On the Efficiency of Local Search Methods for the Molecular Docking Problem

Authors:
Jorge Tavares;Salma Mesmoudi;El-Ghazali Talbi
Affiliations:
Massachusetts Institute of Technology, Cambridge, USA 02139;INRIA Lille - Nord Europe Research Centre, Villeneuve d'Ascq, France 59650;INRIA Lille - Nord Europe Research Centre, Villeneuve d'Ascq, France 59650
Venue:
EvoBIO '09 Proceedings of the 7th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Year:
2009

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Abstract

Evolutionary approaches to molecular docking typically hybridize with local search methods, more specifically, the Solis-Wet method. However, some studies indicated that local search methods might not be very helpful in the context of molecular docking. An evolutionary algorithm with proper genetic operators can perform equally well or even outperform hybrid evolutionary approaches. We show that this is dependent on the type of local search method. We also propose an evolutionary algorithm which uses the L-BFGS method as local search. Results demonstrate that this hybrid evolutionary outperforms previous approaches and is better suited to serve as a basis for evolutionary docking methods.