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English(EN) SurfSpec: Enhancing Off-Target-Agnostic Specificity by Bounding Pocket-Ligand Geometric Mismatch

新的SurfSpec框架在没有脱靶数据的情况下提高了药物设计的特异性

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了SurfSpec，这是一个用于基于结构的药物设计的新框架，通过分析配体与其目标口袋之间的几何不匹配来提高特异性。该方法在不需要了解脱靶结构的情况下，提供了特异性的下界。SurfSpec通过将配体迭代地生长到目标口袋的特定表面区域，从而提高了经验特异性，同时保持了具有竞争力的目标亲和力改进，这在CrossDocked2020测试集上得到了证明。 AI

影响 引入了一种新颖的计算方法来优化药物特异性，有可能加速药物发现中的先导化合物优化。

排序理由 详细介绍一种新的药物设计计算方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新的SurfSpec框架在没有脱靶数据的情况下提高了药物设计的特异性

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详细介绍一种新的药物设计计算方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Minyeong Hwang, Yoorim Gang, Ziseok Lee, Wooyeol Lee, Young Bin Park, Jae-Mun Choi, Kyungsu Kim, Eunho Yang ·

    SurfSpec：通过限制口袋-配体几何不匹配来增强脱靶无关特异性

    arXiv:2609.02963v1 Announce Type: cross Abstract: Lead optimization in structure-based drug design aims to improve target binding while avoiding unintended interactions with off-target pockets. However, existing affinity-driven methods do not explicitly control specificity, where…

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