T-cell epitope prediction with combinatorial peptide libraries.
T cell receptors (TCR) recognize antigenic peptides in complex with the major histocompatibility complex (MHC) molecules and this trimolecular interaction initiates antigen-specific signaling pathways in the responding T lymphocytes. For the study of autoimmune diseases and vaccine development, it is important to identify peptides (epitopes) that can stimulate a given TCR. The use of combinatorial peptide libraries has recently been introduced as a powerful tool for this purpose. A combinatorial library of n-mer peptides is a set of complex mixtures each characterized by one position fixed to be a specified amino acid and all other positions randomized. A given TCR can be fingerprinted by screening a variety of combinatorial libraries using a proliferation assay. Here, we present statistical models for elucidating the recognition profile of a TCR using combinatorial library proliferation assay data and known MHC binding data.
Sung
Myong-Hee
MH
Molecular Statistics and Bioinformatics Section, Biometric Research Branch, National Cancer Institute, National Institutes of Health, 6130 Executive Boulevard, EPN 8146, MSC 7434, Bethesda, MD 20892-7434, USA.
Zhao
Yingdong
Y
Martin
Roland
R
Simon
Richard
R
D020650:Combinatorial Chemistry Techniques; D018984:Epitopes, T-Lymphocyte / Q000032:analysis*; D006801:Humans; D008024:Ligands; D008213:Lymphocyte Activation; D019151:Peptide Library; D011948:Receptors, Antigen, T-Cell / Q000276:immunology
D018984:Epitopes, T-Lymphocyte; D008024:Ligands; D019151:Peptide Library; D011948:Receptors, Antigen, T-Cell