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

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 con...

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Vydané v:Journal of bioinformatics and computational biology Ročník 23; číslo 5; s. 2550014
Hlavný autor: Fath, Mohsen Karami
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Singapore 01.10.2025
Predmet:
Computational Biology - methods
Dengue - immunology
Dengue - prevention & control
Dengue Vaccines - chemistry
Dengue Vaccines - immunology
Dengue Virus - immunology
Epitopes - chemistry
Epitopes - immunology
Epitopes, B-Lymphocyte - chemistry
Epitopes, B-Lymphocyte - immunology
Epitopes, T-Lymphocyte - chemistry
Epitopes, T-Lymphocyte - immunology
Humans
Immunoinformatics
Molecular Docking Simulation
Molecular Dynamics Simulation
Viral Envelope Proteins - chemistry
Viral Envelope Proteins - immunology
Viral Nonstructural Proteins - chemistry
Viral Nonstructural Proteins - immunology
computational immunology
structural bioinformatics
dengue virus
Immunoinformatics
ISSN:1757-6334, 1757-6334
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Shrnutí: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. 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. 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. 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. 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.
Bibliografia:ObjectType-Article-1
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ISSN:1757-6334
1757-6334
DOI:10.1142/S0219720025500143