A conserved capsid-based multi-epitope vaccine targeting dengue virus serotypes (DENV1–4): an integrated computational and in vivo study

BACKGROUND: Dengue virus (DENV), comprising four antigenically distinct serotypes (DENV1-4), continues to pose a major global health burden. The lack of a universally protective vaccine capable of inducing balanced immunity against all serotypes remains a critical challenge, largely due to antigenic diversity and the risk of antibody-dependent enhancement (ADE). Conserved capsid proteins represent promising targets for epitope-based vaccine development because of their structural stability and immunogenic potential. METHODS: An integrated reverse vaccinology and immunoinformatics strategy was employed to design a conserved capsid-based multi-epitope vaccine (MEV-DV) targeting DENV1-4. B-cell, cytotoxic T-lymphocyte (CTL), and helper T-lymphocyte (HTL) epitopes were screened for antigenicity, non-allergenicity, non-toxicity, and sequence conservancy. Selected epitopes were assembled using appropriate linkers with β-defensin as an adjuvant and a PADRE sequence. The construct was evaluated for physicochemical properties, 3D structure modeling and validation, solubility, disulfide engineering, molecular docking with TLR4 and TLR8, molecular dynamics simulation, and immune simulation. Experimental validation was performed in albino mice using an alum-adjuvanted formulation, and humoral responses were assessed by hemagglutination inhibition (HI) assay. RESULTS: The finalized MEV-DV construct exhibited high antigenicity (0.8559), favorable physicochemical properties, and structural stability, with 97.6% of residues located in favored Ramachandran regions. Docking studies demonstrated strong binding affinity with TLR4 and TLR8, and molecular dynamics simulations confirmed stable receptor-vaccine interactions over 50 ns. Immune simulations predicted robust humoral and cellular immune responses with sustained memory formation. In vivo immunization induced detectable antibodies by day 7, with peak HI titers at day 21. Antibody levels were statistically comparable to those elicited by a commercial inactivated dengue vaccine (p > 0.05), and no adverse effects were observed. CONCLUSION: This study demonstrates that a conserved capsid-based multi-epitope vaccine designed through reverse vaccinology and immunoinformatics is structurally stable, immunogenic, and safe in a murine model. The combined computational and experimental findings support the potential of MEV-DV as a promising broadly protective dengue vaccine candidate and warrant further evaluation through neutralization assays and viral challenge studies.

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Journal
BMC Immunology
Published
2026-05-27
DOI
https://doi.org/10.1186/s12865-026-00857-1
Primary Topic
vaccines and immunoinformatics approaches
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article
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article

A conserved capsid-based multi-epitope vaccine targeting dengue virus serotypes (DENV1–4): an integrated computational and in vivo study

Elham Mohammed Khatrawi, Awais Ali, Syed Mudasser Ali, Hind Althagafi et al.
BMC Immunology
vaccines and immunoinformatics approaches
article

A conserved capsid-based multi-epitope vaccine targeting dengue virus serotypes (DENV1–4): an integrated computational and in vivo study

Elham Mohammed Khatrawi, Awais Ali, Syed Mudasser Ali, Hind Althagafi, Syed Muhammad Shamaim Ali
article en

Abstract

BACKGROUND: Dengue virus (DENV), comprising four antigenically distinct serotypes (DENV1-4), continues to pose a major global health burden. The lack of a universally protective vaccine capable of inducing balanced immunity against all serotypes remains a critical challenge, largely due to antigenic diversity and the risk of antibody-dependent enhancement (ADE). Conserved capsid proteins represent promising targets for epitope-based vaccine development because of their structural stability and immunogenic potential. METHODS: An integrated reverse vaccinology and immunoinformatics strategy was employed to design a conserved capsid-based multi-epitope vaccine (MEV-DV) targeting DENV1-4. B-cell, cytotoxic T-lymphocyte (CTL), and helper T-lymphocyte (HTL) epitopes were screened for antigenicity, non-allergenicity, non-toxicity, and sequence conservancy. Selected epitopes were assembled using appropriate linkers with β-defensin as an adjuvant and a PADRE sequence. The construct was evaluated for physicochemical properties, 3D structure modeling and validation, solubility, disulfide engineering, molecular docking with TLR4 and TLR8, molecular dynamics simulation, and immune simulation. Experimental validation was performed in albino mice using an alum-adjuvanted formulation, and humoral responses were assessed by hemagglutination inhibition (HI) assay. RESULTS: The finalized MEV-DV construct exhibited high antigenicity (0.8559), favorable physicochemical properties, and structural stability, with 97.6% of residues located in favored Ramachandran regions. Docking studies demonstrated strong binding affinity with TLR4 and TLR8, and molecular dynamics simulations confirmed stable receptor-vaccine interactions over 50 ns. Immune simulations predicted robust humoral and cellular immune responses with sustained memory formation. In vivo immunization induced detectable antibodies by day 7, with peak HI titers at day 21. Antibody levels were statistically comparable to those elicited by a commercial inactivated dengue vaccine (p > 0.05), and no adverse effects were observed. CONCLUSION: This study demonstrates that a conserved capsid-based multi-epitope vaccine designed through reverse vaccinology and immunoinformatics is structurally stable, immunogenic, and safe in a murine model. The combined computational and experimental findings support the potential of MEV-DV as a promising broadly protective dengue vaccine candidate and warrant further evaluation through neutralization assays and viral challenge studies.

BMC Immunology
Princess Nourah bint Abdulrahman University (SA), Abdul Wali Khan University Mardan (PK), Taibah University (SA), Abasyn University (PK)
Good health and well-being
Openalex Percentile: Top 10%
vaccines and immunoinformatics approaches
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