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成都中医药大学 药学院, 西南特色中药资源国家重点实验室,成都 611100
王佳俊,在读硕士,从事中药药性理论与应用研究,E-mail:526632532@qq.com
王建,教授,博士生导师,从事中药药性理论与应用研究,E-mail:jianwang08@163.com
收稿日期:2021-11-27,
网络出版日期:2022-03-23,
纸质出版日期:2022-07-05
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王佳俊,杨显娟,王立映等.黄连厚朴汤改善溃疡性结肠炎的网络药理学机制分析[J].中国实验方剂学杂志,2022,28(13):217-224.
WANG Jiajun,YANG Xianjuan,WANG Liying,et al.Mechanism of Huanglian Houpotang on Ulcerative Colitis by Network Pharmacology and Experimental Verification[J].Chinese Journal of Experimental Traditional Medical Formulae,2022,28(13):217-224.
王佳俊,杨显娟,王立映等.黄连厚朴汤改善溃疡性结肠炎的网络药理学机制分析[J].中国实验方剂学杂志,2022,28(13):217-224. DOI: 10.13422/j.cnki.syfjx.20220711.
WANG Jiajun,YANG Xianjuan,WANG Liying,et al.Mechanism of Huanglian Houpotang on Ulcerative Colitis by Network Pharmacology and Experimental Verification[J].Chinese Journal of Experimental Traditional Medical Formulae,2022,28(13):217-224. DOI: 10.13422/j.cnki.syfjx.20220711.
目的
2
基于网络药理学及动物实验,对黄连厚朴汤治疗溃疡性结肠炎(UC)的主要活性成分及其潜在的作用机制进行探讨。
方法
2
运用中药系统药理分析平台(TCMSP)和BATMAN-TCM数据库初步获取黄连厚朴汤的活性成分,结合TCMSP、SwissADME和SwissTargetPrediction平台筛选其中的主要活性成分,并预测其靶点。借助基因表达综合数据库(GEO)检索相关芯片以获得疾病基因。取药物靶点与疾病基因交集,筛选黄连厚朴汤治疗UC的潜在治疗靶点。利用Cytoscape 3.7.2软件构建“药物-活性成分-靶点-疾病”相互作用网络图,同时,将潜在治疗靶点导入DAVID 6.8网站做基因本体(GO)生物学过程(BP)分析以预测相关的生物学过程。最后通过动物实验对主要生物学过程进行验证。采用酶联免疫吸附测定法(ELISA)检测黄连厚朴汤对小鼠结肠组织炎症因子的影响;使用蛋白免疫印迹法(Western blot)检测相关凋亡蛋白B细胞淋巴瘤-2(Bcl-2)相关X的蛋白质(Bax)、Bcl-2、胱天冬蛋白酶-3(Caspase-3)的表达;运用IVIS系统检测活性氧(ROS)在各组小鼠结肠组织的含量。
结果
2
该研究共筛选出黄连厚朴汤19个活性成分,涉及32个UC潜在治疗靶点及158个生物学过程;动物实验结果表明,黄连厚朴汤可以通过抑制炎症因子肿瘤坏死因子(TNF)-
α
、白细胞介素-1
β
(IL-1
β
)表达、降低凋亡蛋白含量、调控ROS表达以发挥抗UC作用。
结论
2
该研究揭示了网络药理学预测并指导实验设计的合理性,证实黄连厚朴汤可以通过参与免疫炎症、细胞凋亡、ROS等生物过程发挥效用,为黄连厚朴汤治疗UC的机制研究提供依据。
Objective
2
To explore the active components and underlying mechanism of Huanglian Houpotang (HHD) against ulcerative colitis(UC) based on network pharmacology and animal experiments.
Method
2
The active components of HHD were preliminarily obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) and Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) and screened out by TCMSP, SwissADME, and SwissTargetPrediction, and their targets were predicted. Relevant microarrays were searched for disease genes with the help of Gene Expression Omnibus (GEO). The common targets of HHD and disease genes were screened out to obtain the potential targets of HHD against UC. The drug-active component-target-disease network was constructed using Cytoscape 3.7.2. The potential therapeutic targets were imported into the DAVID 6.8 for GO-Biological process (GO-BP) analysis to predict related biological processes which were subsequently verified by the animal experiment. Enzyme-linked immunosorbent assay (ELISA) was used to detect the effect of HHD on inflammatory factors in colon tissues of mice. Western blot was used to detect the protein expression of B-cell lymphoma 2 (Bcl-2), Bcl-2-associated X protein (Bax), and cysteinyl aspartate-specific protease 3 (Caspase-3). The IVIS system was used to detect the content of reactive oxygen species (ROS) in colon tissues of mice in each group.
Result
2
Nineteen active components of HHD were screened out, involving 32 potential therapeutic targets against UC and 158 biological processes. The results of the animal experiment showed that HHD exerted its anti-UC effect by inhibiting the expression of inflammatory factors tumor necrosis factor (TNF)-
α
and interleukin-1
β
(IL-1
β
), reducing the content of apoptotic proteins, and regulating the expression of ROS.
Conclusion
2
This study revealed the rationality of predictions and guidance of network pharmacology in experimental design, and confirmed that HHD could exert its effects by participating in biological processes such as immune inflammation, apoptosis, and ROS, which is expected to provide a basis for the mechanism research of HHD in the treatment of UC.
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