TY - JOUR
T1 - Immunoinformatics Aided Design and In-Vivo Validation of a Cross-Reactive Peptide Based Multi-Epitope Vaccine Targeting Multiple Serotypes of Dengue Virus
AU - Kaushik, Vikas
AU - G, Sunil Krishnan
AU - Gupta, Lovi Raj
AU - Kalra, Utkarsh
AU - Shaikh, Abdul Rajjak
AU - Cavallo, Luigi
AU - Chawla, Mohit
N1 - KAUST Repository Item: Exported on 2022-06-23
Acknowledgements: This research received no external funding. The APC charges was funded by KAUST baseline research funding (to LC). The research reported in this publication was supported by funding from King Abdullah University of Science and Technology (KAUST). For computer time, this research used the resources of the Supercomputing Laboratory at King Abdullah University of Science & Technology (KAUST) in Thuwal, Saudi Arabia. Authors would also like to acknowledge team members from STEMskills Research and Education Lab Private Limited for critical reading of manuscript and computational support.
PY - 2022/6/21
Y1 - 2022/6/21
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/679243
UR - https://www.frontiersin.org/articles/10.3389/fimmu.2022.865180/full
U2 - 10.3389/fimmu.2022.865180
DO - 10.3389/fimmu.2022.865180
M3 - Article
C2 - 35799781
SN - 1664-3224
VL - 13
JO - Frontiers in Immunology
JF - Frontiers in Immunology
ER -