Tuberculosis and HIV responses threatened by nCOVID-19: A situation prompting an in silico investigation of reported MbtA inhibitors for combined inhibition of SARS-CoV-2 and HIV-TB co-infection

ABSTRACT

The menace of infectious diseases has constantly been a reason of concern for humankind since time immemorial. As evident by the name, infectious diseases can infect a huge population within a short period, leading to an eruption of pandemics and epidemics. The present human era is fortunate enough to have a wide array of readily available drugs that help cure and prevent various diseases. Moreover, the scientific community has always responded to the needs of society through its drug discovery and development programs. The co-existence of multiple diseases calls forth the scientific community to design and develop drugs that could have a broad spectrum of activity. In this perspective, our goal was to investigate the potential of reported MbtA inhibitors (antitubercular molecules) in inhibiting HIV-1 RT and nCovid-19-RdRp and eventually leading to the identification of a multi-targeted ligand (triple co-infection inhibitor). In this study, the primary success was attained by capitalizing on the structure-based virtual screening drug discovery approach. Results were quite promising. Molecular docking results showed that GV17 interacted strongly with the active site residues of both the target proteins (HIV-1 RT and nCOVID-19-RdRp). Moreover, the docking score of GV17 was more than that of the internal ligands of both the target proteins, which indicates a firm binding. Molecular dynamics further validated these results as identical amino acid residues were observed in the protein's docked pose with the ligand. The detailed atomic interactions of ligand GV17 with the protein residues have been discussed. Overall, the protein–ligand complexes remained stable throughout the simulation, and the system's backbone fluctuations were modest. MM-GBSA analysis revealed free binding energy of − 72.30 ± 7.85 kcal/mol and − 65.40 ± 7.25 kcal/mol for 1RT2 and 7BV2, respectively. The more negative binding energy indicates a stronger affinity of GV17 with both the receptors. GV17 also gave satisfactory predictive in silico ADMET results. Overall, this computational study identified GV17 as a potential HIT molecule and findings can open up a new avenue to explore and develop inhibitors against nCOVID-19-HIV-TB triple-infections.