Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers.
Several accurate prediction systems have been developed for prediction of class I major histocompatibility complex (MHC):peptide binding. Most of these are trained on binding affinity data of primarily 9mer peptides. Here, we show how prediction methods trained on 9mer data can be used for accurate binding affinity prediction of peptides of length 8, 10 and 11. The method gives the opportunity to predict peptides with a different length than nine for MHC alleles where no such peptides have been measured. As validation, the performance of this approach is compared to predictors trained on peptides of the peptide length in question. In this validation, the approximation method has an accuracy that is comparable to or better than methods trained on a peptide length identical to the predicted peptides.


BACKGROUND
The algorithm has been implemented in the web-accessible servers NetMHC-3.0: http://www.cbs.dtu.dk/services/NetMHC-3.0, and NetMHCpan-1.1: http://www.cbs.dtu.dk/services/NetMHCpan-1.1
Lundegaard
Claus
C
Center for Biological Sequence Analysis--CBS, Department of Systems Biology, The Technical University of Denmark--DTU, Kemitorvet Build. 208, 2800 Lyngby, Denmark. lunde@cbs.dtu.dk
Lund
Ole
O
Nielsen
Morten
M
D000465:Algorithms; D001185:Artificial Intelligence; D001665:Binding Sites; D015395:Histocompatibility Antigens Class I / Q000737:chemistry*; D010455:Peptides / Q000737:chemistry*; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D020539:Sequence Analysis, Protein / Q000379:methods*; D012984:Software
D015395:Histocompatibility Antigens Class I; D010455:Peptides