ArticleNucleic acids research2023
TCRmodel2: high-resolution modeling of T cell receptor recognition using deep learning.
Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers.
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Who cites it
83 citing papers in PubMed, 93 citations in OpenAlex.
- A p53Molecular therapy. Oncology · 2026Article
- Structural T-Cell Receptor Analysis in the Age of Machine Learning.Immunological reviews · 2026Review
- Structural basis for T-cell receptor recognition of p53Acta crystallographica. Section D, Structural biology · 2026Article
- T Cell Thoughts.Immunological reviews · 2026Review
- Structure-based TCR-pMHC binding prediction and generalization to unseen peptides.npj drug discovery · 2026Article
- TcrDesign: de novo design of epitope-specific full-length T cell receptors.Science China. Life sciences · 2026Article
- Ensembles ofbioRxiv : the preprint server for biology · 2026Article
- Computational identification of antigen-specific T cell groups through generative epitope modeling.iScience · 2026Article
- AI-driven neoantigen identification: a comprehensive review from somatic variant calling to T cell recognition.Journal of translational medicine · 2026Review
- Benchmarking AlphaFold and related deep learning approaches for modeling antibody and TCR antigen recognition.bioRxiv : the preprint server for biology · 2026Article
- A comparative and exploratory analysis of computational methods for TCR structural prediction and antigen-specific TCR discovery.Briefings in bioinformatics · 2026Article
- Modeling TCR-Epitope Recognition Specificity: What We Should Learn to Succeed.Immunological reviews · 2026Review
- Computational prediction of TCR cross-reactivity: principles, challenges and translational opportunities.Journal of translational medicine · 2026Review
- Mapping the TCR landscape: computational tools empowering translational immunology and therapy design.Journal for immunotherapy of cancer · 2026Review
- General prediction of T cell receptor antigen specificity from sequence using AlphaFold 3.bioRxiv : the preprint server for biology · 2026Article
- FOXM1-Specific TCR-Engineered T Cells Target Non-Small Cell Lung Cancer.Cancer immunology research · 2026Article
- TCRBinder: Unified pre-trained language model with paired-chain synergy for predicting T-cell receptor binding specificity.PLoS computational biology · 2026Article
- Post-Translational Modifications Modulate the HLA-DR3 Restricted Epitope Landscape of Sjögren's Associated Autoantigens.Medicina (Kaunas, Lithuania) · 2026Article
- AI-aided design of multi-epitope peptide vaccine elicits cellular and humoral immunity to broad Omicron subvariants.Zoological research · 2026Article
- SwiftTCR: efficient computational docking protocol of TCRpMHC-I complexes using restricted rotation matrices.Briefings in bioinformatics · 2026Article
23 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
Abstract
The cellular immune system, which is a critical component of human immunity, uses T cell receptors (TCRs) to recognize antigenic proteins in the form of peptides presented by major histocompatibility complex (MHC) proteins. Accurate definition of the structural basis of TCRs and their engagement of peptide-MHCs can provide major insights into normal and aberrant immunity, and can help guide the design of vaccines and immunotherapeutics. Given the limited amount of experimentally determined TCR-peptide-MHC structures and the vast amount of TCRs within each individual as well as antigenic targets, accurate computational modeling approaches are needed. Here, we report a major update to our web server, TCRmodel, which was originally developed to model unbound TCRs from sequence, to now model TCR-peptide-MHC complexes from sequence, utilizing several adaptations of AlphaFold. This method, named TCRmodel2, allows users to submit sequences through an easy-to-use interface and shows similar or greater accuracy than AlphaFold and other methods to model TCR-peptide-MHC complexes based on benchmarking. It can generate models of complexes in 15 minutes, and output models are provided with confidence scores and an integrated molecular viewer. TCRmodel2 is available at https://tcrmodel.ibbr.umd.edu.
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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.