Theoretical modelling and molecular docking simulation evaluating 3-aryl-5-(alkyl-thio)-1 H-1,2,4-triazoles derivatives as potent anti-tubercular agents against MTB CYP121 receptor

Abstract

This work applies a Quantitative Structure Activity Relationship (QSAR) model, developed with the help of the QSARIN program, to predict the bioactivities of both active and dormant Mycobacterium tuberculosis (mtb) inhibitors. Four QSAR models were constructed using a molecular docking study on a series of Nitrophenyltriazole compounds retrieved from the literature, with two models specifically designed for the active and dormant Mtb H37Ra strain, and the other two for the dormant and active M bovis strain. The models were validated and the applicability domain was also presented. In silico molecular docking studies, molecular dynamics and ADMET study were undertaken to interpret the potential mechanisms of antimycobacterial activity of the bioactive Nitrophenyltriazole derivatives (NPT) with two different mtb receptors. Compound 5 was found to be a potent inhibitor of the growth of Mycobacterium tuberculosis H37Rv. Molecular dynamics simulation of compound 5 and MTB InhA (4OHU) complex showed that the NPT binds with residues SER123, Lys165, Phe149, Tyr158 and Asp148, which are essential for the transformation of MTB Inh.