Abstract
The problem of molecular docking focuses on minimizing the binding energy of a complex composed by a ligand and a receptor. In this paper, we propose a new approach based on the joint optimization of three conflicting objectives: \(E_{inter}\) that relates to the ligand-receptor affinity, the \(E_{intra}\) characterizing the ligand deformity and the RMSD score (Root Mean Square Deviation), which measures the difference of atomic distances between the co-crystallized ligand and the computed ligand. In order to deal with this multi-objective problem, three different metaheuristic solvers (SMPSO, MOEA/D and MPSO/D) are used to evolve a numerical representation of the ligand’s conformation. An experimental benchmark is designed to shed light on the comparative performance of these multi-objective heuristics, comprising a set of HIV-proteases/inhibitors complexes where flexibility was applied. The obtained results are promising, and pave the way towards embracing the proposed algorithms for practical multi-criteria in the docking problem.
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Acknowledgments
This work has been partially supported by the proyect grants TIN2014-58304 y TIN2017-86049-R (Ministerio de Economía, Industria y Competividad) and P12-TIC-1519 (Plan Andaluz de Investigación, Desarrollo e Innovación). Javier Del Ser would also like to thank the Basque Government for its support through the EMAITEK Funding Program.
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Camacho, E.L., García-Godoy, M.J., Del Ser, J., Nebro, A.J., Aldana-Montes, J.F. (2018). Multi-objective Metaheuristics for a Flexible Ligand-Macromolecule Docking Problem in Computational Biology. In: Del Ser, J., Osaba, E., Bilbao, M., Sanchez-Medina, J., Vecchio, M., Yang, XS. (eds) Intelligent Distributed Computing XII. IDC 2018. Studies in Computational Intelligence, vol 798. Springer, Cham. https://doi.org/10.1007/978-3-319-99626-4_32
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