Predicting MHC class I epitopes in large datasets

Background: Experimental screening of large sets of peptides with respect to their MHC binding capabilities is still very demanding due to the large number of possible peptide sequences and the extensive polymorphism of the MHC proteins. Therefore, there is significant interest in the development of computational methods for predicting the binding capability of peptides to MHC molecules, as a first step towards selecting peptides for actual screening. Results: We have examined the performance of four diverse MHC Class I prediction methods on comparatively large HLA-A and HLA-B allele peptide binding datasets extracted from the Immune Epitope Database and Analysis resource (IEDB). The chosen methods span a representative cross-section of available methodology for MHC binding predictions. Until the development of IEDB, such an analysis was not possible, as the available peptide sequence datasets were small and spread out over many separate efforts. We tested three datasets which differ ...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Kirsten Roomp, Iris Antes, Thomas Lengauer
• Keywords: BMCBI 2010, MHC Binding Capabilities, Peptide, Peptide Sequence