Contrastive learning-based drug screening model for GluN1/GluN3A inhibitors
文献类型：期刊论文
| 作者 | Li, Kun7; Zeng, Yue4,5,6; Xiong, Yi-da7; Wu, Hao-chen6; Fang, Sui6; Qu, Zhi-yan5,6; Zhu, Yan3; Du, Bo7; Gao, Zhao-bing2,5,6 ; Hu, Wen-bin1,7
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| 刊名 | ACTA PHARMACOLOGICA SINICA
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| 出版日期 | 2025-06-06 |
| 页码 | 13 |
| 关键词 | drug-target affinity prediction
virtual screening
contrastive learning
graph neural network
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| ISSN号 | 1671-4083 |
| DOI | 10.1038/s41401-025-01580-0 |
| 英文摘要 | GluN3A-containing NMDA receptors have recently emerged as promising therapeutic targets for neurological disorders. However, discovering potent modulators remains a significant challenge, primarily due to the limitations of traditional high-throughput screening methods. In this study, we introduce a novel drug-target affinity prediction method, CLG-DTA, designed to enhance drug discovery for the GluN1/GluN3A receptor. This graph contrastive learning-based method incorporates natural language supervision by transforming regression labels into textual representation, and integrating them with traditional affinity data to enhance molecular representation. Additionally, a numerical knowledge graph is employed to refine continuous text embeddings, enabling precise modeling of complex drug-target interactions across diverse data modalities. Using CLG-DTA, we screened a library of 18 million compounds and identified 12 candidates for experimental validation. Among them, five compounds exhibited significant activity, with Boeravinone E demonstrating the highest potency (IC50\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{{\rm{IC}}}}_{50}$$\end{document} = 3.40 +/-\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pm$$\end{document} 0.91 mu M). These findings highlight the potential of CLG-DTA in accelerating the identification of promising GluN1/GluN3A modulators and lay a robust foundation for future therapeutic development. |
| WOS关键词 | EXCITATORY GLYCINE RECEPTORS ; NMDA RECEPTOR ; AFFINITY PREDICTION ; BOERHAAVIA-DIFFUSA ; BINDING-AFFINITY ; EXPRESSION ; SUBUNIT ; GRAPH |
| 资助项目 | National Key Research and Development Program of China[2023YFC2705700] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDB0830403] ; National Science Foundation of China[62476203] ; Guangdong Provincial Natural Science Foundation General Project[2025A1515012155] ; Guangdong Provincial Natural Science Foundation General Project[2021ZD0200900] ; Open Fund for Research Projects of the Ministry of Education Key Laboratory of Embedded System and Service Computing, Tongji University ; Key Program of Hubei Natural Science Foundation Traditional Chinese Medicine Innovation and Development Joint Fund[2025AFD470] |
| WOS研究方向 | Chemistry ; Pharmacology & Pharmacy |
| 语种 | 英语 |
| WOS记录号 | WOS:001503260800001 |
| 出版者 | NATURE PUBL GROUP |
| 源URL | [http://119.78.100.183/handle/2S10ELR8/318273]  |
| 专题 | 新药研究国家重点实验室 |
| 通讯作者 | Zhu, Yan; Du, Bo; Gao, Zhao-bing; Hu, Wen-bin |
| 作者单位 | 1.Wuhan Univ, Shenzhen Res Inst, Shenzhen 518057, Peoples R China 2.Chinese Acad Sci, Zhongshan Inst Drug Discovery, Shanghai Inst Mat Med, Zhongshan 528400, Peoples R China 3.China Acad Chinese Med Sci, Inst Informat Tradit Chinese Med, Beijing 100700, Peoples R China 4.Fudan Univ, Sch Pharm, Dept Pharmacol, Shanghai 200032, Peoples R China 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 6.Chinese Acad Sci, Shanghai Inst Mat Med, State Key Lab Drug Res, Shanghai 201203, Peoples R China 7.Wuhan Univ, Sch Comp Sci, Wuhan 430037, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Kun,Zeng, Yue,Xiong, Yi-da,et al. Contrastive learning-based drug screening model for GluN1/GluN3A inhibitors[J]. ACTA PHARMACOLOGICA SINICA,2025:13. |
| APA | Li, Kun.,Zeng, Yue.,Xiong, Yi-da.,Wu, Hao-chen.,Fang, Sui.,...&Hu, Wen-bin.(2025).Contrastive learning-based drug screening model for GluN1/GluN3A inhibitors.ACTA PHARMACOLOGICA SINICA,13. |
| MLA | Li, Kun,et al."Contrastive learning-based drug screening model for GluN1/GluN3A inhibitors".ACTA PHARMACOLOGICA SINICA (2025):13. |
入库方式： OAI收割
来源：上海药物研究所
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