NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning

doi:10.1371/journal.pcbi.1004975

CSpace > 应用数学研究所

	NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning
	Chen, Xing 1; Ren, Biao 2,3; Chen, Ming 2; Wang, Quanxin 2,4; Zhang, Lixin 2,5; Yan, Guiying6
	2016-07-01
发表期刊	PLOS COMPUTATIONAL BIOLOGY
ISSN	1553-734X
卷号	12 期号:7 页码:23
摘要	Fungal infection has become one of the leading causes of hospital-acquired infections with high mortality rates. Furthermore, drug resistance is common for fungus-causing diseases. Synergistic drug combinations could provide an effective strategy to overcome drug resistance. Meanwhile, synergistic drug combinations can increase treatment efficacy and decrease drug dosage to avoid toxicity. Therefore, computational prediction of synergistic drug combinations for fungus-causing diseases becomes attractive. In this study, we proposed similar nature of drug combinations: principal drugs which obtain synergistic effect with similar adjuvant drugs are often similar and vice versa. Furthermore, we developed a novel algorithm termed Network-based Laplacian regularized Least Square Synergistic drug combination prediction (NLLSS) to predict potential synergistic drug combinations by integrating different kinds of information such as known synergistic drug combinations, drug-target interactions, and drug chemical structures. We applied NLLSS to predict antifungal synergistic drug combinations and showed that it achieved excellent performance both in terms of cross validation and independent prediction. Finally, we performed biological experiments for fungal pathogen Candida albicans to confirm 7 out of 13 predicted antifungal synergistic drug combinations. NLLSS provides an efficient strategy to identify potential synergistic antifungal combinations.
DOI	10.1371/journal.pcbi.1004975
语种	英语
资助项目	National Natural Science Foundation of China[11301517] ; National Natural Science Foundation of China[11371355] ; National Natural Science Foundation of China[10531070] ; National Natural Science Foundation of China[10721101] ; National Natural Science Foundation of China[30973665] ; National Natural Science Foundation of China[30700015] ; National Natural Science Foundation of China[30901849] ; National Natural Science Foundation of China[30910376] ; National Natural Science Foundation of China[30911120484] ; National Natural Science Foundation of China[81011120046] ; National Natural Science Foundation of China[30911120483] ; National 863 Project[2006AA09Z402] ; National 863 Project[2007AA09Z443] ; Key Project for International Cooperation[2007DFB31620] ; National Key Technology RD Program[2007BAI26B02] ; CAS Pillar Program[KSCX2-YW-R-164] ; Important National Science & Technology Specific Projects[2008ZX09401-05] ; Important National Science & Technology Specific Projects[2009ZX09302-004] ; National Center for Mathematics and Interdisciplinary Sciences, CAS
WOS研究方向	Biochemistry & Molecular Biology ; Mathematical & Computational Biology
WOS类目	Biochemical Research Methods ; Mathematical & Computational Biology
WOS记录号	WOS:000383351400013
出版者	PUBLIC LIBRARY SCIENCE
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/23687
专题	应用数学研究所
通讯作者	Zhang, Lixin
作者单位	1.China Univ Min & Technol, Sch Informat & Elect Engn, Xuzhou, Peoples R China 2.Chinese Acad Sci, Key Lab Pathogen Microbiol & Immunol, Inst Microbiol, Beijing, Peoples R China 3.Sichuan Univ, West China Hosp Stomatol, State Key Lab Oral Dis, Chengdu, Peoples R China 4.Univ Chinese Acad Sci, Beijing, Peoples R China 5.Chinese Acad Sci, South China Sea Inst Oceanol, Guangzhou, Guangdong, Peoples R China 6.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Chen, Xing,Ren, Biao,Chen, Ming,et al. NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning[J]. PLOS COMPUTATIONAL BIOLOGY,2016,12(7):23.
APA	Chen, Xing,Ren, Biao,Chen, Ming,Wang, Quanxin,Zhang, Lixin,&Yan, Guiying.(2016).NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning.PLOS COMPUTATIONAL BIOLOGY,12(7),23.
MLA	Chen, Xing,et al."NLLSS: Predicting Synergistic Drug Combinations Based on Semi-supervised Learning".PLOS COMPUTATIONAL BIOLOGY 12.7(2016):23.