ArticleFrontiers in immunology2020
Unbiased Characterization of Peptide-HLA Class II Interactions Based on Large-Scale Peptide Microarrays; Assessment of the Impact on HLA Class II Ligand and Epitope Prediction.
Article in Frontiers in immunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 11 citations in OpenAlex.
- AI-Driven Discovery and Design of Antimicrobial Peptides: Progress, Challenges, and Opportunities.Probiotics and antimicrobial proteins · 2026Review
- In Silico-Identified Peptides of FiveBiology · 2026Article
- Mass Spectrometry-Based Immunopeptidomics of Peptides Presented on Human Leukocyte Antigen Proteins.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Vaccines for immunoprevention of DNA mismatch repair deficient cancers.Journal for immunotherapy of cancer · 2022Review
- HLA Class II Presentation Is Specifically Altered at Elevated Temperatures in the B-Lymphoblastic Cell Line JY.Molecular & cellular proteomics : MCP · 2021Article
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human Leukocyte Antigen class II (HLA-II) molecules present peptides to T lymphocytes and play an important role in adaptive immune responses. Characterizing the binding specificity of single HLA-II molecules has profound impacts for understanding cellular immunity, identifying the cause of autoimmune diseases, for immunotherapeutics, and vaccine development. Here, novel high-density peptide microarray technology combined with machine learning techniques were used to address this task at an unprecedented level of high-throughput. Microarrays with over 200,000 defined peptides were assayed with four exemplary HLA-II molecules. Machine learning was applied to mine the signals. The comparison of identified binding motifs, and power for predicting eluted ligands and CD4+ epitope datasets to that obtained using NetMHCIIpan-3.2, confirmed a high quality of the chip readout. These results suggest that the proposed microarray technology offers a novel and unique platform for large-scale unbiased interrogation of peptide binding preferences of HLA-II molecules.
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Registered trials
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