The global escalation of antimicrobial resistance poses a critical challenge to modern healthcare, necessitating computational approaches to identify novel vaccine targets against multidrug-resistant pathogens. Stenotrophomonas maltophilia, an opportunistic Gram-negative bacterium associated with hospital-acquired infections, is known for its intrinsic resistance to multiple antibiotic classes and currently lacks an approved vaccine. This study applied a reverse vaccinology-driven immunoinformatics framework to design a potential multi-epitope vaccine candidate against S. maltophilia. The complete proteome was systematically screened to identify surface-exposed and virulence-associated proteins, followed by antigenicity assessment to prioritize suitable targets. Selected proteins were subjected to B-cell and T-cell epitope prediction, and the predicted epitopes were further filtered based on antigenicity, non-allergenicity, non-toxicity, and immunogenic potential. To improve broad applicability, conserved epitope analysis across multiple strains was incorporated. The shortlisted epitopes were assembled into a multi-epitope construct using appropriate linkers and an adjuvant to enhance immune response. Molecular docking and immune simulation analyses were performed to evaluate the interaction of the vaccine construct with immune receptors and to assess its immunogenic response. Population coverage analysis was performed to evaluate the global applicability of the selected epitopes. The final construct exhibited favorable immunogenicity and safety profiles based on immunoinformatics criteria. This study highlights the utility of integrating reverse vaccinology with advanced immunoinformatics approaches to address antimicrobial resistance and provides a foundation for subsequent experimental validation.

Co-authors: Sumithra B, Nusaybah Mohammed Saleem