PXD015240 is an
original dataset announced via ProteomeXchange.
Dataset Summary
Title | NNAlign_MA; MHC peptidome deconvolution for accurate MHC binding motif characterization and improved T cell epitope predictions |
Description | Current mass spectrometry technologies allow for identification of MHC-associated peptide ligands. Studies have proven these data to be a rich source of information for learning the rules of MHC-mediated antigen presentation. Such immunopeptidomes are usually poly-specific, containing multiple sequence motifs matching the MHC molecules expressed in the system under investigation. Motif deconvolution -the process of associating each ligand to its presenting MHC molecule(s)- is a critical and challenging step in the analysis of MS-eluted MHC ligand data. Here, we describe NNAlign_MA, a computational method designed to address this challenge. NNAlign_MA simultaneously performs the tasks of i) clustering peptides into individual specificities; ii) automatic annotation of each cluster to an MHC molecule; and iii) training of a prediction model covering all MHCs present in the training set. NNAlign_MA was benchmarked on large and diverse datasets, covering class I and class II data. In all cases, the method was demonstrated to outperform state-of-the-art methods, effectively expanding the coverage of alleles for which accurate predictions can be made, resulting in improved identification of both eluted ligands and T cellepitopes. Given its high flexibility and ease of use, we expect NNAlign_MA to serve as an effective tool to increase our understanding of the rules of MHC antigen presentation and guide the development of novel T cell-based therapeutics. |
HostingRepository | PRIDE |
AnnounceDate | 2024-10-08 |
AnnouncementXML | Submission_2024-10-08_11:38:36.189.xml |
DigitalObjectIdentifier | https://dx.doi.org/10.6019/PXD015240 |
ReviewLevel | Peer-reviewed dataset |
DatasetOrigin | Original dataset |
RepositorySupport | Supported dataset by repository |
PrimarySubmitter | Nicola Ternette |
SpeciesList | scientific name: Bos taurus (Bovine); NCBI TaxID: 9913; |
ModificationList | GG; Crotonaldehyde; Amidated; Diethyl; Cys->Dha; Hex; Thiazolidine; Methylphosphonate; Ethanolyl; Propionamide; Phospho; Deamidated; Acetyl; Trp->Oxolactone; Myristoyl; Cation:Ni[II]; Methylthio; Carboxymethyl; HexNAc; Glycosyl; Carbamidomethyl; Cysteinyl; Gln->pyro-Glu; Met->Hsl; Trioxidation; Guanidinyl; Glu->pyro-Glu; DAET; Carboxyethyl; Hydroxymethyl; Dehydro; Trimethyl; Ethyl; Ammonia-loss; AEBS; Pyridylacetyl; Oxidation; AEC-MAEC; Carboxy; Pyridylethyl; O-pinacolylmethylphosphonate; MolybdopterinGD; Ethanolamine; Didehydro; Cation:Na; Trp->Kynurenin; Hydroxytrimethyl; Pro->Pyrrolidinone; Sulfo; Iminobiotin; SMA; Deoxy; HexN; Methyl+Deamidated; Nmethylmaleimide; Glutathione; Formyl; Carbamyl; Lys->Allysine; 3-deoxyglucosone; Amidine; Amino; Ammonium; Dehydrated; Biotin; Dioxidation; Xlink:DTSSP[88]; Lipoyl; glycidamide; Pro->Pyrrolidone |
Instrument | Orbitrap Fusion Lumos |
Dataset History
Revision | Datetime | Status | ChangeLog Entry |
0 | 2019-08-30 02:05:58 | ID requested | |
⏵ 1 | 2024-10-08 11:38:37 | announced | |
Publication List
10.6019/PXD015240; |
Alvarez B, Reynisson B, Barra C, Buus S, Ternette N, Connelley T, Andreatta M, Nielsen M, NNAlign_MA |
MHC Peptidome Deconvolution for Accurate MHC Binding Motif Characterization and Improved T-cell Epitope Predictions. Mol Cell Proteomics, 18(12):2459-2477(2019) [pubmed] |
10.1074/mcp.tir119.001658; |
Keyword List
submitter keyword: Immunopeptidomics, BoLA ligandome |
Contact List
Nicola Ternette |
contact affiliation | University of Oxford |
contact email | nicola.ternette@ndm.ox.ac.uk |
lab head | |
Nicola Ternette |
contact affiliation | University of Oxford |
contact email | nicola.ternette@ndm.ox.ac.uk |
dataset submitter | |
Full Dataset Link List
Dataset FTP location
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PRIDE project URI |
Repository Record List
[ + ]
[ - ]
- PRIDE
- PXD015240
- Label: PRIDE project
- Name: NNAlign_MA; MHC peptidome deconvolution for accurate MHC binding motif characterization and improved T cell epitope predictions