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: Einter that relates to the ligand-receptor affinity, the Eintra 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.
CITATION STYLE
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 Studies in Computational Intelligence (Vol. 798, pp. 369–379). Springer Verlag. https://doi.org/10.1007/978-3-319-99626-4_32
Mendeley helps you to discover research relevant for your work.