Halgren Thomas A
Schrödinger, Inc., 120 West 45th Street, New York, New York 10036, USA.
J Chem Inf Model. 2009 Feb;49(2):377-89. doi: 10.1021/ci800324m.
Identification and characterization of binding sites is key in the process of structure-based drug design. In some cases there may not be any information about the binding site for a target of interest. In other cases, a putative binding site has been identified by computational or experimental means, but the druggability of the target is not known. Even when a site for a given target is known, it may be desirable to find additional sites whose targeting could produce a desired biological response. A new program, called SiteMap, is presented for identifying and analyzing binding sites and for predicting target druggability. In a large-scale validation, SiteMap correctly identifies the known binding site as the top-ranked site in 86% of the cases, with best results (>98%) coming for sites that bind ligands with subnanomolar affinity. In addition, a modified version of the score employed for binding-site identification allows SiteMap to accurately classify the druggability of proteins as measured by their ability to bind passively absorbed small molecules tightly. In characterizing binding sites, SiteMap provides quantitative and graphical information that can help guide efforts to critically assess virtual hits in a lead-discovery application or to modify ligand structure to enhance potency or improve physical properties in a lead-optimization context.
结合位点的识别与表征是基于结构的药物设计过程中的关键。在某些情况下，可能没有关于感兴趣靶点结合位点的任何信息。在其他情况下，通过计算或实验手段已确定了一个假定的结合位点，但靶点的可成药性未知。即使已知给定靶点的一个位点，也可能希望找到其他位点，靶向这些位点可能产生期望的生物学反应。本文介绍了一个名为SiteMap的新程序，用于识别和分析结合位点以及预测靶点的可成药性。在大规模验证中，SiteMap在86%的情况下能正确地将已知结合位点识别为排名最高的位点，对于以亚纳摩尔亲和力结合配体的位点，结果最佳（>98%）。此外，用于结合位点识别所采用分数的一个修改版本使SiteMap能够根据蛋白质紧密结合被动吸收小分子的能力准确地对蛋白质的可成药性进行分类。在表征结合位点时，SiteMap提供定量和图形信息，这有助于指导在先导物发现应用中严格评估虚拟命中物的工作，或在先导物优化背景下修改配体结构以提高效力或改善物理性质。
