Computational approaches to identify novel inhibitors for the drug‐ resistant Mycobacterium tuberculosis DprE1 enzyme

Abstract

Mycobacterium tuberculosis causes Tuberculosis (TB), which is a common but life‐debilitating disease. The continued development of resistance to frontline anti‐TB drugs such as isoniazid and rifampicin threatens the efficacy of currently available treatment procedures. This highlights the need to explore diverse approaches essential for drug development against multi‐drug‐resistant strains of tuberculosis. Drug development relies on the findings associated with novel protein targets, which play a crucial role in the disease life cycle. DprE1, an enzyme that plays a critical role in the cell wall synthesis of M. tuberculosis, has been recognized as a promising target for drug development. In the present study, based on previous experimental findings, seven mutant models of DprE1 involved in DprE1 resistance are predicted using homology modeling. Further, potential inhibitors are selected based on their efficacy and IC50 values. Shortlisted inhibitors are docked with the wild‐type and mutant structures of DprE1. The deduced inhibitor molecule (ZINC5) is found to possess high potential as a lead inhibitor for all the models of DprE1. It can be used to circumvent drug resistance in the current treatment regime.