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Chemical information management in drug discovery: optimizing the computational and combinatorial chemistry interfaces.

作者信息

Oprea T I, Gottfries J, Sherbukhin V, Svensson P, Kühler T C

机构信息

Department of Medicinal Chemistry, AstraZeneca R&D Mölndal, S-431 83 Mölndal, Sweden.

出版信息

J Mol Graph Model. 2000 Aug-Oct;18(4-5):512-24, 541. doi: 10.1016/s1093-3263(00)00066-8.

DOI:10.1016/s1093-3263(00)00066-8
PMID:11143566
Abstract

Structure-property relationships, central to many of today's drug discovery strategies, are not straightforward to deal with when trying to predict drug efficacy, that is, the combined outcome of target affinity, pharmacodynamic behavior, pharmacokinetic properties, and metabolic fate. In this article, we discuss the handling of chemical property information in reagents-for-synthesis selection, enumeration, and virtual library construction. We describe the use of diversity assessment and/or experimental design in selection of compound-libraries-to-be-synthesized. Our overall objective was to identify good-quality drug candidates through reliable structure-activity relationship data, with the minimum number of compounds synthesized and tested. Chemical filters, property filters, scoring functions, and utilization of interactive visualization tools are discussed. The concept of chemical diversity and aspects of chemical space navigation employing a proprietary tool, Chemical Global Positioning System (ChemGPS), for mapping the drug-related chemical space are examined. Guidelines and workflow recommendations for the practicing medicinal chemist are proposed.

摘要

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