Development of a novel multiepitope vaccine against Gag polyprotein of HTLV using in silico approaches

Human T-cell Lymphotropic Virus ( HTLV ) is a retrovirus associated with various diseases, including adult T-cell leukemia/lymphoma, uveitis, dermatitis, polymyositis, arthritis, alveolitis, and Sjogren’s syndrome. Despite its prevalence, especially in certain regions of the world, such as Japan, parts of Africa, and the Caribbean, there is a substantial gap in preventive measures such as vaccination. Therefore, the development of an effective vaccine against HTLV not only holds the promise of reducing the incidence of associated diseases but also aims to alleviate the economic burden on healthcare systems. For the first time, the present study employed in silico approaches to predict various epitopes to design a multiepitope vaccine against the HTLV Gag polyprotein. Our vaccine coverage analysis revealed that the vaccine construct was highly effective, making it a potential candidate for worldwide use. Furthermore, the vaccine construct was able to interact effectively with immune receptors such as TLRs. Molecular dynamic (MD) simulations revealed that the vaccine attained its stable conformation within the biological environment after a brief temporal interval, thereby indicating stabilized behavior in practical settings. Finally, the vaccine construct was also able to induce immune responses, such as the activation of B cells and T cells and increase antibody and cytokine responses. To the best of our knowledge, this is the first study that has focused on HTLV Gag epitopes to design a multiepitope vaccine in silico, which needs in-vitro/in-vivo experimental validation.

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Journal
Scientific Reports
Published
2026-09-04
DOI
https://doi.org/10.1038/s41598-026-64039-0
Primary Topic
vaccines and immunoinformatics approaches
Type
article
Field-Weighted Citation Impact
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article

Development of a novel multiepitope vaccine against Gag polyprotein of HTLV using in silico approaches

Tayebeh Hashempour, Maryam Zare, Amin Zahmatkesh, Mohammad-Matin Karbalaee-Alinazari et al.
Scientific Reports
vaccines and immunoinformatics approaches
article

Development of a novel multiepitope vaccine against Gag polyprotein of HTLV using in silico approaches

Tayebeh Hashempour, Maryam Zare, Amin Zahmatkesh, Mohammad-Matin Karbalaee-Alinazari, Kimia Salajeghe
article en

Abstract

Human T-cell Lymphotropic Virus ( HTLV ) is a retrovirus associated with various diseases, including adult T-cell leukemia/lymphoma, uveitis, dermatitis, polymyositis, arthritis, alveolitis, and Sjogren’s syndrome. Despite its prevalence, especially in certain regions of the world, such as Japan, parts of Africa, and the Caribbean, there is a substantial gap in preventive measures such as vaccination. Therefore, the development of an effective vaccine against HTLV not only holds the promise of reducing the incidence of associated diseases but also aims to alleviate the economic burden on healthcare systems. For the first time, the present study employed in silico approaches to predict various epitopes to design a multiepitope vaccine against the HTLV Gag polyprotein. Our vaccine coverage analysis revealed that the vaccine construct was highly effective, making it a potential candidate for worldwide use. Furthermore, the vaccine construct was able to interact effectively with immune receptors such as TLRs. Molecular dynamic (MD) simulations revealed that the vaccine attained its stable conformation within the biological environment after a brief temporal interval, thereby indicating stabilized behavior in practical settings. Finally, the vaccine construct was also able to induce immune responses, such as the activation of B cells and T cells and increase antibody and cytokine responses. To the best of our knowledge, this is the first study that has focused on HTLV Gag epitopes to design a multiepitope vaccine in silico, which needs in-vitro/in-vivo experimental validation.

Scientific Reports
Shiraz University of Medical Sciences (IR), Islamic Azad University, Jahrom Branch (IR)
Shiraz University of Medical Sciences, Shiraz University
Good health and well-being
Openalex Percentile: Top 18%
vaccines and immunoinformatics approaches
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