Veterinary medicine and science · 2026
Computational and Experimental Development of a Novel Multi-Epitope Vaccine Candidate Against Bovine Leukaemia Virus.
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Dini Yasaman, Piri-Gharaghie Tohid, Hamdi Elahe, Goodarzi Pegah, Ahmadi Ronak
Аннотация
BACKGROUND: Bovine leukaemia virus (BLV) is the causative agent of enzootic bovine leukosis, a chronic infectious disease that causes significant economic losses in the dairy and beef industries worldwide. Despite extensive research, there is no licensed vaccine available for effective prevention and control of BLV infection.
OBJECTIVES: This study aimed to design and evaluate a novel multi-epitope vaccine candidate against BLV using an integrated computational and experimental approach to enhance immunogenicity, expression efficiency, and molecular stability.
METHODS: Major BLV structural proteins (gp51, gp30, and p24) were analyzed for B- and T-cell epitope prediction using immunoinformatics tools. Selected epitopes were assembled into a single chimeric construct with appropriate linkers and an N-terminal β-defensin adjuvant. The vaccine was evaluated for antigenicity, allergenicity, and physicochemical properties. Structural modelling, molecular docking with Toll-like receptors (TLRs), and RNA stability analyses were performed to assess receptor binding affinity and translational efficiency. Codon optimization for Lactococcus lactis expression was conducted using the JCAT server, and in silico cloning was verified in the NICE pNZ8148 vector.
RESULTS: The designed vaccine showed high antigenicity (VaxiJen score: 0.7261), non-allergenicity, and stability, with an optimal codon adaptation index (0.94) and GC content (48.55%). Molecular docking revealed strong interactions with TLR9 (z-score = -2.5; van der Waals energy = -56.5 ± 3.8 kcal/mol), suggesting effective immune receptor engagement. RNAfold analysis indicated a stable mRNA structure (MFE = -155.20 kcal/mol), supporting efficient expression.
CONCLUSIONS: The multi-epitope vaccine candidate demonstrated favourable immunological, structural, and translational properties, indicating its strong potential as a next-generation recombinant vaccine against BLV. Further in vitro and in vivo validation is warranted to confirm its immunogenicity and protective efficacy in cattle.
OBJECTIVES: This study aimed to design and evaluate a novel multi-epitope vaccine candidate against BLV using an integrated computational and experimental approach to enhance immunogenicity, expression efficiency, and molecular stability.
METHODS: Major BLV structural proteins (gp51, gp30, and p24) were analyzed for B- and T-cell epitope prediction using immunoinformatics tools. Selected epitopes were assembled into a single chimeric construct with appropriate linkers and an N-terminal β-defensin adjuvant. The vaccine was evaluated for antigenicity, allergenicity, and physicochemical properties. Structural modelling, molecular docking with Toll-like receptors (TLRs), and RNA stability analyses were performed to assess receptor binding affinity and translational efficiency. Codon optimization for Lactococcus lactis expression was conducted using the JCAT server, and in silico cloning was verified in the NICE pNZ8148 vector.
RESULTS: The designed vaccine showed high antigenicity (VaxiJen score: 0.7261), non-allergenicity, and stability, with an optimal codon adaptation index (0.94) and GC content (48.55%). Molecular docking revealed strong interactions with TLR9 (z-score = -2.5; van der Waals energy = -56.5 ± 3.8 kcal/mol), suggesting effective immune receptor engagement. RNAfold analysis indicated a stable mRNA structure (MFE = -155.20 kcal/mol), supporting efficient expression.
CONCLUSIONS: The multi-epitope vaccine candidate demonstrated favourable immunological, structural, and translational properties, indicating its strong potential as a next-generation recombinant vaccine against BLV. Further in vitro and in vivo validation is warranted to confirm its immunogenicity and protective efficacy in cattle.