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DeepR2cov: deep representation learning on heterogeneous drug networks to discover anti-inflammatory agents for COVID-19

文献类型：期刊论文

作者Wang, Xiaoqi1; Xin, Bin1; Tan, Weihong4; Xu, Zhijian5; Li, Kenli1; Li, Fei2; Zhong, Wu3; Peng, Shaoliang1
刊名BRIEFINGS IN BIOINFORMATICS
出版日期2021-11-01
卷号22期号:6页码:14
关键词heterogeneous drug networks deep representation learning drug discovery excessive inflammatory response COVID-19
ISSN号1467-5463
DOI10.1093/bib/bbab226
通讯作者Li, Fei(pittacus@gmail.com) ; Zhong, Wu(zhongwu@bmi.ac.cn) ; Peng, Shaoliang(slpeng@hnu.edu.cn)
英文摘要Recent studies have demonstrated that the excessive inflammatory response is an important factor of death in coronavirus disease 2019 (COVID-19) patients. In this study, we propose a deep representation on heterogeneous drug networks, termed DeepR2cov, to discover potential agents for treating the excessive inflammatory response in COVID-19 patients. This work explores the multi-hub characteristic of a heterogeneous drug network integrating eight unique networks. Inspired by the multi-hub characteristic, we design 3 billion special meta paths to train a deep representation model for learning low-dimensional vectors that integrate long-range structure dependency and complex semantic relation among network nodes. Based on the representation vectors and transcriptomics data, we predict 22 drugs that bind to tumor necrosis factor-alpha or interleukin-6, whose therapeutic associations with the inflammation storm in COVID-19 patients, and molecular binding model are further validated via data from PubMed publications, ongoing clinical trials and a docking program. In addition, the results on five biomedical applications suggest that DeepR2cov significantly outperforms five existing representation approaches. In summary, DeepR2cov is a powerful network representation approach and holds the potential to accelerate treatment of the inflammatory responses in COVID-19 patients. The source code and data can be downloaded from https://github.com/pengsl-lab/DeepR2cov.git.
WOS关键词CYTOKINE STORM ; IDENTIFICATION
资助项目National Key Research and Development Program of China[2017YFB0202602] ; National Key Research and Development Program of China[2018YFC0910405] ; National Key Research and Development Program of China[2017YFC1311003] ; National Key Research and Development Program of China[2016YFC1302500] ; National Key Research and Development Program of China[2016YFB0200400] ; National Key Research and Development Program of China[2017 YFB0202104] ; National Nature Science Foundation of China[81973244] ; National Nature Science Foundation of China[U19A2067] ; National Nature Science Foundation of China[61772543] ; National Nature Science Foundation of China[U1435222] ; National Nature Science Foundation of China[61625202] ; National Nature Science Foundation of China[61272056] ; Fundamental Research Funds for the Central Universities ; Guangdong Provincial Department of Science and Technology[2016B090918122]
WOS研究方向Biochemistry & Molecular Biology ; Mathematical & Computational Biology
语种英语
WOS记录号WOS:000733325700096
出版者OXFORD UNIV PRESS
源URL[http://119.78.100.183/handle/2S10ELR8/300673]  
专题中国科学院上海药物研究所
通讯作者Li, Fei; Zhong, Wu; Peng, Shaoliang
作者单位1.Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Hunan, Peoples R China
2.Chinese Acad Sci, Comp Network Informat Ctr, Beijing 100850, Peoples R China
3.Beijing Inst Pharmacol & Toxicol, Natl Engn Res Ctr Emergency Drug, Beijing 100080, Peoples R China
4.Hunan Univ, Chinese Acad Sci, Coll Biol, Coll Chem & Chem Engn, Changsha, Hunan, Peoples R China
5.Chinese Acad Sci, Drug Discovery & Design Ctr, Shanghai Inst Mat Med, Shanghai, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Xiaoqi,Xin, Bin,Tan, Weihong,et al. DeepR2cov: deep representation learning on heterogeneous drug networks to discover anti-inflammatory agents for COVID-19[J]. BRIEFINGS IN BIOINFORMATICS,2021,22(6):14.
APA Wang, Xiaoqi.,Xin, Bin.,Tan, Weihong.,Xu, Zhijian.,Li, Kenli.,...&Peng, Shaoliang.(2021).DeepR2cov: deep representation learning on heterogeneous drug networks to discover anti-inflammatory agents for COVID-19.BRIEFINGS IN BIOINFORMATICS,22(6),14.
MLA Wang, Xiaoqi,et al."DeepR2cov: deep representation learning on heterogeneous drug networks to discover anti-inflammatory agents for COVID-19".BRIEFINGS IN BIOINFORMATICS 22.6(2021):14.

入库方式： OAI收割

来源：上海药物研究所

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