Hybrid Computational Simulation and Modeling Assisted Structural Analysis of Anti-tubercular Molecules

Tuberculosis (TB), a leading cause of death worldwide, in association with HIV-AIDS and the emergence of multi-drug resistance (MDR) or extensively drug resistance (XDR) strains, has created necessity to develop new class of anti-tubercular drug. Strategic implementation of hybrid computational simulation and searching method has been used to analyze and explore new chemical entity effective against MDR Tuberculosis strains. Initially a ligand-based pharmacophore hypothesis and 3D Quantitative structure activity relationship (QSAR) model with statistical significance (R2=0.985, SD=0.146, Pearson R=0.936, Q2= 0.849, R2Pred=0.851, Q2(F2)=0.854) was generated by well validated algorithm. Concurrently molecular docking analysis was performed by considering three individual grid points of InhA enzyme. Moreover Ligand-based pharmacophoric model was drastically re-assessed against receptor-based docking simulation model to authenticate this in silico trialing. The docking analysis indicates that this class of ligands nicely occupies the hydrophobic pocket of InhA enzyme, which is an important feature of direct InhA inhibitors and it reveals that the chemical entities can inhibit the aforementioned enzyme without activating katG (a catalase/peroxidase enzyme) enzyme pathway.