ArticleProtein science : a publication of the Protein Society2013
A flexible docking approach for prediction of T cell receptor-peptide-MHC complexes.
Article in Protein science : a publication of the Protein Society, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.
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Who cites it
63 citing papers in PubMed.
- Structural Basis for Clonal Diversity of the Public T Cell Response to a Dominant Human Cytomegalovirus Epitope.The Journal of biological chemistry · 2015Trial
- Toward next-generation therapeutic HPV vaccines: A review on expanding the antigen repertoire and an integrated bioinformatics selection framework.Human vaccines & immunotherapeutics · 2026Review
- 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
- Benchmarking AlphaFold and related deep learning approaches for modeling antibody and TCR antigen recognition.bioRxiv : the preprint server for biology · 2026Article
- TCR-FramePose: a local-frame representation for decomposing global docking and CDR3 loop geometry in TCR-pMHC recognition.bioRxiv : the preprint server for biology · 2026Article
- General prediction of T cell receptor antigen specificity from sequence using AlphaFold 3.bioRxiv : the preprint server for biology · 2026Article
- Benchmarking TCR-pMHC structure prediction: a unified evaluation and CDR3-based functional insights.Briefings in bioinformatics · 2026Article
- Engineered antibodies that stabilize drug-modified KRASNature communications · 2025Article
- Structural insights into clonal restriction and diversity in T cell recognition of two immunodominant SARS-CoV-2 nucleocapsid epitopes.Nature communications · 2025Article
- Article
- Advancing human leukocyte antigen-based cancer immunotherapy: from personalized to broad-spectrum strategies for genetically heterogeneous populations.Trends in cancer · 2025Review
- PInteract: Detecting Aromatic-Involving Motifs in Proteins and Protein-Nucleic Acid Complexes.Biomolecules · 2025Article
- Generation of actionable, cancer-specific neoantigens from KRAS(G12C) with adagrasib.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- A roadmap for T cell receptor-peptide-bound major histocompatibility complex binding prediction by machine learning: glimpse and foresight.Briefings in bioinformatics · 2025Review
- TRain: T-cell receptor automated immunoinformatics.BMC bioinformatics · 2025Article
- STAG-LLM: Predicting TCR-pHLA binding with protein language models and computationally generated 3D structures.Computational and structural biotechnology journal · 2025Article
- Structural characterization and AlphaFold modeling of human T cell receptor recognition of NRAS cancer neoantigens.Science advances · 2024Article
- Molecular basis for antibody recognition of multiple drug-peptide/MHC complexes.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Structural characterization and AlphaFold modeling of human T cell receptor recognition of NRAS cancer neoantigens.bioRxiv : the preprint server for biology · 2024Article
3 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors.
Funding
Abstract
T cell receptors (TCRs) are immune proteins that specifically bind to antigenic molecules, which are often foreign peptides presented by major histocompatibility complex proteins (pMHCs), playing a key role in the cellular immune response. To advance our understanding and modeling of this dynamic immunological event, we assembled a protein-protein docking benchmark consisting of 20 structures of crystallized TCR/pMHC complexes for which unbound structures exist for both TCR and pMHC. We used our benchmark to compare predictive performance using several flexible and rigid backbone TCR/pMHC docking protocols. Our flexible TCR docking algorithm, TCRFlexDock, improved predictive success over the fixed backbone protocol, leading to near-native predictions for 80% of the TCR/pMHC cases among the top 10 models, and 100% of the cases in the top 30 models. We then applied TCRFlexDock to predict the two distinct docking modes recently described for a single TCR bound to two different antigens, and tested several protein modeling scoring functions for prediction of TCR/pMHC binding affinities. This algorithm and benchmark should enable future efforts to predict, and design of uncharacterized TCR/pMHC complexes.
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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.