dc.creator | López Camacho, Esteban | es |
dc.creator | García Godoy, María Jesús | es |
dc.creator | García Nieto, José Manuel | es |
dc.creator | Nebro, Antonio J. | es |
dc.creator | Aldana Montes, José F. | es |
dc.date.accessioned | 2021-05-11T11:36:30Z | |
dc.date.available | 2021-05-11T11:36:30Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | López Camacho, E., García Godoy, M.J., García Nieto, J.M., Nebro, A.J. y Aldana Montes, J.F. (2020). Optimizing ligand conformations in flexible protein targets: amulti-objective strategy. Soft Computing, 24 (July 2020), 10705-10719. | |
dc.identifier.issn | 1432-7643 | es |
dc.identifier.uri | https://hdl.handle.net/11441/108857 | |
dc.description.abstract | Finding 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 multiobjective
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 studies in silico are necessary to test new candidate drugs (or analogue drugs) to a given
therapeutic target. | es |
dc.description.sponsorship | Ministerio de Educación y Ciencia TIN2017-86049-R | es |
dc.format | application/pdf | es |
dc.format.extent | 15 | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.relation.ispartof | Soft Computing, 24 (July 2020), 10705-10719. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Molecular Docking | es |
dc.subject | Multi-objective optimization | es |
dc.subject | Metaheuristics | es |
dc.title | Optimizing ligand conformations in flexible protein targets: amulti-objective strategy | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial | es |
dc.relation.projectID | TIN2017-86049-R | es |
dc.relation.publisherversion | https://link.springer.com/article/10.1007/s00500-019-04575-2 | es |
dc.identifier.doi | 10.1007/s00500-019-04575-2 | es |
dc.journaltitle | Soft Computing | es |
dc.publication.volumen | 24 | es |
dc.publication.issue | July 2020 | es |
dc.publication.initialPage | 10705 | es |
dc.publication.endPage | 10719 | es |
dc.contributor.funder | Ministerio de Educación y Ciencia (MEC). España | es |