Objectives: This study aimed to identify the optimal protein construction for designing a multi-epitope vaccine with both prophylactic and therapeutic effects against cervical cancer, utilizing an immunoinformatics approach. The construction process involved using capsid epitopes L1 and L2, as well as oncoproteins E5, E6, and E7 from human papillomavirus (HPV) types 16 and 18. Methods: An experimental in silico analysis with an immunoinformatics approach was used todevelop 2 multi-epitope vaccine constructs (A and B). Further analysis was then conducted tocompare the constructs and select the one with the highest potential against cervical cancer. Results: This study produced 2 antigenic, non-allergenic, and nontoxic multi-epitope vaccine constructs (A and B), which exhibited the ideal physicochemical properties for a vaccine.Further analysis revealed that construct B effectively induced both cellular and humoralimmune responses. Conclusion The multi-epitope vaccine construct B for HPV 16 and 18, designed for both prophylactic and therapeutic purposes, met the development criteria for a cervical cancer vaccine. However, these findings need to be validated through in vitro and in vivo experiments.

Objectives: Current tuberculosis (TB) control strategies face limitations, such as low antibiotic treatment compliance and a rise in multidrug resistance. Furthermore, the lack of a safeand effective vaccine compounds these challenges. The limited efficacy of existing vaccines against TB underscores the urgency for innovative strategies, such as immunoinformatics.Consequently, this study aimed to design a targeted multi-epitope vaccine against TB infectionutilizing an immunoinformatics approach. Methods: The multi-epitope vaccine targeted Ag85A, Ag85B, ESAT-6, and CFP-10 proteins. The design adopted various immunoinformatics tools for cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and linear B lymphocyte (LBL) epitope prediction, the assessment of vaccine characteristics, structure modeling, population coverage analysis, disulfide engineering, solubility prediction, molecular docking/dynamics with toll-like receptors (TLRs), codon optimization/cloning, and immune simulation. Results: The multi-epitope vaccine, which was assembled using 12 CTL, 25 HTL, and 21 LBL epitopesassociated with CpG adjuvants, showed promising characteristics. The immunoinformaticsanalysis confirmed the antigenicity, immunogenicity, and lack of allergenicity. Physicochemical evaluations indicated that the proteins were stable, thermostable, hydrophilic, and highly soluble. Docking simulations suggested high-affinity binding to TLRs, including TLR2, TLR4, and TLR9. In silico immune simulation predicted strong T cell (cytokine release) and B cell(immunoglobulin release) responses. Conclusion This immunoinformatics-designed multi-epitope vaccine targeting Ag85A, Ag85B, ESAT-6, and CFP-10 proteins showed promising characteristics in terms of stability, immunogenicity, antigenicity, solubility, and predicted induction of humoral and adaptive immune responses. This suggests its potential as a prophylactic and therapeutic vaccineagainst TB.