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中药方剂（葛根芩连汤）治疗溃疡性结肠炎机制的计算机模拟及体内研究

In Silico and In Vivo Studies on the Mechanisms of Chinese Medicine Formula (Gegen Qinlian Decoction) in the Treatment of Ulcerative Colitis.

作者信息

Liu Xiaolu, Fan Yuling, Du Lipeng, Mei Zhigang, Fu Yang

机构信息

Institute of Basic Theory for Integrated Traditional Chinese and Western Medicine, College of Integrated Traditional Chinese and Western Medicine, Hunan University of Chinese Medicine, Changsha, China.

Third-Grade Pharmacological Laboratory on Chinese Medicine Approved by State Administration of Traditional Chinese Medicine, Medical College of China Three Gorges University, Yichang, China.

出版信息

Front Pharmacol. 2021 Jun 11;12:665102. doi: 10.3389/fphar.2021.665102. eCollection 2021.

DOI:10.3389/fphar.2021.665102
PMID:34177580
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8232523/
Abstract

Ulcerative colitis (UC) is a chronic inflammatory bowel disease, and Gegen Qinlian Decoction (GQD), a Chinese botanical formula, has exhibited beneficial efficacy against UC. However, the mechanisms underlying the effect of GQD still remain to be elucidated. In this study, network pharmacology approach and molecular docking in silico were applied to uncover the potential multicomponent synergetic effect and molecular mechanisms. The targets of ingredients in GQD were obtained from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Bioinformatics Analysis Tool for Molecular mechANism of TCM (BATMAN-TCM) database, while the UC targets were retrieved from Genecards, therapeutic target database (TTD) and Online Mendelian Inheritance in Man (OMIM) database. The topological parameters of Protein-Protein Interaction (PPI) data were used to screen the hub targets in the network. The possible mechanisms were investigated with gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was used to verify the binding affinity between the active compounds and hub targets. Network pharmacology analysis successfully identified 77 candidate compounds and 56 potential targets. The targets were further mapped to 20 related pathways to construct a compound-target-pathway network and an integrated network of GQD treating UC. Among these pathways, PI3K-AKT, HIF-1, VEGF, Ras, and TNF signaling pathways may exert important effects in the treatment of UC via inflammation suppression and anti-carcinogenesis. In the animal experiment, treatment with GQD and sulfasalazine (SASP) both ameliorated inflammation in UC. The proinflammatory cytokines (TNF-α, IL-1β, and IL-6) induced by UC were significantly decreased by GQD and SASP. Moreover, the protein expression of EGFR, PI3K, and phosphorylation of AKT were reduced after GQD and SASP treatment, and there was no significance between the GQD group and SASP group. Our study systematically dissected the molecular mechanisms of GQD on the treatment of UC using network pharmacology, as well as uncovered the therapeutic effects of GQD against UC through ameliorating inflammation via downregulating EGFR/PI3K/AKT signaling pathway and the pro-inflammatory cytokines such as TNF-α, IL-1β and IL-6.

摘要

溃疡性结肠炎（UC）是一种慢性炎症性肠病，而中药方剂葛根芩连汤（GQD）已显示出对UC的有益疗效。然而，GQD作用的潜在机制仍有待阐明。在本研究中，应用网络药理学方法和计算机辅助分子对接技术来揭示其潜在的多成分协同效应和分子机制。GQD中成分的靶点从中药系统药理学数据库与分析平台（TCMSP）和中药分子机制生物信息学分析工具（BATMAN-TCM）数据库中获取，而UC的靶点则从基因卡片数据库（Genecards）、治疗靶点数据库（TTD）和人类孟德尔遗传在线数据库（OMIM）中检索。利用蛋白质-蛋白质相互作用（PPI）数据的拓扑参数筛选网络中的核心靶点。通过基因本体（GO）富集分析和京都基因与基因组百科全书（KEGG）通路富集分析对可能的机制进行研究。分子对接用于验证活性化合物与核心靶点之间的结合亲和力。网络药理学分析成功鉴定出77种候选化合物和56个潜在靶点。这些靶点进一步映射到20条相关通路，构建了化合物-靶点-通路网络以及GQD治疗UC的整合网络。在这些通路中，PI3K-AKT、HIF-1、VEGF、Ras和TNF信号通路可能通过抑制炎症和抗癌作用在UC治疗中发挥重要作用。在动物实验中，GQD和柳氮磺胺吡啶（SASP）治疗均改善了UC的炎症。GQD和SASP显著降低了UC诱导的促炎细胞因子（TNF-α、IL-1β和IL-6）。此外，GQD和SASP治疗后EGFR、PI3K的蛋白表达以及AKT的磷酸化水平均降低，且GQD组和SASP组之间无显著差异。我们的研究利用网络药理学系统地剖析了GQD治疗UC的分子机制，并通过下调EGFR/PI3K/AKT信号通路以及TNF-α、IL-1β和IL-6等促炎细胞因子来改善炎症，从而揭示了GQD对UC的治疗作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11b6/8232523/8bc6c50ebd7b/fphar-12-665102-g011.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11b6/8232523/048d4dcdcc52/fphar-12-665102-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11b6/8232523/e91337325ba7/fphar-12-665102-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11b6/8232523/927682a4f7db/fphar-12-665102-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11b6/8232523/754ac41fe1e2/fphar-12-665102-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11b6/8232523/5b2c83d61184/fphar-12-665102-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11b6/8232523/8bc6c50ebd7b/fphar-12-665102-g011.jpg

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