PXD044810

PXD044810 is an original dataset announced via ProteomeXchange.

Title	Accurate prediction of antigen presentation for HLA class II across loci using tailored data acquisition and refined machine learning
Description	Accurate prediction of antigen presentation by Human Leukocyte Antigen (HLA) class II molecules is crucial for rational development of immunotherapies and vaccines targeting CD4 T cell activation. So far, most prediction methods for HLA class II antigen presentation have focused on HLA-DR due to limited availability of immunopeptidomics data for HLA-DQ and HLA-DP, while not taking into account alternative peptide binding modes. Here, we present an update to the NetMHCIIpan prediction method which closes the performance gap between all three HLA class II loci. We accomplish this by first integrating large immunopeptidomics datasets describing the HLA class II specificity space across loci using a refined machine learning framework that accommodates inverted peptide binders. Next, we apply targeted immunopeptidomics assays to generate novel data that covers additional HLA-DP specificities. The final method, NetMHCIIpan-4.3, achieves high accuracy and molecular coverage across all HLA class II allotypes.
HostingRepository	PRIDE
AnnounceDate	2025-07-21
AnnouncementXML	Submission_2025-07-20_16:11:15.760.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Hooman Yari
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: 9606;
ModificationList	phosphorylated residue; monosodium salt; acetylated residue; monohydroxylated residue; deamidated residue
Instrument	TripleTOF 5600

Revision	Datetime	Status	ChangeLog Entry
0	2023-08-23 13:35:26	ID requested
⏵ 1	2025-07-20 16:11:16	announced

Nilsson JB, Kaabinejadian S, Yari H, Kester MGD, van Balen P, Hildebrand WH, Nielsen M, Accurate prediction of HLA class II antigen presentation across all loci using tailored data acquisition and refined machine learning. Sci Adv, 9(47):eadj6367(2023) [pubmed]

10.1126/sciadv.adj6367;

submitter keyword: HLA-Class II, NetMHCIIpan-4.3,Antigen Presentation, Machine learning, HLA-DP

William Hildebrand
contact affiliation	University of Oklahoma Health Sciences Center
contact email	william-hildebrand@ouhsc.edu
lab head
Hooman Yari
contact affiliation	University of Oklahoma Health Sciences Center
contact email	hooman-yari@ouhsc.edu
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2025/07/PXD044810

PRIDE project URI

• PRIDE
  1. PXD044810
     1. Label: PRIDE project
     2. Name: Accurate prediction of antigen presentation for HLA class II across loci using tailored data acquisition and refined machine learning