A New Multi-objective Approach for Molecular Docking Based on RMSD and Binding Energy

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• 关键词：Molecular docking ; Multi ; objective optimization ; Nature inspired metaheuristics ; Algorithm comparison
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9702
• 期：1
• 页码：65-77
• 全文大小：649 KB
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  11.López-Camacho, E., García-Godoy, M.J., García-Nieto, J., Nebro, A.J., Aldana-Montes, J.F.: Solving molecular flexible docking problems with metaheuristics: a comparative study. Appl. Soft Comput. 28, 379–393 (2015)CrossRef
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  13.Nebro, A.J., Durillo, J.J., Garcia-Nieto, J., Coello Coello, C.A., Luna, F., Alba, E.: SMPSO: a new PSO-based metaheuristic for multi-objective optimization. In: IEEE Symposium on Computational Intelligence in Multi-criteria Decision-Making, pp. 66–73, March 2009
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• 作者单位：Esteban López-Camacho (17)
  María Jesús García-Godoy (17)
  José García-Nieto (17)
  Antonio J. Nebro (17)
  José F. Aldana-Montes (17)
  
  17. Khaos Research Group, Department of Computer Science, University of Málaga, ETSI Informática, Campus de Teatinos, 29071, Málaga, Spain
  
• 丛书名：Algorithms for Computational Biology
• ISBN：978-3-319-38827-4
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9702

文摘

Ligand-protein docking is an optimization problem based on predicting the position of a ligand with the lowest binding energy in the active site of the receptor. Molecular docking problems are traditionally tackled with single-objective, as well as with multi-objective approaches, to minimize the binding energy. In this paper, we propose a novel multi-objective formulation that considers: the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands and the binding (intermolecular) energy, as two objectives to evaluate the quality of the ligand-protein interactions. To determine the kind of Pareto front approximations that can be obtained, we have selected a set of representative multi-objective algorithms such as NSGA-II, SMPSO, GDE3, and MOEA/D. Their performances have been assessed by applying two main quality indicators intended to measure convergence and diversity of the fronts. In addition, a comparison with LGA, a reference single-objective evolutionary algorithm for molecular docking (AutoDock) is carried out. In general, SMPSO shows the best overall results in terms of energy and RMSD (value lower than 2Å for successful docking results). This new multi-objective approach shows an improvement over the ligand-protein docking predictions that could be promising in in silico docking studies to select new anticancer compounds for therapeutic targets that are multidrug resistant.