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Molecules 2016, 21(11), 1575; doi:10.3390/molecules21111575

Molecular Docking Optimization in the Context of Multi-Drug Resistant and Sensitive EGFR Mutants

Khaos Research Group, Departament of Computer Sciences, University of Málaga (UMA), ETSI Informática, Campus de Teatinos, 29071 Málaga, Spain
The authors contributed equally to this manuscript.
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Academic Editors: Rino Ragno and Derek J. Mcphee
Received: 26 September 2016 / Revised: 13 November 2016 / Accepted: 15 November 2016 / Published: 19 November 2016
(This article belongs to the Collection Molecular Docking)
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Abstract

The human Epidermal Growth Factor (EGFR) plays an important role in signaling pathways, such as cell proliferation and migration. Mutations like G719S, L858R, T790M, G719S/T790M or T790M/L858R can alter its conformation, and, therefore, drug responses from lung cancer patients. In this context, candidate drugs are being tested and in silico studies are necessary to know how these mutations affect the ligand binding site. This problem can be tackled by using a multi-objective approach applied to the molecular docking problem. According to the literature, few studies are related to the application of multi-objective approaches by minimizing two or more objectives in drug discovery. In this study, we have used four algorithms (NSGA-II, GDE3, SMPSO and MOEA/D) to minimize two objectives: the ligand–receptor intermolecular energy and the RMSD score. We have prepared a set of instances that includes the wild-type EGFR kinase domain and the same receptor with somatic mutations, and then we assessed the performance of the algorithms by applying a quality indicator to evaluate the convergence and diversity of the reference fronts. The MOEA/D algorithm yields the best solutions to these docking problems. The obtained solutions were analyzed, showing promising results to predict candidate EGFR inhibitors by using this multi-objective approach. View Full-Text
Keywords: molecular docking; metaheuristics; multi-objective optimization; drug resistance; epidermal growth factor; Epidermal Growth Factor Receptor; Epidermal Growth Factor Receptor mutants molecular docking; metaheuristics; multi-objective optimization; drug resistance; epidermal growth factor; Epidermal Growth Factor Receptor; Epidermal Growth Factor Receptor mutants
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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García-Godoy, M.J.; López-Camacho, E.; García-Nieto, J.; Nebro, A.J.; Aldana-Montes, J.F. Molecular Docking Optimization in the Context of Multi-Drug Resistant and Sensitive EGFR Mutants. Molecules 2016, 21, 1575.

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