Predictions versus high-throughput experiments in T-cell epitope discovery: competition or synergy?

Abstract

Prediction methods as well as experimental methods for T-cell epitope discovery have developed significantly in recent years. High-throughput experimental methods have made it possible to perform full-length protein scans for epitopes restricted to a limited number of MHC alleles. The high costs and limitations regarding the number of proteins and MHC alleles that are feasibly handled by such experimental methods have made in silico prediction models of high interest. MHC binding prediction methods are today of a very high quality and can predict MHC binding peptides with high accuracy. This is possible for a large range of MHC alleles and relevant length of binding peptides. The predictions can easily be performed for complete proteomes of any size. Prediction methods are still, however, dependent on good experimental methods for validation, and should merely be used as a guide for rational epitope discovery. We expect prediction methods as well as experimental validation methods to continue to develop and that we will soon see clinical trials of products whose development has been guided by prediction methods.

Figure 1. Structural surface representations of MHC class I (A) and MHC class II (B) molecules in complex with peptide shown in stick representation

(A) The peptide is green and the residues in the α chain considered important for peptide binding [73] is colored dust green. The rest of the α chain is dark blue and β-2-microglobulin is light blue. (B) The binding core of the peptide is dark green, and the rest of the peptide is bright green. The residues in the β chain considered important for peptide binding [83] are colored dust green. The rest of the β chain is colored dark blue, and the α chain is light blue. The figure has been created using PyMol with the PDB available templates of an HLA-A*11:01-peptide complex structure, 2HN7 [105] (A) and an HLA-DR1-peptide structure, 1AQD [106] (B).

Figure 2. The Kullback–Leibler binding peptide sequence logo for the HLA-A*30:01 (A) and HLA-A*30:02 (B) alleles is generated using the MHC Motif Viewer website

The Kullback–Leibler information content is plotted along the nonamer. Amino acids with positive influence on binding are plotted on the positive y-axis, and amino acids with a negative influence on binding are plotted on the negative y-axis. The height of each amino acid is determined by their relative contribution to the binding specificity.