Multi-epitope Vaccine Design against Grouper Iridovirus (GIV) Using Immuno-bioinformatics Approach

Grouper Iridovirus (GIV) infection induced cell death in grouper spleen cells and caused serious systemic diseases with more than 90% mortality. Therefore, effective strategies are critically needed to prevent economic losses and maintain the sustainability of grouper aquaculture. Using immuno-bioinformatics, this study aimed to create a multi-epitope vaccine (MEV) that would be effective against GIV. The GIV major capsid protein sequences were retrieved from the NCBI proteome database. Out of 284 epitopes, 17 CTL, 12 HTL, and 10 B-cell epitopes were predicted to be antigenic, non-allergenic, and non-toxic. 10 highly antigenic and overlapping epitopes were shortlisted. To generate full-length epitope vaccine candidates, the selected antigenic epitopes were fused with linkers and adjuvants. Four sets of different linker combinations (no linker, GGS, EAAK, GGGS, GPGPG, KK, and AAY) were tested and compared for their antigenicity, allergenicity, and toxicity using several servers. Molecular dynamics simulations with GROMACS were used on the modelled 3D structures to examine their stability. The results of vaccine candidate sequences screening and MD simulation predicted that the structure with GGS linker is relatively stable with a high antigenic index, non-allergenic, and nontoxic. The designed MEV in the present study could be a potential candidate for further vaccine production process against GIV.