Immunoinformatics-Driven Design of a Multi-Epitope Subunit Vaccine Against Human Rhinovirus A for Pediatric Respiratory and Asthmatic Conditions

These supplementary data document an immunoinformatics workflow for designing a multi-epitope subunit vaccine against Human Rhinovirus A, with relevance to pediatric respiratory disease and asthma. The datasets include sequence-similarity results for viral capsid proteins, predicted linear B-cell epitopes with residue-level scores, and extensive MHC class I and II binding predictions across multiple HLA alleles. Together, these analyses identify candidate antigenic regions capable of supporting both humoral and cellular immune recognition. The accompanying C-IMMSIM output evaluates the vaccine construct computationally by tracking B-cell, helper and cytotoxic T-cell, natural killer cell, macrophage, dendritic-cell, antibody, cytokine, and interleukin responses over time. Overall, the data provide systematic computational evidence for epitope selection, HLA coverage, construct immunogenicity, and simulated immune-response potential in a vaccine-development framework.