Understanding the underlying resistance mechanism of Mycobacterium tuberculosis against Rifampicin by analyzing mutant DNA - directed RNA polymerase proteins via bioinformatics approaches

Tuberculosis or TB is an airborne disease caused by the non-motile bacilli, Mycobacterium tuberculosis (MTB). There are two main forms of TB, namely, latent TB or LTB, asymptomatic and non-contagious version which according to the World Health Organization (WHO) is estimated to afflict over a third of the world’s population; and active TB or ATB, a symptomatic and contagious version which continues to spread, affecting millions worldwide. With the already high reported prevalence of TB, the emergence of drug-resistant strains has prompted the development of novel approaches to enhance the efficacy of known drugs and a desperate search for novel compounds to combat MTB infections. It was for this very purpose that this study was conducted. A look into the resistance mechanism of Rifampicin (Rifampin or RIF), one of the more potent first-line drugs, might prove beneficial in predicting the consequence of an introduced mutation (which usually occur as single nucleotide polymorphisms or SNPs) and perhaps even overcome it using appropriate therapeutic interventions that improve RIF’s efficacy. To accomplish this task, models of acceptable quality were generated for the WT and clinically relevant, RIF resistance conferring, SNPs occurring at codon positions D516, H526 and S531 (E .coli numbering system) using MODELLER. The models were accordingly ranked using GA341 and z-DOPE score, and subsequently validated with QMEAN, PROCHECK and VERIFY3D. MD simulations spanning 100 ns were run for RIF-bound (complex) and RIF-free (holo) DNA-directed RNA polymerase (DDRP) protein systems for the WT and SNP mutants using GROMACS. The MD frames were analyzed using RMSD, Rg and RMSF. For further analysis, MD-TASK was used to analyze the calculated dynamic residue networks (DRNs) from the generated MD frames, determining both change in average shortest path (ΔL) and betweenness centrality (ΔBC). The RMSD analysis revealed that all of the SNP complex models displayed a level instability higher than that of the WT complex. A majority of the SNP complex models were also observed to have similar compactness to the WT holo when looking at the calculated Rg. The RMSF results also hinted towards possible physiological consequences of the mutations (generally referred to as a fitness cost) highlighted by the increased fluctuations of the zinc-binding domain and the MTB SI α helical coiled coil. For the first time, to the knowledge of the authors, DRN analysis was employed for the DDRP protein for both holo and complex systems, revealing insightful information about the residues that play a key role in the change in distance between residue pairs along with residues that play an essential role in protein communication within the calculated RIN. Overall, the data supported the conclusions drawn by a recent study that only concentrated on RIF-resistance in rpoB models which suggested that the binding pocket for the SNP models may result in the changed coordination of RIF which may be the main contributor to its impaired efficacy