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In silico prediction of pKa values using explainable deep learning methods

Chen Yang Changda Gong Zhixing Zhang Jiaojiao Fang Weihua Li Guixia Liu Yun Tang

药物分析学报（英文）2025，Vol.15Issue(6)：1264-1276,13.

药物分析学报（英文）2025，Vol.15Issue(6)：1264-1276,13.DOI:10.1016/j.jpha.2024.101174

In silico prediction of pKa values using explainable deep learning methods

Chen Yang ¹Changda Gong ¹Zhixing Zhang ¹Jiaojiao Fang ¹Weihua Li ¹Guixia Liu ¹Yun Tang¹

作者信息

1. Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism,Shanghai Key Laboratory of New Drug Design,School of Pharmacy,East China University of Science and Technology,Shanghai,200237,China
折叠

摘要

关键词

pKa/Deep learning/Graph neural networks/AttentiveFP/Integrated gradients/In silico prediction

Key words

pKa/Deep learning/Graph neural networks/AttentiveFP/Integrated gradients/In silico prediction

引用本文复制引用

Chen Yang,Changda Gong,Zhixing Zhang,Jiaojiao Fang,Weihua Li,Guixia Liu,Yun Tang..In silico prediction of pKa values using explainable deep learning methods[J].药物分析学报（英文）,2025,15(6):1264-1276,13.

基金项目

This work was supported by the National Key Research and Development Program of China(Grant No.:2023YFF1204904),the National Natural Science Foundation of China(Grant Nos.:U23A20530 and 82173746)and Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism(Shanghai Municipal Education Commission,China). （Grant No.:2023YFF1204904）

药物分析学报（英文）

ISSN：2095-1779

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