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Updated: May 30, 2025

Methods for the Discovery of Novel Compounds Modulating a Gamma-Aminobutyric Acid Receptor Type A Neurotransmission
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hERGAT:通过原子和分子层面的相互作用分析,利用图形注意力机制预测hERG阻塞剂

Dohyeon Lee1, Sunyong Yoo2

  • 1Department of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, Republic of Korea.

Journal of cheminformatics
|January 28, 2025
PubMed
概括

我们开发了hERGAT,一种使用图表注意力网络 (GAT) 和封闭循环单元 (GRU) 的深度学习模型,用于预测人类以太基因相关基因 (hERG) 通道阻塞. 该模型通过在早期发育中识别心脏毒性化合物来增强药物安全性评估.

关键词:
心脏有毒性 - 心脏有毒性毒性药物毒性 毒性药物毒性图表注意力机制的机制.图表神经网络的神经网络一个hERG通道阻塞器.

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