Molecular docking and dynamics simulations of novel drug targets

Abstract In the previous chapters, potential drug targets were identified using subtractive genomic techniques and the structures of those identified drug targets were modeled using advanced computational tools. In the current study, potential drugs were screened against the targets identified in Brucella militensis 16M and the screened ligands or drug candidates were docked against the drug targets to know the interactions between the proteins and the ligands. To accomplish this task, the modeled proteins from B. militensis 16M were subjected to zinc database to screen the potential drug compounds followed by molecular docking analysis using PyRx containing an inbuilt program docking program, Autodock Vina. The interactions between the bacterial protein and the ligand were visualized using PyMol platform and the bonds between the targets to ligand were determined through Ligplus tool. Accordingly, a total of 2285, 3364, 2821, 2828, 688, 2950, 23491, 2822, and 2245 lead molecules available in the Zinc Database were screened against malate synthase G, carboxynorpsermidine decarboxylase, urease accessory protein, nicotinate phosphoribosyl transferase, 3-phosphoshikimate-1-carboxyvinyltransferase, 2,3,4,5-tetradihydropyridine-2-carboxylate N-succinyl transferase, nitric oxide reductase subunit B, transcription termination factor and hypothetical protein, respectively. Out of the total lead molecules, best three lead molecules were selected based on the docking scores for each modeled protein and the interactions were visualized using PyMol visualization tool.