C-P.23: A Unified Framework for TCR-pMHC Structural Model Assessment
Authors
Alex Ascunce-París
Barcelona Supercomputing Center
Alfonso Valencia
Barcelona Supercomputing Center
Roc Farriol-Duran
Barcelona Supercomputing Center
Victor Guallar
Barcelona Supercomputing Center
Keywords
T cell receptor, TCR-pMHC specificity, Protein modelling, Structural quality assessment, T-cell immunotherapies
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Structural characterization of T cell receptor (TCR) and peptide-MHC complex (pMHC) interactions is fundamental to understanding adaptive immunity. However, the scarcity of experimentally resolved TCR-pMHC structures constrains progress in this field. Computational modelling tools can help bridge this gap, but their predictions are difficult to evaluate reliably without experimental references.
We present a scalable and interpretable framework for reference-free quality assessment of TCR-pMHC class I structural models.
We benchmarked seven state-of-the-art modelling methods on 265 experimentally determined PDB complexes, covering pre- and post-training-cutoff datasets. AlphaFold3 demonstrated superior generalization, achieving over 90% acceptable-quality predictions for structures absent from its training set.
Then, we integrated multiple confidence metrics into a random forest classifier trained on 1,325 AlphaFold3 models, with quality labels derived from their 265 experimental counterparts. The classifier stratifies models into four tiers (low, acceptable, medium, high), outperforming single-metric approaches. SHAP analysis identified pDockQ2 and iPDE as the strongest predictors of structural quality.
Finally, we applied this framework to a VDJdb/TCRvdb-derived subset of validating and non-validating TCR-pMHC pairs, and to IMMREP23, comprising validated positives and synthetic negatives. True binders were consistently enriched in higher quality tiers, confirming that structural quality is a reliable indicator of functional interaction.
Overall, this work contributes a large-scale dataset of evaluated TCR-pMHC structural models (21,775 models from 4,355 complexes; 265 PDB, 609 TCRvdb, 3,484 IMMREP23), and a robust framework for their quality assessment. This will facilitate the curation of structural TCR-pMHC datasets, and downstream applications in immunology and TCR-based therapeutics.
Co-authors: Alex Ascunce-ParÃs, Alfonso Valencia, Roc Farriol-Duran, Victor Guallar
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