Sheridan R P, Singh S B, Fluder E M, Kearsley S K
Department of Molecular Systems, RY50SW-100 Merck Research Laboratories, P.O. Box 2000, Rahway, NJ 07065, USA.
J Chem Inf Comput Sci. 2001 Sep-Oct;41(5):1395-406. doi: 10.1021/ci0100144.
Similarity searches based on chemical descriptors have proven extremely useful in aiding large-scale drug screening. Typically an investigator starts with a "probe", a drug-like molecule with an interesting biological activity, and searches a database to find similar compounds. In some projects, however, the only known actives are peptides, and the investigator needs to identify drug-like actives. 3D similarity methods are able to help in this endeavor but suffer from the necessity of having to specify the active conformation of the probe, something that is not always possible at the beginning of a project. Also, 3D methods are slow and are complicated by the need to generate low-energy conformations. In contrast, topological methods are relatively rapid and do not depend on conformation. However, unmodified topological similarity methods, given a peptide probe, will preferentially select other peptides from a database. In this paper we show some simple protocols that, if used with a standard topological similarity search method, are sufficient to select nonpeptide actives given a peptide probe. We demonstrate these protocols by using 10 peptide-like probes to select appropriate nonpeptide actives from the MDDR database.
基于化学描述符的相似性搜索已被证明在大规模药物筛选中非常有用。通常，研究人员从一个“探针”开始，即一个具有有趣生物活性的类药物分子，并在数据库中搜索相似的化合物。然而，在一些项目中，唯一已知的活性物质是肽，研究人员需要识别类药物活性物质。三维相似性方法能够在这一工作中提供帮助，但存在必须指定探针活性构象的必要性，而这在项目开始时并非总是可行的。此外，三维方法速度较慢，并且由于需要生成低能量构象而变得复杂。相比之下，拓扑方法相对较快且不依赖于构象。然而，给定一个肽探针，未修改的拓扑相似性方法将优先从数据库中选择其他肽。在本文中，我们展示了一些简单的方案，如果与标准拓扑相似性搜索方法一起使用，足以在给定肽探针的情况下选择非肽活性物质。我们通过使用10个类肽探针从MDDR数据库中选择合适的非肽活性物质来证明这些方案。
