Artificial intelligence in drug design

doi:10.1007/s11427-018-9342-2

CORC > 上海药物研究所 > 中国科学院上海药物研究所 > 药物发现与设计中心

	Artificial intelligence in drug design
	Zhong, Feisheng 2,5; Xing, Jing 2,5; Li, Xutong 2,5; Liu, Xiaohong 1,2; Fu, Zunyun 2,5; Xiong, Zhaoping 1,2; Lu, Dong 2,5; Wu, Xiaolong 2,5; Zhao, Jihui 2,5; Tan, Xiaoqin 2,5
刊名	SCIENCE CHINA-LIFE SCIENCES
	2018-10
卷号	61 期号:10 页码:1191-1204
关键词	drug design artificial intelligence deep learning QSAR ADME/T
ISSN号	1674-7305
DOI	10.1007/s11427-018-9342-2
文献子类	Review
英文摘要	Thanks to the fast improvement of the computing power and the rapid development of the computational chemistry and biology, the computer-aided drug design techniques have been successfully applied in almost every stage of the drug discovery and development pipeline to speed up the process of research and reduce the cost and risk related to preclinical and clinical trials. Owing to the development of machine learning theory and the accumulation of pharmacological data, the artificial intelligence (AI) technology, as a powerful data mining tool, has cut a figure in various fields of the drug design, such as virtual screening, activity scoring, quantitative structure-activity relationship (QSAR) analysis, de novo drug design, and in silico evaluation of absorption, distribution, metabolism, excretion and toxicity (ADME/T) properties. Although it is still challenging to provide a physical explanation of the AI-based models, it indeed has been acting as a great power to help manipulating the drug discovery through the versatile frameworks. Recently, due to the strong generalization ability and powerful feature extraction capability, deep learning methods have been employed in predicting the molecular properties as well as generating the desired molecules, which will further promote the application of AI technologies in the field of drug design.
资助项目	National Natural Science Foundation of China[21210003] ; National Natural Science Foundation of China[81230076] ; National Natural Science Foundation of China[81773634] ; National Natural Science Foundation of China[81430084] ; "Personalized Medicines-Molecular Signature-based Drug Discovery and Development", Strategic Priority Research Program of the Chinese Academy of Sciences[XDA12050201] ; National Key Research & Development Plan[2016YFC1201003] ; National Basic Research Program[2015CB910304]
WOS关键词	PROTEIN-PROTEIN-INTERACTION ; MACHINE LEARNING-METHODS ; NEURAL-NETWORKS ; IN-SILICO ; COMPUTATIONAL METHODS ; STRUCTURE PREDICTION ; MOLECULAR-PROPERTIES ; RANDOM FOREST ; DISCOVERY ; DOCKING
WOS研究方向	Life Sciences & Biomedicine - Other Topics
语种	英语
出版者	SCIENCE PRESS
WOS记录号	WOS:000449299900007
内容类型	期刊论文
源URL	[http://119.78.100.183/handle/2S10ELR8/279548]
专题	药物发现与设计中心中科院受体结构与功能重点实验室新药研究国家重点实验室
通讯作者	Zheng, Mingyue; Jiang, Hualiang
作者单位	1.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 200031, Peoples R China; 2.Chinese Acad Sci, Shanghai Inst Mat Med, Drug Discovery & Design Ctr, State Key Lab Drug Res, Shanghai 201203, Peoples R China; 3.Dezhou Univ, Sch Informat Management, Dezhou 253023, Peoples R China 4.Shanghai Univ, Dept Chem, Coll Sci, Shanghai 200444, Peoples R China; 5.Univ Chinese Acad Sci, Sch Pharm, Beijing 100049, Peoples R China;
推荐引用方式 GB/T 7714	Zhong, Feisheng,Xing, Jing,Li, Xutong,et al. Artificial intelligence in drug design[J]. SCIENCE CHINA-LIFE SCIENCES,2018,61(10):1191-1204.
APA	Zhong, Feisheng.,Xing, Jing.,Li, Xutong.,Liu, Xiaohong.,Fu, Zunyun.,...&Jiang, Hualiang.(2018).Artificial intelligence in drug design.SCIENCE CHINA-LIFE SCIENCES,61(10),1191-1204.
MLA	Zhong, Feisheng,et al."Artificial intelligence in drug design".SCIENCE CHINA-LIFE SCIENCES 61.10(2018):1191-1204.