Prediction of promiscuous T cell epitopes in Hepatitis B virus proteome as a starting point for designing immunotherapy and vaccine

Abstract

Hepatitis B virus is endemic in Indonesia and causes a range of liver damage. Recently, the development of therapy aiming to improve immune response has gained a priority. T-cell immunity plays an essential role to control viral infections. Cytotoxic CD8+ T-cells are responsible for the elimination of virus-infected cells, while CD4+ T-cells are essential for the regulation and maintenance of immune responses and the production of cytokines. T-cells recognize peptides derived from the HBV proteins as a complex with HLA (human leukocyte antigen) on the surface of the infected cells. The strong link between HBV genotype and the ethnicity of the population suggests that immunotherapy needs to be based on the epitopes derived from the prevalent viral strain and presented by the prevalent HLA types in the related population. In this study, immunoinformatic prediction using netMHCpan and netMHCIIpan were used to identify T-cell epitopes from the major HBV genotypes in Indonesia. The likelihood that the predicted peptides will be processed inside the cells was assessed using the netCTLpan server. Other prediction tools housed in the IEDB server were employed to generate a consensus result. BLAST analysis was done to exclude epitopes that resemble human self-peptides. The epitope conservancy analysis and population coverage were carried out using tools in IEDB. The set of promiscuous epitopes that bind to HLA Class I and II predominant in the Indonesian population were identified. These epitopes could be used as a starting point to develop a new and more efficient vaccine and immunotherapies against HBV.