{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T17:46:25Z","timestamp":1789494385651,"version":"build-2803163510"},"reference-count":81,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,1,7]],"date-time":"2025-01-07T00:00:00Z","timestamp":1736208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:p>Human rhinovirus C (HRV-C) is a significant contributor to respiratory tract infections in children and is implicated in asthma exacerbations across all age groups. Despite its impact, there is currently no licensed vaccine available for HRV-C. Here, we present a novel approach to address this gap by employing immunoinformatics techniques for the design of a multi-epitope-based vaccine against HRV-C. The sequences of the chosen structural proteins VP1 and VP2, along with the non-structural protein 2C of HRV-C, were downloaded in FASTA format from the NCBI server for further analysis. Through an exhaustive analysis of HRV-C genomic sequences, we identified highly conserved immunogenic regions capable of eliciting a protective immune response. Leveraging advanced immunoinformatics tools, we predicted epitopes for B-cells, Cytotoxic T lymphocytes, and Helper T lymphocytes, ensuring broad coverage across different HRV-C strains. The vaccine candidate was constructed by integrating selected antigens with immunogenic epitopes and adjuvants, employing optimal linkers. Three vaccine constructs were developed, with V2 being the most promising, consisting of 480 amino acids residues. V2 exhibited strong antigenicity, non-allergenicity, and solubility, with a solubility score greater than 0.550, and demonstrated excellent structural stability, with 91.9% of residues in the most favorable regions of the Ramachandran plot. Molecular dynamics and simulation studies revealed a stable Vaccine-TLR8 complex, with a binding energy of -296.15 and consistent RMSD values. Furthermore, in silico cloning and sequence optimization ensured efficient expression in <jats:italic>E. coli<\/jats:italic>, with a Codon Adaptation Index of 0.99 and GC content of 54.58%. The minimum free energy of the RNA secondary structure was -494.90 kcal\/mol. While our findings suggest the potential effectiveness of the designed vaccine candidate against HRV-C, further <jats:italic>in vitro<\/jats:italic> and <jats:italic>in vivo<\/jats:italic> investigations are warranted to validate its safety and efficacy.<\/jats:p>","DOI":"10.3389\/fimmu.2024.1364129","type":"journal-article","created":{"date-parts":[[2025,1,7]],"date-time":"2025-01-07T07:46:39Z","timestamp":1736235999000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["Designing a multi-epitope vaccine candidate against human rhinovirus C utilizing immunoinformatics approach"],"prefix":"10.3389","volume":"15","author":[{"given":"Tajul Islam","family":"Mamun","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Md. Ahad","family":"Ali","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Md. 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