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PXD034773-1

PXD034773 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleMachine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopes
DescriptionCD4+ T cells orchestrate the adaptive immune response against pathogens and cancer by recognizing epitopes presented on MHC-II molecules. The high polymorphism of MHC-II genes represents an important hurdle towards accurate predictions of CD4+ T-cell epitopes in different individuals and different species. Here we generated and curated a dataset of 627,013 unique MHC-II ligands identified by mass spectrometry. This enabled us to determine the binding motifs of 88 MHC-II alleles across human, mouse, cattle and chicken. Analysis of these binding specificities combined with X-ray crystallography refined our understanding of the molecular determinants of MHC-II motifs and revealed a widespread reverse binding mode in MHC-II ligands. We then developed a machine learning framework to accurately predict binding specificities and ligands of any MHC-II allele. This tool improves and expands predictions of CD4+ T-cell epitopes, as demonstrated by the identification of several viral and bacterial epitopes following the aforementioned reverse binding mode.
HostingRepositoryPRIDE
AnnounceDate2023-04-07
AnnouncementXMLSubmission_2023-04-07_10:24:40.272.xml
DigitalObjectIdentifier
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportUnsupported dataset by repository
PrimarySubmitterMichalBassani-Sternberg
SpeciesList scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationListNo PTMs are included in the dataset
InstrumentQ Exactive HF
Dataset History
RevisionDatetimeStatusChangeLog Entry
02022-06-21 01:52:27ID requested
12023-04-07 10:24:40announced
Publication List
Dataset with its publication pending
Keyword List
ProteomeXchange project tag: Human Immuno-Peptidome Project (HUPO-HIPP) (B/D-HPP), Biology/Disease-Driven Human Proteome Project (B/D-HPP), Human Proteome Project
submitter keyword: HLA-II binding motifs, machine learning predictions, HLA-II peptides
Contact List
MichalBassani-Sternberg
contact affiliationLudwig Institute for Cancer Research Lausanne Centre de recherche Agora Rue du Bugnon 25A CH-1011 Lausanne
contact emailmichal.bassani@chuv.ch
lab head
MichalBassani-Sternberg
contact affiliationUNIL/CHUV
contact emailmichal.bassani@chuv.ch
dataset submitter
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Dataset FTP location
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