Introduction The increasing prevalence of penicillin-resistant Streptococcus pneumoniae (PRSP) has compromised the efficacy of conventional β-lactam therapies, and the inefficiency of penicillin-binding proteins (PBPs) as reliable drug targets further underscores the urgent need to explore novel alternatives. The current study employs an in silico strategy that integrates genomics, genome-wide association studies (GWASs), network analyses, and membrane protein simulations to systematically identify and prioritize new antimicrobial targets. Methodology A total of 665 PRSP genomes from Indian clinical isolates collected between 1996 and 2022 were analyzed. High-quality genome assemblies were annotated and used for pangenome construction and GWASs to identify gene clusters associated with penicillin resistance. Candidate genes were further prioritized through essentiality screening, functional annotation, subcellular localization prediction, evolutionary conservation analysis, druggability assessment, and structural modeling. Results Integrated analysis identified OppC2, an essential oligopeptide permease of the ABC transporter family, as a highly favorable drug target. Network and functional enrichment analyses linked OppC2 to transport-associated pathways relevant to pneumococcal survival and adaptation. Structural modeling revealed a high-confidence protein model with a druggable binding pocket, while molecular dynamics simulations confirmed the stability of the structure in a physiological membrane environment. Conclusion This comprehensive approach enabled the identification of conserved, essential, and accessible drug targets within PRSP populations, providing an adaptable framework to guide next-generation antimicrobial target identification beyond traditional PBPs.
Panickar et al. (Wed,) studied this question.