ReviewFrontiers in immunology2013
Structure-Based, Rational Design of T Cell Receptors.
Review in Frontiers in immunology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.
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Who cites it
46 citing papers in PubMed, 63 citations in OpenAlex.
- Structural T-Cell Receptor Analysis in the Age of Machine Learning.Immunological reviews · 2026Review
- Benchmarking AlphaFold and related deep learning approaches for modeling antibody and TCR antigen recognition.bioRxiv : the preprint server for biology · 2026Article
- Targeting peptide-MHC complexes with designed T cell receptors and antibodies.bioRxiv : the preprint server for biology · 2025Article
- Phage display enables machine learning discovery of cancer antigen-specific TCRs.Science advances · 2025Article
- A fingerprint approach to pioneer structure-based T cell receptor repertoire analysis and specificity prediction.Frontiers in immunology · 2025Article
- Preclinical model for evaluating human TCRs against chimeric syngeneic tumors.Journal for immunotherapy of cancer · 2024Article
- TCR-T cell therapy: current development approaches, preclinical evaluation, and perspectives on regulatory challenges.Journal of translational medicine · 2024Review
- Article
- Exploring the potential of structure-based deep learning approaches for T cell receptor design.PLoS computational biology · 2024Article
- Exploring the Potential of Structure-Based Deep Learning Approaches for T cell Receptor Design.bioRxiv : the preprint server for biology · 2024Article
- Combining SiRPα decoy-coengineered T cells and antibodies augments macrophage-mediated phagocytosis of tumor cells.The Journal of clinical investigation · 2024Article
- Strategies and rules for tuning TCR-derived therapy.Expert reviews in molecular medicine · 2023Review
- TCR-engineered T cell therapy in solid tumors: State of the art and perspectives.Science advances · 2023Review
- Current Trends and Changes in Use of Membrane Molecular Dynamics Simulations within Academia and the Pharmaceutical Industry.Membranes · 2023Review
- CrossDome: an interactive R package to predict cross-reactivity risk using immunopeptidomics databases.Frontiers in immunology · 2023Article
- Quantitative immunopeptidomics reveals a tumor stroma-specific target for T cell therapy.Science translational medicine · 2022Article
- Engineering the T cell receptor for fun and profit: Uncovering complex biology, interrogating the immune system, and targeting disease.Current opinion in structural biology · 2022Review
- ReliableJournal of chemical information and modeling · 2022Article
- Engineering soluble T-cell receptors for therapy.The FEBS journal · 2021Review
- Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Adoptive cell transfer using engineered T cells is emerging as a promising treatment for metastatic melanoma. Such an approach allows one to introduce T cell receptor (TCR) modifications that, while maintaining the specificity for the targeted antigen, can enhance the binding and kinetic parameters for the interaction with peptides (p) bound to major histocompatibility complexes (MHC). Using the well-characterized 2C TCR/SIYR/H-2K(b) structure as a model system, we demonstrated that a binding free energy decomposition based on the MM-GBSA approach provides a detailed and reliable description of the TCR/pMHC interactions at the structural and thermodynamic levels. Starting from this result, we developed a new structure-based approach, to rationally design new TCR sequences, and applied it to the BC1 TCR targeting the HLA-A2 restricted NY-ESO-1157-165 cancer-testis epitope. Fifty-four percent of the designed sequence replacements exhibited improved pMHC binding as compared to the native TCR, with up to 150-fold increase in affinity, while preserving specificity. Genetically engineered CD8(+) T cells expressing these modified TCRs showed an improved functional activity compared to those expressing BC1 TCR. We measured maximum levels of activities for TCRs within the upper limit of natural affinity, K D = ∼1 - 5 μM. Beyond the affinity threshold at K D < 1 μM we observed an attenuation in cellular function, in line with the "half-life" model of T cell activation. Our computer-aided protein-engineering approach requires the 3D-structure of the TCR-pMHC complex of interest, which can be obtained from X-ray crystallography. We have also developed a homology modeling-based approach, TCRep 3D, to obtain accurate structural models of any TCR-pMHC complexes when experimental data is not available. Since the accuracy of the models depends on the prediction of the TCR orientation over pMHC, we have complemented the approach with a simplified rigid method to predict this orientation and successfully assessed it using all non-redundant TCR-pMHC crystal structures available. These methods potentially extend the use of our TCR engineering method to entire TCR repertoires for which no X-ray structure is available. We have also performed a steered molecular dynamics study of the unbinding of the TCR-pMHC complex to get a better understanding of how TCRs interact with pMHCs. This entire rational TCR design pipeline is now being used to produce rationally optimized TCRs for adoptive cell therapies of stage IV melanoma.
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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.