ArticlePeerJ2025
Construction of an immunoinformatics-based multi-epitope vaccine candidate targeting Kyasanur forest disease virus.
Article in PeerJ, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Achievements and Challenges in Therapy and Vaccines Development of Viral Hemorrhagic Fevers: An Up-to-Date Review.Pharmaceutics · 2026Review
- Comparative Sequence Analysis of the Envelope Gene of Kyasanur Forest Disease Virus Vaccine Strain With Currently Circulating Field Strains.Advances in virology · 2026Article
- Pathogenicity and virulence of Kyasanur Forest disease: A comprehensive review of an expanding zoonotic threat in southwestern India.Virulence · 2025Review
- Review
- Using immunoinformatics and bioinformatics approach to design novel and effective rational in-silico vaccine against humanIn silico pharmacology · 2025Article
- Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Kyasanur forest disease (KFD) is one of the neglected tick-borne viral zoonoses. KFD virus (KFDV) was initially considered endemic to the Western Ghats region of Karnataka state in India. Over the years, there have been reports of its spread to newer areas within and outside Karnataka. The absence of an effective treatment for KFD mandates the need for further research and development of novel vaccines. The present study was designed to develop a multi-epitope vaccine candidate against KFDV using immunoinformatics approaches. A total of 74 complete KFDV genome sequences were analysed for genetic recombination followed by phylogeny. Computational prediction of B- and T-cell epitopes belonging to envelope protein was performed and epitopes were prioritised based on IFN-Gamma, IL-4, IL-10 stimulation and checked for allergenicity and toxicity. The eight short-listed epitopes (three MHC-Class 1, three MHC-Class 2 and two B-cell) were then combined using various linkers to construct the vaccine candidate. Molecular docking followed by molecular simulations revealed stable interactions of the vaccine candidate with immune receptor complex namely Toll-like receptors (TLR2-TLR6). Codon optimization followed by
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Registered trials
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