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Updated: Jun 12, 2025

Author Spotlight: Streamlining Protein Target Prediction and Validation via Molecular Docking and CETSA
10:21

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

Published on: February 23, 2024

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SSR-DTA:用于药物标结合亲缘关系预测的子结构意识的多层图形神经网络

Yuansheng Liu1, Xinyan Xia2, Yongshun Gong3

  • 1College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410086, Hunan, China; Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education, Anhui University, Hefei, 230601, Anhui, China.

Artificial intelligence in medicine
|September 25, 2024
PubMed
概括

新型人工智能模型SSR-DTA通过有效提取分子亚结构和整合蛋白质序列和结构数据来增强药物标结合亲和力 (DTA) 预测. 这种方法显著提高了预测准确度,减少了错误,并帮助药物发现.

关键词:
深度学习是一种深度学习.药物目标亲和度预测功能表示学习学习的特征表示.图形神经网络是一个神经网络.

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Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions08:31

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