AntiPan: a genome-informed in silico pipeline for advancing subunit vaccine discovery against Staphylococcus aureus

Staphylococcus aureus (S. aureus) remains a major global health threat due to its multidrug resistance and immune evasion mechanisms. Despite numerous vaccine trials, no licensed vaccine is currently available for human use. Existing reverse vaccinology pipelines often neglect key host-pathogen immune interactions or rely on limited toolsets. This study introduces AntiPan, an enhanced in silico pipeline for identifying high-potential protein antigens for subunit vaccine design. AntiPan integrates five modules: pan-genome analysis, reverse vaccinology filters, protein assessment, immunoinformatics, and Toll-like receptors binding evaluation, while accounting for genomic diversity and immune evasion mechanisms. Using the genome of S. aureus isolated in Egypt, AntiPan identified 29 protective antigen candidates (PACs) implicated in host invasion, nutrient acquisition, and immune evasion. Ten PACs were shortlisted for future experimental validation, including IsdC, EbpS, SspB, EssA, TagH, SirA, EsxA, AmiA, HlgC, and HlgB. Molecular docking demonstrated that IsdC, AmiA, and TagH bind strongly and complementarily to the TLR1/TLR2 and TLR4/MD2 complexes, making them top vaccine candidates. Molecular dynamics simulations and MHC-epitope docking results further confirmed the immunogenicity potential of the top-ranked PACs. AntiPan is a command-line tool that provides an accessible, reproducible, and scalable platform for discovering bacterial vaccine targets. It applies to multidrug-resistant pathogens and is publicly available at: https://github.com/ComputationalBiologyLab/AntiPan .