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◆ Briefings in Bioinformatics2026-05-01· Benchmarking

Benchmarking TCR–pMHC structure prediction: a unified evaluation and CDR3-based functional insights

J D Lu, Xinyuan Zhu, Xinting Hu, Cheng Zhang, Fuli Feng

原始摘要(英文原文)· Original abstract
Interactions between T cell receptors (TCRs) and peptide-major histocompatibility complexes (pMHCs) are central to adaptive immunity. Recent advances in structure prediction tools have enabled atomic-level modeling of TCR-pMHC interactions. However, the lack of systematic evaluation forces practitioners to invest substantial resources in selecting appropriate tools. Here, we present a comprehensive benchmark of TCR-pMHC structure prediction with 70 previously unseen complexes and 13 models spanning MSA-based, PLM-based, and docking-based approaches, revealing the superior modeling accuracy and docking quality of MSA-based methods, especially AlphaFold3. To further enhance the utility of AlphaFold3 predictions, we identify the pLDDT score of the TCR CDR3 region as an informative indicator of both structural correctness and functional relevance. Specifically, it enables up to 4.3% Top-1 success gain through reranking and captures mutation-induced affinity changes in 75.3% of cases. Overall, our analysis would facilitate the practical usage of immune structure prediction models and guide the advancement of these models.
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Benchmarking TCR–pMHC structure prediction: a unified evaluation and CDR3-based functional insights — 科研速览 Science Skim