Graph-based generative models for de Novo drug design.

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作者： Xiaolin,Xia ^[1] ; Jianxing,Hu ^[1] ; Yanxing,Wang ^[1] ; Liangren,Zhang ^[2] ; Zhenming,Liu ^[3]

作者单位： State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Xueyuan Road 38, Haidian District, 100191 Beijing, China. ^[1] State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Xueyuan Road 38, Haidian District, 100191 Beijing, China. Electronic address: liangren@bjmu.edu.cn. ^[2] State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Xueyuan Road 38, Haidian District, 100191 Beijing, China. Electronic address: zmliu@bjmu.edu.cn. ^[3]

主题词药物设计(Drug Design);药物发现(Drug Discovery);人类(Humans);模型, 分子(Models, Molecular);药用制剂(Pharmaceutical Preparations);量化构效关系(Quantitative Structure-Activity Relationship)

DOI 10.1016/j.ddtec.2020.11.004

PMID 33386094

发布时间 2021-09-06

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Drug discovery today. Technologies

2019年32-33卷

45-53页

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Graph-based generative models for de Novo drug design.

Drug discovery today. Technologies

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Graph-based generative models for de Novo drug design.

Drug discovery today. Technologies

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Drug discovery today. Technologies

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