Comparative Assessment of Scoring Functions on an Updated Benchmark: 2. Evaluation Methods and General Results

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• 作者：Yan Li ; Li Han ; Zhihai Liu ; Renxiao Wang
• 刊名：Journal of Chemical Information and Modeling
• 出版年：2014
• 出版时间：June 23, 2014
• 年：2014
• 卷：54
• 期：6
• 页码：1717-1736
• 全文大小：718K
• ISSN：1549-960X

文摘

Our comparative assessment of scoring functions (CASF) benchmark is created to provide an objective evaluation of current scoring functions. The key idea of CASF is to compare the general performance of scoring functions on a diverse set of protein鈥搇igand complexes. In order to avoid testing scoring functions in the context of molecular docking, the scoring process is separated from the docking (or sampling) process by using ensembles of ligand binding poses that are generated in prior. Here, we describe the technical methods and evaluation results of the latest CASF-2013 study. The PDBbind core set (version 2013) was employed as the primary test set in this study, which consists of 195 protein鈥搇igand complexes with high-quality three-dimensional structures and reliable binding constants. A panel of 20 scoring functions, most of which are implemented in main-stream commercial software, were evaluated in terms of 鈥渟coring power鈥?(binding affinity prediction), 鈥渞anking power鈥?(relative ranking prediction), 鈥渄ocking power鈥?(binding pose prediction), and 鈥渟creening power鈥?(discrimination of true binders from random molecules). Our results reveal that the performance of these scoring functions is generally more promising in the docking/screening power tests than in the scoring/ranking power tests. Top-ranked scoring functions in the scoring power test, such as X-Score^HM, ChemScore@SYBYL, ChemPLP@GOLD, and PLP@DS, are also top-ranked in the ranking power test. Top-ranked scoring functions in the docking power test, such as ChemPLP@GOLD, Chemscore@GOLD, GlidScore-SP, LigScore@DS, and PLP@DS, are also top-ranked in the screening power test. Our results obtained on the entire test set and its subsets suggest that the real challenge in protein鈥搇igand binding affinity prediction lies in polar interactions and associated desolvation effect. Nonadditive features observed among high-affinity protein鈥搇igand complexes also need attention.