Abstract
Sequence based T-cell epitope predictions have improved immensely in the last decade. From predictions of peptide binding to major histocompatibility complex molecules with moderate accuracy, limited allele coverage, and no good estimates of the other events in the antigen-processing pathway, the field has evolved significantly. Methods have now been developed that produce highly accurate binding predictions for many alleles and integrate both proteasomal cleavage and transport events. Moreover have so-called pan-specific methods been developed, which allow for prediction of peptide binding to MHC alleles characterized by limited or no peptide binding data. Most of the developed methods are publicly available, and have proven to be very useful as a shortcut in epitope discovery. Here, we will go through some of the history of sequence-based predictions of helper as well as cytotoxic T cell epitopes. We will focus on some of the most accurate methods and their basic background.
Highlights
Sequence based T-cell epitope predictions have improved immensely in the last decade
This million-year old arms race has led to the development of a defense system, the immune system, which itself consists of genetically diverse unicellular components that can evolve within the host organism when put under selective pressure
During or after transport into the endoplasmic reticulum (ER) a potential epitope must bind to the major histocompatibility complex (MHC) class I molecule [18,19] generally facilitated by the helper protein tapasin [20,21], before it can be presented on the cell surface
Summary
MHC peptide-binding data were available for only a few human and mouse alleles. Despite the great advances in the accuracy and allelic coverage of methods for prediction of peptide binding to MHC molecules, a great proportion of recent papers published on the subject of rational T cell epitope discovery apply relatively ancient methods like BIMAS and SYPHITHI for MHC class I and TEPITOPE/ProPred for MHC class II [109]. This is surprising because many benchmark studies have shown that state-of-the-art data-driven methods significantly outperform these older methods when it comes to identification of MHC ligands and T cell epitopes. List of abbreviations HCV: hepatitis C virus; HIV: human immunodeficiency virus; TB: tuberculosis; CTL: cytotoxic T lymphocytes; HTL: helper T lymphocytes; MHC: major histocompatibility complex; HLA: Human Leucocyte Antigen; ER: endoplasmic reticulum; TAP: transporter associated with antigen processing; ANN: artificial neural networks; SVM: support vector machine; IEDB: immune epitope database; TCR: T cell receptor; PSSM: position specific scoring matrix; PFR: peptide flanking region
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