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基于网络药理学的车前草治疗高尿酸血症作用机制研究

Network Pharmacology-Based Investigation of the Mechanism of Action of Plantaginis Herba in Hyperuricemia Treatment.

作者信息

Tang Rong, Peng Xiaoqing, Wang Yan, Zhou Xiaohong, Liu Hong

机构信息

Department of Pharmacy, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Panfu Road 1, Guangzhou 510013, Guangdong, China.

Department of Traditional Chinese Medicine, The First Affiliated Hospital of Guangdong Pharmaceutical University, Gonghexiheng Street 1, Guangzhou 510080, Guangdong, China.

出版信息

Evid Based Complement Alternat Med. 2021 Apr 8;2021:5595384. doi: 10.1155/2021/5595384. eCollection 2021.

Abstract

This study used a network pharmacology approach to investigate the potential active ingredients of Plantaginis Herba and its underlying mechanisms in hyperuricemia treatment. The potential active ingredients of Plantaginis Herba were obtained from TCMSP and ETCM databases, and the potential targets of the active ingredients were predicted using the Swiss TargetPrediction database. The potential therapeutic targets of hyperuricemia were retrieved from the GeneCards, DisGeNET, and Online Mendelian Inheritance in Man (OMIM) databases. Then, the integrative bioinformatics analyses of candidates were performed by GO analysis, KEGG analysis, and PPI network construction. There were 15 predicted active ingredients in Plantaginis Herba and 41 common targets that may be involved in the treatment of hyperuricemia. A total of 61 GO annotations and 35 signaling pathways were identified by enrichment analysis ( < 0.01). The underlying mechanisms of Plantaginis Herba may be related to insulin resistance, PI3K/AKT, TNF, VEGF, AMPK, and glucagon signaling pathways. Thus, the present study provided potential and promising strategies of Plantaginis Herba for hyperuricemia treatment.

摘要

本研究采用网络药理学方法,探讨车前草治疗高尿酸血症的潜在活性成分及其潜在机制。从中药系统药理学数据库(TCMSP)和中药综合数据库(ETCM)中获取车前草的潜在活性成分,并使用瑞士药物靶点预测数据库(Swiss TargetPrediction)预测活性成分的潜在靶点。从基因卡片数据库(GeneCards)、疾病基因数据库(DisGeNET)和人类孟德尔遗传在线数据库(OMIM)中检索高尿酸血症的潜在治疗靶点。然后,通过基因本体论(GO)分析、京都基因与基因组百科全书(KEGG)分析和蛋白质-蛋白质相互作用(PPI)网络构建,对候选物进行综合生物信息学分析。车前草中有15种预测的活性成分和41个可能参与高尿酸血症治疗的共同靶点。通过富集分析(<0.01)共鉴定出61个GO注释和35条信号通路。车前草的潜在机制可能与胰岛素抵抗、PI3K/AKT、肿瘤坏死因子(TNF)、血管内皮生长因子(VEGF)、腺苷酸活化蛋白激酶(AMPK)和胰高血糖素信号通路有关。因此,本研究为车前草治疗高尿酸血症提供了潜在且有前景的策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b87b/8052156/d5e9d649a0a5/ECAM2021-5595384.001.jpg

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