神经药理学报 ›› 2024, Vol. 14 ›› Issue (3): 27-.DOI: 10.3969/j.issn.2095-1396.2024.03.004

• 研究论文 • 上一篇    下一篇

基于网络药理学和分子对接分析蒲公英的抗胃癌机制

王静,李璐璐,王邵宣,陶子爱,贾桂岩,董尚林   

  1. 1. 河北北方学院生命科学研究中心,张家口,075000,中国 

    2. 河北北方学院微循环研究所,张家口,075000,中国 

    3. 河北北方学院中医学院,张家口,075000,中国 

    4. 河北北方学院第一临床医学院,张家口,075000,中国

  • 出版日期:2024-06-26 发布日期:2024-08-20
  • 通讯作者: 董尚林,实验师;研究方向:主要从事中药药理学、肿瘤诊断及治疗学相关研究;E-mail:dongshanglin@163.com
  • 作者简介:王静,助理研究员;研究方向:主要从事中药抗肿瘤、微循环相关研究;E-mail:jing-wang1984@163.com
  • 基金资助:
    河北省医学科学研究课题计划项目(No.20220582);张家口市科技计划项目(No.2121082D)

Mechanism of Dandelion's Anti-Gastric Cancer Effects Based on Network Pharmacology and Molecular Docking Analysis

WANG Jing, LI Lu-lu, WANG Shao-xuan, TAO Zi-ai, JIA Gui-yan, DONG Shang-lin   

  1. 1. Life Science Research Center, Hebei North University, Zhangjiakou, 075000, China 

    2. Institution of Microcirculation, Hebei North University, Zhangjiakou, 075000, China 

    3. College of Traditional Chinese Medicine, Hebei North University, Zhangjiakou, 075000, China 

    4. First Clinical Medical College, Hebei North University, Zhangjiakou, 075000, China

  • Online:2024-06-26 Published:2024-08-20

摘要:

目的:通过网络药理学预测蒲公英抗胃癌的活性成分和主要靶点,探析其治疗胃癌的作用机制。方法: 采用TCMID、PubChem 以及Swiss Target Prediction 等数据库检索蒲公英的潜在活性成分,预测蒲公英潜在的作 用靶点。利用OMIM、Genecards、Drugbank 数据库检索胃癌相关靶点,将蒲公英作用靶点与胃癌相关靶点进行 交集,明确药物- 疾病共同靶点。将共同靶点导入STRING 数据库分析蛋白互作关系,Cytoscape 3.9.1 构建“药物- 成分- 靶点- 疾病” 网络图,Network Analyzer 分析核心靶点。利用R 软件使用Bioconductor 对共同靶点进行基 因本体( gene ontology,GO)和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG) 富集分析。根据Degree 值排序,分别取前4 个主要活性成分及核心靶点采用AutoDock 软件进行分子对接分析。 结果:获得药物潜在活性成分65 个,药物靶点577 个,疾病靶点1 517 个,药物- 疾病共同靶点118 个。经分析 得蒲公英中主要活性成分为artemetin、quercetin、luteolin、 myricetin、hesperetin、coniferyl aldehyde、esculetin 等, 蛋白核心靶点为STAT3、SRC、MAPK3、HSP90AA1、PIK3R1、MAPK1、PIK3CA 等。GO 分析结果获得2 402 条 生物过程、91 条细胞组分及168 条分子功能相关过程通路。KEGG 分析获得163 条KEGG 通路。分子对接结 果显示Degree 值前4 的主要活性成分与核心靶点的分子对接结合能均低于-5 Kcal·mol-1,表明结合活性较高。 结论:蒲公英可通过多成分、多通路、多靶点发挥抗胃癌作用,为进一步探讨蒲公英的抗胃癌机制提供了依据。

关键词: 网络药理学, 蒲公英, 胃癌, 分子对接

Abstract:

Objective:To predict the active components and primary targets of dandelion in the treatment of gastric cancer using network pharmacology, and to explore its underlying mechanisms. Methods: Potential active components of dandelion were retrieved from TCMID, PubChem, and Swiss Target Prediction databases, and their corresponding targets were predicted. Gastric cancer-related targets were identified using OMIM, GeneCards and DrugBank databases. Common targets between dandelion and gastric cancer were identified. STRING database was used for protein-protein interaction analysis. Cytoscape 3.9.1 was employed to create a "drug-componenttarget- disease" network, while Network Analyzer was utilized to analyze the key targets. GO and KEGG enrichment analyses were conducted using Bioconductor packages in R software Molecular docking of dandelion's main active components with core targets was conducted using AutoDock. Results: 65 potential active components and 577 drug targets of dandelion were identified, along with 1 517 gastric cancer targets, yielding 118 common targets. Key active components include artemetin, quercetin, luteolin, myricetin, hesperetin, coniferyl aldehyde, and esculetin. Key targets include STAT3, SRC, MAPK3, HSP90AA1, PIK3R1, MAPK1, and PIK3CA. GO analysis identified 2 402 biological processes, 91 cellular components, and 168 molecular functions. KEGG analysis identified 163 pathways. Molecular docking indicated strong binding affinities between major active components and key targets. Conclusion: Dandelion exhibits therapeutic effects on gastric cancer through multiple components, pathways, and targets, providing a theoretical basis for further investigation into its antigastric cancer mechanisms and offering relevant evidence for subsequent experimental validation.

Key words: network pharmacology, dandelion, gastric cancer, molecular docking

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