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EMBER framework predicts TCR-pMHC binding without complex docking

Researchers have developed EMBER, a novel framework for predicting T-cell receptor (TCR) and peptide-MHC (pMHC) binding. Unlike traditional methods that require a docked complex, EMBER analyzes independently folded TCR and pMHC structures, encoding them as SE(3)-invariant residue graphs. This approach bypasses the placement errors inherent in complex docking, leading to improved accuracy and stability across various folding tools. EMBER also offers computational advantages, requiring fewer operations for preprocessing monomer folds compared to complex-based predictors. AI

IMPACT This new framework could accelerate drug discovery and personalized medicine by improving the accuracy and efficiency of predicting immune responses.

RANK_REASON The cluster describes a new scientific paper detailing a novel computational framework for biological binding prediction.

Read on Hugging Face Daily Papers →

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EMBER framework predicts TCR-pMHC binding without complex docking

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The cluster describes a new scientific paper detailing a novel computational framework for biological binding prediction.
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COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Lin Ha, Chen Zhou, Haozheng Luo, Han Liu, Xiaoyu Zhang, Yan Chen ·

    EMBER: Predicting TCR--pMHC Binding Without a Docked Complex

    arXiv:2610.27334v1 Announce Type: cross 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 p…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    EMBER: Predicting TCR--pMHC Binding Without a Docked Complex

    EMBER predicts TCR-pMHC binding from independently folded monomers using SE(3)-invariant graphs, avoiding docking errors and reducing computation while improving accuracy across folding tools.