Ruppert J, Welch W, Jain A N
Arris Pharmaceutical Corporation, South San Francisco, California 94080, USA.
Protein Sci. 1997 Mar;6(3):524-33. doi: 10.1002/pro.5560060302.
Molecular docking is a popular way to screen for novel drug compounds. The method involves aligning small molecules to a protein structure and estimating their binding affinity. To do this rapidly for tens of thousands of molecules requires an effective representation of the binding region of the target protein. This paper presents an algorithm for representing a protein's binding site in a way that is specifically suited to molecular docking applications. Initially the protein's surface is coated with a collection of molecular fragments that could potentially interact with the protein. Each fragment, or probe, serves as a potential alignment point for atoms in a ligand, and is scored to represent that probe's affinity for the protein. Probes are then clustered by accumulating their affinities, where high affinity clusters are identified as being the "stickiest" portions of the protein surface. The stickiest cluster is used as a computational binding "pocket" for docking. This method of site identification was tested on a number of ligand-protein complexes; in each case the pocket constructed by the algorithm coincided with the known ligand binding site. Successful docking experiments demonstrated the effectiveness of the probe representation.
分子对接是筛选新型药物化合物的一种常用方法。该方法包括将小分子与蛋白质结构进行比对，并估计它们的结合亲和力。要对数以万计的分子快速进行此操作，需要对靶蛋白的结合区域进行有效表示。本文提出了一种以特别适合分子对接应用的方式来表示蛋白质结合位点的算法。最初，蛋白质表面覆盖有一系列可能与蛋白质相互作用的分子片段。每个片段或探针都作为配体中原子的潜在比对点，并进行评分以表示该探针与蛋白质的亲和力。然后通过累积它们的亲和力对探针进行聚类，其中高亲和力聚类被识别为蛋白质表面“粘性”最强的部分。粘性最强的聚类用作对接的计算结合“口袋”。这种位点识别方法在多个配体 - 蛋白质复合物上进行了测试；在每种情况下，算法构建的口袋都与已知的配体结合位点重合。成功的对接实验证明了探针表示法的有效性。
