Discovery of multi-target mur enzymes inhibitors with anti-mycobacterial activity through a Scaffold approach.

In the present study, we generated a ligand-based scaffold model from a known bioactive datasets of mur enzymes of other species to identify multi-targeting inhibitors as antitubercular agents. Compounds in the ChEMBL database were first filtered to screen for substructure molecules of multi-target enzymes. 5'-O-(5-Amino-5-deoxy-β-D-ribofuranosyl)uridine has been identified as scaffold to develop compounds targeting mur enzymes. A library of Murcko scaffolds was extracted and evaluated for their in-silico antitubercular activity against mur enzymes. The screened compounds were subjected to molecular docking, molecular dynamics simulations, MM/PBSA calculation with mur enzymes to evaluate the mechanism of interaction to assess inhibitory activity against the target protein. The results revealed that 15 compounds have higher docking scores and good interactions with multiple mur enzymes of . From the docking analysis, compound HPT had the best score and binding affinity with the all mur enzymes. Further, protein-ligand interactions were evaluated by molecular dynamics simulations to assess their stability throughout 100 ns period. From the MD trajectory, we calculated RMSD, RMSF, Rg, PCA, DCCM, FEL, hydrogen bonding, and vector motion. Furthermore, the binding free energies of the all nine mur enzymes with compound HPT exhibited good binding affinity might show the anti-mycobacterial activity. The compound HPT revealed from this computational study could act as potent anti-mycobacterial inhibitors and further serve as lead scaffolds to develop more potent pharmaceutical molecules targeting multiple mur enzymes of Mtb based on 5'-O-(5-Amino-5-deoxy-β-D-ribofuranosyl)uridine in the future.Communicated by Ramaswamy H. Sarma.