Gao Qiang, Tian Danfeng, Han Zhenyun, Lin Jingfeng, Chang Ze, Zhang Dandan, Ma Dayong
Beijing University of Chinese Medicine, Beijing 100029, China.
Shenzhen Hospital of Beijing University of Chinese Medicine (Longgang), Shenzhen 518172, China.
Evid Based Complement Alternat Med. 2021 Feb 26;2021:8815447. doi: 10.1155/2021/8815447. eCollection 2021.
The bioactive components and potential targets of BHD were screened by TCMSP, BATMAN-TCM, ETCM, and SymMap databases. Besides, compounds that failed to find the targets from the above databases were predicted through STITCH, SwissTargetPrediction, and SEA. Moreover, six databases were searched to mine targets of IS. The intersection targets were obtained and analyzed by GO and KEGG enrichment. Furthermore, BHD-IS PPI network, compound-target network, and herb-target-pathway network were constructed by Cytoscape 3.6.0. Finally, AutoDock was used for molecular docking verification.
A total of 235 putative targets were obtained from 59 active compounds in BHD. Among them, 62 targets were related to IS. PPI network showed that the top ten key targets were IL6, TNF, VEGFA, AKT1, etc. The enrichment analysis demonstrated candidate BHD targets were more frequently involved in TNF, PI3K-Akt, and NF-kappa B signaling pathway. Network topology analysis showed that was the main herb in BHD, and the key components were quercetin, beta-sitosterol, kaempferol, stigmasterol, etc. The results of molecular docking showed the active components in BHD had a good binding ability with the key targets.
Our study demonstrated that BHD exerted the effect of treating IS by regulating multitargets and multichannels with multicomponents through the method of network pharmacology and molecular docking.
通过中药系统药理学数据库与分析平台（TCMSP）、中药系统生物学与药物靶点数据库（BATMAN-TCM）、中药成分靶点数据库（ETCM）和中药综合数据库（SymMap）筛选补阳还五汤（BHD）的生物活性成分和潜在靶点。此外，通过STITCH、SwissTargetPrediction和SEA对上述数据库中未找到靶点的化合物进行预测。此外，搜索六个数据库以挖掘缺血性中风（IS）的靶点。通过基因本体论（GO）和京都基因与基因组百科全书（KEGG）富集分析获得并分析交集靶点。此外，使用Cytoscape 3.6.0构建BHD-IS蛋白质-蛋白质相互作用（PPI）网络、化合物-靶点网络和草药-靶点-通路网络。最后，使用自动对接（AutoDock）进行分子对接验证。
从BHD的59种活性化合物中总共获得235个假定靶点。其中，62个靶点与IS相关。PPI网络显示前十个关键靶点为白细胞介素6（IL6）、肿瘤坏死因子（TNF）、血管内皮生长因子A（VEGFA）、蛋白激酶B1（AKT1）等。富集分析表明，候选BHD靶点更频繁地参与TNF、磷脂酰肌醇-3激酶-蛋白激酶B（PI3K-Akt）和核因子κB（NF-κB）信号通路。网络拓扑分析表明黄芪是BHD中的主要草药，关键成分是槲皮素、β-谷甾醇、山奈酚、豆甾醇等。分子对接结果表明BHD中的活性成分与关键靶点具有良好的结合能力。
我们的研究表明，BHD通过网络药理学和分子对接方法，以多成分、多靶点、多途径发挥治疗IS的作用。
