DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening

doi:10.1016/j.gpb.2019.04.003

	DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening
	Wan, Fangping 2; Zhu, Yue 3,4; Hu, Hailin 5; Dai, Antao 3,4; Cai, Xiaoqing 3,4; Chen, Ligong 6; Gong, Haipeng 7; Xia, Tian 8; Yang, Dehua 3,4; Wang, Ming-Wei 1,3,4,9
刊名	GENOMICS PROTEOMICS & BIOINFORMATICS
	2019-10-01
卷号	17 期号:5 页码:478-495
关键词	Deep learning Machine learning Drug discovery In silico drug screening Compound-protein interaction prediction
ISSN号	1672-0229
DOI	10.1016/j.gpb.2019.04.003
通讯作者	Yang, Dehua(dhyang@simm.ac.cn) ; Wang, Ming-Wei(mwwang@simm.ac.cn) ; Zeng, Jianyang(zengjy321@tsinghua.edu.cn)
英文摘要	Accurate identification of compound-protein interactions (CPIs) in silico may deepen our understanding of the underlying mechanisms of drug action and thus remarkably facilitate drug discovery and development. Conventional similarity- or docking-based computational methods for predicting CPIs rarely exploit latent features from currently available large-scale unlabeled compound and protein data and often limit their usage to relatively small-scale datasets. In the present study, we propose DeepCPI, a novel general and scalable computational framework that combines effective feature embedding (a technique of representation learning) with powerful deep learning methods to accurately predict CPIs at a large scale. DeepCPI automatically learns the implicit yet expressive low-dimensional features of compounds and proteins from a massive amount of unlabeled data. Evaluations of the measured CPIs in large-scale databases, such as ChEMBL and BindingDB, as well as of the known drug-target interactions from DrugBank, demonstrated the superior predictive performance of DeepCPI. Furthermore, several interactions among small-molecule compounds and three G protein-coupled receptor targets (glucagon-like peptide-1 receptor, glucagon receptor, and vasoactive intestinal peptide receptor) predicted using DeepCPI were experimentally validated. The present study suggests that DeepCPI is a useful and powerful tool for drug discovery and repositioning.
资助项目	National Natural Science Foundation of China[61872216] ; National Natural Science Foundation of China[81630103] ; National Natural Science Foundation of China[81872915] ; National Natural Science Foundation of China[81573479] ; National Natural Science Foundation of China[81773792] ; National Science and Technology Major Project[2018ZX09711003-004-002] ; National Science and Technology Major Project Key New Drug Creation and Manufacturing Program of China[2018ZX09735-001] ; National Science and Technology Major Project Key New Drug Creation and Manufacturing Program of China[2018ZX09711002002-005] ; Shanghai Science and Technology Development Fund[15DZ2291600] ; Shanghai Science and Technology Development Fund[16ZR1407100]
WOS关键词	PEPTIDE-1 RECEPTOR AGONIST ; ALPHA(2)-ADRENERGIC RECEPTORS ; DOPAMINE BINDS ; DATABASE ; ZINC ; DESIPRAMINE ; PREDICTION ; DISCOVERY ; GLP-1R
WOS研究方向	Genetics & Heredity
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000518438500003
内容类型	期刊论文
源URL	[http://119.78.100.183/handle/2S10ELR8/281328]
专题	中国科学院上海药物研究所
通讯作者	Yang, Dehua; Wang, Ming-Wei; Zeng, Jianyang
作者单位	1.Fudan Univ, Shanghai Med Coll, Shanghai 200032, Peoples R China 2.Tsinghua Univ, Inst Interdisciplinary Informat Sci, Beijing 100084, Peoples R China 3.Chinese Acad Sci, Natl Ctr Drug Screening, Shanghai 201203, Peoples R China 4.Chinese Acad Sci, CAS Key Lab Receptor Res, Shanghai Inst Mat Med, Shanghai 201203, Peoples R China 5.Tsinghua Univ, Sch Med, Beijing 100084, Peoples R China 6.Tsinghua Univ, Sch Pharmaceut Sci, Beijing 100084, Peoples R China 7.Tsinghua Univ, Sch Life Sci, Beijing 100084, Peoples R China 8.Huazhong Univ Sci & Technol, Dept Elect & Informat Engn, Wuhan 430074, Peoples R China 9.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 201210, Peoples R China 10.Tsinghua Univ, MOE Key Lab Bioinformat, Beijing 100084, Peoples R China
推荐引用方式 GB/T 7714	Wan, Fangping,Zhu, Yue,Hu, Hailin,et al. DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening[J]. GENOMICS PROTEOMICS & BIOINFORMATICS,2019,17(5):478-495.
APA	Wan, Fangping.,Zhu, Yue.,Hu, Hailin.,Dai, Antao.,Cai, Xiaoqing.,...&Zeng, Jianyang.(2019).DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening.GENOMICS PROTEOMICS & BIOINFORMATICS,17(5),478-495.
MLA	Wan, Fangping,et al."DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening".GENOMICS PROTEOMICS & BIOINFORMATICS 17.5(2019):478-495.