Computational identification of candidate inhibitors for Dihydrofolate reductase in Acinetobacter baumannii

Abstract

Acinetobacter baumannii is one of the emerging causes of hospital acquired infections and this bacterium, due to multi-drug resistant and Extensive Drug resistant has been able to develop resistance against the antimicrobial agents that are being used to eliminate it. A.baumannii has been the cause of death in immune compromised patients in hospitals. Hence it is the urgent need of time to find potential inhibitors for this bacterium to cease its virulence and affect its survival inside host organisms. The Dihydrofolate reductase enzyme, which is an important biocatalyst in the conversion of Dihydrofolate to Tetrahydrofolate, is an important drug target protein. In the present study high throughput screening is used to identify the inhibitors of this enzyme. The prioritized ligand molecular candidates identified through virtual screening for the substrate binding site of the predicted model are Z1447621107, Z2604448220 and Z1830442365. The Molecular Dynamics Simulation study suggests that potential inhibitor of the Dihydrofolate reductase enzyme would prevent bacteria from completing its life cycle, affecting its survival. Finally the complexes were analysed for binding free energy of the Dihydrofolate reductase enzyme complexes with the ligands.

Keywords

• DHFR enzyme
• Acinetobacter baumannii
• Molecular dynamics simulation
• Virtual high throughput screening
• MM/PBSA