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F-CPI: A Multimodal Deep Learning Approach for Predicting Compound Bioactivity Changes Induced by Fluorine Substitution

文献类型：期刊论文

作者Zhang, Qian2; Yin, Wenhai2; Chen, Xinyao7,8,9; Zhou, Aimin2; Zhang, Guixu2; Zhao, Zhi7,8,9; Li, Zhiqiang6; Zhang, Yan1,3,5; Bunu, Samuel Jacob1,3,4; Shen, Jingshan1,3
刊名JOURNAL OF MEDICINAL CHEMISTRY
出版日期2024-12-20
页码13
ISSN号0022-2623
DOI10.1021/acs.jmedchem.4c02668
通讯作者Jiang, Xiangrui(jiangxiangrui@simm.ac.cn) ; Xu, Zhijian(zjxu@simm.ac.cn)
英文摘要Fluorine (F) substitution is a common method of drug discovery and development. However, there are no accurate approaches available for predicting the bioactivity changes after F-substitution, as the effect of substitution on the interactions between compounds and proteins (CPI) remains a mystery. In this study, we constructed a data set with 111,168 pairs of fluorine-substituted and nonfluorine-substituted compounds. We developed a multimodal deep learning model (F-CPI). In comparison with traditional machine learning and popular CPI task models, the accuracy, precision, and recall of F-CPI (similar to 90, similar to 79, and similar to 45%) were higher than those of GraphDTA (similar to 86, similar to 58, and similar to 40%). The application of the F-CPI for the structural optimization of hit compounds against SARS-CoV-2 3CLpro by F-substitution achieved a more than 100-fold increase in bioactivity (IC50: 0.23 mu M vs 28.19 mu M). Therefore, the multimodal deep learning model F-CPI would be a veritable and effective tool in the context of drug discovery and design.
资助项目the Strategic Priority Research Program of the Chinese Academy of Sciences[82322067] ; National Natural Science Foundation of China[XDB0830000] ; Strategic Priority Research Program of the Chinese Academy of Sciences[2022YFA1004304] ; National Key Research and Development Program of China[SIMM0120231003] ; National Key Research and Development Program of China[CASIMM0120234003] ; Shanghai Institute of Materia Medica
WOS研究方向Pharmacology & Pharmacy
语种英语
WOS记录号WOS:001381648600001
出版者AMER CHEMICAL SOC
源URL[http://119.78.100.183/handle/2S10ELR8/315166]  
专题中国科学院上海药物研究所
通讯作者Jiang, Xiangrui; Xu, Zhijian
作者单位1.Univ Chinese Acad Sci, Sch Phys Sci, Beijing 100049, Peoples R China
2.East China Normal Univ, Shanghai Frontiers Sci Ctr Mol Intelligent Synth, Sch Comp Sci & Technol, Shanghai 200241, Peoples R China
3.Chinese Acad Sci, Shanghai Inst Mat Med, State Key Lab Drug Res, Shanghai 201203, Peoples R China
4.Chinese Acad Sci, Shanghai Inst Mat Med, Drug Discovery & Design Ctr, Shanghai 201203, Peoples R China
5.Bohai Rim Adv Res Inst Drug Discovery, Shandong Lab Yantai Drug Discovery, Yantai 264117, Peoples R China
6.Vigonvita Life Sci Co Ltd, Suzhou 215021, Peoples R China
7.Shenyang Pharmaceut Univ, Wuya Coll Innovat, Shenyang 110016, Peoples R China
8.Yangtze Delta Drug Adv Res Inst, Nantong 226133, Peoples R China
9.Yangtze Delta Pharmaceut Coll, Nantong 226133, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Qian,Yin, Wenhai,Chen, Xinyao,et al. F-CPI: A Multimodal Deep Learning Approach for Predicting Compound Bioactivity Changes Induced by Fluorine Substitution[J]. JOURNAL OF MEDICINAL CHEMISTRY,2024:13.
APA Zhang, Qian.,Yin, Wenhai.,Chen, Xinyao.,Zhou, Aimin.,Zhang, Guixu.,...&Xu, Zhijian.(2024).F-CPI: A Multimodal Deep Learning Approach for Predicting Compound Bioactivity Changes Induced by Fluorine Substitution.JOURNAL OF MEDICINAL CHEMISTRY,13.
MLA Zhang, Qian,et al."F-CPI: A Multimodal Deep Learning Approach for Predicting Compound Bioactivity Changes Induced by Fluorine Substitution".JOURNAL OF MEDICINAL CHEMISTRY (2024):13.

入库方式： OAI收割

来源：上海药物研究所

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