3-Dimethylbutane 3-Heptanone 2-Heptanone m-Xylene E t h y l benzene Cyclohexylacetate 2-0ctanol Coumarine Isophorone Diisobutylketone n-Nonanol Dicyclopentadiene Verbenone Camphor n-Decanol 2-Cyclohexylcyclohexanone 3-Ionone Methyl m y r i s t a t e

III

Results

several

5 6 6 6 6 7 7 8 8 8 8 9 9 9 9 10 10 10 10 12 13 15

obtained

compounds by CHEMICS

10 4 14 14 14 14 14 10 10 14 18 6 14 18 20 12 14 16 22 20 20 30

by

123

Compounds

through

molecular C H

compound

Table

of Organic

number o f I H _ I R , I H ' N M R " through I R , H N M R , analysis analysis 1

1 2 1 1 1 2 1 21 5 1 1 116 12 1 1 41 42 75 1 147 481 1

10 589 3 3 4 3 4 40 5 161 38 834 1895 30 24 1729 53274< 3253 50 2109 57827< 4767

utilizing

various

combinations

of

information

sources

compound

C

H

analytical

0

mode*

number o f ' i n f o r m a t i o n a l homologues'

P

3

6

C 7

3-Heptanone

14

3 2

P+C

1

C+0

2

P+C+0

38

P 2-0ctanol

8

18

41

C P+C

1

13 1

C+0

1

P+C+0

1895

P Isophorone

*

P, C,

9

and 0

off-resonance

mean

14

12

P+C C+0 P+C+0

1

an a n a l y s i s

spectra,

27

C

of

iH

respectively.

27

12

NMR,

13c

NMR

and/or

1 3

CNMR

124

COMPUTER-ASSISTED

STRUCTURE

ELUCIDATION

means o f t h e o l d system and new system a r e p r e s e n t e d i n Table II. The c o r r e c t s t r u c t u r e has been always gene r a t e d among t h e p l a u s i b l e s t r u c t u r e s . The numbers o f i n f o r m a t i o n a l homologues o b t a i n e d by means o f ASSINC a r e reduced t o 19.7 p e r c e n t ( i n s i m p l e average) o r 3.1 p e r c e n t ( i n weighted average) o f those o b t a i n e d by means o f t h e o l d system where o n l y IR and NMR d a t a were a n a l y z e d . As a r e s u l t o f t h e a d d i t i o n o f C NMR s p e c t r a l d a t a a n a l y s i s , i t becomes p o s s i b l e t o d e c r e a s e remarkably t h e numbers o f i n f o r m a t i o n a l homologues. F o r example, t h e number was reduced from 4767 t o one f o r compound 20_ as shown i n T a b l e I I . T a b l e III shows t h e number o f i n f o r m a t i o n a l homologues o f s e v e r a l compounds o b t a i n e d by u t i l i z i n g v a r i o u s c o m b i n a t i o n s o f i n f o r m a t i o n s o u r c e s , namely, 1H NMR, 13c NMR, l H NMR p l u s 13c NMR, 13c NMR p l u s i t s o f f - r e s o n a n c e d a t a , and 1H NMR p l u s 13c NMR p l u s o f f resonance d a t a . As shown i n t h i s t a b l e , t h e number o f i n f o r m a t i o n a l homologues and t h e number o f t h e component s e t s a r e b o t h d e c r e a s e d i n a c c o r d a n c e w i t h t h e a d d i t i o n o f new i n f o r m a t i o n s o u r c e s . In c o n c l u s i o n , t h e number o f t h e ' i n f o r m a t i o n a l homologues' and t h e 'component' s e t s a r e s a t i s f a c t o r i l y reduced by c o n s e c u t i v e a n a l y s e s . As mentioned above, the e f f o r t s t o reduce t h e e x c e s s i v e 'components' b e a r good f r u i t s , i . e . , t h e number o f t h e produced s e t s a r e l e s s than t e n f o r a l l c a s e s . Therefore, the informat i o n about t h e c o n e c t i v i t i e s between a l l t h e 'components ' i n a s e t become i m p o r t a n t d a t a t o i n c l u d e i n a f u t u r e system. That k i n d o f i n f o r m a t i o n w i l l work e f f e c t i v e l y t o r e duce t h e e x c e s s i v e ' i n f o r m a t i o n a l homologues' and n u c l e a r magnetic resonance t e c h n i q u e s w i l l g i v e such information.


1 3

T h i s work was s u p p o r t e d i n p a r t by a S c i e n t i f i c R e s e a r c h Grant from t h e M i n i s t r y o f E d u c a t i o n , Japan.

(1) (2) (3) (4) (5) (6)

Literature Cited Schwarzenbach,R.,Meili,J.,Koenitzer,H. and Clerc, J.T., Org. Mag. Resonance, (1976),8,11 Bremser,W.,Klier,M. and Meyer,E., ibid, (1975), 7,97 Carhart,R.E.,Smith,D.H.,Brown,H. and Djerassi,C., J . Am. Chem. Soc., (1975), 97, 5755 Beech,G.,Jones,R.T. and M i l l e r , K . , Anal. Chem., (1976), 46, 714 Gray,N.A.B., ibid, (1975), 47, 2426 Sasaki,S. et a l , Mikrochimica Acta(Wien), (1971), 726

8.

YAMASAKI E T A L .

(7)

(8) (9) (10) (11) (12)


(13) (14) (15) (16)

Structure

of Organic

Compounds

125

S a s a k i , S . , CHEMICS-F in " I n f o r m a t i o n C h e m i s t r y " , p227, The U n i v e r s i t y o f Tokyo P r e s s , T o k y o , 1975, and the detail o f CHEMICS-F will be r e p o r t e d i n the near f u t u r e . M i y a s h i t a , Y . and Sasaki,S., Jpn.Chem.Soc. Meeting, (1975), I, 174 Y a m a s a k i , T . and Sasaki,S., Jpn. Anal., (1975),213 unpublished Ochiai,S.,Hirota,Y.,Kudo,Y. and Sasaki,S., Jpn. Anal., (1973), 22, 399 Stother,J.B., "Carbon-13 NMR S p e c t r o s c o p y " , Academic P r e s s , New Y o r k , 1972 K u d o , Y . and Sasaki,S., J.Chem. I n f . Comput. Sci., (1976), 16, 43 B e a c h , L . B . , "API 44 S e l e c t e d 13CNMR S p e c t r a l Data" API Research P r o j e c t 44 Publication, T e x a s , 1975 N u c l e a r M a g n e t i c Resonance S p e c t r a l S e a r c h System, NIH/EPA, USA J o h n s o n , L . F . and J a n k o w s k i , W . C . , "Carbon-13 NMR S p e c t r a " , W i l e y I n t e r s c i e n c e , New Y o r k , 1972

9 Computer Assistance for the Structural Chemist


RAYMOND E. CARHART—Department of Computer Science, Stanford University, Stanford, CA 94305 TOMAS H. VARKONY—Department of Chemistry, Stanford University, Stanford, CA 94305 DENNIS H. SMITH—Department of Genetics, Stanford University, Stanford, CA 94305 Elucidation of unknown molecular structures can be thought of as a process of systematic posing, testing and rejection of hypotheses. Each hypothesis i s of course a partial or complete structure which i s evaluated in light of available evidence. Chemists perform these tasks quite well if not completely systematically. We seek computer programs which emulate processes of reasoning about chemical structure to save time, to stimulate the chemist's thinking about an unknown and to guarantee that no plausible alternatives have been overlooked. There are several areas of structure elucidation which are amenable to some degree of computer assistance. Computer techniques are employed routinely to aid in collection and preliminary analysis of data from several types of spectrometers. Applications of problem solving programs to more sophisticated analysis of molecular structure are more recent. For example, several reports have appeared describing computer programs for assisting chemists in the task of constructing plausible candidate structures for unknown compounds (1-3). These programs have matured to the point where successful applications to real-world structural problems have been demonstrated (1,4). The structure generating capabilities of these programs f u l f i l l only the generate phase of the "plangenerate-test" paradigm of heuristic search (5). Much work remains to be done on the structure generators to make them simpler to use and to reduce them i n size, complexity and execution time. However, this work i s primarily developmental. In this report we focus on new research on "planning" and "testing" ("predicting"), and illustrate how computer techniques can provide assistance in these areas also. We define planning to include i n i t i a l interpretation of chemical and spectroscopic data and the translation of results into fragments of molecular structure which can be used manually, or together with a structure generator, to generate structures (2, £.-12 and other papers i n this symposium) . Computer assistance can be provided to the chemist during 126


9.

CARHART E T AL.

Computer

Assistance

for the Structural

Chemist

127

planning i n s e v e r a l ways. We d i s c u s s i n the subsequent s e c t i o n ways i n which our s t r u c t u r e generator, CONGEN, i s being modified to plan more e f f i c i e n t s t r u c t u r e generation by t r a n s l a t i o n o f s t r u c t u r a l data input t o the program. We f e e l that such i n t e l l i g e n t use o f s t r u c t u r a l data as c o n s t r a i n t s i s e s s e n t i a l during s t r u c t u r e generation. In most problems, however, i n i t i a l data and p r e l i m i n a r y a n a l y s i s are i n s u f f i c i e n t t o determine a s t r u c t u r e uniquely; many, perhaps hundreds, of candidate s t r u c t u r e s may remain. Therefore, we a r e a l s o pursuing development o f computer methods to examine or evaluate l a r g e s e t s o f candidate structures to a s s i s t the chemist i n focussing on the c o r r e c t s t r u c t u r e . These methods i n v o l v e : a) t e s t i n g o f s t r u c t u r e s with c o n s t r a i n t s ; and b) p r e d i c t i o n o f r e s u l t s o f manipulation o f the s t r u c t u r e s which can be matched against a c t u a l l a b o r a t o r y measurements. The goal i n both methods i s t o r e j e c t i m p l a u s i b l e candidate s t r u c t u r e s . We d e s c r i b e recent r e s u l t s i n a subsequent s e c t i o n . We f e e l such computer-aided f a c i l i t i e s w i l l be u s e f u l i n d i s c r i m i n a t i n g among a l a r g e set o f candidate s t r u c t u r e s . .11 Planning; v i a C o n s t r a i n t I n t e r p r e t a t i o n We have p r e v i o u s l y described the CONGEN program f o r c o n s t r u c t i n g s t r u c t u r e s under c o n s t r a i n t s ( 3 ) . The program has an extensive r e p e r t o i r e of c o n s t r a i n t s "which prevent the generating algorithm from producing undesired p a r t i a l or complete s t r u c t u r e s ( 1 3 ) . I t has a r i c h language f o r d e f i n i n g p a r t i a l s t r u c t u r e s (substructures) i n c l u d i n g s e v e r a l terms d e s c r i b i n g atom and bond p r o p e r t i e s , r i n g s , c h a i n s , and so f o r t h . The language allows r e p r e s e n t a t i o n o f a r o m a t i c i t y , atoms of indeterminate, or r e s t r i c t e d , i d e n t i t y and chains and r i n g s of v a r i a b l e numbers o f atoms. CONGEN i s an i n t e r a c t i v e program with a h e l p f u l user i n t e r f a c e with extensive e r r o r checking to avoid program crashes. I t i s u s e f u l , and used by a nationwide community o f persons v i a a computer network, even though i t only f u l f i l l s the r o l e o f a s t r u c t u r e generator. I t depends on user inputs t o determine i t s knowledge o f chemistry and, u n t i l r e c e n t l y , u t i l i z e d t h i s i n f o r m a t i o n much as i t was r e c e i v e d . This i s not the most e f f i c i e n t way t o solve problems. Much needs t o be known about the program to use i t i n the most e f f i c i e n t way f o r a given problem. In m o d i f i c a t i o n s and extensions t o CONGEN (below) we are s t r i v i n g to d i v o r c e the chemist from the a l g o r i t h m s . We seek t o solve problems e f f i c i e n t l y , beginning with i n f o r m a t i o n supplied by the chemist to the program i n ways which are i n t u i t i v e to him/her, independent o f the program. Other workers have discussed aspects o f data i n t e r p r e t a t i o n at some l e n g t h (2, .6-12). We a r e d i r e c t i n g our a t t e n t i o n t o the problem o f how to t r a n s l a t e and u t i l i z e the s t r u c t u r a l i n f o r m a t i o n provided by these i n t e r p r e t a t i o n s . A l l s t r u c t u r a l


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ELUCIDATION

i n f o r m a t i o n about an unknown can be viewed as c o n s t r a i n t s . Such c o n s t r a i n t s may be p o s i t i v e statements involving substructures or r i n g systems which must be present, or negative statements f o r b i d d i n g the presence o f other s u b s t r u c t u r e s or r i n g systems. There i s sometimes a s i g n i f i c a n t conceptual gap between the i n t u i t i v e chemical phrasing o f a CONGEN problem and the phrasing f o r most e f f i c i e n t problem s o l v i n g by the program. There are u s u a l l y many ways o f d e f i n i n g a given problem and d i f f e r e n t d e f i n i t i o n s can place widely d i f f e r e n t demands upon the program. We have a c o n t i n u i n g i n t e r e s t i n reducing t h i s conceptual gap by making CONGEN r e s p o n s i b l e f o r rephrasing a problem i n an e f f i c i e n t way, thus f r e e i n g the chemist t o concentrate upon the chemical, r a t h e r than the a l g o r i t h m i c , aspects o f a given problem. We have r e c e n t l y described some i n i t i a l e f f o r t s toward automatic rephrasing o f problems, e.g., i m p l i c a t i o n s o f ranges of hydrogen atoms on a given atom ( 1 3 ) . We have so f a r t r e a t e d i n d e t a i l only the problem o f t r a n s l a t i o n o f GOODLIST (Y3) c o n s t r a i n t s ( r e q u i r e d s t r u c t u r a l f e a t u r e s ) . Although this i s o n l y a part o f the c o n s t r a i n t s i n t e r p r e t a t i o n problem, the r e s u l t i n g a l g o r i t h m i s a s i g n i f i c a n t step forward i n development of our s t r u c t u r e generating c a p a b i l i t i e s f o r reasons discussed below. A. GOODLIST I n t e r p r e t a t i o n . C o n s t r u c t i v e Substructure Search. A l l c u r r e n t s t r u c t u r e generation programs, i n c l u d i n g u n t i l now CONGEN, have a s e r i o u s l i m i t a t i o n . Substructures used as b u i l d i n g b l o c k s , or "superatoms" (3) are r e q u i r e d to be nonoverlapping i . e . , they must have no ""atoms i n common. In many s t r u c t u r a l problems s e v e r a l l a r g e fragments o f the s t r u c t u r e may be known, but the overlaps among them are not known. The chemist ( o r the program ( 2 ) ) must decide what s e t o f fragments cannot overlap and use those as superatoms. Larger fragments which may overlap are t e s t e d a t the end o f s t r u c t u r e generation by a graph-matching procedure. This d i s t i n c t i o n i s c o n c e p t u a l l y i n e l e g a n t and p u z z l i n g to chemists who wish t o use CONGEN. Lack of understanding o f the d i s t i n c t i o n can lead t o t e r r i b l e inefficiencies. I n e f f i c i e n c y a r i s e s i n two ways. A set of s m a l l superatoms w i l l y i e l d many more f i n a l s t r u c t u r e s than a set o f l a r g e superatoms. A great many o f the s t r u c t u r e s produced by the former s e t w i l l be r e j e c t e d on p o s t - t e s t i n g (graph-matching) w i t h the l a r g e r GOODLIST fragments. These computations r e q u i r e c o n s i d e r a b l e time. But chemists must contend w i t h the problem o f o v e r l a p p i n g s u b s t r u c t u r e s i n t h e i r manual e x p l o r a t i o n o f s t r u c t u r a l p o s s i b i l i t i e s . By examining how such problems are solved manually we have developed a new procedure which employs both the e f f i c i e n c y o f non-overlapping superatoms and the e f f i c i e n c y o f i n c o r p o r a t i n g GOODLIST i n f o r m a t i o n a t the beginning o f the process o f s t r u c t u r e generation ( t h u s , "planning") r a t h e r than the end. In s h o r t , we have developed a general s o l u t i o n t o the problem o f c o n s t r u c t i n g

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1) An Example. A recent problem s t u d i e d using CONGEN i n v o l v e d the s t r u c t u r a l i n f o r m a t i o n summarized i n Figure 1. The bonds with u n s p e c i f i e d t e r m i n i i n CEMB are f r e e valences. A l l atoms (excepting seven remaining hydrogens) i n the e m p i r i c a l formula C^^H^O^ are included i n CEMB. The problem c o n s i s t s o f f i n d i n g a l l ways o f a l l o c a t i n g three new bonds among the free valences i n the superatom CEMB such t h a t the three i n d i c a t e d s u b s t r u c t u r e s (Figure 1) are present i n the f i n a l molecules. There are perhaps 10,000 unique a l l o c a t i o n s o f those three new bonds, but only seven pass the GOODLIST t e s t s . Using GOODLIST as a p o s t - t e s t o n l y , CONGEN would generate a l l 10,000 and d i s c a r d n e a r l y a l l o f them, a process which would have been so lengthy t h a t i t was never completed. Yet most chemists given t h i s i n f o r m a t i o n could f a i r l y quickly w r i t e down the seven solutions. I t i s clear c o n c e p t u a l l y how the problem i s solved manually. I t i s obvious that there are only three places i n CEMB where the f i r s t GOODLIST item (Figure 1) can f i t , because there a r e only three methyl groups on the periphery o f CEMB which f i t the s t r u c t u r a l c r i t e r i a o f the s u b s t r u c t u r e . For each o f these matchings, there are four ways o f matching the second s u b s t r u c t u r e , and so f o r t h . In t h i s case, some matchings l e a d t o c o n s t r u c t i o n o f new bonds. In the general case when there are s e v e r a l superatoms and remaining atoms, matchings may r e q u i r e c o n s t r u c t i n g new bonds and s t r u c t u r a l u n i t s , by u t i l i z i n g parts o f e x i s t i n g superatoms or remaining atoms. In t h i s example, CONGEN, using the method o u t l i n e d below, solves the problem i n much the same way as described above f o r the manual method. Rather than generating and t e s t i n g thousands of undesired s t r u c t u r e s , i t q u i c k l y a r r i v e s at the seven s o l u t i o n s by i n c o r p o r a t i n g the GOODLIST i n f o r m a t i o n from the very beginning. 2) The Method. We have developed a method, as an extension to CONGEN, which emulates the manual method. I t matches GOODLIST items t o the i n i t i a l problem f o r m u l a t i o n , which may be anything from the raw e m p i r i c a l formula t o a l i s t o f nonoverlapping superatoms. When new bonds or atoms are r e q u i r e d t o complete the matching, they are constructed from other segments (atoms, superatoms) o f the problem by forming new bonds. In order t o i n c o r p o r a t e a GOODLIST s u b s t r u c t u r e i t i s necessary t o f i n d a l l unique ways that the given s u b s t r u c t u r e can be created using parts o f the e x i s t i n g b u i l d i n g blocks (atoms and superatoms). Figure 2 shows s c h e m a t i c a l l y , together w i t h an example, some o f the ways t h i s c o n s t r u c t i o n might occur: a) by bonding together two (or more) e x i s t i n g superatoms t o c r e a t e one l a r g e r one; b) by bonding a d d i t i o n a l atoms t o a superatom to

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Cemb: H c

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,

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Figure 1. Structural information available for an unknown cembranolide. The superatom "CEMB" was inferred from a variety of data and inferences derived from related, co-occurring compounds. The GOODLIST items were inferred from additional spectroscopic and chemical data.

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Figure 2. A schematic and an example of ways to construct a GOODLIST item from a collection of atoms and superatoms. Each way results in larger superatoms in new problems to be carried on to the next step in structure generation, for example, incorporation of another GOODLIST item.


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c r e a t e a l a r g e r one; and c) by c o n s t r u c t i n g a copy of the s u b s t r u c t u r e from s i n g l e atoms, c r e a t i n g a new superatom. We c a l l t h i s method " c o n s t r u c t i v e s u b s t r u c t u r e search" f o r obvious reasons. The procedure i s stepwise. I t begins with f i n d i n g a l l ways to c o n s t r u c t the f i r s t GOODLIST item. Each o f these ways i s a new problem with the same or l a r g e r superatoms (e*g., Figure 2 ) . Each new problem i s t r e a t e d i n a depth f i r s t generation scheme by c o n s i d e r i n g the next GOODLIST item, and proceeding until a l l GOODLIST items are accounted f o r or u n t i l the next GOODLIST item cannot be b u i l t from the current set of superatoms and atoms. Depending on the problem, the f i n a l set of s o l u t i o n s may be f i n a l s t r u c t u r e s , as i n the previous example ( F i g u r e 1), or may be s e v e r a l new s e t s of superatoms and atoms f o r each of which CONGEN can be used to c o n s t r u c t f i n a l s t r u c t u r e s . In the l a t t e r i n s t a n c e , a l l GOODLIST items are guaranteed to be present so that time-consuming p o s t - t e s t i n g f o r t h e i r e x i s t e n c e i s not r e q u i r e d . D e t a i l s of the a l g o r i t h m are beyond the scope of t h i s p r e s e n t a t i o n and w i l l be discussed s e p a r a t e l y . B r i e f l y , the a l g o r i t h m i s derived from the CONGEN graph-matching r o u t i n e (1_3) w i t h the a d d i t i o n a l f e a t u r e that as i t searches f o r the s u b s t r u c t u r e i t i s allowed to create new bonds (up to the l i m i t of a v a i l a b l e new bonds i n the o r i g i n a l CONGEN problem) whenever they are necessary f o r the search to proceed. New bonds may be used to form m u l t i p l e bonds or r i n g s w i t h i n a superatom. A l t e r n a t i v e l y , use of new bonds to form new connection to atoms outside the superatom leads to extended superatoms (Figure 2 ) . During the search, f u l l account i s taken of the t o p o l o g i c a l symmetry of the superatoms i n the o r i g i n a l problem so t h a t f i t t i n g s which are redundant with respect to these symmetries are avoided. The p o t e n t i a l equivalence of GOODLIST items i s not c u r r e n t l y considered; d u p l i c a t e problems or f i n a l s t r u c t u r e s are removed i n subsequent steps. Most CONGEN problems c o n t a i n one or more GOODLIST items which can be t r e a t e d with our method. The algorithm i s c u r r e n t l y being t e s t e d to understand i t s scope and l i m i t a t i o n s . Although i n t e g r a t e d i n t o CONGEN, i t does not yet have an appropriate user i n t e r f a c e so i s not yet a v a i l a b l e as p a r t of our v e r s i o n a v a i l a b l e over the network. 3) A Second Example. The s t r u c t u r a l i n f o r m a t i o n f o r a second example i s summarized i n Figure 3. This i n f o r m a t i o n i s formulated from data presented i n a previous d i s c u s s i o n of t h i s s t r u c t u r e (Ijl) . In t h i s example, the i n i t i a l set o f nonoverlapping s t r u c t u r a l components c o n s i s t e d o f the off-resonance decoupled 13c NMR data plus the atom Z ( F i g u r e 1). Every bond connecting atoms i n the f i n a l s t r u c t u r e must be used to connect these components. To generate s t r u c t u r e s from t h i s i n f o r m a t i o n alone, with subsequent t e s t i n g f o r the presence of S1- S4 ( F i g u r e 3) would be e f f e c t i v e l y i m p o s s i b l e . The GOODLIST items -SI -S4 can overlap s i g n i f i c a n t l y . The problem was a l s o solved

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by reducing the s u b s t r u c t u r e s S1-S4 t o non-overlapping components and generating structures under extensive constraints. But t h i s s t r u c t u r a l i n f o r m a t i o n can be used d i r e c t l y and e f f i c i e n t l y i n our new method, and CONGEN, using constructive substructure search, arrives quickly at r e p r e s e n t a t i o n s o f the two p o s s i b l e s o l u t i o n s , J_ and 2, F i g u r e 4. I f one assumes t h a t the two amide f u n c t i o n a l i t i e s S2 must be completely d i s j o i n t , the s t r u c t u r e 2, proposed p r e v i o u s l y (14) i s the o n l y s o l u t i o n , excepting s t r u c t u r a l v a r i a t i o n i n Z (see c a p t i o n t o Figure 3 ) .


II.

T e s t i n g v i a PRUNE, SURVEY, REACT and MSPRED

From an a l g o r i t h m i c s t a n d p o i n t , CONGEN i s s u c c e s s f u l i f i t can, i n a reasonable amount o f time and without exhausting storage r e s o u r c e s , produce a l i s t o f candidate s t r u c t u r e s s a t i s f y i n g the chemist's c o n s t r a i n t s . However, t h i s l i s t i s o f t e n q u i t e l a r g e , perhaps s e v e r a l hundred s t r u c t u r e s , and from an a n a l y t i c a l standpoint the problem may be f a r from complete. I t remains f o r the chemist t o d i s c r i m i n a t e among the c a n d i d a t e s , e v e n t u a l l y reducing the p o s s i b i l i t i e s t o j u s t one s t r u c t u r e . We are studying s e v e r a l ways t o provide computer a s s i s t a n c e i n examining and further constraining lists of structural candidates. We have implemented s e v e r a l types o f t e s t s designed to help d i s c r i m i n a t e among candidate s t r u c t u r e s * A. D i r e c t Tests. Two t e s t s are d i r e c t l y s t r u c t u r a l f e a t u r e s o f the candidates.

related

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1. PRUNE. The chemist can f u r t h e r reduce a s e t o f s t r u c t u r e s by "pruning" (J3) the s e t with new s t r u c t u r a l information. This subsequent t e s t i n g has been described i n d e t a i l p r e v i o u s l y (3,13). 2. SURVEY. The second type o f d i r e c t t e s t allows surveying the s e t o f candidate s t r u c t u r e s using a l i b r a r y o f predefined structural features. The f u n c t i o n s o f SURVEY and examples o f a p p l i c a t i o n s are summarized i n Figure 5. The examples are chemical areas where we have u t i l i z e d SURVEY i n our own research. An extensive l i b r a r y o f f u n c t i o n a l groups i s maintained i n order that s e t s o f s t r u c t u r e s may be surveyed for unlikely f u n c t i o n a l groupings. Such groupings are o f t e n overlooked i n the i n i t i a l d e f i n i t i o n o f a problem p r e c i s e l y because they are unlikely. But CONGEN w i l l c o n s t r u c t them u n l e s s c o n s t r a i n t s forbid i t . SURVEY a c t s as a reminder o f such groupings. I t provides a c l a s s i f i c a t i o n o f s t r u c t u r e s by f u n c t i o n a l groups, any set o f which can be kept or pruned away a t the chemist's discretion. Other l i b r a r i e s of structural f e a t u r e s are maintained, i n c l u d i n g , f o r example, l i b r a r i e s o f mono- and

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Figure 3. Structure information for a dehydrotryptophan derivative. The atom Z represents an aromatic ring with several other substituents. The variety of possible substitution patterns on the aromatic ring lends considerable structural variety to this problem beyond our brief presentation. Emperical formula: C J/ N 0 Z. C13 NMR: CH X 3, CH X 2, CH X 12, C X 9. 2C

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Figure 4. Two structural possibilities for the compound whose structural information is summarized in Figure 3

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sesquiterpane s k e l e t o n s . We have u t i l i z e d these l i b r a r i e s i n s t u d i e s of terpenoid c y c l i z a t i o n and rearrangement (1_5) i n order to l o c a t e known skeletons and e l u c i d a t e t h e i r pathways o f formation. A l i b r a r y of amino a c i d skeletons i s used to t e s t s t r u c t u r a l candidates which may be conjugates of organic a c i d s w i t h amino a c i d s i n s t u d i e s of organic c o n s t i t u e n t s o f human body f l u i d s . Any set of f e a t u r e s or s t r u c t u r e s can be defined and used by SURVEY. B. I n d i r e c t Tests. There are two i n f o r m a t i v e sources of data about s t r u c t u r a l candidates which cannot always be phrased as d i r e c t t e s t s on the candidates themselves: 1) s t r u c t u r a l f e a t u r e s observed i n chemical r e a c t i o n s ; and 2) empirical s p e c t r o s c o p i c measurements on the unknown which cannot be i n t e r p r e t e d unambiguously i n p r e c i s e s t r u c t u r a l terms* The program REACT addresses the f i r s t problem while MSPRED i s concerned with the second i n the context of mass spectrometric observations. 1) REACT. The REACT program has two b a s i c g o a l s : 1) to provide the chemist with a computer-based language f o r d e f i n i n g graph transformations and applying them to s t r u c t u r e s , thus simulating chemical reactions; and 2) to keep t r a c k a u t o m a t i c a l l y of the i n t e r r e l a t i o n s h i p s among s t r u c t u r e s i n a complex sequence of r e a c t i o n s so t h a t whenever s t r u c t u r a l claims are made about any product, the i m p l i c a t i o n s of these claims on s t r u c t u r e s at other steps i n the sequence can be t r a c e d . The f i r s t v e r s i o n of the REACT program has been discussed p r e v i o u s l y (J6). Based on our experience and s e v e r a l d i f f i c u l t i e s with r e p r e s e n t a t i o n of the network of r e a c t i o n s and associated s t r u c t u r e s , we have r e c e n t l y completed a second v e r s i o n with s e v e r a l new f e a t u r e s . The goals we set during the w r i t i n g o f t h i s version and for near-term f u t u r e developments are summarized i n Figure 6 . The program has been separated from CONGEN f o r purposes of e f f i c i e n c y (the combination i s too l a r g e a program) and because c e r t a i n f u n c t i o n s l i k e graph matching have a s l i g h t l y d i f f e r e n t meaning when a p p l i e d to r e a c t i o n s v s . structure generation. EDITREACT, the r e a c t i o n - e d i t i n g language, has been extended to a l l o w the user to d e f i n e subgraph c o n s t r a i n t s which apply r e l a t i v e to a p o t e n t i a l r e a c t i o n s i t e r a t h e r than to the molecule as a whole. For example, i n the present v e r s i o n of REACT, we can say e i t h e r that a hydroxyl group (OH), i f present anywhere i n the reactant molecule, would i n h i b i t the r e a c t i o n , or that such i n h i b i t i o n would take place only i f the OH group i s adjacent to the r e a c t i o n s i t e . Such s i t e - s p e c i f i c c o n s t r a i n t s , a p p l i e d e i t h e r before or a f t e r the transformation (i.e., r e a c t i o n ) has been c a r r i e d out on the s i t e , are c r i t i c a l to the d e t a i l e d d e s c r i p t i o n of r e a l chemical r e a c t i o n s . The i n c l u s i o n of t h i s f a c i l i t y i n REACT s u b s t a n t i a l l y i n c r e a s e s i t s usefulness


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i n r e a l - w o r l d chemical problems. The control structure for REACT (Figure 6, 3) has undergone major r e v i s i o n . In the initial implementation, a set of products a r i s i n g from the a p p l i c a t i o n of a given r e a c t i o n to a given s t a r t i n g s t r u c t u r e could be subjected to a m u l t i - l e v e l c l a s s i f i c a t i o n which grouped the products based upon user-defined substructural constraints. Each of these c l a s s e s had an a s s o c i a t e d minimum and maximum number, r e p r e s e n t i n g the numbers o f products which were allowed to be members of the c l a s s . Any s t a r t i n g m a t e r i a l s whose products could not s a t i s f y these c o n d i t i o n s were removed from the l i s t of candidates. S t r u c t u r e s i n any c l a s s could be f u r t h e r r e a c t e d , t h e i r products c l a s s i f i e d , and so on. This treatment of bookkeeping was sufficient for s t a t i n g many chemical problems. For example, suppose a chemist knew t h a t a p a r t i c u l a r r e a c t i o n on an unknown compound y i e l d e d two carbonyl compounds ( i . e . , c o n t a i n i n g C=0), at l e a s t one of which was an e s t e r (R-O-C=0(R')). He could d e f i n e a product c l a s s CARBONYL using the C=0 s u b s t r u c t u r e with a minimum and maximum of two products. He could then d e f i n e a sub-class o f CARBONYL c a l l e d ESTERS using the substructure R-0-C=0(R') w i t h a minimum of one and a maximum of two products. The program would a u t o m a t i c a l l y use t h i s i n f o r m a t i o n to e l i m i n a t e candidate starting structures which could not give the i n d i c a t e d product d i s t r i b u t i o n w i t h the given r e a c t i o n . There are chemical problems, though, f o r which the above scheme i s too r i g i d . For example, suppose a r e a c t i o n g i v e s s e v e r a l products two of which are i s o l a t e d and l a b e l e d dA and dB. Suppose that only a s m a l l amount of dA i s a v a i l a b l e so only mass s p e c t r o s c o p i c measurements are p r a c t i c a l and that a deuterium-exchange experiment shows that dA has two exchangeable protons (say, e i t h e r N-H or 0-H). Presume that dB shows a strong carbonyl absorption i n the IR. Now, _dA might a l s o c o n t a i n a carbonyl group, but t h a t was never determined, and n e i t h e r was the number of exchangeable protons i n dB, which c o u l d be two. No matter how one attempts to use the abovedescribed c l a s s i f i c a t i o n system, one cannot express t h i s information accurately. Our new approach i s designed to express chemical i n f o r m a t i o n to REACT i n a much more n a t u r a l sequence which p a r a l l e l s the experimental steps. Current o p e r a t i o n s , which include functional commands and descriptive terms, are summarized i n Figure 7. Thus, a r e a c t i o n i s c a r r i e d out by using the command REACT and a p p l y i n g a named r e a c t i o n to a set of s t r u c t u r e s ( i n i t i a l l y STRUCS ( F i g u r e 7 ) , but subsequently to the contents o f any named product f l a s k ) . Products are assigned to a named f l a s k . The f i r s t experimental step a f t e r a r e a c t i o n i s u s u a l l y the separation and p u r i f i c a t i o n of products. An analogous step i s i n c l u d e d i n REACT, i n which the separation amounts to d e f i n i n g a number of l a b e l l e d " f l a s k s " each of which i s u l t i m a t e l y to c o n t a i n a s p e c i f i e d number ( u s u a l l y 1) of the products. As experimental data are gathered on each r e a l

136

COMPUTER-ASSISTED REACTION CHEMISTRY

1.

STRUCTURE

ELUCIDATION

DEVELOPMENTS

SEPARATION FROM CONGEN - COMMUNICATION VIA FILES OF STRUCTURES.

2.

ADDING CONSTRAINTS - SITE - AND TRANSFORM - S P E C I F I C

3.

CONTROL STRUCTURE -

4.

RAMIFICATION

A.

ESTABLISH RELATIONSHIPS AMONG PRODUCTS AND REACTANTS

B.

DEAL PROPERLY

WITH RANGES OF NUMBERS OF PRODUCTS

INTERACTION - DEVELOP MANIPULATION COMMANDS WHICH PARALLEL LABORATORY OPERATIONS, SEPARATE VARIOUS

INTO FLASKS, FLASKS,

E.G.,

TEST CONTENTS OF

INCOMPLETE

SEPARATIONS,


ETC. 5.

REPRESENTATION

6.

PROSPECTIVE

OF REACTIONS

DETECTION OF DUPLICATE PRODUCTS BASED ON

SYMMETRY PROPERTIES OF: B)

Figure

A)

STARTING MATERIAL; AND

TRANSFORMATION.

6.

Major

milestones REACT

in the development program

of the

FUNCTIONS

EDITREACT REACT, MREACT SEPARATE PRUNE

TERMS 1, E, NAMES;

Figure 7. Functional commands and descriptive terms used in REACT. EDITREACT allows reaction definition, REACT and MREACT carry out reactions, SEPARATE selects numbers of and flasks for products, PRUNE tests the content of specified flasks for given structural features. Reactions may be carried out as one-step (1), exhaustive (EX), or as equilibrium (E) reactions. STRUCS is the initial list of candidate structures.

EX STEPS;

STRUCS; PRODUCTS;

FLASKS;

LABELS

CONSTRAINTS

DURING REACTION ON STARTING

MATERIALS

SITE-SPECIFIC TRANSFORM-SPECIFIC ON PRODUCTS POST-REACTION NUMBERS OF PRODUCTS AT ANY LEVEL SUBSTRUCTURAL CONSTRAINTS APPLIED TO PRODUCTS (PRUNING) AT ANY LEVEL


9.

CARHART E T A L .

Computer

Assistance

for

the

Structural

Chemist

137

product, corresponding s u b s t r u c t u r a l c o n s t r a i n t s are attached to the corresponding f l a s k i n the program. As each such a s s e r t i o n i s made, the bookkeeping mechanism v e r i f i e s t h a t , f o r a set of r e a c t i o n products from a given s t a r t i n g m a t e r i a l , there i s at l e a s t one way to d i s t r i b u t e them among the f l a s k s such that each product s a t i s f i e s the c o n s t r a i n t s f o r i t s f l a s k . As an example, consider the problem described above w i t h two products dA and dB. Assume that an o x i d a t i v e cleavage r e a c t i o n w i t h appropriate p r o t e c t i o n had been a p p l i e d to a set of candidate s t r u c t u r e s , y i e l d i n g f o r each s t r u c t u r e a set of products placed i n a f l a s k l a b e l l e d ? ( i l l u s t r a t e d s c h e m a t i c a l l y i n Figure 8 ) . Separation y i e l d e d two i d e n t i f i a b l e products and perhaps o t h e r s , placed i n the i n d i c a t e d f l a s k s A, B and C (Figure 8 ) . Data acquired on dA and dB were summarized above. The task of determining l e g a l assignments o f products to i n d i v i d u a l f l a s k s i s given to an a l l o c a t i o n mechanism. The o p e r a t i o n of the a l l o c a t o r w i l l be described i n a subsequent p u b l i c a t i o n d e s c r i b i n g REACT i n more d e t a i l . However, we can illustrate the problem conceptually with the (purely h y p o t h e t i c a l ) s t r u c t u r e s 2rL i F i g u r e 9 . Assuming that 2rl are candidate s t r u c t u r e s f o r an unknown, the statements that the compound dA, i n f l a s k A, must have two exchangeable hydrogens and dB i n f l a s k B, i s a ketone ( F i g u r e 8) are c o n s t r a i n t s on which products o f the r e a c t i o n can be i n which f l a s k . Initial separation r e j e c t s 2. i product, d]_ , because only one product i s obtained and at l e a s t two were r e q u i r e d ( F i g . 9 ) . Cleavage of j£-£ y i e l d s two products d2. However, n e i t h e r product obtained from U s a ketone (both are aldehydes), nor does e i t h e r product possess two exchangeable hydrogens. Therefore n e i t h e r product can be i n e i t h e r f l a s k and k i s r e j e c t e d . Compound £ y i e l d s one product, d±, which i s a ketone and possesses two exchangeable hydrogens. d1_ can be i n e i t h e r f l a s k A or B. But the other product 62, obeys n e i t h e r c o n s t r a i n t , can be i n n e i t h e r f l a s k and £ i s r e j e c t e d . Compound 6. y i e l d s two products which can be assigned to f l a s k s A and B unambiguously. Compound J. y i e l d s two products each o f which possess both a keto group and two exchangeable hydrogens. These c o n s t r a i n t s are i n s u f f i c i e n t f o r unambiguous a l l o c a t i o n and e i t h e r s t r u c t u r e may be i n e i t h e r f l a s k . In the general case, r e a c t i o n s may be c a r r i e d out i n any c o n s i s t e n t sequence, whether or not the contents o f a f l a s k are uniquely s p e c i f i e d . REACT keeps account o f the f a c t that a r e a c t i o n may be applied to a f l a s k whose contents are known but not assigned to a s i n g l e s t r u c t u r e . M u l t i p l e r e a c t i o n s to any level may be c a r r i e d out. The a l l o c a t i o n scheme and r a m i f i c a t i o n mechanism t r a n s l a t e statements about products at any l e v e l to determine the i n f l u e n c e of each statement on the contents o f each f l a s k f o r every s t r u c t u r a l candidate. n

a n d

An

Example. We

t

s

have r e c e n t l y

reexamined

the c o n s t r a i n t s


COMPUTER-ASSISTED

A)

C/

B)

C*

A

B

HAS

2 EXCHANGEABLE

A KETONE BY

STRUCTURE

H'S

IR

Figure 8. Schematic of reaction which yields at tory, both placed in flask separation of P into

the computer representation of a least two products in the laboraP. Flasks A, B, and C result from from two to many products.

ELUCIDATION


9.

CARHART E T A L .

Computer

Assistance

for

the

Structural

Chemist

139

derived from a p p l i c a t i o n s of a dehydration r e a c t i o n to the s t r u c t u r e of p a l u s t r o l . This problem was studied p r i o r to the e x i s t e n c e of REACT, so that c o n s t r a i n t s derived from measurements on the products were t r a n s l a t e d manually i n t o a s u b s t r u c t u r a l c o n s t r a i n t on the s t r u c t u r a l c a n d i d a t e s . The data are summarized i n Figure 10. Three products were i s o l a t e d , one of which possessed only a v i n y l methyl group (1H NMR), 8, a second which possessed only a v i n y l hydrogen, and a t h i r d product with n e i t h e r a v i n y l hydrogen nor a v i n y l methyl group, 10. The substructure derived from those data was JJ_, and pruning with t h i s c o n s t r a i n t reduced a set o f 88 s t r u c t u r e s to 22 ( i ) . This c o n s t r a i n t i s incomplete, however, because s u b s t r u c t u r e JJ_ does not prevent s t r u c t u r e s i n which a methyl group i s connected to the methine carbon which does not already bear a methyl group. A more l o g i c a l way to do t h i s problem i s to c a r r y out the r e a c t i o n , s e p a r a t i o n and t e s t i n g with c o n s t r a i n t s i n REACT and l e t the a l l o c a t i o n and r a m i f i c a t i o n mechanisms decide which s t r u c t u r e s are l e g a l and which are n o t . Doing the problem i n t h i s way, using substructure 8., £ and J_0 as c o n s t r a i n t s on the contents of the i n d i c a t e d f l a s k s (Figure 10), reduces the set of 88 s t r u c t u r e s t o 14 r a t h e r than 22 because now a l l i m p l i c a t i o n s of the c o n s t r a i n t s are u t i l i z e d p r e c i s e l y . Major tasks mentioned i n Figure 6 which remain uncompleted i n c l u d e the problem d e a l i n g with i n c o m p l e t e l y separated mixtures and a general treatment of symmetry p r o p e r t i e s o f s t r u c t u r e s and transforms. The former problem i s d i f f i c u l t because of the c o m b i n a t o r i a l complexity of the a l l o c a t i o n scheme when one cannot assume a s i n g l e s t r u c t u r e per f l a s k (as mentioned p r e v i o u s l y , however, many p o s s i b l e i d e n t i t i e s f o r that s i n g l e s t r u c t u r e are handled p r o p e r l y ) . The l a t t e r problem r e q u i r e s only implementation of procedures f o r d e t e c t i o n of symmetry p r o p e r t i e s o f graphs; procedures which e x i s t i n parts o f the CONGEN program. 2) MSPRED. Mass spectrometry i s an important t o o l i n organic a n a l y t i c a l chemistry. When no other s t r u c t u r a l i n f o r m a t i o n i s a v a i l a b l e mass spectrometry i s used as a standalone method f o r s t r u c t u r a l i n f e r e n c e . In combination with other a n a l y t i c a l methods i t i s a l s o extremely u s e f u l f o r post t e s t i n g p o s s i b l e candidate s t r u c t u r e s . Mass s p e c t r a l data may be used i n s t r u c t u r a l s t u d i e s i n s e v e r a l ways. For example, we can c r e a t e a fragmentation theory based on examination of s e t s o f known s t r u c t u r e s and t h e i r a s s o c i a t e d mass s p e c t r a . Or, assuming that peaks i n the mass spectrum o f an unknown o r i g i n a t e from unrearranged molecular i o n s , we can propose p o s s i b l e s t r u c t u r e s by combining the fragments together under the guidance o f a fragmentation theory. When the s t r u c t u r e i s g i v e n we can p r e d i c t a mass spectrum which w i l l obey the r u l e s o f a fragmentation theory. A l l of these

140

COMPUTER-ASSISTED

_

.1

I

r-

I

STRUCTURE

I

2

Cf

-7

ELUCIDATION

I

cf

^1


OH REJECT ON

REJECT ON

SEPARATE

PRUNE

PRUNE

(ONLY

(FAILS A

UFd -d

REJECT ON I

PRODUCT)

Figure

9.

AND

O.K.

O.K.

=c 1§)> and i n c l u d e l i m i t a t i o n of the number of bonds broken and the number of steps i n a process, the p r o x i m i t y of p a i r s o f cleaved bonds ( i . e . whether or not two adjacent bonds can break i n a g i v e n process) the m u l t i p l i c i t y or a r o m a t i c i t y of each cleaved bond, the allowed hydrogen atoms t r a n s f e r e d from or i n t o the charged fragment and the n e u t r a l fragments which can be l o s t . The program c a l c u l a t e s the composition and the mass o f the fragment which can be obtained i n a fragmentation process. The

COMPUTER-ASSISTED STRUCTURE E L U C I D A T I O N

142

program then combines these r e s u l t s i n t o a p r e d i c t e d mass spectrum with peaks of uniform i n t e n s i t y . The best p r e d i c t i v e t h e o r i e s of mass spectrometry are l i m i t e d to f a m i l i e s of c l o s e l y r e l a t e d s t r u c t u r e s ( i . e . , c l a s s s p e c i f i c t h e o r i e s ) . However, given the wide v a r i e t y of s t r u c t u r a l types which can be produced by CONGEN and REACT, i t i s necessary f o r MSPRED to use t h i s very general model of mass s p e c t r a l fragmentation.


E v a l u a t i o n and Ranking. For t h i s general approach we decided to use an e v a l u a t i o n f u n c t i o n which takes i n t o account that peaks at high m/e values and high i n t e n s i t y have more d i a g n o s t i c value then peaks i n the low m/e region of the spectrum with low i n t e n s i t y . The simplest form of v a r i o u s e v a l u a t i o n f u n c t i o n s we have used i s given i n Equation 1. SCORE = M _I j

i

1

where M^ i s the mass of a peak present i n both the p r e d i c t e d and observed s p e c t r a . I i s the i n t e n s i t y of the ( c o r r e c t l y predicted) peak i n the observed spectrum. We expect the h a l f - o r d e r theory to be o v e r l y complete i n the sense t h a t , when a p p l i e d to the c o r r e c t s t r u c t u r e f o r an unknown, i t w i l l doubtless p r e d i c t many p l a u s i b l e fragments which are not observed. This simply r e f l e c t s the f a c t that the "break everything" approach to mass spectrometry is a considerable o v e r s i m p l i f i c a t i o n . Thus the e v a l u a t i o n f u n c t i o n does not p e n a l i z e f o r p r e d i c t e d but unobserved peaks. What we do expect, though, i s that a l a r g e number of the observed peaks, p a r t i c u l a r l y the intense ones, w i l l have p l a u s i b l e explanations w i t h respect to the c o r r e c t s t r u c t u r e . Thus a "reward" i s given to every observed peak which i s c o r r e c t l y p r e d i c t e d (Equation i

1).

Example: Our i n t e r e s t i n mass s p e c t r a of s t e r o i d s l e d us to examine a c l a s s of mono-keto androstanes as a t e s t case. We obtained the high r e s o l u t i o n mass s p e c t r a f o r 10 of the 11 p o s s i b l e mono-ketoandrostanes. These 11 s t r u c t u r e s were our l i s t of candidate s t r u c t u r e s . We p r e d i c t e d the high r e s o l u t i o n spectra f o r each of the 11 s t r u c t u r e s using the h a l f - o r d e r theory, and then ranked them against each of the 10 observed s p e c t r a . The r e s u l t s are summarized i n Table I . In most of the cases i n Table I the c o r r e c t s t r u c t u r e was ranked f i r s t and i n the remaining i t was ranked second. The h a l f - o r d e r theory i s i n s u f f i c i e n t to d i f f e r e n t i a t e among monoketo androstanes when the keto group i s l o c a t e d i n one of the 4 p o s s i b l e p o s i t i o n s i n r i n g A or among s t r u c t u r e s which are d i f f e r e n t i n the l o c a t i o n of the keto s u b s t i t u e n t i n Ring D. MSPRED i s q u i t e new and we have not yet had s u f f i c i e n t experience with i t to evaluate i t s o v e r a l l u s e f u l n e s s . We are now doing a systematic study of v a r i o u s c l a s s e s of compounds by

9.

CARHART E T A L .

Computer

Assistance for the Structural

Chemist

143


ranking the spectrum o f a known s t r u c t u r e against a CONGEN or REACT generated l i s t o f s t r u c t u r e s which contains the c o r r e c t s t r u c t u r e among s e v e r a l which are c l o s e l y r e l a t e d . In most o f the t e s t cases ( i n c l u d i n g low and high r e s o l u t i o n mass s p e c t r a l data) the c o r r e c t s t r u c t u r e was ranked among the upper ten percent o f the s t r u c t u r e s . We are o p t i m i s t i c that the r e s u l t s of ranking based on the h a l f - o r d e r theory can be used as a p r e l i m i n a r y f i l t e r t o d i v i d e a set o f candidate s t r u c t u r e s i n t o two p o r t i o n s , one o f which has an extremely high p r o b a b i l i t y of c o n t a i n i n g the c o r r e c t s t r u c t u r e . To t h i s set o f top-ranked s t r u c t u r e s we can apply a more d e t a i l e d fragmentation theory t o make s p c i f i c p r e d i c t i o n s . We are developing computer-assisted methods to make use o f a rule-based theory. Table I . Ranking o f Mono-Ketoandrostanes Based on the Half-Order Theory. a

STRUCTURE (Keto Position)

RANKING

7 16 11 3 17 6 12 15 1 4

2 1 2 1 2 1 1 1 1 1

STRUCTURES WITH THE SAME SCORE

BETTER RANKED STRUCTURES

6 17,15 12 1,2,4 15,16

2,3,4,1

17,16 2,3,4 1,2,3

a) C o n s t r a i n t s used i n p r e d i c t i n g spectra i n c l u d e d Bonds/Step = 2, //Steps/Process = 1, H Transfers (-2 - 1 0 1 2 ) . 2) Rule-based theory. When the candidate s t r u c t u r e i s known to belong to a p r e v i o u s l y i n v e s t i g a t e d c l a s s o f compounds, then we can use a d d i t i o n a l information t o p r e d i c t a more p r e c i s e mass spectrum. This information i s i n the form o f s p e c i f i c fragmentation r u l e s . These r u l e s can be used to make p r e d i c t i o n s o f occurrence o f ions t o supplement or supplant the p r e d i c t i o n s o f the h a l f - o r d e r theory. We can a l s o use i n f o r m a t i o n about the frequency o f c o r r e c t a p p l i c a t i o n o f the r u l e i n the set o f compounds from which the r u l e s were developed. We c a l l t h i s information the confidence f a c t o r associated with the r u l e . Other important i n f o r m a t i o n i s the i n t e n s i t y range associated with the peaks which are p r e d i c t e d by a r u l e . We have the c a p a b i l i t y of p r e d i c t i n g mass s p e c t r a using a rule-based theory and have found that by t h i s approach we can

144


p r e d i c t a more accurate spectrum and get a b e t t e r ranking then w i t h the h a l f - o r d e r theory. D e t a i l s o f the methods and r e s u l t s of MSPRED using both rule-based and h a l f - o r d e r theory w i l l be presented s e p a r a t e l y *


Summary We have i l l u s t r a t e d a number o f approaches t o extend the concept o f computer-assisted s t r u c t u r e e l u c i d a t i o n beyond t h a t of simple s t r u c t u r e g e n e r a t i o n . We have i l l u s t r a t e d how chemical i n f o r m a t i o n together w i t h a computer program can a s s i s t chemists i n both planning p r i o r t o s t r u c t u r e generation and, subsequently, t e s t i n g o f candidates. In work described here, the chemist plays an i n t e g r a l part i n e f f e c t i v e use o f the problem-solving t o o l s we provide i n the form o f i n t e r a c t i v e programs* Literature

Cited

1. Munk, Μ. Ε., Sodano, C. S . , McLean, R. L., and H a s k e l l , H., J. Amer. Chem. Soc. (1967), 89, 4158. 2. S a s a k i , S . , Kudo, Y., O c h i a i , S . , and Abe, H . , Mikrochim. A c t a , (1971), 726. 3. Carhart, R. E., Smith, D. H., Brown, H., and D j e r a s s i , C., J. Amer. Chem. Soc. (1975), 97, 5755. 4. Cheer, C . , Smith, D. H . , D j e r a s s i , C . , Tursch, B., Braekman, J. C . , and Daloze, D . , Tetrahedron (1976), 2, 1807. 5. Feigenbaum, Ε. Α . , i n "Information Processing 68". North Holland P u b l i s h i n g C o . , Amsterdam, 1968. 6. Kwok, K.-S, Venkataraghavan, R . , and M c L a f f e r t y , F . W., J. Amer. Chem. Soc. (1973), 95, 4185. 7. Hertz, H . S . , H i t e s , R. Α . , and Biemann, Κ . , A n a l . Chem. (1971), 43, 681. 8. Yamasaki, T . , and S a s a k i , S . , J p n . A n a l . (1975), 213. 9. J e z l , Β. Α., and Dalrymple, D. L., A n a l . Chem. (1975), 47, 203. 10. Schwarzenbach, R., Meili, J., K o e n i t z e r , H . , and C l e r c , J. T . , Org. Mag. Resonance (1976), 8, 11. 11. Smith, D. H., Buchanan, B . G., Engelmore, R. S . , D u f f i e l d , Α. Μ., Yeo, Α., Feigenbaum, Ε. Α . , Lederberg, J., and D j e r a s s i , C . , J. Amer. Chem. Soc. (1972), 94, 5962. 12. Gray, Ν. Α. Β., A n a l . Chem. (1975), 4 7 , 2926. 13. C a r h a r t , R. E . , and Smith, D. H . , Computers and Chemistry (1976), 1, 79. 14. Gatti, G., Cardillo, R., Fuganti, C . , and Ghiringhelli, D . , Chem. Commun. (1976), 435. 15. Smith, D. H., and C a r h a r t , R. E., Tetrahedron (1976), 3 2 , 2513. 16. Varkony, T. H., C a r h a r t , R. E., and Smith, D. H . , i n "Computer-Assisted Organic S y n t h e s i s , " W. T. Wipke, E d . , T.

9.

CARHART E T A L .

Computer

Assistance for the Structural

Chemist

145

American Chemical Society, Washington, D. C. in press. 17. Smith, D. H., Buchanan, B. G., White, W. C., Feigenbaum, E. A., Lederberg, J., and Djerassi, C., Tetrahedron (1973), 29, 3117. 18. Buchanan, B. G., Smith, D. H., White, W. C., Gritter, R., Feigenbaum, E. A., Lederberg, J., and Djerassi, C., J. Amer. Chem. Soc. (1976),98,6168. 19. Smith, D. H., Buchanan, B. G., Engelmore, R. S., Adelcreutz, H., and Djerassi, C., J. Amer. Chem. Soc. (1973), 95, 6078.


Ac kn o wl ed gme n t We wish to thank the National Institutes of Health, (RR 00612 and GM 20832), and the National Aeronautics and Space Administration (NGR 05-020-004) for their support of this research; and for the NIH support of the SUMEX computer f a c i l i t y (RR 00785) on which the CONGEN program i s developed, maintained and made available to the nationwide community of users.

INDEX

Publication Date: June 1, 1977 | doi: 10.1021/bk-1977-0054.ix001

A A 2 a n d A 3 ions 22 A c e t o x y groups 11 12/?-Acetoxy sandaracopimar-15-en8j8,lL*-diol 12 Actinobolamine 103 Actinobolin 100 A c y c l i c amines 59 A c y c l i c saturated hydrocarbons 77 Adamantyl 5 A d d i t i v i t y parameters 78 ALACON 110 Alanine-aspartic acid-alanine 52 A l g o r i t h m for c o m p l e x p e p t i d e mixtures, interpretive 21,24 Algorithm, predictive 53 A l l o c a t o r , candidate structures a n d flask assignment b y 140 Amines 78 A m i n o a c i d sequence of p o l y p e p t i d e s 21 AMSOM 48 A n a l y s i s (es) of c o m p o u n d , consecutive 119 of complex mixtures, comprehensive system for the 19 PRIMARY 110 program, N M R spectrum 41 SECONDARY 115 A n a l y t i c a l programs 27 Androstane 73 A O C ( a l l o c a t i o n of carbons) 112 ASSINC 110 Aspartic acid-alanine, alanine52 A s p a r t i c a c i d pentapeptide 52

B B a t c h - t y p e search 29,31 Benzphenanthrene 5 Best-matching compounds and their M F 11.0 values 12 B e t a sheets 46 Bis (2-chloroethyl) ether 7 Butterfat m e t h y l ester 13

C C -benzene 3

13

C (Continued) NMR c h e m i c a l shift range of component 121 d a t a analysis, s u r v i v e d c o m ponents of c o m p o u n d 1 through 116 data of c o m p o u n d Ill rules, automatically a c q u i r e d 58 spectra, c o m p u t e r i z e d structural predictions f r o m 77 spectra, data base of 59 spectral data analysis, general feature 110 spectrum analysis p r o g r a m 41 search system, h y d r o c a r b o n - b a s e d .. 86 spectra w i t h k n o w n multiplicities 85 normal 84 w i t h u n o b s e r v e d quaternary carbons 86 Carbon(s) allocation of ( A O C ) 112,113 h a v i n g C c h e m i c a l shifts 83 C spectra w i t h u n o b s e r v e d quaternary 86 nuclear magnetic resonance ( C N M R ) spectral search system 31 rules, a l p h a 73 for each signal, n u m b e r of ( C N S ) .. 112 treated as one carbon, e q u i v a l e n t . . . . 88 Carbonyl 5 ESTERS 135 group 96 C a r b o x y l i c acids 93 CASE network 94 description of 92 -draw, program 103 Cembranolide 130 Chemical i n f o r m a t i o n system ( C I S ) , NIH-EPA 26 a d d i t i o n of components to 27,30 components of 29 computers facilities u s e d b y 28 shift range of component, C N M R 121 shift table 118

1 3

7

1 3

1 3

1 3

C

c h e m i c a l shifts, carbons h a v i n g

83


148

C H E M I C S : Computer program system for structure e l u c i d a t i o n of organic c o m p o u n d s 108 - F , b l o c k d i a g r a m of 109 C h e m i s t s , n a t u r a l products 92 Cineole 105 COMPARE 84 C o m p a t i b i l i t y table 6 Component(s) of c o m p l e x mixtures b y G C - M S , identification of the 18 of c o m p o u n d s 1 t h r o u g h C N M R d a t a analysis, s u r v i v e d 116 selective 117 sets 124 Computer assistance for the structural chemist 126 assisted structure e l u c i d a t i o n 93 using automatically acquired C N M R rules 58 f r o m C N M R spectra 77 f o r organic c o m p o u n d s (CHEMICS) 108 of u n k n o w n mass spectra 1 facilities used b y the C I S 28 representation of a reaction 138 C o n f i d e n c e index ( K ) 2 C o n f o r m a t i o n a l analysis of molecules i n solution 42 graph-matching routine 131 structure generator 127 C o n s t r a i n e d structure generator ( C O N G E N ) program 6, 7 3 , 1 2 7 Constraints 97 interpretation, p l a n n i n g v i a 127 of p a l u s t r o l 140 Coronafacic acid 105 Coronatine 105 Crystal d a t a r e t r i e v a l system, x-ray 32 file, C a m b r i d g e 33 literature r e t r i e v a l system, x-ray 40 C r y s t a l l o g r a p h i c search system, x-ray 32 Cyclohexane ring 96

D e c a l i n , trans D e c a l i n s w i t h trans r i n g fusions, sample rules constructed f r o m .... D e h y d r a t i o n products of p a l u s t r o l D e h y d r o t r y p t o p h a n derivative 3,4-Dichlorofuran D i f f r a c t i o n r e t r i e v a l p r o g r a m , x-ray powder 3,4-Dimethyl-4-ethylheptane 3,3-Dimethylhexane D i s k - s t o r e d data bases

73 74 140 133 35 34 81 64 27


1 3

E EDITREACT E m p i r i c a l rule formation E P A c h e m i c a l i n f o r m a t i o n system (CIS), N I H E q u a t i o n s , simultaneous linear Evaluation

134,136 60 26 117 142

1 3

F

1 3

D Data analysis, general feature of C spectral analysis, s u r v i v e d components of compounds 1 through C N M R base of C N M R spectra bases, disk-stored classes u s e d i n S T I R S , mass spectral INPUT processing 1 3

1 3

1 3

110 116 59 27 4 110 19

F a l s e positives ( F P ) F a t t y a c i d esters F l a s k assignment b y allocator F l a s k assignment of p a l u s t r o l FORTRAN F r a g m e n t p r o b e i n substrcuture search system F u n c t i o n a l groups, extension of h y d r o c a r b o n scheme to cover

2 11 140 140 78 36 89

G G C - M S , i d e n t i f i c a t i o n of the c o m ponents of complex mixtures b y .. 18 G C - M S systems configuration, basic .. 20 G l o b u l a r proteins, secondary structure of 46 G l y c e r y l tridodecanoate 15 G O O D L I S T interpretation 128 G O O D L I S T i t e m , construction of 130 G r a p h - m a t c h i n g routine, C O N G E N .. 131

H H a l f - o r d e r theory 141 r a n k i n g of mono-ketoandrostanes based o n the 143 Helices, alpha 46 Heuristics 69,126 Homologs, informational 124 Hydrocarbon(s) a c y c l i c saturated 77 based C search system 86 identified b y p r o g r a m M A T C H 89 scheme to cover f u n c t i o n a l groups, extension of 89 1 3

149

INDEX

M a t h e m a t i c a l m o d e l i n g system (MLAB) 41 MAXIMUM-RANGE 60 m/e values 21,142 M e t a - D E N D R A L program 63 Methine group 98 I M e t h y l ester, butterfat 13 IDENT 38 3-Methyl-4-ethylheptane 81 I n f o r m a t i o n theoretical a p p r o a c h to M e t h y l 10-methylnonadecanoate 14 the determination of secondary M e t h y l 3-oxonoadecanoate 15 M e t h y l 3,7-11,15-tetramethyl structure of g l o b u l a r proteins 46 hexadecanoic a c i d 11 I n f o r m a t i o n a l homologs 124 10-Methyl-trans-decalin 73 Interactive computing 26 M e t h y l e n e g r o u p 98 searches 2 9 , 3 1 M F 11.0 values i n S T I R S examination 12 MINIMUM-EXAMPLES 60 structure e l u c i d a t i o n 92 Interpretive a n d r e t r i e v a l system, Mixtures self-training ( S T I R S ) 1,3 analysis of complex ... 19 b y G C - M S , identification of the Ion components of c o m p l e x 18 A2 22 interpretive a l g o r i t h m for complex A3 22 Zl 22 peptide 21 I S O M E R ... ..... .79,80 M o l e c u l a r w e i g h t search i n C a m b r i d g e crystal file 33 Isomers, geometrical 79 M o l e c u l e assembler 96, 97 Isomers h a v i n g potentially n o n e q u i v a lent spectra, n u m b e r of 90 M o l e c u l e s i n solution, c o n f o r m a t i o n a l Isotopic l a b e l i n c o r p o r a t i o n deteranalysis of 42 mination ( L A B D E T ) 42 M o n e l l i n 21 Mono-ketoandrostanes 143 M o n o t e r p e n e f r o m a sea hare, K halogenated 99 K (confidence i n d e x ) 2 MREACT 136 MSPRED 132,139


H y d r o x y steroids w i t h trans r i n g fusions 1-Hydroxyethyl group H y d r o x y l groups

74 96 11

L L A B D E T (isotopic l a b e l i n c o r p o r a t i o n determination) L i t e r a t u r e retrieval system, x-ray L i t e r a t u r e search system, mass spectrometry

N 42 38

M

M a n u a l structure e l u c i d a t i o n Mass spectra, computer-assisted structure identification of u n k n o w n spectral data classes used i n S T I R S spectral search system ( M S S S ) 29, spectrometry literature search system s p e c t r u m of n - p r o p y l p - h y d r o x y benzoate MATCH flowchart for p r o g r a m hydrocarbons identified b y p r o g r a m M a t c h factor ( M F ) M a t c h i n g system ( P B M ) , retrieval p r o b a b i l i t y based

N a t u r a l products chemists Networked machine N I H - E P A chemical information system ( C I S ) NMDR N M R , C (see C NMR) N u c l e a r Overhauser effect ( N O E ) 1 3

94

92 28 26 110

1 3

.85,112

O 1 4 30 38 9 86 87 89 3 1

O r g a n i c compounds, structure e l u c i d a t i o n of O v e r l a p process Oxazole

108 72 5

P Palustrol Paraffins Parameter a p p r o a c h P B M system (retrieval p r o b a b i l i t y based m a t c h i n g )

140 59 58 1



150

P B M system (Continued) e x a m i n a t i o n of u n k n o w n spectra of fatty a c i d esters 11 p r a c t i c a l use of 16 results o n u n k n o w n a n d r e s i d u a l spectra 9 s p e c t r u m subtraction 7 PEAK 95,105 Peak search i n M S S S 30 Peptide(s) approximations to the structure of the proteins, t h i r d - o r d e r 46 interpretive a l g o r i t h m 24 mixtures, interpretive a l g o r i t h m for complex 21 nth-order 49 Periodate 95 Phenyl 3 P l a n n i n g v i a constraint interpretation 127 P o l y a m i n o a l c o h o l derivative of a tetrapeptide, trimethylsilylated 23 P o l y p e p t i d e s , a m i n o a c i d sequence of 21 Precision 53-55 P r o b a b i l i t y based m a t c h i n g system, r e t r i e v a l (see P B M ) Probability weighting 1 P r o p y l ester 10 n - P r o p y l p-hydroxybenzoate 9 P r o t e i n sequence data tape 76 48 Proteins, secondary structure of globular 46 P r o t o n affinity retrieval p r o g r a m 41 PRUNE 132,136

R REACT 132,134,136 Recall ( R C ) 2,53-55 R e d u c t i o n of table entry of a l a n i n e aspartic a c i d - a l a n i n e 52 Reliability ( R L ) 2 Retention index 22 Retrieval p r o b a b i l i t y based m a t c h i n g system (see P B M ) p r o g r a m , p r o t o n affinity 41 p r o g r a m , x-ray p o w d e r d i f f r a c t i o n .. 34 system self-training 2 x-ray crystal data 32 x-ray crystal literature 40 Reverse search strategy 2 Ring cyclohexane 96 fusions, decalins a n d h y d r o x y steroids w i t h trans 74 p r o b e i n substructure search system 37 Rule(s) -based theory 143

Rule(s) (Continued) computer-assisted structure e l u c i d a t i o n u s i n g automatically acquired C N M R constructed f r o m decalins a n d h y d r o x y steroids w i t h trans r i n g fusions, sample form for structure e l u c i d a t i o n formation, empirical generation search seed 1 3

58

74 61 67 60 60 62 61

S Scan f u n c t i o n 19 Sea hare, halogenated monoterpene from a 99 Search (es) batch-type 29,31 i n C a m b r i d g e crystal file, space group a n d m o l e c u l a r w e i g h t .... 33 constructive substructure 128 heuristic 126 interactive 29, 31 rule 62 special properties 38 strategy, reverse 2 structure 67, 70 system c a r b o n nuclear m a g n e t i c resonance ( C N M R ) spectral 31 fragment p r o b e i n substructure .. 36 hydrocarbon-based C 86 mass spectrometry literature 38 ( M S S S ) mass spectral 29,30 ( S S S ) substructure 34 x-ray crystallographic 32 Seed r u l e 61 Selective components 117 Self-training interpretive a n d r e t r i e v a l system (see S T I R S ) SEPARATE 136 Sheets, b e t a 46 Shift ranges 60 of component, C N M R c h e m i c a l .. 121 Shift table, p r e p a r a t i o n of c h e m i c a l . . . . 118 Solution, c o n f o r m a t i o n a l analysis of molecules i n 42 Space g r o u p search i n C a m b r i d g e crystal file 33 S p e c i a l properties searches 38 Spectra of fatty a c i d esters, P B M / S T I R S examination of u n k n o w n 11 generation 81 a n d uniqueness tests 78 1 3

1 3

151

INDEX

Spectra

(Continued)


PBM results on unknown and residual 9 reconstruction of the 21 Spectrum predictions for 3,3-dimethylhexane, partial 64 simulator 95 subtraction, PBM 7 procedure 2 SPECGEN 81,82 Stereochemistry, handling 73 Steroids with trans ring fusions, hydroxy 74 STIRS (self-training interpretive and retrieval system) 1,3 examination of 12/?-acetoxy san-

Structure(s) (Continued) of the proteins, third-order peptide approximations to the 46 search 67,70 selection 63 results of 66 Substructure control 100 identification 3 search, constructive 128 search system (SSS) 34,36,37 Subtraction procedure, spectrum 2 Superatoms 128 SURVEY 132,133 Survived components of compounds 1 through C NMR data analysis .. 116 13

daracopimar-15-en-8/?,lla-diol 12 T examination of unknown spectra of Terminals, typewriter 29 fatty acid ester 11 Terpenes in STIRS, unknown 10 mass spectral data classes used in .. 4 practical use of PBM 16 Testing via PRUNE, SURVEY, REACT, and MSPRED 132 results for the mass spectrum of 132 n-propyl p-hydroxybenzoate .... 9 Tests, direct 134 results on a river water extract 7 Tests, indirect unknown terpene 10 Tetrapeptide, trimethylsilylated polyaminoalcohol derivative of a 23 Structural chemist, computer assistance for the 126 Tripeptide conformations, possible . . . 5 0 , 5 5 Typewriter terminals 29 information available for unknown cembranolide 130 U possibilities 133 predictions from C NMR spectra, Uniqueness tests 78, 81 computerized 77 Unsaturation, a,/?98 Structure(s) application of SURVEY to test 133 W assignment by allocator candidate .. 140 Water extract, STIRS results on a elucidation 67 river 7 interactive 92 manual 94 Water supply, unknown from the Philadelphia drinking 8 of organic compounds 108 3 rule form for 67 Wiswesser line notation (WLN) using automatically acquired C X NMR rules, computerassisted 58 X-ray generated from each set of crystal data retrieval system 32 compounds 121 crystal literature retrieval system .... 40 generation 79 crystallographic search system 32 generator, CONGEN 127 powder diffraction retrieval of globular proteins, secondary 46 program 34 identification of unknown mass o-Xylene 35 spectra, computer-assisted 1 information for a dehydroZ tryptophan derivative 133 22 partial 96 Z l ion 13

13

Computer-Assisted Structure Elucidation

Structure Elucidation by NMR in Organic Chemistry

Structure Elucidation by NMR in Organic Chemistry: A Practical Guide

Structure elucidation by NMR in organic chemistry: a practical guide

Structure Elucidation by NMR in Organic Chemistry: A Practical Guide

Structure Elucidation by NMR in Organic Chemistry: A Practical Guide

Classics in Spectroscopy Isolation and Structure Elucidation of Natural Products

Structure Elucidation by NMR in Organic Chemistry: A Practical Guide, Third Edition

Structure

Nuclear Structure

Nuclear Structure

Coal Structure

Structure Systems

Enzyme Structure

Protein Structure

Constituent Structure

Atomic Structure

The ritual process: structure and anti-structure

The ritual process: structure and anti-structure

Bonding Structure

HARMONIC STRUCTURE

Nuclear structure

Strategy = structure

Social Structure

Image Structure

Stellar Structure

Bond and Structure Models (Structure and Bonding)

Theories of Spiral Structure

Crystallography and Surface Structure

Germanic Kinship Structure

Atomic structure and periodicity

Computer-Assisted Structure Elucidation

Structure Elucidation by NMR in Organic Chemistry

Structure Elucidation by NMR in Organic Chemistry: A Practical Guide

Structure elucidation by NMR in organic chemistry: a practical guide

Structure Elucidation by NMR in Organic Chemistry: A Practical Guide

Structure Elucidation by NMR in Organic Chemistry: A Practical Guide

Classics in Spectroscopy Isolation and Structure Elucidation of Natural Products

Structure Elucidation by NMR in Organic Chemistry: A Practical Guide, Third Edition

Structure

Nuclear Structure

Nuclear Structure

Coal Structure

Structure Systems

Enzyme Structure

Protein Structure

Constituent Structure

Atomic Structure

The ritual process: structure and anti-structure

The ritual process: structure and anti-structure

Bonding Structure

HARMONIC STRUCTURE

Nuclear structure

Strategy = structure

Social Structure

Image Structure

Stellar Structure

Bond and Structure Models (Structure and Bonding)

Theories of Spiral Structure

Crystallography and Surface Structure

Germanic Kinship Structure

Atomic structure and periodicity

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