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Chapter 6 Support of Industry Information Needs Norman J. Santora

Downloaded by UNIV OF CALIFORNIA SAN DIEGO on July 15, 2016 | http://pubs.acs.org Publication Date: August 17, 1990 | doi: 10.1021/bk-1990-0436.ch006

SmithKline Beecham Pharmaceuticals, 709 Swedeland Road, King of Prussia, PA 19406 The Beilstein Online Database provides pharmaceutical chemists with a powerful tool to support their varied needs. This paper gives examples on the use of the database in assisting the medicinal chemist with a problem in drug design; the isolation chemist with the determination of the structure of a natural product; the chemical information chemist with a Markush search; and the organic chemist with a reaction search. The latter two examples demonstrate novel applications of the Lawson Number field code.

The examples make use of the variety and range-searching capabilities of the quantitative field codes available to the user of the Beilstein Online Database.

Medicinal Chemistry: Drug Design A medicinal chemist would like to do a pattern recognition study on antibiotic candidates related to penicillin G 1 :

ΟΥ

NH

\

s

CH

3

1 wherein,

CH,

ο7 Gl 8

Bond 6-8 is single or normal Bond 6-7 Is double or normal All bonds are Ring or Chain G1 « Ο or N, allowing for carboxylic acids, esters or amides

fJ097^156/90A>436-(X)80$06.00A) © 1990 American Chemical Society

Heller; The Beilstein Online Database ACS Symposium Series; American Chemical Society: Washington, DC, 1990.

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Pattern recognition, a branch of artificial intelligence, can be viewed as consisting of two techniques: 1.

Preprocessing technique: Intended to reduce the number of molecular descriptors in the data matrix; then, to separate the compounds into classes based upon the reduced number of molecular descriptors in the data matrix.


2.

Display technique: In which the results of the preprocessing technique are operated upon by a graphical program in order to discriminate between the classes revealed. The compounds obtained from this search of the Beilstein Online Database will provide a supervised learning set in which some of the compounds will be tagged with known classifications with regard to antibiotic activity, and the primary objective is to develop a rule which classifies them correctly; then, to apply the same rule to classify the remaining compounds whose antibiotic activities are unknown. Methodology. The method of choice for this pattern recognition study is that developed by Cammarata (!) to classify pressor agents. The compounds chosen are selected such that they will be superimposable upon the template 2 of atoms from penicillin G; wherein, the numbered atoms correspond to the atoms numbered in 1. All of the compounds obtained from a substructure search of 2, indicated as L1 in the Beilstein Online Database, will be superimposable upon 2; thereby, enabling the structural features at those atoms to be expressed in terms of molecular descriptor codings. The latter operation results in a template-feature data matrix.

Ο

2 Cammarata has emphasized that molecular descriptor codings should be used, such as molar refraction, which can be employed as a measure of isosterism and bioisosterism. The preprocessing technique chosen for this study is principle component analysis, in which the dimensionality of the template-feature data matrix is reduced. The principle component analysis determines the minimum number of molecular descriptor codings which will account for £ 80% of the variance in the data; thereby, allowing those molecular descriptor codings to represent the original template-feature data matrix. Classification is accomplished by using a modification of the Andrews (2) technique for plotting data of more than two dimensions, in which the molecular descriptors for each molecule are transformed into variables which reflect the variance in the data as determined by the preprocessing step. Search Of L1 In The Beilstein File A full substructure search of L1 gave 3,273 answers: L2

3273

S L1 SSS FULL

Restriction of L2 to records containing optical rotation information narrowed the answer set dramatically: L3

180

S L2 AND (ORP OR ORD)/FA


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THE BEILSTEIN ONLINE DATABASE wherein, ORP is the Optical Rotatory Power field code ORD is the Optical Rotation Dispersion field code FA is Field Availability field code

The final answer set of 41 structures was obtained by requiring optical activity similar to that of Penicillin G:


L4

41

S L3 AND (175-310/ORP OR 300-550/ORD)

The diversity of structures obtained for the pattern recognition study 3,4 demonstrates the potential of this pattern recognition technique in enabling intuitive extrapolations to be made from the results of the classifications obtained.

3 Isolation Chemistry: Identification Of A Natural Product Many compounds isolated from one species are structurally related to compounds isolated from another species; for instance, compounds isolated from marine species are often similar in structure to compounds isolated from plants. Isolation chemists can make use of the Beilstein File to maximize the information gleaned about the structure of the compound in question from its initially-determined spectral and physical properties; in particular, because of the INP search field: Isolation from Natural Product. A recent paper (3) described the use of single-crystal X-ray analysis to determine the structure 5 of an ethanol extract isolated from T. Purpurea, an Indian medicinal plant; however, the following example illustrates that the same information was available by making use of the earlier-determined physical and spectral properties of the compound: MF = C H 0 UVmax = 235 nm Recognized as having a chelated OH group from red color with concentrated sulfuric acid. 1 8

1 4

4

Beilstein File Search. Although the use of search terms for UVmax and anticipated, the initial search statement resulted in a single hit: L1 1

1 3

C NMR were

S C H 0 / M F AND INP/FA 1 8

1 4

4

wherein, MF is the Molecular Formula field code INP is the Isolated from Natural Product field code


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A display of L1 in the STR HIT format revealed a diketone 6 isolated (4) from Pongamia glabra in 1942:


6 It is apparent that the latter authors may have isolated the enol form of the compound, 5, since it was stated that the compound gave a ferric chloride color indicative of an enolic or phenolic hydroxy I group; however, that possibility was discounted since the compound doesn't undergo methylation or benzoylation reactions expected of such groups. Exact searches, in the Registry File, of compounds 5 and 6, showed that Chemical Abstracts Services considers both compounds to be unique. Chemical Information Specialist: Markush Search This example, as well as the next example, utilize the Lawson Number search term in place of structures. Chemical information specialists are often required to due exhaustive priority searches of Markush structures. This example illustrates the usefulness of the Lawson Number search term to represent the Markush structure. A search was requested for compounds represented by the Markush structure 7:

wherein, A is a 6-membered ring bearing a Ν atom such that the fused ring system becomes a benzoquinoline. R is C-j_3 alkyl, straight-chained or branched, and the ester group can be attached to any of the rings of the benzoquinoline system. Y is H, OH or OR'; wherein, R is C-alkyl, straight-chained or branched provided that the C-count of R + R' < 8. Rationale for Use of the Lawson Number. This Markush was considered too complex to be represented unambiguously in a strucural format for use in a substructure search; hence, it was decided to represent the Markush structure by a Lawson Number Range. Robert Badger, of Springer Verlag, had revealed that the Lawson Number was equal approximately to eight times the System Number; thereby, making it attractive to explore the possibility of using the the latter relationship to provide a way of emulating the similarity search mode of Molecular Design Limited's REACCS database


84

THE BEILSTEIN ONLINE DATABASE

Estimation of the Lawson Number Range of 7. The Beilstein Institute's SANDRA program provided the System Number Range, SNrange, by inputting many different structural permutations and combinations of the variable groups in 7. The highest value of the system number was 3346; whereas, the lowest value was 3268.


The Lawson Number Range, LNrange, equation was arrived at quite arbitrarily, after experimenting with correlations of system numbers of structures whose Lawson numbers were known. The study indicated that a broad similarity search would be possible, with confidence that the dictionary terms contemplated could reduce the initial large answer set to a reasonably sized final answer set. LNrange - (8.0 ± 0.3) χ SNrange » (7.7 χ 3268) - (8.3 x 3346) = 25164-27772 Selection of Dictionary Terms. Name segments and atom counts were chosen which would serve to restrict the anticipated large answer set resulting from the Lawson Number Range search. A. Name Segments 1. BENZO 2. QUINOLINE 3. ESTER 4. PHEN? wherein, (1) and (2) provide for a variable benzoquinoline. (4) provides for an ether linkage (phenyl) as well as OH (phenol) B. Atom Counts 1.1/N 2.1 < 0 < 4 3. 20 < C < 30 wherein, (3) is based on 7 ( R « C H ; Y « OH ) 3

Beilstein File Search. A search of the Lawson Number Range provided an answer set, L1, larger than 63,000; however, the addition of the selected name segments, L2, and atom counts resulted in a final answer set,L3, of 16 structures. L1

6333 125163 < LN < 27773

L2

25

L1 AND BENZO/CNS AND QUINOLINE/CNS AND ESTER/CNS AND PHEN7/CNS

L3

16

L2 AND 1/N AND 1 < Ο < 4 AND 20 < C < 30


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Results. The structures obtained support the use of this technique for carrying out inexpensive, non-structural Markush searches; since, 50 % of the structures matched the requirements of the Markush perfectly; 38 % of the structures are similar; and 12 % of the structures are thought-provoking, at least. Examples of the structures which match the Markush 8, are similar 9, and provoke thought 10 are shown:

10 Organic Chemistry: Reaction Search This example illustrates the use of the Lawson Number in place of the reaction product in the study of the Michael addition of aziridines to acrylamide, methyl acrylate or ethyl aery I ate.

wherein, X = NH , OCH , O C H C H 2

3

2

3

The use of a Lawson Number Range to represent a molecule provides the potential of performing similarity reaction searches. Similarity reaction searches can provide chemists with unexpected assistance in developing a scheme for carrying out an uncommon reaction. Investigations with using the Lawson Number Range in place of the traditional terms: molecular formula, compound name, structure or Beilstein Registry Number, proved that the Lawson Number Range could not be used in the same manner as described in the Beilstein Database Manual; therefore, it was decided to use dictionary terms along with the Lawson Number Range.


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THE BEILSTEIN ONLINE DATABASE


Beilstein File Search. A search of the Lawson Number Range gave more than 17,000 answers, L1, which were reduced to the final answer set, L2, by the restrictions imposed by the dictionary terms for the name segments selected previously. The use of the (S) operator in L2 was to assure that the combined terms would be in the name of a single chemical substance: L1

17631 S 23369 < LN < 25200

L2

10

S L1 AND (AZIRIDIN? (S) PROPION?)/CNS

Five of the ten structures, 11,12 and 13, were relevant to the requirements of the search request:

wherein, R = C H or C H C H 3

3

2

R

12 wherein, R » C H OR C H C H 3

3

13

2

Ο


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Conclusion


The Lawson Number Range was introduced as a viable representation of a similarity substructural unit, which emulates the REACCS similarity modes for substructure searching and reaction searching. It must be emphasized that the method of calculating the Lawson Number Range, introduced in this paper, is not to be regarded as being generally applicable; nevertheless, examples have illustrated their utility in performing Markush and reaction searches. Other examples have illustrated that the Beilstein Online File can aid medicinal chemists in drug design and isolation chemists in the identification of compounds isolated from natural products.

Literature Cited 1. Cammarata, Α.; Menon, G. K. J. Med. Chem. 1976, 19, 739-748. 2. Andrews, D. F. Biometrics 1972, 28, 125-136. 3. Parmar, V. S.; Rathore, J. S.; Jain, R.; Henderson, D. Α.; Malone, J. F. Phytochemistry 1989, 28, 591-593. 4. Rangaswami, S. Pr. Indian Acad. 1942, 15, 417-418. RECEIVED May 17, 1990


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