title: Identifying MHC class I epitopes by predicting the TAP transport efficiency of epitope precursors.
abstract: We are able to make reliable predictions of the efficiency with which peptides of arbitrary lengths will be transported by TAP. The pressure exerted by TAP on Ag presentation thus can be assessed by checking to what extent MHC class I (MHC-I)-presented epitopes can be discriminated from random peptides on the basis of predicted TAP transport efficiencies alone. Best discriminations were obtained when N-terminally prolonged epitope precursor peptides were included and the contribution of the N-terminal residues to the score were down-weighted in comparison with the contribution of the C terminus. We provide evidence that two factors may account for this N-terminal down-weighting: 1) the uncertainty as to which precursors are used in vivo and 2) the coevolution in the C-terminal sequence specificities of TAP and other agents in the pathway, which may vary among the various MHC-I alleles. Combining predictions of MHC-I binding affinities with predictions of TAP transport efficiency led to an improved identification of epitopes, which was not the case when predictions of MHC-I binding affinities were combined with predictions of C-terminal cleavages made by the proteasome.
authors.affiliation: Institut für Biochemie, Charite, Humboldt Universität, Berlin, Germany. bjoern_peters@gmx.net
authors.forename: Björn
authors.initials: B
authors.lastname: Peters
authors.forename: Sascha
authors.initials: S
authors.lastname: Bulik
authors.forename: Robert
authors.initials: R
authors.lastname: Tampe
authors.forename: Peter M
authors.initials: PM
authors.lastname: Van Endert
authors.forename: Hermann-Georg
authors.initials: HG
authors.lastname: Holzhütter
mesh_terms: D018528:ATP-Binding Cassette Transporters / Q000378:metabolism*; D000483:Alleles; D000818:Animals; D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data; D016384:Consensus Sequence / Q000276:immunology; D003546:Cysteine Endopeptidases / Q000378:metabolism; D030562:Databases, Protein / Q000706:statistics & numerical data; D018984:Epitopes, T-Lymphocyte / Q000235:genetics / Q000378:metabolism*; D006680:HLA Antigens / Q000235:genetics / Q000378:metabolism*; D015234:HLA-A Antigens / Q000235:genetics / Q000378:metabolism; D015789:HLA-A2 Antigen; D015395:Histocompatibility Antigens Class I / Q000235:genetics / Q000378:metabolism*; D006801:Humans; D006868:Hydrolysis; D051379:Mice; D018448:Models, Immunological; D009097:Multienzyme Complexes / Q000378:metabolism; D010446:Peptide Fragments / Q000235:genetics / Q000378:metabolism; D019151:Peptide Library; D011237:Predictive Value of Tests; D046988:Proteasome Endopeptidase Complex; D011485:Protein Binding / Q000276:immunology; D011498:Protein Precursors / Q000235:genetics / Q000378:metabolism*
chemical_list: D018528:ATP-Binding Cassette Transporters; D018984:Epitopes, T-Lymphocyte; D006680:HLA Antigens; D015234:HLA-A Antigens; C435939:HLA-A*02:01 antigen; D015789:HLA-A2 Antigen; D015395:Histocompatibility Antigens Class I; D009097:Multienzyme Complexes; D010446:Peptide Fragments; D019151:Peptide Library; D011498:Protein Precursors; D003546:Cysteine Endopeptidases; D046988:Proteasome Endopeptidase Complex