Abstract
Breast cancer remains a significant global health challenge, requiring innovative therapeutic strategies. In silico methods, which leverage computational tools, offer a promising pathway for vaccine development. These methods facilitate antigen identification, epitope prediction, immune response modelling, and vaccine optimization, accelerating the design process. This study employed a reverse vaccinology approach combined with various bioinformatic tools to design a multi-epitope peptide vaccine. Using reverse vaccinology, AKT1 and PARP1 were identified as potential vaccine candidates, as their expression levels were significantly higher in breast cancer samples compared to healthy controls. The vaccine was designed by integrating immune cell epitopes with a TLR4 agonist as an adjuvant. It demonstrated high antigenicity, no allergenicity, and no toxicity. Validation of its 3D structure using the Ramachandran plot confirmed optimal conformation and stereochemical properties. Molecular docking and simulation studies showed the vaccine was stable and compact when interacting with TLR4. Moreover, the subunit vaccine effectively eliminated the antigen and triggered a strong IgG/IgM immune response lasting approximately one year (350 days). These findings suggest that the designed vaccine holds promise as a therapeutic option for breast cancer. However, further in vitro and in vivo studies are necessary to validate its efficacy before advancing to clinical trials.
Published Version
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