Central Research Laboratories, Kaken Pharmaceutical Co. Ltd. , 14, Shinomiya Minamikawara-cho, Yamashina, Kyoto 607-8042, Japan.
J Chem Inf Model. 2014 Jan 27;54(1):49-56. doi: 10.1021/ci400418c. Epub 2014 Jan 13.
This paper describes a similarity-driven simple evolutionary approach to producing candidate molecules of new drugs. The aim of the method is to explore the candidates that are structurally similar to the reference molecule and yet somewhat different in not only peripheral chains but also their scaffolds. The method employs a known active molecule of our interest as a reference molecule which is used to navigate a huge chemical space. The reference molecule is also used to obtain seed fragments. An initial set of individual structures is prepared with the seed fragments and additional fragments using several connection rules. The fragment library is preferably prepared from a collection of known molecules related to the target of the reference molecule. Every fragment of the library can be used for fragment-based mutation. All the fragments are categorized into three classes; rings, linkers, and side chains. New individuals are produced by the crossover and the fragment-based mutation with the fragment library. Computer experiments with our own fragment library prepared from GPCR SARfari verified the feasibility of our approach to drug discovery.
本文描述了一种基于相似性的简单进化方法,用于生成新药物的候选分子。该方法的目的是探索与参考分子在结构上相似但不仅在侧链而且在其支架上有所不同的候选分子。该方法使用我们感兴趣的已知活性分子作为参考分子,用于在巨大的化学空间中导航。参考分子也用于获得种子片段。使用几个连接规则,用种子片段和其他片段准备初始的一组个体结构。片段库最好从与参考分子的靶标相关的已知分子的集合中制备。库中的每个片段都可以用于基于片段的突变。所有片段都分为三类:环、接头和侧链。使用片段库通过交叉和基于片段的突变生成新个体。使用我们自己从 GPCR SARfari 制备的片段库进行计算机实验验证了我们的药物发现方法的可行性。