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SymMap:一个通过症状映射增强的传统中药整合数据库。

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

机构信息

Beijing University of Chinese Medicine, ChaoYang District, Beijing 100029, China.

Key Laboratory of Intelligent Information Processing, Advanced Computer Research Center, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.

出版信息

Nucleic Acids Res. 2019 Jan 8;47(D1):D1110-D1117. doi: 10.1093/nar/gky1021.


DOI:10.1093/nar/gky1021
PMID:30380087
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6323958/
Abstract

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.

摘要

最近,制药行业高度强调表型药物发现(PDD),该方法主要依赖于与疾病相关的表型变化的知识。传统中药(TCM)提供了大量关于天然产物及其用于治疗的临床症状的信息,这些都是用于临床诊断和治疗的可观察疾病表型。整理 TCM 症状及其与草药和疾病之间的关系的知识,将为基于证据的 PDD 计划提供候选先导物和筛选方向。因此,我们提出了 SymMap,这是一个通过症状映射增强的传统中药综合数据库。我们根据 17 位从事 TCM 的领先专家委员会的意见,手动整理了 1717 个 TCM 症状,并将其与 499 种草药和 961 种现代医学中使用的症状相关联。接下来,我们收集了与这些症状相关的 5235 种疾病、19595 种草药成分(成分)和 4302 个靶基因,并构建了一个包含所有这些成分的大型异构网络。因此,SymMap 在表型和分子水平上整合了 TCM 和现代医学的常见方面。此外,我们使用统计检验推断了 SymMap 成分之间的所有成对关系,为制药科学家提供了对有前途的结果进行排名和过滤以指导药物发现的能力。SymMap 数据库可在 http://www.symmap.org/ 和 https://www.bioinfo.org/symmap 上访问。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17e8/6323958/37cf63da79da/gky1021fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17e8/6323958/e476cf247c1c/gky1021fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17e8/6323958/4c07cd72281d/gky1021fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17e8/6323958/37cf63da79da/gky1021fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17e8/6323958/e476cf247c1c/gky1021fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17e8/6323958/4c07cd72281d/gky1021fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17e8/6323958/37cf63da79da/gky1021fig3.jpg

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本文引用的文献

[1]
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Nucleic Acids Res. 2018-1-4

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