Lopez-Camacho, EstebanJesus Garcia-Godoy, MariaGarcia-Nieto, JoseNebro, Antonio J.Aldana-Montes, Jose F.2023-02-122023-02-122020-07-011432-7643http://hdl.handle.net/10668/18635Finding the orientation of a ligand (small molecule) with the lowest binding energy to the macromolecule (receptor) is a complex optimization problem, commonly called ligand-protein docking. This problem has been usually approached by minimizing a single objective that corresponds to the final free energy of binding. In this work, we propose a new multi-objective strategy focused on minimizing: (1) the root mean square deviation (RMSD) between the co-crystallized and predicted ligand atomic coordinates, and (2) the ligand-receptor intermolecular energy. This multi-objective strategy provides the molecular biologists with a range of solutions computing different RMSD scores and intermolecular energies. A set of representative multi-objective algorithms, namely NSGA-II, SMPSO, GDE3 and MOEA/D, have been evaluated in the scope of an extensive set of docking problems, which are featured by including HIV-proteases with flexible ARG8 side chains and their inhibitors. As use cases for biological validation, we have included a set of instances based on new retroviral inhibitors to HIV-proteases. The proposed multi-objective approach shows that the predictions of ligand's pose can be promising in cases in which studiesin silicoare necessary to test new candidate drugs (or analogue drugs) to a given therapeutic target.enAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Molecular dockingMulti-objective optimizationMetaheuristicsHiv-1 proteaseMolecular dockingWild-typeInhibitionAlgorithmAccuracyresearch articleopen access10.1007/s00500-019-04575-21433-7479https://idus.us.es/bitstream/11441/108857/1/Optimizing%20ligand%20conformations.pdf540633700035