Multi-objective Metaheuristics for a Flexible Ligand-Macromolecule Docking Problem in Computational Biology.

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.