Artículo
Multi-objective ligand-protein docking with particle swarm optimizers
Autor/es | García Nieto, José Manuel
López Camacho, Esteban García Godoy, María Jesús Nebro, Antonio J. Aldana Montes, José F. |
Departamento | Universidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificial |
Fecha de publicación | 2019 |
Fecha de depósito | 2021-05-11 |
Publicado en |
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Resumen | In the last years, particle swarm optimizers have emerged as prominent search methods to solve the molecular docking problem. A new approach to address this problem consists in a multi-objective formulation, minimizing the ... In the last years, particle swarm optimizers have emerged as prominent search methods to solve the molecular docking problem. A new approach to address this problem consists in a multi-objective formulation, minimizing the intermolecular energy and the Root Mean Square Deviation (RMSD) between the atom coordinates of the co-crystallized and the predicted ligand conformations. In this paper, we analyze the performance of a set of multi-objective particle swarm optimization variants based on different archiving and leader selection strategies, in the scope of molecular docking. The conducted experiments involve a large set of 75 molecular instances from the Protein Data Bank database (PDB) characterized by different sizes of HIV-protease inhibitors. The main motivation is to provide molecular biologists with unbiased conclusions concerning which algorithmic variant should be used in drug discovery. Our study confirms that the multi-objective particle swarm algorithms SMPSOhv and MPSO/D show the best overall performance. An analysis of the resulting molecular ligand conformations, in terms of binding site and molecular interactions, is also performed to validate the solutions found, from a biological point of view. |
Agencias financiadoras | Ministerio de Ciencia e Innovación (MICIN). España Junta de Andalucía |
Identificador del proyecto | TIN2017-86049-R
TIN2014- 58304 P12-TIC-1519 |
Cita | García Nieto, J.M., López Camacho, E., García Godoy, M.J., Nebro, A.J. y Aldana Montes, J.F. (2019). Multi-objective ligand-protein docking with particle swarm optimizers. Swarm and Evolutionary Computation, 44 (February 2019), 439-452. |
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