Suppr超能文献

药物发现中的化学亚结构

Chemical substructures in drug discovery.

作者信息

Merlot Cédric, Domine Daniel, Cleva Christophe, Church Dennis J

机构信息

Serono Pharmaceutical Research Institute, 14, ch. des Aulx, 1228-Plan-les-Ouates, Geneva, Switzerland.

出版信息

Drug Discov Today. 2003 Jul 1;8(13):594-602. doi: 10.1016/s1359-6446(03)02740-5.

Abstract

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.

摘要

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。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验