Radek Halfar, Jiří Damborský, Sérgio M. Marques, Jan Martinovič
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引用次数: 0
Abstract
Protein-ligand docking is a computational method routinely used in many structural biology applications. It usually involves one receptor and one ligand. The docking of multiple ligands, however, can be important in several situations, such as the study of synergistic effects, substrate and product inhibition, or competitive binding. This can be a challenging and computationally demanding process. By integrating Particle Swarm Optimization into the established AutoDock Vina framework, we provided a powerful tool capable of accelerating drug discovery, and computational enzymology. Here we present Moldina (Multiple-Ligand Molecular Docking over AutoDock Vina), a new algorithm built upon AutoDock Vina. Through comprehensive testing against AutoDock Vina, the algorithm exhibited comparable accuracy in predicting ligand binding conformations while significantly reducing the computational time up to several hundred times. Moldina and the benchmark data are freely available at https://opencode.it4i.eu/permed/moldina-multiple-ligand-molecular-docking-over-autodock-vina and https://github.com/It4innovations/moldina-multiple-ligand-molecular-docking-over-autodock-vina.
期刊介绍:
Journal of Cheminformatics is an open access journal publishing original peer-reviewed research in all aspects of cheminformatics and molecular modelling.
Coverage includes, but is not limited to:
chemical information systems, software and databases, and molecular modelling,
chemical structure representations and their use in structure, substructure, and similarity searching of chemical substance and chemical reaction databases,
computer and molecular graphics, computer-aided molecular design, expert systems, QSAR, and data mining techniques.