In Silico prediction and validation of unique antigenic epitopes from Human Pegivirus (HPgV) for possible immunodiagnostic applications

Nick Austin A. Bayot
Nier Byron B. Reyes
Maria Athena G. Villarroel


The human pegivirus (HPgV) has been detected worldwide with about 3% of the world population being infected and approximately 12-15% individuals with common hepatitis infections have been co-infected with HPgV. As the discovery of HPgV is still recent, detection of the virus through immunodiagnostic tests within infected individuals is limited and prone to inaccurate results due to structurally similar epitopes existing in other hepatitis viruses. At this end, the study aims to perform in-depth prediction and validation of unique antigenic epitopes from selected candidate nonstructural (NS) proteins (NS5A, NS5B, NS4A, NS4B, NS3, NS2) of HPgV via in silico methods. The antigenicity, hydrophilicity, and surface accessibility scores of each candidate epitope from the NS proteins were determined using the IEDB software. Sequentially, the uniqueness of the epitopes were evaluated using the BLASTp tool. From the 2,135 generated epitopes screened, the peptides 244QQVDYCDKVSAV255, 46QATPQPVVQVPP57, 223MGLPVVARRGDE234, 66QLKEPVYSTKLC77, 76SASDDVTVYPLP87, 58RVHDKYLVDSIE69, and 59VHDKYLVDSIER70 were determined to be unique and highly antigenic. These epitopes can potentially contribute to the improvement of immunodiagnostic tests in detecting various hepatitis viruses. Specifically, the predicted epitopes that are highly unique and antigenic to HPgV can potentially minimize crossreactivity issues thereby allowing molecular HPgV detection to be more specific and highly reliable. Future research directions of this study include the in vivo antigenicity and immunogenicity analysis of the peptides to further validate the results of the study.