Identification of a Potential Compound against Drug Resistant Strain of Mycobacterium tuberculosis Using in silico Methods

Background Uninterrupted spread of drug-resistant tuberculosis has necessitated prioritization of new and effective antitubercular compound. This investigation aimed to apply in silico methods to find out potential inhibitor to KatG protein which is the major cause of drug-resistance in Mycobacterium tuberculosis strains. Materials and Methods To understand and identify effective candidate as inhibitor, virtual screening of 2632 compounds of ZINC library, modelling of KatG and its docking with 3 best hit compounds were performed. ADMET analysis of best hit compounds and MD Simulation of KatG with lead compound were also executed. Results Molecular docking exhibited higher binding affinity (-11.3 Kcal/mol) for ZINC-65407173 hit compound indicating its strong binding with KatG. Analysis of MD Simulation indicated that deviations (2-3 stable bonds) and fluctuation (RMSF<0.5 nm) were minimal at ZINC-65407173 binding residues for KatG and this compound was identified as a new lead for KatG inhibition based on higher confidence score (0.997), higher drug score (0.994), drug-likeness (3.6), better interaction (ΔG=-22.64 kcal/mol), no toxicity risks, ADMET profiling, stable binding (RMSD=0.4 nm) and insignificant conformational change (SASA=320 nm2). Conclusion Experimental validation combined with clinical trials should be performed to determine the efficacy of this lead compound.