Web of Science: 2 cites, Scopus: 3 cites, Google Scholar: cites,
Gpathfinder : Identification of ligand-binding pathways by a multi-objective genetic algorithm
Sánchez-Aparicio, J.E (Universitat Autònoma de Barcelona. Departament de Química)
Sciortino, Giuseppe (Universitat Autònoma de Barcelona. Departament de Química)
Viladrich Herrmannsdoerfer, Daniel (Universitat Autònoma de Barcelona. Departament de Química)
Orenes Chueca, Pablo (Universitat Autònoma de Barcelona. Departament de Química)
Rodríguez-Guerra Pedregal, Jaime (Universitat Autònoma de Barcelona. Departament de Química)
Maréchal, Jean-Didier (Universitat Autònoma de Barcelona. Departament de Química)

Data: 2019
Resum: Protein-ligand docking is a widely used method to generate solutions for the binding of a small molecule with its target in a short amount of time. However, these methods provide identification of physically sound protein-ligand complexes without a complete view of the binding process dynamics, which has been recognized to be a major discriminant in binding affinity and ligand selectivity. In this paper, a novel piece of open-source software to approach this problem is presented, called GPathFinder. It is built as an extension of the modular GaudiMM platform and is able to simulate ligand diffusion pathways at atomistic level. The method has been benchmarked on a set of 20 systems whose ligand-binding routes were studied by other computational tools or suggested from experimental "snapshots". In all of this set, GPathFinder identifies those channels that were already reported in the literature. Interestingly, the low-energy pathways in some cases indicate novel possible binding routes. To show the usefulness of GPathFinder, the analysis of three case systems is reported. We believe that GPathFinder is a software solution with a good balance between accuracy and computational cost, and represents a step forward in extending protein-ligand docking capacities, with implications in several fields such as drug or enzyme design.
Ajuts: AGAUR/2017/SGR-1323
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Llengua: Anglès
Document: Article ; recerca ; Versió publicada
Matèria: Multi-objective genetic algorithm ; Molecular modeling ; Ligand diffusion ; Computational chemistry ; Molecular docking ; Drug design
Publicat a: International journal of molecular sciences, Vol. 20, Issue 13 (July 2019) , art. 3155, ISSN 1422-0067

DOI: 10.3390/ijms20133155
PMID: 31261636

18 p, 3.9 MB

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