Comparison of Consensus Scoring Strategies for Evaluating Computational Models of Protein−Ligand Complexes

计算机科学 计算生物学 配体(生物化学) 人工智能 化学 生物 生物化学 受体
作者
Akifumi Oda,Keiichi Tsuchida,Tadakazu Takakura,Noriyuki Yamaotsu,Shuichi Hirono
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:46 (1): 380-391 被引量:165
标识
DOI:10.1021/ci050283k
摘要

Here, the comparisons of performance of nine consensus scoring strategies, in which multiple scoring functions were used simultaneously to evaluate candidate structures for a protein−ligand complex, in combination with nine scoring functions (FlexX score, GOLD score, PMF score, DOCK score, ChemScore, DrugScore, PLP, ScreenScore, and X-Score), were carried out. The systematic naming of consensus scoring strategies was also proposed. Our results demonstrate that choosing the most appropriate type of consensus score is essential for model selection in computational docking; although the vote-by-number strategy was an effective selection method, the number-by-number and rank-by-number strategies were more appropriate when computational tractability was taken into account. By incorporating these consensus scores into the FlexX program, reasonable complex models can be obtained more efficiently than those selected by independent FlexX scores. These strategies might also improve the scoring of other docking programs, and more-effective structure-based drug design should result from these improvements.
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