SymMap: an integrative database of traditional Chinese medicine enhanced by symptom mapping

被引:453
作者
Wu, Yang [1 ,2 ]
Zhang, Feilong [1 ]
Yang, Kuo [3 ,4 ]
Fang, Shuangsang [2 ]
Bu, Dechao [2 ]
Li, Hui [2 ]
Sun, Liang [2 ]
Hu, Hairuo [2 ]
Gao, Kuo [1 ]
Wang, Wei [1 ]
Zhou, Xuezhong [3 ,4 ]
Zhao, Yi [1 ,2 ]
Chen, Jianxin [1 ]
机构
[1] Beijing Univ Chinese Med, Beijing 100029, Peoples R China
[2] Chinese Acad Sci, Inst Comp Technol, Adv Comp Res Ctr, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
[3] Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China
[4] Beijing Jiaotong Univ, Beijing Key Lab Traff Data Anal & Min, Beijing 100044, Peoples R China
基金
中国国家自然科学基金;
关键词
DRUG DISCOVERY; COMPREHENSIVE RESOURCE; NATURAL-PRODUCTS; MECHANISM; ONTOLOGY;
D O I
10.1093/nar/gky1021
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Recently, the pharmaceutical industry has heavily emphasized phenotypic drug discovery (PDD), which relies primarily on knowledge about phenotype changes associated with diseases. Traditional Chinese medicine (TCM) provides a massive amount of information on natural products and the clinical symptoms they are used to treat, which are the observable disease phenotypes that are crucial for clinical diagnosis and treatment. Curating knowledge of TCM symptoms and their relationships to herbs and diseases will provide both candidate leads and screening directions for evidence-based PDD programs. Therefore, we present SymMap, an integrative database of traditional Chinese medicine enhanced by symptom mapping. We manually curated 1717 TCM symptoms and related them to 499 herbs and 961 symptoms used in modern medicine based on a committee of 17 leading experts practicing TCM. Next, we collected 5235 diseases associated with these symptoms, 19 595 herbal constituents (ingredients) and 4302 target genes, and built a large heterogeneous network containing all of these components. Thus, SymMap integrates TCM with modern medicine in common aspects at both the phenotypic and molecular levels. Furthermore, we inferred all pairwise relationships among SymMap components using statistical tests to give pharmaceutical scientists the ability to rank and filter promising results to guide drug discovery. The SymMap database can be accessed at http://www.symmap.org/ and https://www.bioinfo.org/symmap.
引用
收藏
页码:D1110 / D1117
页数:8
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