A novel conformation optimization model and algorithm for structure-based drug design

被引:0
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作者
Ling Kang
Honglin Li
Xiaoyu Zhao
Hualiang Jiang
Xicheng Wang
机构
[1] Dalian University of Technology,Department of Computer Science and Engineering, School of Electronic and Information Engineering
[2] Dalian University of Technology,Department of Engineering Mechanics, State Key Laboratory of Structural Analysis for Industrial Equipment
[3] Shanghai Institute of Materia Medica,Drug Discovery and Design Center, State Key Laboratory of Drug Research
[4] Chinese Academy of Sciences,undefined
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关键词
Information entropy; Genetic algorithm; Molecular docking; Multi-scale optimization model; Residue groups;
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摘要
In this paper, we present a multi-scale optimization model and an entropy-based genetic algorithm for molecular docking. In this model, we introduce to the refined docking design a concept of residue groups based on induced-fit and adopt a combination of conformations in different scales. A new iteration scheme, in conjunction with multi-population evolution strategy, entropy-based searching technique with narrowing down space and the quasi-exact penalty function, is developed to address the optimization problem for molecular docking. A new docking program that accounts for protein flexibility has also been developed. The docking results indicate that the method can be efficiently employed in structure-based drug design.
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