Graph neural networks for automated de novo drug design
文献类型：期刊论文
| 作者 | Xiong, Jiacheng1,2; Xiong, Zhaoping1,3,4; Chen, Kaixian1,2 ; Jiang, Hualiang1,2; Zheng, Mingyue1,2
|
| 刊名 | DRUG DISCOVERY TODAY
 |
| 出版日期 | 2021-06-01 |
| 卷号 | 26期号:6页码:1382-1393 |
| ISSN号 | 1359-6446 |
| DOI | 10.1016/j.drudis.2021.02.011 |
| 通讯作者 | Jiang, Hualiang(hljiang@simm.ac.cn) ; Zheng, Mingyue(myzheng@simm.ac.cn) |
| 英文摘要 | The goal of de novo drug design is to create novel chemical entities with desired biological activities and pharmacokinetics (PK) properties. Over recent years, with the development of artificial intelligence (AI) technologies, data-driven methods have rapidly gained in popularity in this field. Among them, graph neural networks (GNNs), a type of neural network directly operating on the graph structure data, have received extensive attention. In this review, we introduce the applications of GNNs in de novo drug design from three aspects: molecule scoring, molecule generation and optimization, and synthesis planning. Furthermore, we also discuss the current challenges and future directions of GNNs in de novo drug design. |
| WOS关键词 | RECEPTOR STRUCTURE ; TRANSFORMER ; DISCOVERY ; INDUSTRY ; MODEL ; END |
| 资助项目 | National Natural Science Foundation of China[81773634] ; National Science & Technology Major Project 'Key New Drug Creation and Manufacturing Program', China[2018ZX09711002] ; 'Personalized Medicines-Molecular Signaturebased Drug Discovery and Development', Strategic Priority Research Program of the Chinese Academy of Sciences[XDA12050201] |
| WOS研究方向 | Pharmacology & Pharmacy |
| 语种 | 英语 |
| WOS记录号 | WOS:000664035500007 |
| 出版者 | ELSEVIER SCI LTD |
| 源URL | [http://119.78.100.183/handle/2S10ELR8/296865]  |
| 专题 | 新药研究国家重点实验室 |
| 通讯作者 | Jiang, Hualiang; Zheng, Mingyue |
| 作者单位 | 1.Chinese Acad Sci, Shanghai Inst Mat Med, State Key Lab Drug Res, Drug Discovery & Design Ctr, 555 Zuchongzhi Rd, Shanghai 201203, Peoples R China 2.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China 3.ShanghaiTech Univ, Shanghai Inst Adv Immunochem Studies, Shanghai 200031, Peoples R China 4.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 200031, Peoples R China |
| 推荐引用方式 GB/T 7714 | Xiong, Jiacheng,Xiong, Zhaoping,Chen, Kaixian,et al. Graph neural networks for automated de novo drug design[J]. DRUG DISCOVERY TODAY,2021,26(6):1382-1393. |
| APA | Xiong, Jiacheng,Xiong, Zhaoping,Chen, Kaixian,Jiang, Hualiang,&Zheng, Mingyue.(2021).Graph neural networks for automated de novo drug design.DRUG DISCOVERY TODAY,26(6),1382-1393. |
| MLA | Xiong, Jiacheng,et al."Graph neural networks for automated de novo drug design".DRUG DISCOVERY TODAY 26.6(2021):1382-1393. |
入库方式： OAI收割
来源：上海药物研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。