Sheridan Robert P, Kearsley Simon K
Dept of Molecular Systems, RY50SW-100 Merck Research Laboratories, Rahway, NJ 07065, USA.
Drug Discov Today. 2002 Sep 1;7(17):903-11. doi: 10.1016/s1359-6446(02)02411-x.
Computational tools to search chemical structure databases are essential to finding leads early in a drug discovery project. Similarity methods are among the most diverse and most useful. We will present some lessons we have gathered over many years experience with in-house methods on several therapeutic problems. The effectiveness of any similarity method can vary greatly from one biological activity to another in a way that is difficult to predict. Also, any two methods tend to select different subsets of actives from a database, so it is advisable to use several search methods where possible.
在药物发现项目的早期寻找先导化合物时,用于搜索化学结构数据库的计算工具至关重要。相似性方法是最多样化且最有用的方法之一。我们将介绍我们在多年内部方法处理多个治疗问题的经验中积累的一些经验教训。任何相似性方法的有效性在不同生物活性之间可能会有很大差异,且难以预测。此外,任意两种方法往往会从数据库中选择不同的活性化合物子集,因此在可能的情况下,建议使用多种搜索方法。