NetMHCpan - 4.0

Pan-specific binding of peptides to MHC class I alleles of known sequence

Prediction of peptide-MHC class I binding using artificial neural networks (ANNs).

New in this version: the method is trained on naturally eluted ligands AND on binding affinity data. It returns two properties: either the likelihood of a peptide becoming a natural ligands, or the predicted binding affinity.

NetMHCpan server predicts binding of peptides to any MHC molecule of known sequence using artificial neural networks (ANNs). The method is trained on a combinatino of more than 180,000 quantitative binding data and MS derived MHC eluted ligands. The binding affinity data covers 172 MHC molecules from human (HLA-A, B, C, E), mouse (H-2), cattle (BoLA), primates (Patr, Mamu, Gogo) and swine (SLA). The MS eluted ligand data covers 55 HLA and mouse allelee. Furthermore, the user can obtain redictions to the any custom MHC class I molecule by uploading a full length MHC protein sequence.

Predictions can be made for peptides of any length.

11-03-2019: Server updated to have precalculated percentile rank values and binding motifs for all HLA alleles included in the latest IMGT HLA release

The project is a collaboration between CBS, ISIM, and LIAI.


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