Abstract

This study aimed to screen putative drug targets associated with biofilm formation of multidrug-resistant Acinetobacter baumannii and Pseudomonas areugenosa and prioritize carbon nano-fullerene as potential lead molecule by structure-based virtual screening. Based on the functional role, 36 and 83 genes that are involved in biofilm formation of A. baumannii and P. areugenosa respectively were selected and metabolic network was computationally constructed. The genes that lack three-dimensional structures were predicted and validated. Carbon nano-fullerene selected as lead molecule and their drug-likeliness and pharmacokinetics properties were computationally predicted. The binding potential of carbon nano-fullerene toward selected drug targets was modeled and compared with the binding of conventional drugs, doripenem, and polymyxin-B with their usual targets. The stabilities of four best-docked complexes were confirmed by molecular dynamic (MD) simulation. This study suggested that selected genes demonstrated relevant interactions in the constructed metabolic pathways. Carbon fullerene exhibited significant binding abilities to most of the prioritized targets in comparison with the binding of last-resort antibiotics and their usual target. The four best ligand–receptor interactions predicted by molecular docking revealed that stability throughout MD simulation. Notably, carbon fullerene exhibited profound binding with outer membrane protein (OmpA) and ribonuclease-HII (rnhB) of A. baumannii and 2-heptyl-4(1H)-quinolone synthase (pqsBC) and chemotaxis protein (wspA) of P. aeruginosa. Thus, the current study suggested that carbon fullerene was probably used as potential lead molecules toward selected targets of A. baumannii and P. aeruginosa and the applied aspects probably scaled up to design promising lead molecules toward these pathogens. Communicated by Ramaswamy H. Sarma.

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