Ensemble-based high-throughput virtual screening of natural ligands using the Super Natural-II database against cell-wall protein dTDP-4-dehydrorhamnose reductase (RmlD) in .

The disease Tuberculosis (TB) is caused by a bacterium called (). The bacterial cell-wall consists of peptidoglycan layer maintains the cellular integrity and cell viability. The main problem resides in the cell cycle of in its quiescent form which is not targeted by any drugs hence there is an immediate need for new antibiotics to target the cell wall. The current study deals with the dTDP-4-dehydrorahmnose reductase (RmlD) which is the final enzyme in the series of cell-wall proteins of . The RmlD is a part of Carbohydrate biosynthesis has been considered as a good drug target for the novel class of antibiotics. Our study begins with the protein structure prediction, Homology studies were conducted using the Phyre2 web server. The structure is then refined and subjected to molecular dynamics simulations for 50 ns using GROMACS. The clustering analysis has been carried out and generated 41 clusters with 2 Å as the cut-off. Blind docking virtual screening was performed against RmlD protein using the Super Natural-II database with AutoDock4.0. its results helped to screen top ligands based on best binding energies. In both dockings, there are some common residues in which the ligands are interacting and forming the Hydrogen bonds such as Asp-105, Val-158, Thr-160, Gly-161, Arg-224, Arg-256. The ligand-567 giving the best results by being in the top-3 of all the clusters in both blind docking as well as the active-site docking. Hence ligand-567 can be a potential inhibitor of RmlD which can further inhibit the cell-wall synthesis of Communicated by Ramaswamy H. Sarma.