基于网络药理学与分子对接技术探究木犀草素治疗宫颈癌的分子机制

卢俊伟, 祝璟哲, 陈鸿儒, 解举民

卢俊伟, 祝璟哲, 陈鸿儒, 解举民. 基于网络药理学与分子对接技术探究木犀草素治疗宫颈癌的分子机制[J]. 实用临床医药杂志, 2024, 28(16): 26-33. DOI: 10.7619/jcmp.20241525
引用本文: 卢俊伟, 祝璟哲, 陈鸿儒, 解举民. 基于网络药理学与分子对接技术探究木犀草素治疗宫颈癌的分子机制[J]. 实用临床医药杂志, 2024, 28(16): 26-33. DOI: 10.7619/jcmp.20241525
LU Junwei, ZHU Jingzhe, CHEN Hongru, XIE Jumin. Molecular mechanism of luteolin in treatment of cervical cancer based on network pharmacology and molecular docking technology[J]. Journal of Clinical Medicine in Practice, 2024, 28(16): 26-33. DOI: 10.7619/jcmp.20241525
Citation: LU Junwei, ZHU Jingzhe, CHEN Hongru, XIE Jumin. Molecular mechanism of luteolin in treatment of cervical cancer based on network pharmacology and molecular docking technology[J]. Journal of Clinical Medicine in Practice, 2024, 28(16): 26-33. DOI: 10.7619/jcmp.20241525

基于网络药理学与分子对接技术探究木犀草素治疗宫颈癌的分子机制

基金项目: 

湖北省中央引导地方科技发展专项项目 2022BCE054

湖北理工学院科研重点项目 23xjz08A

湖北理工学院·黄石大冶湖高新区大学科技园联合开放基金立项项目 23xjz04AK

详细信息
    通讯作者:

    解举民, E-mail: xiejm922@163.com

  • 中图分类号: R737.33;R319;R966

Molecular mechanism of luteolin in treatment of cervical cancer based on network pharmacology and molecular docking technology

  • 摘要:
    目的 

    基于网络药理学与分子对接技术探讨木犀草素治疗宫颈癌的分子机制。

    方法 

    运用中药系统药理学数据库与分析平台(TCMSP)对木犀草素进行类药性分析。分别在PharmMapper、Super-PRED和Swiss Target Prediction数据库中获取木犀草素作用靶点。运用GeneCards、OMIM和PharmGKB数据库获取宫颈癌相关靶点。通过EVenn获得木犀草素与宫颈癌的交集靶点, 并使用Cytoscape3.8.1构建“木犀草素-交集靶点-宫颈癌”网络图。利用STRIING数据库对交集靶点进行蛋白质互作(PPI)网络分析,筛选核心靶点。采用David数据库对靶点进行基因本体论(GO)基因功能分析、京都基因和基因组百科全书(KEGG)信号通路富集分析。利用PyMoL 2.6.0、AutoDockTool 1.5.7和OpenBabel 2.4.1软件开展核心靶点与木犀草素的分子对接。将核心靶点在GEPIA数据库中进行生存分析及泛癌分析。

    结果 

    获得木犀草素靶点449个、宫颈癌相关靶点1 334个; 木犀草素与宫颈癌交集靶点100个,其中核心靶点有24个,包括MMP2HRASMAPK1AKT1RHOAPGR等。GO和KEGG富集分析发现交集靶点参与生物过程455条,细胞组分70条,分子功能119条和143条KEGG信号通路。分子对接发现MMP2与木犀草素结合较好。宫颈癌患者生存曲线显示RHOAMAPK1MMP2AKT1基因风险比率>1, HRASPGR的风险比率 < 1。泛癌分析显示HRASMAPK1在宫颈癌中高表达,并且HRAS有显著表达差异。

    结论 

    木犀草素通过多靶点、多途径的作用方式治疗宫颈癌。

    Abstract:
    Objective 

    To explore the molecular mechanism of luteolin in the treatment of cervical cancer based on network pharmacology and molecular docking technology.

    Methods 

    The drug-like properties of luteolin were analyzed by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The targets of luteolin were obtained from PharmMapper, Super-PRED, and Swiss Target Prediction databases. The targets related to cervical cancer were acquired from GeneCards, OMIM, and PharmGKB databases. The intersection targets of luteolin and cervical cancer were obtained through EVenn, and the "luteolin-intersection targets-cervical cancer" network diagram was constructed by Cytoscape 3.8.1. The STRING database was used to analyze the protein-protein interaction (PPI) network of intersection targets and screen the core targets. The Database for Annotation, Visualization and Integrated Discovery (David) was used to conduct Gene Ontology (GO) gene function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis of the targets. PyMoL 2.6.0, AutoDockTool 1.5.7 and OpenBabel 2.4.1 software were used to perform molecular docking between the core targets and luteolin. The survival analysis and pan-cancer analysis of the core targets were performed in the GEPIA database.

    Results 

    A total of 449 targets of luteolin and 1 334 targets related to cervical cancer were obtained; there were 100 intersection targets between luteolin and cervical cancer, of which 24 were core targets, including MMP2, HRAS, MAPK1, AKT1, RHOA and PGR. GO and KEGG enrichment analyses revealed that the intersection targets participated in 455 biological processes, 70 cellular components, 119 molecular functions, and 143 KEGG signaling pathways. Molecular docking revealed a good binding of MMP2 with luteolin. The survival curves of cervical cancer patients showed that the risk ratios of RHOA, MAPK1, MMP2 and AKT1 genes were greater than 1, while those of HRAS and PGR were less than 1. Pan-cancer analysis showed that HRAS and MAPK1 were highly expressed in cervical cancer, and HRAS had significant expression differences.

    Conclusion 

    Luteolin treats cervical cancer through a multi-target and multi-pathway mechanism.

  • 图  1   木犀草素治疗宫颈癌网络药理学分析流程图

    图  2   木犀草素-宫颈癌靶点

    A: 木犀草及木犀草素; B: 宫颈癌示意图; C: 蓝色、黄色和绿色分别代表在PharmMapper、Super-PRED和Swiss Target Prediction数据库获得的药物靶点; D: 蓝色、黄色和绿色分别代表GeneCards、OMIM和PharmGKB数据库获得的宫颈癌靶点。

    图  3   木犀草素-宫颈癌靶点可视化

    A: 木犀草素与宫颈癌交集靶点图,紫色代表木犀草素,蓝色代表宫颈癌; B: 成分-靶点-疾病图,红色菱形代表木犀草素,粉色正方形代表宫颈癌,深绿、浅绿和黄色代表木犀草素和宫颈癌的交集靶点。

    图  4   木犀草素抗宫颈癌PPI网络

    >A: 交集靶点PPI网络; B: 交集靶点PPI网络可视化; C: 核心靶点PPI网络; D: 核心靶点PPI网络可视化。

    图  5   木犀草素治疗宫颈癌的GO富集分析

    A、B、C: 木犀草素治疗宫颈癌的49个交集靶点前20条涉及的生物过程、细胞组分和分子功能,气泡大小表示富集靶点的数量,气泡颜色的深浅代表P值大小。

    图  6   “靶点-通路”图和KEGG富集分析

    A: 木犀草素抗肾癌“靶点-通路”的可视化图,橙色代表通路,黄色代表靶点; B: KEGG前10条通路富集分析可视化图。

    图  7   木犀草素抗宫颈癌信号通路图

    图  8   木犀草素与其抗宫颈癌核心靶点存在直接相互作用

    A: 木犀草素与其抗宫颈癌核心靶点分子对接评分热图; B: 木犀草素与核心靶点的分子对接3D可视化图,黄色虚线表示氢键,小分子表示木犀草素,木犀草素通过氢键相连的部分为互作氨基酸。

    图  9   宫颈癌患者生存分析

    A: MMP2在宫颈癌患者中的生存曲线; B: HRAS在宫颈癌患者中的生存曲线; C: MAPK1在宫颈癌患者中的生存曲线; D: AKT1在宫颈癌患者中的生存曲线; E: RHOA在宫颈癌患者中的生存曲线; F: PGR在宫颈癌患者中的生存曲线。

    图  10   宫颈癌患者泛癌分析

    A: MMP基因的表达差异; B: HRAS基因的表达差异; C: MAPK1基因的表达差异; D: AKT1基因的表达差异; E: RHOA基因的表达差异; F: PGR基因的表达差异。红色部分表示宫颈癌样本,蓝色部分表示正常样本。

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出版历程
  • 收稿日期:  2024-04-14
  • 修回日期:  2024-06-10
  • 刊出日期:  2024-08-27

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