Bioinformatics and immunoinformatics approaches in the design of a multi-epitope vaccine targeting CTLA-4 for melanoma treatment

Melanoma, a highly aggressive skin cancer, remains a significant cause of mortality despite advancements in therapeutic strategies. There is an urgent demand for developing vaccines that can elicit strong and comprehensive immune responses against this malignancy. Achieving this goal is crucial to enhance the efficacy of immunological defense mechanisms in combating this disease. This research provides a thorough examination of the design, optimization, and validation of a multi-epitope vaccine (MEV) construct. Using computational and in silico methods, the study specifically targets key immune receptors including MHC-I, MHC-I, and TLR4. The MEV construct was codon-optimized and effectively cloned into the E. coli pET-28a(+) vector to improve expression efficiency. To assess the stability and flexibility of the vaccine constructs in complex with their target receptors, molecular dynamics (MD) simulations were performed. The findings showed that the MHC-I-MEV complex demonstrated the greatest stability, with the MHC-II-MEV and TLR4-MEV complexes following instability. Immune simulation analyses revealed robust immune responses, evidenced by significant antibody production and the activation of cell mediated immune responses. These results highlight the MEV construct's potential as a versatile vaccine candidate, capable of eliciting strong and diverse immune responses. The integration of structural and energetic analyses, combined with immune simulation, provides a solid foundation for further experimental validation and therapeutic development.