Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism

doi:10.1021/acs.jmedchem.9b00959

	Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism
	Xiong, Zhaoping1,2,3,4 ; Wang, Dingyan 3,4; Liu, Xiaohong1,2,3 ; Zhong, Feisheng 3,4; Wan, Xiaozhe 3,4; Li, Xutong 3,4; Li, Zhaojun 3; Luo, Xiaomin 3; Chen, Kaixian1,2,3 ; Jiang, Hualiang1,2,3 ; Zheng, Mingyue 3
	2020-08-27
发表期刊	JOURNAL OF MEDICINAL CHEMISTRY (IF:6.8[JCR-2023],7.1[5-Year])
ISSN	0022-2623
EISSN	1520-4804
卷号	63 期号:16 页码:8749-8760
DOI	10.1021/acs.jmedchem.9b00959
摘要	Hunting for chemicals with favorable pharmacological, toxicological, and pharmacokinetic properties remains a formidable challenge for drug discovery. Deep learning provides us with powerful tools to build predictive models that are appropriate for the rising amounts of data, but the gap between what these neural networks learn and what human beings can comprehend is growing. Moreover, this gap may induce distrust and restrict deep learning applications in practice. Here, we introduce a new graph neural network architecture called Attentive FP for molecular representation that uses a graph attention mechanism to learn from relevant drug discovery data sets. We demonstrate that Attentive FP achieves state-of-the-art predictive performances on a variety of data sets and that what it learns is interpretable. The feature visualization for Attentive FP suggests that it automatically learns nonlocal intramolecular interactions from specified tasks, which can help us gain chemical insights directly from data beyond human perception.
收录类别	SCIE
语种	英语
WOS研究方向	Pharmacology & Pharmacy
WOS类目	Chemistry, Medicinal
WOS记录号	WOS:000566757500009
出版者	AMER CHEMICAL SOC
原始文献类型	Article
引用统计	被引频次：584[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/243210
专题	生命科学与技术学院_博士生生命科学与技术学院_特聘教授组_陈凯先组免疫化学研究所_特聘教授组_蒋华良组
通讯作者	Jiang, Hualiang; Zheng, Mingyue
作者单位	1.ShanghaiTech Univ, Shanghai Inst Adv Immunochem Studies, Shanghai 200031, Peoples R China; 2.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 200031, Peoples R China; 3.Chinese Acad Sci, Drug Discovery & Design Ctr, State Key Lab Drug Res, Shanghai Inst Mat Med, 555 Zuchongzhi Rd, Shanghai 201203, Peoples R China; 4.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China
第一作者单位	免疫化学研究所; 生命科学与技术学院
通讯作者单位	免疫化学研究所; 生命科学与技术学院
第一作者的第一单位	免疫化学研究所
推荐引用方式 GB/T 7714	Xiong, Zhaoping,Wang, Dingyan,Liu, Xiaohong,et al. Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism[J]. JOURNAL OF MEDICINAL CHEMISTRY,2020,63(16):8749-8760.
APA	Xiong, Zhaoping.,Wang, Dingyan.,Liu, Xiaohong.,Zhong, Feisheng.,Wan, Xiaozhe.,...&Zheng, Mingyue.(2020).Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism.JOURNAL OF MEDICINAL CHEMISTRY,63(16),8749-8760.
MLA	Xiong, Zhaoping,et al."Pushing the Boundaries of Molecular Representation for Drug Discovery with the Graph Attention Mechanism".JOURNAL OF MEDICINAL CHEMISTRY 63.16(2020):8749-8760.