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基于网络药理学和分子对接的分析预测黄芩汤治疗结直肠癌的潜在机制

Network pharmacology and molecular docking-based analyses to predict the potential mechanism of Huangqin decoction in treating colorectal cancer.

作者信息

Li Ying-Jie, Tang Dong-Xin, Yan Hong-Ting, Yang Bing, Yang Zhu, Long Feng-Xi

机构信息

Guizhou University of Traditional Chinese Medicine, Guizhou University of Traditional Chinese Medicine, Guiyang 550005, Guizhou Province, China.

Digestive Department, The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang 550001, Guizhou Province, China.

出版信息

World J Clin Cases. 2023 Jul 6;11(19):4553-4566. doi: 10.12998/wjcc.v11.i19.4553.

DOI:10.12998/wjcc.v11.i19.4553
PMID:37469733
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10353508/
Abstract

BACKGROUND

To analyze the potential action mechanism of Huangqin decoction (HQD) in colorectal cancer (CRC) treatment on the basis of network pharmacology and molecular docking.

AIM

To investigate the molecular mechanisms of HQD for CRC treatment by using network pharmacology and molecular docking.

METHODS

All HQD active ingredients were searched using the Systematic Pharmacology and Traditional Chinese Medicine Systems Pharmacology databases and the Bioinformatics Analysis Tool for Molecular Mechanisms in traditional Chinese medicine. Then, the targets of the active ingredients were screened. The abbreviations of protein targets were obtained from the UniProt database. A "drug-compound-target" network was constructed to screen for some main active ingredients. Some targets related to the therapeutic effect of CRC were obtained from the GeneCards, DisGeNET, Therapeutic Target Database, and Online Mendelian Inheritance in Man databases. The intersection of targets of Chinese herbs and CRC was taken. A Venn diagram was drawn to construct the intersection target interactions network by referring to the STRING database. Topological analysis of the protein interaction network was performed using Cytoscape 3.7.2 software to screen the core HQD targets for CRC. The core targets were imported into the DAVID 6.8 analysis website for gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses and visualization. Finally, molecular docking was performed using AutoDockTool and PyMOL for validation.

RESULTS

In total, 280 potential drug-active ingredients were present in HQD, including 1474 targets of the drug-active ingredients. The main active ingredients identified were betulin, tetrahydropalmatine, and quercetin. In total, 10249 CRC-related targets and 1014 drug-disease intersecting targets were identified, including 28 core targets of action such as Jun proto-oncogene, AP-1 transcription factor subunit, signal transducer and activator of transcription 3, tumor protein p53, vascular endothelial growth factor, and AKT serine/threonine kinase 1. The gene ontology enrichment functional analysis yielded 503 enrichment results, including 406 biological processes that were mainly related to the positive regulation of both gene expression and transcription and cellular response to hypoxia, In total, 38 cellular components were primarily related to polymer complexes, transcription factor complexes, and platelet alpha granule lumen. Then, 59 molecular functions were closely related to the binding of enzymes, homologous proteins, and transcription factors. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis yielded 139 enrichment results, involving epidermal growth factor receptor tyrosine kinase inhibitor resistance and HIF-1 and mitogen-activated protein kinase signaling pathways.

CONCLUSION

HQD can play a role in CRC treatment through the "multi-component-target-pathway". The active ingredients betulin, tetrahydropalmatine, and quercetin may act on targets such as Jun proto-oncogene, AP-1 transcription factor subunit, signal transducer and activator of transcription 3, tumor protein p53, vascular endothelial growth factor, and AKT serine/threonine kinase 1, which in turn regulate HIF-1 and mitogen-activated protein kinase signaling pathways in CRC treatment. The molecular docking junction clarified that all four key target proteins could bind strongly to the main HQD active ingredients. This indicates that HQD could slow down CRC progression by modulating multiple targets and signaling pathways.

摘要

背景

基于网络药理学和分子对接分析黄芩汤(HQD)治疗结直肠癌(CRC)的潜在作用机制。

目的

运用网络药理学和分子对接研究HQD治疗CRC的分子机制。

方法

通过系统药理学数据库、中药系统药理学数据库及中药分子机制生物信息学分析工具检索HQD所有活性成分,然后筛选活性成分的靶点,蛋白靶点缩写从UniProt数据库获取,构建“药物-化合物-靶点”网络以筛选一些主要活性成分。从GeneCards、DisGeNET、治疗靶点数据库及人类孟德尔遗传在线数据库获取一些与CRC治疗效果相关的靶点,取中药靶点与CRC靶点的交集,绘制韦恩图并参照STRING数据库构建交集靶点相互作用网络。使用Cytoscape 3.7.2软件对蛋白质相互作用网络进行拓扑分析,筛选HQD治疗CRC的核心靶点。将核心靶点导入DAVID 6.8分析网站进行基因本体论和京都基因与基因组百科全书富集分析及可视化。最后,使用AutoDockTool和PyMOL进行分子对接验证。

结果

HQD中共有280种潜在药物活性成分,包括1474个药物活性成分靶点。鉴定出的主要活性成分有桦木醇、延胡索乙素和槲皮素。共鉴定出10249个CRC相关靶点和1014个药物-疾病交叉靶点,包括28个核心作用靶点,如原癌基因Jun、AP-1转录因子亚基、信号转导和转录激活因子3、肿瘤蛋白p53、血管内皮生长因子和AKT丝氨酸/苏氨酸激酶1。基因本体论富集功能分析产生503个富集结果,包括406个主要与基因表达和转录的正调控以及细胞对缺氧反应相关的生物学过程。共有38个细胞成分主要与聚合物复合物、转录因子复合物和血小板α颗粒腔相关。然后,59个分子功能与酶、同源蛋白和转录因子的结合密切相关。京都基因与基因组百科全书通路富集分析产生139个富集结果,涉及表皮生长因子受体酪氨酸激酶抑制剂抗性以及HIF-1和丝裂原活化蛋白激酶信号通路。

结论

HQD可通过“多成分-靶点-通路”在CRC治疗中发挥作用。活性成分桦木醇、延胡索乙素和槲皮素可能作用于原癌基因Jun、AP-1转录因子亚基、信号转导和转录激活因子3、肿瘤蛋白p53、血管内皮生长因子和AKT丝氨酸/苏氨酸激酶1等靶点,进而在CRC治疗中调节HIF-1和丝裂原活化蛋白激酶信号通路。分子对接结果表明,所有四个关键靶蛋白均可与HQD主要活性成分强烈结合。这表明HQD可通过调节多个靶点和信号通路减缓CRC进展。

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