文献类型：期刊文献

英文题名：An effective docking strategy for virtual screening based on multi-objective optimization algorithm

作者：Li, Honglin[1,2,3];Zhang, Hailei[4,5];Zheng, Mingyue[2];Luo, Jie[6];Kang, Ling[3];Liu, Xiaofeng[2];Wang, Xicheng[3];Jiang, Hualiang[1,2]

机构：[1]E China Univ Sci & Technol, Sch Pharm, Shanghai 200237, Peoples R China;[2]Chinese Acad Sci, Shanghai Inst Mat Med, State Key Lab Drug Res, Drug Discovery & Design Ctr, Shanghai 201203, Peoples R China;[3]Dalian Univ Technol, Dept Engn Mech, State Key Lab Struct Analyses Ind Equipment, Dalian 116023, Peoples R China;[4]Dana Farber Canc Inst, Dept Med Oncol, Boston, MA 02115 USA;[5]Harvard Univ, Sch Med, Boston, MA 02115 USA;[6]E China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China

年份：2009

卷号：10

外文期刊名：BMC BIOINFORMATICS

收录：;EI(收录号：20131116099833);WOS:【SCI-EXPANDED(收录号:WOS:000265603900001)】；

语种：英文

外文关键词：Binding sites - Binding energy

摘要：Background: Development of a fast and accurate scoring function in virtual screening remains a hot issue in current computer-aided drug research. Different scoring functions focus on diverse aspects of ligand binding, and no single scoring can satisfy the peculiarities of each target system. Therefore, the idea of a consensus score strategy was put forward. Integrating several scoring functions, consensus score re-assesses the docked conformations using a primary scoring function. However, it is not really robust and efficient from the perspective of optimization. Furthermore, to date, the majority of available methods are still based on single objective optimization design. Results: In this paper, two multi-objective optimization methods, called MOSFOM, were developed for virtual screening, which simultaneously consider both the energy score and the contact score. Results suggest that MOSFOM can effectively enhance enrichment and performance compared with a single score. For three different kinds of binding sites, MOSFOM displays an excellent ability to differentiate active compounds through energy and shape complementarity. EFMOGA performed particularly well in the top 2% of database for all three cases, whereas MOEA_Nrg and MOEA_Cnt performed better than the corresponding individual scoring functions if the appropriate type of binding site was selected. Conclusion: The multi-objective optimization method was successfully applied in virtual screening with two different scoring functions that can yield reasonable binding poses and can furthermore, be ranked with the potentially compromised conformations of each compound, abandoning those conformations that can not satisfy overall objective functions.