Computational design and immunoinformatic evaluation of a multi-epitope vaccine candidate against Border Disease Virus
Year: 2025
Type: article
Abstract: Border Disease Virus (BDV), a Flaviviridae pestivirus, cause major reproductive and financial losses to small ruminants, and no licensed vaccine is currently available. In this study, a multi-epitope vaccine (MEV) against BDV was designed using immunoinformatics approach. The construct exhibited favorable physiochemical properties, including an aliphatic index of 68.02, solubility probability of 0.96, and overall stability. It contained multiple high-scoring linear and conformational B-cell epitopes and showed strong predicted binding to MHC class I/II molecules. Molecular docking with TLR-4 revealed stable interactions (binding score: − 312.73). Immune simulations indicated robust primary IgM and secondary IgG responses with memory B- and T-cell formation. Codon optimization confirmed high expression potential in E. coli , (CAI: 1.0; GC content: 61 %), and in-silico cloning indicate vector compatibility. These results suggest that the proposed MEV has potential to induce both humoral and cellular immunity. Further experimental validation is recommended to confirm safety, immunogenicity, and protective efficacy.
Authors: Salman Khan, Nisar Ahmad, Sami Ullah, Liaqat Ali, Sajjad Ahmad, Hina Fazal
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,440
OpenAlex ID: W4417515978