The Novel design of a multi-epitope vaccine candidate against the Dengue virus using advanced immunoinformatics and structural analysis

<b>Background:</b> Dengue virus (DENV) remains a major public health challenge with limited vaccine options, and current licensed vaccines exhibit restricted efficacy and safety concerns in certain populations. Advanced immunoinformatics approaches offer opportunities for designing multi-epitope vaccines targeting conserved and immunogenic regions of viral proteins. <b>Objective:</b> To design and computationally evaluate a novel multi-epitope vaccine targeting the Envelope (E) and Non-Structural protein 1 (NSP1) of DENV-1 and DENV-2 using integrated immunoinformatics and structural bioinformatics. <b>Methods:</b> CTL, HTL, and B-cell epitopes were predicted from the E and NSP1 proteins and screened for antigenicity, non-allergenicity, and non-toxicity. High-affinity epitopes were linked with appropriate spacers and adjuvants (human [Formula: see text]-defensin-3 or 50S ribosomal protein L7/L12) to construct two vaccine candidates. Molecular docking with TLR2/TLR4, molecular dynamics (MD) simulations, MM/GBSA binding free energy analysis, population coverage assessment, codon optimization, and immune simulations were conducted. Control docking using scrambled peptides was included to evaluate binding specificity. <b>Results:</b> Both vaccine constructs were predicted to be stable, soluble, non-allergenic, and non-toxic. Vaccine 2 showed higher antigenicity (VaxiJen: 0.6127) and stronger TLR2 binding ([Formula: see text]: -110.37[Formula: see text]kcal/mol), whereas vaccine 1 demonstrated better solubility and TLR4 interaction stability. Control docking with scrambled peptides produced less favorable binding energies, supporting specificity. MD simulations confirmed structural stability, and immune simulations predicted robust humoral and cellular responses with high IFN-[Formula: see text] production. Population coverage exceeded 98% in most regions. <b>Conclusion:</b> The designed multi-epitope vaccines demonstrate promising immunogenic potential in silico. Experimental validation is required to confirm safety, efficacy, and protective capability against multiple DENV serotypes.

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Publication Details

Journal
Journal of Bioinformatics and Computational Biology
Published
2025-09-12
DOI
https://doi.org/10.1142/s0219720025500143
Primary Topic
vaccines and immunoinformatics approaches
Type
article
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article

The Novel design of a multi-epitope vaccine candidate against the Dengue virus using advanced immunoinformatics and structural analysis

Mohsen Karami Fath
Journal of Bioinformatics and Computational Biology
vaccines and immunoinformatics approaches
article

The Novel design of a multi-epitope vaccine candidate against the Dengue virus using advanced immunoinformatics and structural analysis

Mohsen Karami Fath
article en

Abstract

<b>Background:</b> Dengue virus (DENV) remains a major public health challenge with limited vaccine options, and current licensed vaccines exhibit restricted efficacy and safety concerns in certain populations. Advanced immunoinformatics approaches offer opportunities for designing multi-epitope vaccines targeting conserved and immunogenic regions of viral proteins. <b>Objective:</b> To design and computationally evaluate a novel multi-epitope vaccine targeting the Envelope (E) and Non-Structural protein 1 (NSP1) of DENV-1 and DENV-2 using integrated immunoinformatics and structural bioinformatics. <b>Methods:</b> CTL, HTL, and B-cell epitopes were predicted from the E and NSP1 proteins and screened for antigenicity, non-allergenicity, and non-toxicity. High-affinity epitopes were linked with appropriate spacers and adjuvants (human [Formula: see text]-defensin-3 or 50S ribosomal protein L7/L12) to construct two vaccine candidates. Molecular docking with TLR2/TLR4, molecular dynamics (MD) simulations, MM/GBSA binding free energy analysis, population coverage assessment, codon optimization, and immune simulations were conducted. Control docking using scrambled peptides was included to evaluate binding specificity. <b>Results:</b> Both vaccine constructs were predicted to be stable, soluble, non-allergenic, and non-toxic. Vaccine 2 showed higher antigenicity (VaxiJen: 0.6127) and stronger TLR2 binding ([Formula: see text]: -110.37[Formula: see text]kcal/mol), whereas vaccine 1 demonstrated better solubility and TLR4 interaction stability. Control docking with scrambled peptides produced less favorable binding energies, supporting specificity. MD simulations confirmed structural stability, and immune simulations predicted robust humoral and cellular responses with high IFN-[Formula: see text] production. Population coverage exceeded 98% in most regions. <b>Conclusion:</b> The designed multi-epitope vaccines demonstrate promising immunogenic potential in silico. Experimental validation is required to confirm safety, efficacy, and protective capability against multiple DENV serotypes.

Journal of Bioinformatics and Computational BiologyVol. 23(5)
Kharazmi University (IR)
Openalex Percentile: Top 77%
vaccines and immunoinformatics approaches
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