HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes

• Published in: Nature communications Vol. 14; no. 1; pp. 6349 - 13
• Main Authors: Gupta, Sagar, Nerli, Santrupti, Kutti Kandy, Sreeja, Mersky, Glenn L., Sgourakis, Nikolaos G.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 10.10.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/2411; 631/535/1267; Allotypes; Annotations; Antigens; Cell surface; Cross-reactivity; Epitopes; Epitopes, T-Lymphocyte; Histocompatibility antigen HLA; Histocompatibility Antigens; Histocompatibility Antigens Class I - metabolism; Humanities and Social Sciences; Humans; Immunogenicity; Immunosurveillance; Lymphocytes; Lymphocytes T; Major histocompatibility complex; Modelling; multidisciplinary; Peptides; Peptides - chemistry; Predictions; Proteins; Receptors; Receptors, Antigen, T-Cell; Regression models; Science; Science (multidisciplinary); T cell receptors
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-023-42163-z

The class I proteins of the major histocompatibility complex (MHC-I) display epitopic peptides derived from endogenous proteins on the cell surface for immune surveillance. Accurate modeling of peptides bound to the human MHC, HLA, has been mired by conformational diversity of the central peptide residues, which are critical for recognition by T cell receptors. Here, analysis of X-ray crystal structures within our curated database (HLA3DB) shows that pHLA complexes encompassing multiple HLA allotypes present a discrete set of peptide backbone conformations. Leveraging these backbones, we employ a regression model trained on terms of a physically relevant energy function to develop a comparative modeling approach for nonamer pHLA structures named RepPred. Our method outperforms the top pHLA modeling approach by up to 19% in structural accuracy, and consistently predicts blind targets not included in our training set. Insights from our work may be applied towards predicting antigen immunogenicity, and receptor cross-reactivity. Structure prediction of peptide/HLA (pHLA) complexes has been mired by the inability to accurately model the middle of the peptide. Here, the authors present a curated database of pHLA structures (HLA3DB) and identify discrete peptide backbone conformations that are used for high fidelity modelling.