中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 上海药物研究所
  3. 中国科学院上海药物研究所
  4. 新药研究国家重点实验室
Graph neural network approaches for drug-target interactions

文献类型：期刊论文

作者Zhang, Zehong1,2; Chen, Lifan1,2; Zhong, Feisheng1,2; Wang, Dingyan1,2; Jiang, Jiaxin1; Zhang, Sulin1,2; Jiang, Hualiang1,2,3; Zheng, Mingyue1,2; Li, Xutong1,2
刊名CURRENT OPINION IN STRUCTURAL BIOLOGY
出版日期2022-04
卷号73页码:102327
ISSN号0959-440X
DOI10.1016/j.sbi.2021.102327
文献子类Article
英文摘要Developing new drugs remains prohibitively expensive, time-consuming, and often involves safety issues. Accurate prediction of drug-target interactions (DTIs) can guide the drug discovery process and thus facilitate drug development. Non -Euclidian data such as drug-like molecule structures, key pocket residue structures, and protein interaction networks can be represented effectively using graphs. Therefore, the emerging graph neural network has been rapidly applied to predict DTIs, and proved effective in finding repositioning drugs and accelerating drug discovery. In this review, we provide a brief overview of deep neural networks used in DTI models. Then, we summarize the database required for DTI prediction, followed by a comprehensive introduction of applications of graph neural networks for DTI prediction. We also highlight current challenges and future directions to guide the further development of this field.
WOS关键词KNOWLEDGE ; INFORMATION ; MODEL ; SETS
WOS研究方向Biochemistry & Molecular Biology ; Cell Biology
语种英语
WOS记录号WOS:000829027900005
出版者CURRENT BIOLOGY LTD
源URL[http://119.78.100.183/handle/2S10ELR8/309361]  
专题新药研究国家重点实验室
通讯作者Zheng, Mingyue; Li, Xutong
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, Sch Life Sci & Technol, 393 Huaxiazhong Rd, Shanghai 200031, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Zehong,Chen, Lifan,Zhong, Feisheng,et al. Graph neural network approaches for drug-target interactions[J]. CURRENT OPINION IN STRUCTURAL BIOLOGY,2022,73:102327.
APA Zhang, Zehong.,Chen, Lifan.,Zhong, Feisheng.,Wang, Dingyan.,Jiang, Jiaxin.,...&Li, Xutong.(2022).Graph neural network approaches for drug-target interactions.CURRENT OPINION IN STRUCTURAL BIOLOGY,73,102327.
MLA Zhang, Zehong,et al."Graph neural network approaches for drug-target interactions".CURRENT OPINION IN STRUCTURAL BIOLOGY 73(2022):102327.

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。