Immunoinformatics-Based Design of Multi-epitope DNA and mRNA Vaccines Against Zika Virus.
Autor: | Braz JM; Laboratory of Molecular Genetics and Biotechnology (GMBio), Department of Biology, Center for Biological and Health Sciences, Federal University of Sergipe, São Cristóvão, Brazil., Batista MVA; Laboratory of Molecular Genetics and Biotechnology (GMBio), Department of Biology, Center for Biological and Health Sciences, Federal University of Sergipe, São Cristóvão, Brazil. |
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Jazyk: | angličtina |
Zdroj: | Bioinformatics and biology insights [Bioinform Biol Insights] 2024 May 31; Vol. 18, pp. 11779322241257037. Date of Electronic Publication: 2024 May 31 (Print Publication: 2024). |
DOI: | 10.1177/11779322241257037 |
Abstrakt: | In this study, we used an immunoinformatics approach to predict antigenic epitopes of Zika virus (ZIKV) proteins to assist in designing a vaccine antigen against ZIKV. We performed the prediction of CD8+ T-lymphocyte and antigenic B-cell epitopes of ZIKV proteins. The binding interactions of T-cell epitopes with major histocompatibility complex class I (MHC-I) proteins were assessed. We selected the antigenic, conserved, nontoxic, and immunogenic epitopes, which indicated significant interactions with the human leucocyte antigen (HLA-A and HLA-B) alleles and worldwide population coverage of 76.35%. The predicted epitopes were joined with the help of linkers and an adjuvant. The vaccine antigen was then analyzed through molecular docking with TLR3 and TLR8, and it was in silico cloned in the pVAX1 vector to be used as a DNA vaccine and designed as a mRNA vaccine. Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. (© The Author(s) 2024.) |
Databáze: | MEDLINE |
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