Bioinformatics tools for epitope prediction

Abstract

Immunological protection is conferred by immune cells, i.e., B and T cells, which can efficiently develop pathogen-specific memory and thus involved in adaptive immunity. More specifically, these immune cells can recognize a specific portion of their respective antigens termed as epitopes which possess their own significant values. There is a noble reason to identify the antigenic region of an antigen as it is having a great empirical cause, which includes exploration of disease etiology, the advancement of diagnosis assays, immune monitoring, and to design epitope-based vaccines. It requires detection and prediction of epitopes which is a considerable concern in the preparation of a peptide-based vaccine that is the centralized issue of immunoinformatics. Experimental screening is involved for large arrays of probable epitope candidates; thereby it is pricey and tedious. There is a requirement of more-advanced immunoinformatics tools as a prodigious amount of information has accumulated because of the onset of next-generation sequencing approaches for collection, analysis, and interpretation of data. Further, development of in silico epitope prediction methods has substantially reduced the difficulties related to epitope mapping by shortening potential epitope candidates list for experimental testing. These software tools have diverse applications in diagnosis of infectious diseases and allergies, understanding immune system function, vaccine designing, and prognosis of cancer. This chapter presents an outlook on how these tools are capable to predict epitopes of various antigens.