Moldina: a fast and accurate search algorithm for simultaneous docking of multiple ligands

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 .

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Publication Details

Journal
Journal of Cheminformatics
Published
2025-04-28
DOI
https://doi.org/10.1186/s13321-025-01005-4
Citations
2
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
3.01

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article

Moldina: a fast and accurate search algorithm for simultaneous docking of multiple ligands

Sérgio M. Marques, Radek Halfar, Jiřı́ Damborský, Jan Martinovič
2 citations
Journal of Cheminformatics
Computational Drug Discovery Methods
3.01
article

Moldina: a fast and accurate search algorithm for simultaneous docking of multiple ligands

Sérgio M. Marques, Radek Halfar, Jiřı́ Damborský, Jan Martinovič
article en
2 citations

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 .

Journal of CheminformaticsVol. 17(1)
Masaryk University (CZ)
Technology Agency of the Czech Republic, European Commission, Ministerstvo Školství, Mládeže a Tělovýchovy, National Supercomputing Centre Singapore
Openalex Percentile: Top 9%
Computational Drug Discovery Methods
3.01
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