Prediction of potential epitope within segment 1 of Tilapia Lake Virus (TILV) using In-Silico Immunoinformatic Approach

Tilapia Lake Virus (TiLV) is a new emerging disease that responsible for the mortality of farmed tilapia in many countries such as Israel, Egypt, Thailand and Malaysia. To date, there is still no commercial cure or vaccines that would treat the TiLV disease. Therefore, this study was conducted to predict B-cell and T-cell epitopes within Segment 1 protein of TiLV genome through immunoinformatics tools which later could be proposed as candidate target for development of peptide- based treatment or prevention tools. In this study, epitope is referring to part of antigen protein that can be recognized by B-cells or T-cells to initiate immune response. In addition, this study also determined the antigenicity and allergenicity profile of the selected epitopes to further ensure the potential of antigenic peptides. The sequence of amino acids of Segment 1 (Acc. No. KU751814) was obtained and downloaded from Genbank through National Centre International Biotechnology (NCBI) database in FASTA format. A series of immunoinformatics prediction was employed which involved prediction of B-cell epitopes through Kolaskar and Tangoankar tool, prediction of T-cell epitopes through Proped and Proped 1 server and prediction of binding affinity between epitopes and antigen-presenting cell of major histocompatibility complex (MHC) molecules through MHCPred 2.0.Further analysis was done to identify antigenicity and allergenicity profile of the epitope through Vaxijen 2.0 and AllerTop2.0 respectively. As a result, the present study has successfully identified 10 antigenic peptides that are potential to be proposed as candidate targets for development of peptide-based therapeutics such as vaccine. This study employed a computational approach to predict potential epitopes that are antigenic and safe, within Segment 1 of TiLV genome with advantages of speeding up the long and costly process of candidate target discovery for development of peptide-based therapeutic.