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Sci Rep ; 14(1): 10904, 2024 05 13.
Artigo em Inglês | MEDLINE | ID: mdl-38740859

RESUMO

Tuberculosis (TB), caused by Mycobacterium tuberculosis, ranks among the top causes of global human mortality, as reported by the World Health Organization's 2022 TB report. The prevalence of M. tuberculosis strains that are multiple and extensive-drug resistant represents a significant barrier to TB eradication. Fortunately, having many completely sequenced M. tuberculosis genomes available has made it possible to investigate the species pangenome, conduct a pan-phylogenetic investigation, and find potential new drug targets. The 442 complete genome dataset was used to estimate the pangenome of M. tuberculosis. This study involved phylogenomic classification and in-depth analyses. Sequential filters were applied to the conserved core genome containing 2754 proteins. These filters assessed non-human homology, virulence, essentiality, physiochemical properties, and pathway analysis. Through these intensive filtering approaches, promising broad-spectrum therapeutic targets were identified. These targets were docked with FDA-approved compounds readily available on the ZINC database. Selected highly ranked ligands with inhibitory potential include dihydroergotamine and abiraterone acetate. The effectiveness of the ligands has been supported by molecular dynamics simulation of the ligand-protein complexes, instilling optimism that the identified lead compounds may serve as a robust basis for the development of safe and efficient drugs for TB treatment, subject to further lead optimization and subsequent experimental validation.


Assuntos
Antituberculosos , Desenho de Fármacos , Mycobacterium tuberculosis , Proteômica , Tuberculose , Mycobacterium tuberculosis/efeitos dos fármacos , Mycobacterium tuberculosis/genética , Mycobacterium tuberculosis/metabolismo , Antituberculosos/farmacologia , Humanos , Tuberculose/tratamento farmacológico , Tuberculose/microbiologia , Proteômica/métodos , Genoma Bacteriano , Proteínas de Bactérias/genética , Proteínas de Bactérias/metabolismo , Filogenia , Simulação de Acoplamento Molecular , Simulação de Dinâmica Molecular , Genômica/métodos
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