Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Standard
Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity. / Rasmussen, Michael; Fenoy, Emilio; Harndahl, Mikkel; Kristensen, Anne Bregnballe; Nielsen, Ida Kallehauge; Nielsen, Morten Milek; Buus, Søren.
I: Journal of Immunology, Bind 197, Nr. 4, 15.08.2016, s. 1517-1524.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - JOUR
T1 - Pan-specific prediction of peptide-MHC Class I complex stability, a correlate of T cell immunogenicity
AU - Rasmussen, Michael
AU - Fenoy, Emilio
AU - Harndahl, Mikkel
AU - Kristensen, Anne Bregnballe
AU - Nielsen, Ida Kallehauge
AU - Nielsen, Morten Milek
AU - Buus, Søren
PY - 2016/8/15
Y1 - 2016/8/15
N2 - 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.
AB - 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.
U2 - 10.4049/jimmunol.1600582
DO - 10.4049/jimmunol.1600582
M3 - Journal article
C2 - 27402703
AN - SCOPUS:84983738683
VL - 197
SP - 1517
EP - 1524
JO - Journal of Immunology
JF - Journal of Immunology
SN - 0022-1767
IS - 4
ER -
ID: 168933628