Langer Thierry, Krovat Eva Maria
Leopold-Franzens University of Innsbruck, Institute of Pharmacy, Computer Aided Molecular Design Group, Innrain 52, A-6020 Innsbruck, Austria.
Curr Opin Drug Discov Devel. 2003 May;6(3):370-6.
During the past years, efforts in the pharmaceutical industry have focused on optimizing the early phase hit-to-lead development of the drug discovery process. In silico-based high-throughput screening (HTS) approaches emerged, with a number of issues arising, such as the need for efficient search algorithms, library design, diversity, drug- and/or lead-likeness. These problems were addressed in numerous publications. This review focuses on the generation and use of virtual compound libraries, and on studies in which chemical feature-based pharmacophore models are used in combination with in silico screening. These procedures are generally used to obtain hits (or leads) that are more likely to give successful clinical candidates.
在过去几年中，制药行业的工作重点是优化药物发现过程中从早期命中物到先导物的开发。基于计算机的高通量筛选（HTS）方法应运而生，随之出现了许多问题，例如需要高效的搜索算法、库设计、多样性、药物和/或类先导物性质。众多出版物都探讨了这些问题。本综述聚焦于虚拟化合物库的生成与应用，以及基于化学特征的药效团模型与计算机筛选相结合的研究。这些方法通常用于获得更有可能成为成功临床候选药物的命中物（或先导物）。
