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Updated: Jan 9, 2026

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
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Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA

Published on: February 23, 2024

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通过在文本化蛋白质-连接物相互作用上训练的大型语言模型系统地探索小分子结合

Taeseob Lee1,2, Heehoon Jung1, Ahnjae Jung1,3

  • 1Syntekabio Inc., 18 Gukjegwahak 17-ro, Yuseong-gu, Daejeon 34002, Republic of Korea.

Molecules (Basel, Switzerland)
|December 11, 2025
PubMed
概括

大型语言模型 (LLM) 现在可以通过将3D分子结构转换为语言来分析生物物理数据. 这种方法揭示了新的药物相互作用和蛋白质网络,推动了药物发现.

关键词:
人工智能药物发现在 GPT 申请时,申请人必须提交 GPT 申请书.分类化学性质化学性质.文本化的约束性相互作用.

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The Equilibrium Binding Constant and Binding Strength

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Conserved Binding Sites

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