ArticleProtein engineering, design & selection : PEDS2016
A generalized framework for computational design and mutational scanning of T-cell receptor binding interfaces.
Article in Protein engineering, design & selection : PEDS, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
22 citing papers in PubMed, 23 citations in OpenAlex.
- 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
- Article
- STCRpy: a software suite for T-cell receptor structure parsing, interaction profiling, and machine learning dataset preparation.Bioinformatics (Oxford, England) · 2025Article
- Exploring the potential of structure-based deep learning approaches for T cell receptor design.PLoS computational biology · 2024Article
- Can AlphaFold's breakthrough in protein structure help decode the fundamental principles of adaptive cellular immunity?Nature methods · 2024Review
- Exploring the Potential of Structure-Based Deep Learning Approaches for T cell Receptor Design.bioRxiv : the preprint server for biology · 2024Article
- TCR-engineered T cell therapy in solid tumors: State of the art and perspectives.Science advances · 2023Review
- HLA-A∗02-gated safety switch for cancer therapy has exquisite specificity for its allelic target antigen.Molecular therapy oncolytics · 2022Article
- Structural insights into engineering a T-cell receptor targeting MAGE-A10 with higher affinity and specificity for cancer immunotherapy.Journal for immunotherapy of cancer · 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
- Adoptive T cell therapy: Boosting the immune system to fight cancer.Seminars in immunology · 2020Review
- Predicting Cross-Reactivity and Antigen Specificity of T Cell Receptors.Frontiers in immunology · 2020Review
- Understanding TCR affinity, antigen specificity, and cross-reactivity to improve TCR gene-modified T cells for cancer immunotherapy.Cancer immunology, immunotherapy : CII · 2019Review
- Improving T Cell Receptor On-Target Specificity via Structure-Guided Design.Molecular therapy : the journal of the American Society of Gene Therapy · 2019Article
- Molecular properties of gp100-reactive T-cell receptors drive the cytokine profile and antitumor efficacy of transgenic host T cells.Pigment cell & melanoma research · 2019Article
- The intersection of affinity and specificity in the development and optimization of T cell receptor based therapeutics.Seminars in cell & developmental biology · 2018Review
- T cell receptor cross-reactivity expanded by dramatic peptide-MHC adaptability.Nature chemical biology · 2018Article
- STCRDab: the structural T-cell receptor database.Nucleic acids research · 2018Article
- Integrating Experiment and Theory to Understand TCR-pMHC Dynamics.Frontiers in immunology · 2018Review
- ATLAS: A database linking binding affinities with structures for wild-type and mutant TCR-pMHC complexes.Proteins · 2017Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
T-cell receptors (TCRs) have emerged as a new class of therapeutics, most prominently for cancer where they are the key components of new cellular therapies as well as soluble biologics. Many studies have generated high affinity TCRs in order to enhance sensitivity. Recent outcomes, however, have suggested that fine manipulation of TCR binding, with an emphasis on specificity may be more valuable than large affinity increments. Structure-guided design is ideally suited for this role, and here we studied the generality of structure-guided design as applied to TCRs. We found that a previous approach, which successfully optimized the binding of a therapeutic TCR, had poor accuracy when applied to a broader set of TCR interfaces. We thus sought to develop a more general purpose TCR design framework. After assembling a large dataset of experimental data spanning multiple interfaces, we trained a new scoring function that accounted for unique features of each interface. Together with other improvements, such as explicit inclusion of molecular flexibility, this permitted the design new affinity-enhancing mutations in multiple TCRs, including those not used in training. Our approach also captured the impacts of mutations and substitutions in the peptide/MHC ligand, and recapitulated recent findings regarding TCR specificity, indicating utility in more general mutational scanning of TCR-pMHC interfaces.
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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.