ArticleCommunications biology2021
Connecting MHC-I-binding motifs with HLA alleles via deep learning.
Article in Communications biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Advancing human leukocyte antigen-based cancer immunotherapy: from personalized to broad-spectrum strategies for genetically heterogeneous populations.Trends in cancer · 2025Review
- A small set of critical hyper-motifs governs heterogeneous flow-weighted network resilience.Nature communications · 2025Article
- PepCARES: A Comprehensive Advanced Refinement and Evaluation System for Peptide Design and Affinity Screening.ACS omega · 2024Article
- Building trust in deep learning-based immune response predictors with interpretable explanations.Communications biology · 2024Article
- ERAP1 and ERAP2 Haplotypes Influence Suboptimal HLA-B*27:05-Restricted Anti-Viral CD8+ T Cell Responses Cross-Reactive to Self-Epitopes.International journal of molecular sciences · 2023Article
- Decoupling peptide binding from T cell receptor recognition with engineered chimeric MHC-I molecules.Frontiers in immunology · 2023Article
- Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications.International journal of molecular sciences · 2022Article
- Individual HLA heterogeneity and its implications for cellular immune evasion in cancer and beyond.Frontiers in immunology · 2022Review
- Connecting MHC-I-binding motifs with HLA alleles via deep learning.Communications biology · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
The selection of peptides presented by MHC molecules is crucial for antigen discovery. Previously, several predictors have shown impressive performance on binding affinity. However, the decisive MHC residues and their relation to the selection of binding peptides are still unrevealed. Here, we connected HLA alleles with binding motifs via our deep learning-based framework, MHCfovea. MHCfovea expanded the knowledge of MHC-I-binding motifs from 150 to 13,008 alleles. After clustering N-terminal and C-terminal sub-motifs on both observed and unobserved alleles, MHCfovea calculated the hyper-motifs and the corresponding allele signatures on the important positions to disclose the relation between binding motifs and MHC-I sequences. MHCfovea delivered 32 pairs of hyper-motifs and allele signatures (HLA-A: 13, HLA-B: 12, and HLA-C: 7). The paired hyper-motifs and allele signatures disclosed the critical polymorphic residues that determine the binding preference, which are believed to be valuable for antigen discovery and vaccine design when allele specificity is concerned.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.