Structure-aware conditional variational auto-encoder for constrained molecule optimization

doi:10.1016/j.patcog.2022.108581

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	Structure-aware conditional variational auto-encoder for constrained molecule optimization
	Yu, Junchi 1,2,3; Xu, Tingyang 3; Rong, Yu 3; Huang, Junzhou 3; He, Ran1,2,4
发表期刊	PATTERN RECOGNITION
ISSN	0031-3203
	2022-06-01
卷号	126 页码:9
通讯作者	He, Ran(rhe@nlpr.ia.ac.cn)
摘要	The goal of molecule optimization is to optimize molecular properties by modifying molecule structures. Conditional generative models provide a promising way to transfer the input molecules to the ones with better property. However, molecular properties are highly sensitive to small changes in molecular struc-tures. This leads to an interesting thought that we can improve the property of molecules with lim-ited modification in structure. In this paper, we propose a structure-aware conditional Variational Auto-Encoder, namely SCVAE, which exploits the topology of molecules as structure condition and optimizes the molecular properties with constrained structural modification. SCVAE leverages graph alignment of two-level molecule structures in an unsupervised manner to bind the structure conditions between two molecules. Then, this structure condition facilitates the molecule optimization with limited struc-tural modification, namely, constrained molecule optimization, under a novel variational auto-encoder framework. Extensive experimental evaluations demonstrate that structure-aware CVAE generates new molecules with high similarity to the original ones and better molecular properties. (c) 2022 Elsevier Ltd. All rights reserved.
关键词	Molecule optimization Conditional generation Drug discovery
DOI	10.1016/j.patcog.2022.108581
关键词[WOS]	GRAPH ALIGNMENT
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[U20A20223] ; Youth Innovation Promotion Association CAS[Y201929]
项目资助者	National Natural Science Foundation of China ; Youth Innovation Promotion Association CAS
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000761147800004
出版者	ELSEVIER SCI LTD
七大方向——子方向分类	机器学习
引用统计	被引频次：11[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/48064
专题	智能感知与计算研究中心
通讯作者	He, Ran
作者单位	1.Univ Chinese Acad Sci, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 3.Tencent AI Lab, Shanghai, Peoples R China 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Yu, Junchi,Xu, Tingyang,Rong, Yu,et al. Structure-aware conditional variational auto-encoder for constrained molecule optimization[J]. PATTERN RECOGNITION,2022,126:9.
APA	Yu, Junchi,Xu, Tingyang,Rong, Yu,Huang, Junzhou,&He, Ran.(2022).Structure-aware conditional variational auto-encoder for constrained molecule optimization.PATTERN RECOGNITION,126,9.
MLA	Yu, Junchi,et al."Structure-aware conditional variational auto-encoder for constrained molecule optimization".PATTERN RECOGNITION 126(2022):9.