Merlot Cédric, Domine Daniel, Cleva Christophe, Church Dennis J
Serono Pharmaceutical Research Institute, 14, ch. des Aulx, 1228-Plan-les-Ouates, Geneva, Switzerland.
Drug Discov Today. 2003 Jul 1;8(13):594-602. doi: 10.1016/s1359-6446(03)02740-5.
The widespread use of HTS and combinatorial chemistry techniques has led to the generation of large amounts of pharmacological data, which, in turn, has catalyzed the development of computational methods designed to reduce the time and cost in identifying molecules suitable for pharmaceutical development. This review focuses on the use of substructure-based in silico techniques for lead discovery, an effective and increasingly popular approach for augmenting the chance of selecting drug-like compounds for preclinical and clinical development.
高通量筛选（HTS）和组合化学技术的广泛应用产生了大量药理学数据，这反过来又推动了计算方法的发展，这些方法旨在减少识别适合药物开发的分子所需的时间和成本。本综述重点关注基于子结构的计算机辅助技术在先导化合物发现中的应用，这是一种有效且越来越受欢迎的方法，可增加为临床前和临床开发选择类药物化合物的机会。
