In silico prediction of B and T cell epitopes of infectious salmon anemia virus proteins and molecular modeling of T cell epitopes to salmon major histocompatibility complex (MHC) class I

Infectious salmon anemia (ISA) can be devastating in farmed Atlantic salmon (Salmo salar). The disease can evolve into epidemics if it is not contained and controlled. ISA epidemics were seen in Norway in the early 1990s and Chile in 2007-2009.Consequently, there is an urgent need to develop a vaccine to prevent or treat the infection. In this study, an immunoinformatic approach was employed to predict 32 lineal B-cell epitopes based on antigenicity and surface accessibility prediction for ISAV fusion (F), hemagglutinin-esterase (HE), and matrix (M) proteins. On the other hand, twelve conformational B-cell epitopes were also predicted.We further identified six antigenic cytotoxic T lymphocyte (CTL) epitopes and investigated the binding in-teractions with five salmon MHC-I proteins after docking the peptides to the binding groove of the MHC-I proteins. Our results showed that all the predicted epitopes could bind to salmon MHC-I with high negative Delta G values with medium to high binding affinities. Hence, the predicted epitopes have a high potential of being recognized by Atlantic salmon MHC-I to elicit a CD8+ T cell response in salmon. The predicted and analyzed B and T cell antigenic epitopes in this work might present an initial set of peptides for future vaccine development against ISAV.The ability to model and predict these interactions will ultimately lead to the ability to predict potential binding for MHCs and epitopes that were not studied previously. As current knowledge of salmon MHC speci-ficity is limited, studying and modeling interactions in the peptide/MHC complex is a key to resolving unknown epitope specificity.