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基于结构的三维蛋白质文库虚拟筛选中的靶点排序:方法与问题

Ranking targets in structure-based virtual screening of three-dimensional protein libraries: methods and problems.

作者信息

Kellenberger Esther, Foata Nicolas, Rognan Didier

机构信息

Bioinformatics of the Drug, UMR 7175 CNRS-ULP (Université Louis Pasteur-Strasbourg I), F-67400 Illkirch, France.

出版信息

J Chem Inf Model. 2008 May;48(5):1014-25. doi: 10.1021/ci800023x. Epub 2008 Apr 16.

Abstract

Structure-based virtual screening is a promising tool to identify putative targets for a specific ligand. Instead of docking multiple ligands into a single protein cavity, a single ligand is docked in a collection of binding sites. In inverse screening, hits are in fact targets which have been prioritized within the pool of best ranked proteins. The target rate depends on specificity and promiscuity in protein-ligand interactions and, to a considerable extent, on the effectiveness of the scoring function, which still is the Achilles' heel of molecular docking. In the present retrospective study, virtual screening of the sc-PDB target library by GOLD docking was carried out for four compounds (biotin, 4-hydroxy-tamoxifen, 6-hydroxy-1,6-dihydropurine ribonucleoside, and methotrexate) of known sc-PDB targets and, several ranking protocols based on GOLD fitness score and topological molecular interaction fingerprint (IFP) comparison were evaluated. For the four investigated ligands, the fusion of GOLD fitness and two IFP scores allowed the recovery of most targets, including the rare proteins which are not readily suitable for statistical analysis, while significantly filtering out most false positive entries. The current survey suggests that selecting a small number of targets (<20) for experimental evaluation is achievable with a pure structure-based approach.

摘要

基于结构的虚拟筛选是一种很有前景的工具,可用于识别特定配体的潜在靶点。与将多个配体对接至单个蛋白质腔不同,这里是将单个配体对接至一系列结合位点。在反向筛选中,命中的实际上是在排名最靠前的蛋白质库中已被优先排序的靶点。靶点率取决于蛋白质 - 配体相互作用中的特异性和多配体选择性,并且在很大程度上取决于评分函数的有效性,而评分函数仍然是分子对接的致命弱点。在本回顾性研究中,通过GOLD对接对已知sc - PDB靶点的四种化合物(生物素、4 - 羟基他莫昔芬、6 - 羟基 - 1,6 - 二氢嘌呤核糖核苷和甲氨蝶呤)进行了sc - PDB靶点库的虚拟筛选,并评估了基于GOLD适应度评分和拓扑分子相互作用指纹(IFP)比较的几种排名方案。对于所研究的四种配体,GOLD适应度与两个IFP评分的融合能够找回大多数靶点,包括那些不易进行统计分析的稀有蛋白质,同时能显著滤除大多数假阳性条目。当前的调查表明,使用纯粹基于结构的方法可以选择少量靶点(<20个)进行实验评估。

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