Anti-cancer Mechanism of Polygonati Rhizoma-Lilii Bulbus Based on Network Pharmacology

Ting YU; Zhu YANG; Feng-xi LONG; Wen-yu WU; Jia WANG; Jin-lin WU; Dong-xin TANG

doi:10.13422/j.cnki.syfjx.20192123

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Anti-cancer Mechanism of Polygonati Rhizoma-Lilii Bulbus Based on Network Pharmacology

Data Mining | 更新时间：2021-02-09

- Anti-cancer Mechanism of Polygonati Rhizoma-Lilii Bulbus Based on Network Pharmacology
- Chinese Journal of Experimental Traditional Medical Formulae Vol. 26, Issue 5, Pages: 168-177(2020)
- 作者机构：
  
  贵州中医药大学　贵州省中医肿瘤传承与科技创新人才基地，贵阳　 550002
- 作者简介：
- 基金信息：
- DOI：10.13422/j.cnki.syfjx.20192123
  CLC： R22; R242; R2-031;R285.5; R287
- Received：18 April 2019，
  
  Published Online：17 July 2019，
  
  Published：05 March 2020
- 稿件说明：
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Ting YU, Zhu YANG, Feng-xi LONG, et al. Anti-cancer Mechanism of Polygonati Rhizoma-Lilii Bulbus Based on Network Pharmacology[J]. Chinese journal of experimental traditional medical formulae, 2020, 26(5): 168-177.
DOI：

Ting YU, Zhu YANG, Feng-xi LONG, et al. Anti-cancer Mechanism of Polygonati Rhizoma-Lilii Bulbus Based on Network Pharmacology[J]. Chinese journal of experimental traditional medical formulae, 2020, 26(5): 168-177. DOI： 10.13422/j.cnki.syfjx.20192123.

摘要

目的：

通过网络药理学的方法筛选黄精-百合药对中的有效成分，预测治疗癌症的作用靶点及信号通路，进一步探讨潜在作用机制。

方法：

使用全称为中药系统药理学分析平台筛选黄精-百合药对中的活性成分和靶点，通过基因疾病关联数据库(DisGeNET)与人类孟德尔遗传数据库(OMIM)预测与筛选药对中有效的中药成分作用的疾病靶点。选择生物信息分析学习平台(Omicshare)匹配药物和疾病的靶点，借助复杂网络可视化平台(Cytoscape3.7.0)软件构建“药物-成分-疾病”网络。采用蛋白质相互作用网络数据库(String)构建黄精-百合药对治疗癌症的靶点相互作用的网络。最后通过功能注释生物信息学分析平台(DAVID)对黄精-百合药对中关键作用的节点进行生物功能及代谢通路分析。

结果：

筛选出19个黄精-百合药对的活性成分，根据靶点预测技术预测出相关靶点234个，与疾病靶点有关的活性成分为6个，主要通过调控丝氨酸(Akt)/苏氨酸激酶1(Akt1)，Jun原癌基因，AP-1转录因子亚基(JUN)，血管内皮生长因子A(VEGFA)，基质金属蛋白酶-9(MMP-9)，半胱氨酸蛋白酶-3(Caspase-3)等靶蛋白，以及癌症中的蛋白多糖，雌激素信号转导通路，人免疫缺陷病毒1感染，缺氧诱导因子-1(HIF-1)信号通路，肿瘤坏死因子(TNF)信号通路，癌症中的微型核糖核酸(MicroRNAs)等通路发挥抗癌作用。

结论：

黄精-百合药对治疗癌症的作用体现了中药多成分-多靶点-多途径的特点，为阐释其抗癌治疗的作用机制与物质基础提供了科学依据。

Abstract

Objective:

To screen out active ingredients of Polygonati Rhizoma-Lilii Bulbus

and predict the targets and signaling pathways

in order to explore the potential mechanism in treatment of cancer by using network pharmacology.

Method:

All of active ingredients and targets of Polygonati Rhizoma-Lilii Bulbus were screened out through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Disease targets for cancer were collected through databases of gene-disease associations (DisGeNET) and Online Mendelian Inheritance in Man (OMIM). Then the Omicshare platform was used to match the active ingredients and the targets for treating cancer. And the " drug-active ingredients-disease targets" network was established using Cytoscape 3.7.0 software. The functional protein association networks (String) database was used to construct the protein interaction network of drug pair targets for treating cancer. Finally

the Functional Annotation Bioinformatics Microarray Analysis (DAVID) database was used to analyze the biological functions and metabolic pathways of key targets.

Result:

A total of 19 active ingredients were screened out

234 targets were predicted

6 active ingredients were identified to be related to cancer. The anti-cancer effect was mainly correlated with the regulation of target proteins in treating cancer

such as Akt serine/threonine kinase 1 (Akt1)

Jun proto-oncogene

AP-1 transcription factor subunit (JUN)

vascular endothelial growth factor A (VEGFA)

matrix metallopeptidase-9 (MMP-9)

Caspase-3

Fos proto-oncogene

AP-1 transcription factor subunit (FOS)

proteoglycans in cancer

estrogen signaling pathway

human immunodeficiency virus 1 infection

hypoxia inducible factor-1 (HIF-1) signaling pathway

tumor necrosis factor(TNF) signaling pathway

microRNAs in cancer and other pathways.

Conclusion:

The anti-cancer effect of Polygonati Rhizoma-Lilii Bulbus reflects multi-component

multi-target

multi-pathway characteristics of TCM

and provides a scientific basis for explaining the mechanism and material basis of anti-cancer treatment.

关键词

Keywords

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