Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at https://www.cbs.dtu.dk/services/NetMHCstabpan.
Originalsprog | Engelsk |
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Tidsskrift | Journal of Immunology |
Vol/bind | 197 |
Udgave nummer | 4 |
Sider (fra-til) | 1517-1524 |
Antal sider | 8 |
ISSN | 0022-1767 |
DOI | |
Status | Udgivet - 15 aug. 2016 |
ID: 168933628