Abstract
Human papillomavirus (HPV), which is transmitted through sexual activity, is the primary cause of cervical cancer and the fourth most common type of cancer in women. In this study, an immunoinformatics approach was employed to predict immunodominant epitopes from a diverse array of antigens with the ultimate objective of designing a potent multiepitope vaccine against multiple HPV types. Immunodominant B cell, cytotoxic T cell (CTL), and helper T cell (HTL) epitopes were predicted using bioinformatics tools These epitopes were subsequently analyzed using various immunoinformatics tools, and those that exhibited high antigenicity, immunogenicity, non-allergenicity, non-toxicity, and excellent conservation were selected. The selected epitopes were linked with appropriate linkers and adjuvants to formulate a broad-spectrum multiepitope vaccine candidate against HPV. The stability of the multiepitope vaccine candidate was confirmed through structural analysis, and docking results indicated a high affinity for Toll-like receptors (TLR2 and TLR4). Molecular dynamics simulations demonstrated a persistent interaction of TLR2 and TLR4 with the multiepitope vaccine candidate. In silico immunological simulations showed that three injections of the multiepitope vaccine candidate resulted in high levels of B- and T-cell immune responses. Moreover, the in silico cloning results indicated that the multiepitope vaccine candidate could be expressed in substantial amounts in E. coli. The results of this study imply that designing a broad-spectrum vaccine against various HPV types using computational methods is plausible; however, experimental validation and safety testing to confirm the findings is essential.