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The influence of mutation on protein-ligand docking optimization: a locality analysis

Jorge Tavares 1 Alexandru-Adrian Tantar 2 Nouredine Melab El-Ghazali Talbi 1, 3 
1 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
2 ALEA - Advanced Learning Evolutionary Algorithms
Inria Bordeaux - Sud-Ouest, UB - Université de Bordeaux, CNRS - Centre National de la Recherche Scientifique : UMR5251
Abstract : Evolutionary approaches to protein-ligand docking typically use a real-value encoding and mutation operators based on Gaussian and Cauchy distributions. The choice of mutation is important for an efficient algorithm for this problem.We investigate the effect of mutation operators by locality analysis. High locality means that small variations in the genotype imply small variations in the phenotype. Results show that Gaussian-based operators have stronger locality than Cauchy-based ones, especially if an annealing scheme is used to control the variance.
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Submitted on : Monday, April 23, 2012 - 12:22:55 PM
Last modification on : Thursday, January 20, 2022 - 5:27:52 PM

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Jorge Tavares, Alexandru-Adrian Tantar, Nouredine Melab, El-Ghazali Talbi. The influence of mutation on protein-ligand docking optimization: a locality analysis. PPSN 2008 : 10th International Conference on Parallel Problem Solving From Nature, Sep 2008, Dortmund, Germany. pp.589-598, ⟨10.1007/978-3-540-87700-4_59⟩. ⟨hal-00690373⟩



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