| title | EMBER: Predicting TCR--pMHC Binding Without a Docked Complex |
|---|---|
| authors | Lin Ha, Chen Zhou, Haozheng Luo, Han Liu, Xiaoyu Zhang, Yan Chen |
| date | 2026-10-19 |
| venue | arXiv (preprint, not peer reviewed) |
| id | arXiv:2610.27334 |
| affiliation | NWULIST |
| upvotes | 5 (Hugging Face Daily Papers, 2026-11-01) |
| links | abs pdf hf |
| abstract | We propose EMBER, a structure-based framework for TCR--pMHC binding prediction that eliminates the need for a predicted docked complex, and with it the placement error that dominates such predictions. Traditional structure-based predictors utilize the co-folded complex structure of the receptor and the antigen and interpret binding from its contact surface. Consequently, every downstream feature inherits any deviation the structure-prediction tool introduced. Methodologically, EMBER folds the TCR and pMHC independently, encodes them as SE(3)-invariant residue graphs, and compares their learned representations without constructing a shared coordinate frame. A relative pose is therefore not an input of the model, so placement error cannot propagate into the prediction. Computationally, EMBER preprocesses O(N{+}M) monomer folds where a complex-based predictor needs O(NM) operations. Experimentally, under epitope-disjoint evaluation with six retrained baselines, EMBER is first on every metric under all four folding tools, by 0.9 to 14.4% in micro-AUROC, 18.5 to 25.3% in micro-AUPRC and 10.6 to 24.1% in MCC. Its ranking is also up to 85% more stable across folding tools. |
cite
@misc{ha2026ember,
title={EMBER: Predicting TCR--pMHC Binding Without a Docked Complex},
author={Lin Ha and Chen Zhou and Haozheng Luo and Han Liu and Xiaoyu Zhang and Yan Chen},
year={2026},
eprint={2610.27334},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2610.27334}
}