3 - Use of Bioinformatics to Predict MHC Ligands and T-Cell Epitopes: Application to Epitope-Driven Vaccine Design

Abstract

This chapter discusses use of bioinformatics to predict MHC ligands and T-cell epitopes. At the heart of the bioinformatics discipline is the concept that biological entity that is described as being composed of patterns. These patterns can be discovered, described, and interpreted using computer-driven algorithms, enabling the discovery and comparison of biological entities as well as approximate predictions of their functions. One useful application of pattern matching algorithms is in the identification of major histocompatibility complex (MHC) ligands and T-cell epitopes. In addition, the ability to induce an immune response to a broad repertoire of epitopes that are universally recognized across continents and across genetic backgrounds is considered to be a critical characteristic of an effective vaccine. Opportunities for epitope discovery are expanding as the number of entirely sequenced pathogens approaches increases access to these data improves. Cancer therapy and autoimmune disease are two additional fields that may benefit from the application of epitope-mapping tools to novel vaccine design. Over the past decade bioinformatics tools have been systematically applied to whole genomes and are now being used in combination with immunoinformatics methods for screening and confirming epitopes. The chapter also reviews antigens recognition by T-cells.