Literature DB >> 35624324

In silico and in vitro study of Mycobacterium tuberculosis H37Rv uncharacterized protein (RipD): an insight on tuberculosis therapeutics.

Aregitu Mekuriaw Arega1,2, Ajit Kumar Dhal1, Sasmita Nayak1, Rajani Kanta Mahapatra3.   

Abstract

Tuberculosis caused by Mycobacterium tuberculosis (Mtb) is responsible for the highest global health problem, with the deaths of millions of people. With prevalence of multiple drug resistance (MDR) strains and extended therapeutic times, it is important to discover small molecule inhibitors against novel hypothetical proteins of the pathogen. In this study, a virtual screening protocol was carried out against MtbH37Rv hypothetical protein RipD (Rv1566c) for the identification of potential small molecule inhibitors. The 3D model of the protein structure binding site was used for virtual screening (VS) of inhibitors from the Pathogen Box, followed by its validation through a molecular docking study. The stability of the protein-ligand complex was assessed using a 150 ns molecular dynamics simulation. MM-PBSA and MM-GBSA are the two approaches that were used to perform the trajectory analysis and determine the binding free energies, respectively. The ligand binding was observed to be stable across the entire time frame with an approximate binding free energy of -22.9916 kcal/mol. The drug-likeness of the inhibitors along with a potential anti-tuberculosis compound was validated by ADMET prediction software. Furthermore, a CFU inhibition assay was used to validate the best hit compound's in vitro inhibitory efficacy against a non-pathogenic Mycobacterium smegmatis MC2155 under low nutrient culture conditions. The study reported that the compound proposed in our study (Pathogen Box ID: MMV687700) will be useful for the identification of potential inhibitors against Mtb in future.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  In vitro inhibition assay; MM-PB/GBSA approach; Molecular dynamics simulations; Tuberculosis, Hypothetical protein; Virtual screening

Mesh:

Substances:

Year:  2022        PMID: 35624324     DOI: 10.1007/s00894-022-05148-1

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


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