Radek Halfar, Jiří Damborský, Sérgio M. Marques, Jan Martinovič
{"title":"Moldina:一种快速准确的多配体同时对接搜索算法","authors":"Radek Halfar, Jiří Damborský, Sérgio M. Marques, Jan Martinovič","doi":"10.1186/s13321-025-01005-4","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":617,"journal":{"name":"Journal of Cheminformatics","volume":"17 1","pages":""},"PeriodicalIF":7.1000,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/s13321-025-01005-4","citationCount":"0","resultStr":"{\"title\":\"Moldina: a fast and accurate search algorithm for simultaneous docking of multiple ligands\",\"authors\":\"Radek Halfar, Jiří Damborský, Sérgio M. Marques, Jan Martinovič\",\"doi\":\"10.1186/s13321-025-01005-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":617,\"journal\":{\"name\":\"Journal of Cheminformatics\",\"volume\":\"17 1\",\"pages\":\"\"},\"PeriodicalIF\":7.1000,\"publicationDate\":\"2025-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/s13321-025-01005-4\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cheminformatics\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s13321-025-01005-4\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cheminformatics","FirstCategoryId":"92","ListUrlMain":"https://link.springer.com/article/10.1186/s13321-025-01005-4","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
摘要
蛋白质-配体对接是许多结构生物学应用中常用的计算方法。它通常包括一个受体和一个配体。然而,多个配体的对接在一些情况下是重要的,例如研究协同效应、底物和产物抑制或竞争结合。这可能是一个具有挑战性和计算要求很高的过程。通过将粒子群优化集成到已建立的AutoDock Vina框架中,我们提供了一个能够加速药物发现和计算酶学的强大工具。本文提出了基于AutoDock Vina的多配体分子对接算法Moldina (Multiple-Ligand Molecular Docking over AutoDock Vina)。通过对AutoDock Vina的全面测试,该算法在预测配体结合构象方面具有相当的准确性,同时显着减少了数百倍的计算时间。Moldina和基准数据可以在https://opencode.it4i.eu/permed/moldina-multiple-ligand-molecular-docking-over-autodock-vina和https://github.com/It4innovations/moldina-multiple-ligand-molecular-docking-over-autodock-vina上免费获得。这种高效和准确的性能使我们的算法成为研究人员进行基于片段的药物发现或高通量虚拟筛选的宝贵资产。
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.
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.