Deutsch(DE) zPocket: Better Pocket Finding with Frozen Co-Folding Features

zPocket 方法推进蛋白质-配体结合位点预测

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-15 04:00

研究人员开发了 zPocket，一种预测蛋白质-配体结合位点（也称为口袋）的新颖方法。该方法利用了来自共折叠模型的冻结特征，并在名为 PocketWatch 的新数据集上进行训练，该数据集旨在评估对未见口袋的泛化能力。zPocket 在预测结合位点方面显著优于 VN-EGNN、UniSite-1D 和 P2Rank 等现有方法，取得了更高的精确率-召回率曲线下面积 (AUPRC)。该方法在提高预测口袋质心的召回率方面也显示出潜力，并可能应用于片段筛选和大规模蛋白质组分析。 AI

影响这项研究通过提高结合位点预测的准确性和效率，有望加速药物发现和对蛋白质功能的理解。

排序理由该集群包含一篇详细介绍特定科学任务新方法和数据集的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.AI TIER_1 Deutsch(DE) · Tally Portnoi, Allison M Keys, Benjamin R DiFrancesco, Nate Gruver · 2026-10-15 04:00

zPocket：通过冷冻共折叠特性实现更好的口袋查找

arXiv:2610.17696v1 Announce Type: cross Abstract: Identifying protein-ligand binding sites (pockets) is important for understanding protein function and developing drugs. However, no public method has leveraged co-folding models for novel pocket prediction; furthermore, this task…

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zPocket：通过冷冻共折叠特性实现更好的口袋查找

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