DockThor-VS: A Free Platform for Receptor-Ligand Virtual Screening.

Autor: Guedes IA; Laboratório Nacional de Computação Científica (LNCC), Avenida Getúlio Vargas, 333, Petrópolis CEP 25651-075, Brazil., Pereira da Silva MM; Laboratório Nacional de Computação Científica (LNCC), Avenida Getúlio Vargas, 333, Petrópolis CEP 25651-075, Brazil., Galheigo M; Laboratório Nacional de Computação Científica (LNCC), Avenida Getúlio Vargas, 333, Petrópolis CEP 25651-075, Brazil., Krempser E; Laboratório Nacional de Computação Científica (LNCC), Avenida Getúlio Vargas, 333, Petrópolis CEP 25651-075, Brazil., de Magalhães CS; Universidade Federal do Rio de Janeiro - Polo Xerém (UFRJ), Rod. Washington Luiz, 19.593, Duque de Caxias CEP 25240-005, Brazil., Correa Barbosa HJ; Laboratório Nacional de Computação Científica (LNCC), Avenida Getúlio Vargas, 333, Petrópolis CEP 25651-075, Brazil., Dardenne LE; Laboratório Nacional de Computação Científica (LNCC), Avenida Getúlio Vargas, 333, Petrópolis CEP 25651-075, Brazil. Electronic address: dardenne@lncc.br.
Jazyk: angličtina
Zdroj: Journal of molecular biology [J Mol Biol] 2024 Sep 01; Vol. 436 (17), pp. 168548. Date of Electronic Publication: 2024 Mar 20.
DOI: 10.1016/j.jmb.2024.168548
Abstrakt: The DockThor-VS platform (https://dockthor.lncc.br/v2/) is a free protein-ligand docking server conceptualized to facilitate and assist drug discovery projects to perform docking-based virtual screening experiments accurately and using high-performance computing. The DockThor docking engine is a grid-based method designed for flexible-ligand and rigid-receptor docking. It employs a multiple-solution genetic algorithm and the MMFF94S molecular force field scoring function for pose prediction. This engine was engineered to handle highly flexible ligands, such as peptides. Affinity prediction and ranking of protein-ligand complexes are performed with the linear empirical scoring function DockTScore. The main steps of the ligand and protein preparation are available on the DockThor Portal, making it possible to change the protonation states of the amino acid residues, and include cofactors as rigid entities. The user can also customize and visualize the main parameters of the grid box. The results of docking experiments are automatically clustered and ordered, providing users with a diverse array of meaningful binding modes. The platform DockThor-VS offers a user-friendly interface and powerful algorithms, enabling researchers to conduct virtual screening experiments efficiently and accurately. The DockThor Portal utilizes the computational strength of the Brazilian high-performance platform SDumont, further amplifying the efficiency and speed of docking experiments. Additionally, the web server facilitates and enhances virtual screening experiments by offering curated structures of potential targets and compound datasets, such as proteins related to COVID-19 and FDA-approved drugs for repurposing studies. In summary, DockThor-VS is a dynamic and evolving solution for docking-based virtual screening to be applied in drug discovery projects.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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