Abstract
Bovine leukosis continues to impose significant economic losses on the global cattle industry due to its persistent infection and widespread prevalence worldwide. Although control strategies such as test-and-cull programs have been implemented in some countries, an effective and safe vaccine remains unavailable. In this study, an immunoinformatics-based approach combined with reverse vaccinology was applied to design a multi-epitope peptide (MEP) vaccine candidate against Bovine leukemia virus (BLV). Conserved protein regions were analyzed to identify potential immune targets, resulting in the selection of five epitopes, including three cytotoxic T-lymphocyte (CTL) epitopes, one helper T-lymphocyte (Th) epitope, and one linear B-cell epitope derived from the highly conserved BLV Gag and RT-IN proteins. These epitopes were assembled using AAY and GPGPG linkers to generate a 67-amino-acid MEP construct. In silico evaluation indicated that the designed construct possesses favorable immunological properties, including high predicted antigenicity (VaxiJen score: 0.6511, which is notably higher than the baseline score of 0.4784 for the native viral proteins; Pr44: 0.4784, RT-IN: 0.4214), non-allergenic characteristics, and absence of predicted toxic motifs. Homology analysis against the Bos taurus proteome revealed no significant similarity, suggesting a low risk of host cross-reactivity. Structural analyses using PSIPRED and AlphaFold 3 predicted localized secondary structural elements within an overall flexible peptide architecture; this flexibility is highly advantageous for optimal proteasomal cleavage, efficient antigen processing, and MHC presentation. Taken together, these findings provide a rational framework for the development of a BLV MEP vaccine candidate and support further experimental validation to evaluate its predicted immunogenic potential.