Evidence map›Paper›PMID 42248582›Full record

ArticleBriefings in bioinformatics2026

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

Jiadong Lu, Xinyuan Zhu, Xinting Hu, Cheng Zhang, Fuli Feng

Abstract read
In one paragraph

Article in Briefings in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jiadong LuSchool of Artificial Intelligence and Data Science, University of Science and Technology of China, Huangshan Road, Shushan District, Hefei 230027, Anhui, China.ORCID 0009-0002-9804-0651
Xinyuan ZhuSchool of Information Science and Technology, University of Science and Technology of China, Huangshan Road, Shushan District, Hefei 230027, Anhui, China.
Xinting HuSchool of Artificial Intelligence and Data Science, University of Science and Technology of China, Huangshan Road, Shushan District, Hefei 230027, Anhui, China.
Cheng ZhangBioscience and Biomedical Engineering Thrust, The Hong Kong University of Science and Technology (Guangzhou), Duxue Road, Nansha District, Guangzhou 511458, Guangdong, China.
Fuli FengSchool of Artificial Intelligence and Data Science, University of Science and Technology of China, Huangshan Road, Shushan District, Hefei 230027, Anhui, China.

Funding

Key Science & Technology Project of Anhui Province 202523n10050009
6 · The paper itself

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.

Indexed as

Complementarity Determining RegionsMajor Histocompatibility ComplexPeptidesReceptors, Antigen, T-CellBenchmarkingHumansImmunoinformaticsModels, MolecularProtein ConformationComplementarity Determining RegionsPeptidesReceptors, Antigen, T-CellAlphaFoldbenchmarkprotein structure predictionTCR–pMHC

Identifiers

PMID42248582
PMCPMC13240595

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.