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April 15, 2026Bioinformatics and Biology Insights0 citationsOpen Access

Multi-Epitope mRNA Vaccine Targeting Dabie Bandavirus Glycoprotein: An Immunoinformatics-Based Study

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SASk Faisal AhmedMPMd. Shah ParanMMMd Masudur Rahman Munna

Key Points

  • To design a multi-epitope mRNA vaccine targeting the glycoprotein of Dabie bandavirus using immunoinformatics.
  • In silico analysis of 1042 virus sequences to identify epitopes.
  • Selection of 9 CTL, 6 HTL, and 5 B-cell epitopes based on conservation and predicted antigenicity.
  • Incorporation of beta-defensin-3 as an adjuvant to enhance immune response.
  • Computational predictions for structural stability and binding capabilities to immune receptors.
  • Codon optimization for potential expression in a host.
  • Achieved 94.77% global population coverage with selected epitopes.
  • Predicted favorable structural stability and immune response patterns.
  • Simulations showed consistent behavior over 100 ns molecular dynamics.
  • Identified potential binding sites for TLR3 and TLR4.

Abstract

Dabie bandavirus (DBV), also called severe fever with thrombocytopenia syndrome virus (SFTSV), is a tick-borne virus that leads to a serious illness with high fever, low platelets, bleeding risks, and organ damage. Death rates can reach 5% to 30% in affected areas like China, South Korea, and Japan, where cases continue to rise. No approved vaccines or specific treatments are available, prompting the World Health Organization to mark it as a priority emerging infectious disease. This in silico study designs a multi-epitope mRNA vaccine candidate targeting the virus’s membrane glycoprotein. After reviewing 1042 virus sequences, 9 cytotoxic T-cell (cytotoxic T lymphocyte CTL), 6 helper T-cell (helper T lymphocyte HTL), and 5 B-cell epitopes were chosen for their high conservation, predicted antigenicity, safety (non-toxic, low allergenicity), and lack of similarity to human proteins, achieving 94.77% global population coverage. The construct included beta-defensin-3 as an adjuvant. Computational predictions indicated favorable features: structural stability, potential binding to immune receptors (Toll-like receptor 3 TLR3 and Toll-like receptor 4 TLR4), consistent behavior in molecular dynamics simulations (100 ns), encouraging patterns in immune response modeling, and good codon optimization for possible expression. These results are hypothesis-generating and based solely on in silico tools and require experimental validation, including in vitro studies, immunogenicity tests, and animal challenge models to assess any real-world potential.

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Cite This Study

Ahmed et al. (2026) studied this question.

synapsesocial.com/papers/69df2bcae4eeef8a2a6b0c7chttps://doi.org/10.1177/11779322261438994
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