ArticleCommunications biology2025
T-cell receptor structures and predictive models reveal comparable alpha and beta chain structural diversity despite differing genetic complexity.
Article in Communications biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Article
- Structural T-Cell Receptor Analysis in the Age of Machine Learning.Immunological reviews · 2026Review
- Structure-based TCR-pMHC binding prediction and generalization to unseen peptides.npj drug discovery · 2026Article
- A comparative and exploratory analysis of computational methods for TCR structural prediction and antigen-specific TCR discovery.Briefings in bioinformatics · 2026Article
- Mapping the TCR landscape: computational tools empowering translational immunology and therapy design.Journal for immunotherapy of cancer · 2026Review
- Emerging strategies to reduce the side effects of CAR-T cell therapy: focusing on gene editing and nanotechnology.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Decoding adaptive immunity: advanced strategies in T and B cell repertoire analysis.Journal of translational medicine · 2026Review
- Antibody Screening and Binding Prediction Analysis Targeting Stx2.Antibodies (Basel, Switzerland) · 2026Article
- AlphaFold-RandomWalk and AlphaFold-Ensemble: Sampling Alternative Protein Conformations with Perturbed Versions of AlphaFold.Journal of chemical information and modeling · 2026Article
- Decoding autoimmune disease with single-cell immune repertoire and transcriptome sequencing: mechanisms and therapeutic opportunities.Frontiers in immunology · 2026Review
- Lymphodepleting chemotherapy potentiates neoantigen-directed T cell therapy by enhancing antigen presentation.Cell reports. Medicine · 2025Article
- STCRpy: a software suite for T-cell receptor structure parsing, interaction profiling, and machine learning dataset preparation.Bioinformatics (Oxford, England) · 2025Article
- GRAPE: graph-regularized protein language modeling unlocks TCR-epitope binding specificity.Briefings in bioinformatics · 2025Article
- Predicting the conformational flexibility of antibody and T cell receptor complementarity-determining regions.Nature machine intelligence · 2025Article
- Quantifying conformational changes in the TCR:pMHC-I binding interface.Frontiers in immunology · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
T-cell receptor (TCR) structures are currently under-utilised in early-stage drug discovery and repertoire-scale informatics. Here, we leverage a large dataset of solved TCR structures from Immunocore to evaluate the current state-of-the-art for TCR structure prediction, and identify which regions of the TCR remain challenging to model. Through clustering analyses and the training of a TCR-specific model capable of large-scale structure prediction, we find that the alpha chain VJ-recombined loop (CDR3α) is as structurally diverse and correspondingly difficult to predict as the beta chain VDJ-recombined loop (CDR3β). This differentiates TCR variable domain loops from the genetically analogous antibody loops and supports the conjecture that both TCR alpha and beta chains are deterministic of antigen specificity. We hypothesise that the larger number of alpha chain joining genes compared to beta chain joining genes compensates for the lack of a diversity gene segment. We also provide over 1.5M predicted TCR structures to enable repertoire structural analysis and elucidate strategies towards improving the accuracy of future TCR structure predictors. Our observations reinforce the importance of paired TCR sequence information and capture the current state-of-the-art for TCR structure prediction, while our model and 1.5M structure predictions enable the use of structural TCR information at an unprecedented scale.
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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.