Identification of Ethr Inhibitor Targeting Mycobacterium Tuberculosis: An Insight From Molecular Docking Study

Abstract

Objective: Mycobacterium tuberculosis (MTB) is a pathogenic bacterium of the Mycobacteriaceae family that causes TB. EthR is a transcriptional regulator which is involved in the repression of the monooxygenase EthA which is responsible for the formation of the active metabolite of Eth. Inhibitors of the EthR DNA binding protein induce a conformational change in this repressor, thus preventing its binding to DNA operator, consequently resulting in increased transcription of EthA and bioactivation of Eth. Methods: In this study, we used first-line and second-line drugs and their analogues to validate the binding affinity of EthR DNA binding protein of MTB. Molegro Virtual Docker (MVD) is utilized for virtual screening and validation of MolDoc, Rerank, and hydrogen bond parameters of ETH, isoniazid (INH), clofazimine (CLF), and its modified derivatives to the EthR DNA binding protein of MTB. The modified molecules; ETH4, INZ2, CLF3, and CLF4 show more binding affinities than that of native compounds ETH, INH, and CLF to the EthR DNA binding protein of MTB. The top scoring compound was docked by auto dock vina in PyRx to get the best conformer pose for intermolecular interactions. Results: CLF4 had the best lowest MolDock score -176.29kcal/mol and H-bonding energy -6.89kcal/mol in the MVD virtual screening. The best conformer pose generated by PyRx was shown -7.1 binding affinity and ligand generated hydrogen bond interactions with THR130 and LYS68, respectively, which stabilized the ligand in the active site of EthR protein. Conclusion: We concluded that CLF4 has shown better inhibitory efficacy than other compounds towards EthR protein. However, these results need to be further substantiated through in vitro and in vivo experimental studies.

Natural Plant Compounds as ANGPTL2 Inhibitors in Glioblastoma: An Integrated Bioinformatics and Molecular Docking Analysis

“…They play a crucial role in evaluating the drug's pharmacodynamic activities. There are numerous online tools and offline software programs that are readily accessible for predicting the ADMET properties of a molecule [43,44]. The SwissADME tool [45] and the pkCSM tool were used in this study to evaluate the drug-likeness and ADMET properties of the highest-scoring compounds.…”