ArticleMolecular immunology2018
Identification of the cognate peptide-MHC target of T cell receptors using molecular modeling and force field scoring.
Article in Molecular immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- General prediction of T cell receptor antigen specificity from sequence using AlphaFold 3.bioRxiv : the preprint server for biology · 2026Article
- Three-Dimensional Modeling ofAntibodies (Basel, Switzerland) · 2025Article
- A fingerprint approach to pioneer structure-based T cell receptor repertoire analysis and specificity prediction.Frontiers in immunology · 2025Article
- Predicting Antigen-Specificities of Orphan T Cell Receptors from Cancer Patients with TCRpcDist.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Can AlphaFold's breakthrough in protein structure help decode the fundamental principles of adaptive cellular immunity?Nature methods · 2024Review
- Development and characterization of human T-cell receptor (TCR) alpha and beta clones' library as biological standards and resources for TCR sequencing and engineering.Biology methods & protocols · 2024Article
- Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens.Journal of chemical theory and computation · 2023Review
- TCR sequencing: applications in immuno-oncology research.Immuno-oncology technology · 2023Review
- Article
- Rapid Assessment of T-Cell Receptor Specificity of the Immune Repertoire.Nature computational science · 2021Article
- Predicting TCR-Epitope Binding Specificity Using Deep Metric Learning and Multimodal Learning.Genes · 2021Article
- Predicting T Cell Receptor Antigen Specificity From Structural Features Derived From Homology Models of Receptor-Peptide-Major Histocompatibility Complexes.Frontiers in physiology · 2021Article
- Impact of Structural Observables From Simulations to Predict the Effect of Single-Point Mutations in MHC Class II Peptide Binders.Frontiers in molecular biosciences · 2021Article
- T Cell Specificity: A Great Challenge in Chagas Disease.Frontiers in immunology · 2021Review
- T Cell Epitope Prediction and Its Application to Immunotherapy.Frontiers in immunology · 2021Review
- Main Strategies for the Identification of Neoantigens.Cancers · 2020Review
- Immunoinformatics: Predicting Peptide-MHC Binding.Annual review of biomedical data science · 2020Article
- T cell receptor sequence clustering and antigen specificity.Computational and structural biotechnology journal · 2020Review
- Empirical and Rational Design of T Cell Receptor-Based Immunotherapies.Frontiers in immunology · 2020Review
- TCRpMHCmodels: Structural modelling of TCR-pMHC class I complexes.Scientific reports · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Interactions of T cell receptors (TCR) to peptides in complex with MHC (p:MHC) are key features that mediate cellular immune responses. While MHC binding is required for a peptide to be presented to T cells, not all MHC binders are immunogenic. The interaction of a TCR to the p:MHC complex holds a key, but currently poorly comprehended, component for our understanding of this variation in the immunogenicity of MHC binding peptides. Here, we demonstrate that identification of the cognate target of a TCR from a set of p:MHC complexes to a high degree is achievable using simple force-field energy terms. Building a benchmark of TCR:p:MHC complexes where epitopes and non-epitopes are modelled using state-of-the-art molecular modelling tools, scoring p:MHC to a given TCR using force-fields, optimized in a cross-validation setup to evaluate TCR inter atomic interactions involved with each p:MHC, we demonstrate that this approach can successfully be used to distinguish between epitopes and non-epitopes. A detailed analysis of the performance of this force-field-based approach demonstrate that its predictive performance depend on the ability to both accurately predict the binding of the peptide to the MHC and model the TCR:p:MHC complex structure. In summary, we conclude that it is possible to identify the TCR cognate target among different candidate peptides by using a force-field based model, and believe this works could lay the foundation for future work within prediction of TCR:p:MHC interactions.
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Registered trials
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