A novel conformation optimization model and algorithm for structure-based drug design |
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| Authors: | Ling Kang Honglin Li Xiaoyu Zhao Hualiang Jiang Xicheng Wang |
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| Affiliation: | (1) Department of Computer Science and Engineering, School of Electronic and Information Engineering, Dalian University of Technology, Dalian, 116023, China;(2) Department of Engineering Mechanics, State Key Laboratory of Structural Analysis for Industrial Equipment, Dalian University of Technology, Dalian, 116023, China;(3) Drug Discovery and Design Center, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China; |
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| Abstract: | 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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| Keywords: | Information entropy Genetic algorithm Molecular docking Multi-scale optimization model Residue groups |
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