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Immunoinformatics Aided Design and In-Vivo Validation of a Cross-Reactive Peptide Based Multi-Epitope Vaccine Targeting Multiple Serotypes of Dengue Virus.
- Source :
-
Frontiers in immunology [Front Immunol] 2022 Jun 21; Vol. 13, pp. 865180. Date of Electronic Publication: 2022 Jun 21 (Print Publication: 2022). - Publication Year :
- 2022
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Abstract
- Dengue virus (DENV) is an arboviral disease affecting more than 400 million people annually. Only a single vaccine formulation is available commercially and many others are still under clinical trials. Despite all the efforts in vaccine designing, the improvement in vaccine formulation against DENV is very much needed. In this study, we used a roboust immunoinformatics approach, targeting all the four serotypes of DENV to design a multi-epitope vaccine. A total of 13501 MHC II binding CD4+ epitope peptides were predicted from polyprotein sequences of four dengue virus serotypes. Among them, ten conserved epitope peptides that were interferon-inducing were selected and found to be conserved among all the four dengue serotypes. The vaccine was formulated using antigenic, non-toxic and conserved multi epitopes discovered in the in-silico study. Further, the molecular docking and molecular dynamics predicted stable interactions between predicted vaccine and immune receptor, TLR-5. Finally, one of the mapped epitope peptides was synthesized for the validation of antigenicity and antibody production ability where the in-vivo tests on rabbit model was conducted. Our in-vivo analysis clearly indicate that the imunogen designed in this study could stimulate the production of antibodies which further suggest that the vaccine designed possesses good immunogenicity.<br />Competing Interests: Authors UK, and ARS were employed by the company STEMskills Research and Education Lab Private Limited, Faridabad, Haryana, India. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.<br /> (Copyright © 2022 Kaushik, G, Gupta, Kalra, Shaikh, Cavallo and Chawla.)
Details
- Language :
- English
- ISSN :
- 1664-3224
- Volume :
- 13
- Database :
- MEDLINE
- Journal :
- Frontiers in immunology
- Publication Type :
- Academic Journal
- Accession number :
- 35799781
- Full Text :
- https://doi.org/10.3389/fimmu.2022.865180