Pangenome-based network analysis of Acinetobacter baumannii reveals the landscape of conserved therapeutic targets

The increasing prevalence of Acinetobacter baumannii infections and its severity demand the acute necessity for innovative therapeutic targets against it. This study employs comprehensive pangenome analysis to investigate 124 A. baumannii multidrug-resistant strains, to determine the most promising therapeutic targets derived from its core genome. Nucleotide diversity analysis of core and variable gene clusters identified key polymorphisms, suggesting significant evolutionary adaptation. Our findings revealed significant presence/absence variation (PAV) in resistance genes across strains, with 97 antimicrobial drug resistance genes identified. Two gene clusters, cluster-288 and cluster-566, harbored resistance-related genes encoding for beta-lactamase and multidrug efflux pump, respectively, were identified from the core genome that plays a pivotal role in conferring multidrug resistance. The functional enrichment analysis of these gene clusters highlighted key proteins, such as penicillin-binding proteins and outer membrane efflux proteins, as potential targets for drug design. Furthermore, we analyzed the physicochemical properties, virulence potential, active site prediction, and predicted conserved motifs. Structural predictions via 3D modeling and molecular dynamics simulations revealed high stability of key proteins, with RMSD values of 0.52 nm for outer membrane channel subunit AdeK and 0.85 nm for beta-lactamase, suggesting these proteins' potential as novel drug targets and their structural integrity under physiological conditions. Principal component analysis (PCA) highlighted distinct motion patterns within these proteins, providing insights into their functional dynamics. This research contributes to ongoing efforts to combat antibiotic resistance through innovative approaches in drug design and therapeutic interventions.