info:eu-repo/semantics/article
Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
Fecha
2016-07Registro en:
Rasmussen, Michael; Fenoy, Luis Emilio; Harndahl, Mikkel; Kristensen, Anne Bregnballe; Nielsen, Ida Kallehauge; et al.; Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity; American Association of Immunologists; Journal of Immunology; 197; 4; 7-2016; 1517-1524
0022-1767
CONICET Digital
CONICET
Autor
Rasmussen, Michael
Fenoy, Luis Emilio
Harndahl, Mikkel
Kristensen, Anne Bregnballe
Nielsen, Ida Kallehauge
Nielsen, Morten
Buus, Søren
Resumen
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 http://www.cbs.dtu.dk/services/NetMHCstabpan.