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In silico design of a multi-epitope vaccine targeting DENV-1 and DENV-3
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  • Published: 16 January 2026

In silico design of a multi-epitope vaccine targeting DENV-1 and DENV-3

  • Deepthi Ishwar1,
  • Shruthi Padavu1,
  • Manish Kumar2,
  • Pavan Gollapalli2,
  • Krishna Kumar Ballamoole1,
  • Anoop Kumar3 &
  • …
  • Praveen Rai1 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Computational biology and bioinformatics
  • Virology

Abstract

The co-infection of DENV-1 and DENV-3 during endemic outbreaks can be potentially fatal and complicate the diagnostic process. In our study, we have focused on the development of a multiepitope vaccine against DENV-1 and DENV-3 co-infection, utilizing non-structural protein 1 (NS1) and envelope protein (E) as key antigens. B cell and T cell epitopes were predicted for their immunogenicity, antigenicity, and ability to elicit an IFN-γ response. The final construct showed predicted stability (Instability Index: 30.63), antigenicity (0.5509), non-allergenicity, and hydrophilic character (GRAVY: −0.226) based on computational assessments. Tertiary structural validation revealed 90.1% of residues in a favoured region. Molecular docking revealed a stronger binding of the DENV-TLR3 complex. The receptor and vaccine have stable interactions, according to molecular dynamics simulations and free energy estimations (-90 kJ/mol). Strong B and T cell memory responses were demonstrated by immune simulations, accompanied by increased levels of IgG, IFN-γ, and TGF-β. The codon-optimized sequence was successfully cloned into the pcDNA™3.1/V5-His-TOPO® expression vector for potential experimental validation. As a result of this in silico approach, a targeted vaccine for DENV-1 and DENV-3 co-infections is possible, which merits further experimental evaluation.

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Data availability

This article contains original data and is available from the corresponding author on request.

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Acknowledgements

The authors acknowledge Nitte (Deemed to be University) for providing research facilities.

Funding

This project was supported by the Department of Science and Technology, Government of India (Grant No. TDP/BDTD/31/2021(G)), and Nitte (Deemed to be University) (Grant No. NUFR118B-112).

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Authors and Affiliations

  1. Department of Infectious Diseases and Microbial Genomics, Nitte University Centre for Science Education and Research (NUCSER), Nitte (Deemed to be University), Paneer campus, Kotekar-Beeri Road, Deralakatte, Mangaluru, 575018, Karnataka, India

    Deepthi Ishwar, Shruthi Padavu, Krishna Kumar Ballamoole & Praveen Rai

  2. Department of Bioinformatics and Biostatistics, Nitte University Centre for Science Education and Research (NUCSER), Nitte (Deemed to be University), , Paneer campus, Deralakatte, Mangaluru, 575018, Karnataka, India

    Manish Kumar & Pavan Gollapalli

  3. Molecular Diagnostics Laboratory, National Institute of Biologicals (NIB), Ministry of Health & Family Welfare, Noida, 201309, India

    Anoop Kumar

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Contributions

Deepthi Ishwar: Methodology, Data curation, Formal analysis and Writing – original draft. Shruthi Padavu: Methodology and Data curation. Manish Kumar: Methodology. Pavan Gollapalli: Data curation, Formal analysis and Writing – review & editing. Ballamoole Krishna Kumar: Data curation, Formal analysis and Writing – review & editing. Anoop Kumar: Methodology, Data curation, Formal analysis and Writing – review & editing. Praveen Rai: Data curation, Formal analysis, Conceptualization and Writing – review & editing.

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Correspondence to Praveen Rai.

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Ishwar, D., Padavu, S., Kumar, M. et al. In silico design of a multi-epitope vaccine targeting DENV-1 and DENV-3. Sci Rep (2026). https://doi.org/10.1038/s41598-026-35678-0

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  • Received: 27 May 2025

  • Accepted: 07 January 2026

  • Published: 16 January 2026

  • DOI: https://doi.org/10.1038/s41598-026-35678-0

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Keywords

  • Dengue virus
  • Co-infection
  • Epitope
  • Immune simulation
  • Linkers
  • Multi-epitope vaccine
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