药学学报, 2018, 53(9): 1458-1466
引用本文:
时悦, 姚璎珈, 蔺莹, 梁喜才, 倪颖男, 吴雨桐, 杨静娴. 基于网络药理学的开心散治疗阿尔茨海默病的作用机制分析[J]. 药学学报, 2018, 53(9): 1458-1466.
SHI Yue, YAO Ying-jia, LIN Ying, LIANG Xi-cai, NI Ying-nan, WU Yu-tong, YANG Jing-xian. Mechanism of Kai Xin San in the treatment of Alzheimer's disease based on network pharmacology[J]. Acta Pharmaceutica Sinica, 2018, 53(9): 1458-1466.

基于网络药理学的开心散治疗阿尔茨海默病的作用机制分析
时悦, 姚璎珈, 蔺莹, 梁喜才, 倪颖男, 吴雨桐, 杨静娴
辽宁中医药大学, 辽宁 大连 116600
摘要:
采用网络药理学方法筛选开心散治疗阿尔茨海默病的主要活性成分并研究其作用机制。利用中药系统药理学分析平台(TCMSP)和TTD数据库查找阿尔茨海默病的靶标蛋白,取两种方法交集得到的靶蛋白确定为阿尔茨海默病的靶蛋白;基于ADME算法筛选开心散药效成分并利用反向药效团匹配方法(PharmMapper)进行开心散靶点预测,运用Uniprot数据库查询靶蛋白对应的基因名称并选择人源蛋白最终得到开心散调控的阿尔茨海默病靶蛋白;运用Cytoscape 3.5.1软件构建开心散活性成分-阿尔茨海默病靶标网络并进行网络拓扑学分析;通过STRING数据库和DAVID数据库对靶点进行基因本体(Gene Ontology,GO)富集分析及基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路分析。通过Discovery Studio分子对接软件对网络药理学分析结果进行验证。研究得到开心散中满足类药性、口服生物利用度和入血的药效成分有31个,与阿尔茨海默病相关的靶点有8个。GO条目31个,其中生物过程条目有13个,分子功能条目7个,细胞组成条目11个。KEGG通路5条,包括钙信号通路和PI3K-Akt信号通路等。Discovery Studio分子对接结果表明,开心散活性成分与重要靶点结合活性较好,且阳性药与靶点的结合有很高的评分。开心散治疗阿尔茨海默病具有多成分、多靶点的优点,通过网络药理学方法研究开心散治疗阿尔茨海默病的活性成分和作用机制,为进一步揭示其作用机制提供了新的思路。
关键词:    开心散      阿尔茨海默病      网络药理学      靶点      分子对接     
Mechanism of Kai Xin San in the treatment of Alzheimer's disease based on network pharmacology
SHI Yue, YAO Ying-jia, LIN Ying, LIANG Xi-cai, NI Ying-nan, WU Yu-tong, YANG Jing-xian
Liaoning University of Traditional Chinese Medicine, Dalian 116600, China
Abstract:
The study was designed to explore the active components and mechanism of Kai Xin San in the treatment of Alzheimer's disease (AD) based on network pharmacology. All targets related to AD were researched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Therapeutic Targets Database (TTD). The common targets obtained by two databases were determined as candidate proteins involved in AD. All active components related to Kai Xin San were researched from ADME (absorption, distribution, metabolism and excretion). PharmMapper was used to obtain the primary candidate targets of Kai Xin San. The corresponding gene name of each target protein was obtained from the UniProt database and selected human target proteins. Finally, the target proteins related to AD by Kai Xin San were acquired; Cytoscape 3.5.1 was used to construct the topology analysis for the active ingredient-AD target interaction network of Kai Xin San. According to STRING database and DAVID annotation databases, Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the targets was performed. The network pharmacology analysis results were verified by Discovery Studio molecular docking software. There were 31 components meeting the conditions of ADME and 8 targets relating to AD. Thirteen kinds of biological process, 7 related to molecular function and 11 related to cellar components, were included in 31 GO entries. There were 5 KEGG pathways, involving the calcium signaling pathway and PI3K-Akt signaling pathway. The docking results of Discovery Studio showed that active ingredients of Kai Xin San and the positive controls all have good binding activity with important targets. In conclusion, the Kai Xin San as applied for treating AD has the advantages of multi-components and targets, to investigate the active components and mechanism of Kai Xin San for treating AD based on network pharmacology to eludicate possible studies of the mechanisms of action.
Key words:    Kai Xin San    Alzheimer    network pharmacology    target    molecular docking   
收稿日期: 2018-05-21
DOI: 10.16438/j.0513-4870.2018-0474
通讯作者: 杨静娴,Tel:86-411-87586009,E-mail:jinxiangyang@163.com
Email: jinxiangyang@163.com
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