基础医学与临床 ›› 2025, Vol. 45 ›› Issue (7): 939-946.doi: 10.16352/j.issn.1001-6325.2025.07.0939

• 研究论文 • 上一篇    下一篇

基于网络药理学的抗肺癌茶叶小分子筛选及验证

杨瑞, 杜斯奋, 蒋乐辉, 付恬, 任鹏举, 蒋澄宇, 张艳丽*   

  1. 中国医学科学院基础医学研究所 北京协和医学院基础学院 生物化学与分子生物学系,重大疾病共性机制研究全国重点实验室,北京 100005
  • 收稿日期:2025-04-14 修回日期:2025-05-21 出版日期:2025-07-05 发布日期:2025-06-24
  • 通讯作者: *zhangyanli@ibms.pumc.edu.cn
  • 基金资助:
    中国医学科学院医学与健康科技创新工程重大协同创新项目(2021-I2M-1-022)

Network pharmacology-based screening and validation of tea-derived small molecules against lung cancer

YANG Rui, DU Sifen, JIANG Lehui, FU Tian, REN Pengju, JIANG Chengyu, ZHANG Yanli*   

  1. Department of Biochemistry and Molecular Biology,State Key Laboratory of Common Mechanism Research for Major Diseases, Institute of Basic Medical Sciences CAMS, School of Basic Medicine PUMC, Beijing 100005, China
  • Received:2025-04-14 Revised:2025-05-21 Online:2025-07-05 Published:2025-06-24
  • Contact: *zhangyanli@ibms.pumc.edu.cn

摘要: 目的 筛选茶叶中对肺癌有潜在治疗效果的活性化学成分,为肺癌的治疗与预防提供新的思路。方法 本研究基于网络药理学方法,首先通过液质联用质谱(LC-MS)技术检测13个茶叶中的主要活性成分,通过BATMAN-TCM数据库获得小分子的作用靶点,构建“成分-靶点-疾病”网络。结合GeneCard和Malacard数据库获取肺癌相关疾病靶点,对潜在药理靶点进行GO功能和KEGG通路富集分析,并借助STRING数据库构建蛋白质互作网络(PPI)。最后通过分子对接筛选潜在治疗癌症的活性小分子,并检测其在人非小细胞肺癌细胞系A549和人大细胞肺癌细胞系H460抑制肺癌细胞增殖活性的能力。结果 筛选得到茶叶中的37个活性成分与429个作用靶点,与肺癌相关的交集靶点共计182个;GO分析结果显示,这些靶点主要参与细胞增殖、刺激反应、代谢过程等生物过程;KEGG通路分析结果显示,这些靶点主要参与p53信号通路、ErbB 信号通路、PI3K-Akt 信号通路等。PPI网络分析发现MAPK1、AKT1、SRC、MAPK3、p53等关键靶点。分子对接筛选出能结合人雌激素受体2(ESR2)的分子香豆雌酚,并在A549细胞和H460细胞上验证了香豆雌酚能抑制肺癌细胞的增殖活性(P<0.000 1 )。结论 茶叶中的活性成分可能通过多成分、多靶点、多通路机制干预肺癌的发生发展,为茶叶中有效成分的开发利用提供新思路。

关键词: 茶叶, 肺癌, 网络药理学, 蛋白质互作网络

Abstract: Objective To screen the active chemical components with potential therapeutic effects against lung cancer in tea and to provide new insights into the treatment and prevention of lung cancer. Methods Based on network pharmacology, the main active components from 13 types of tea samples were analyzed using liquid chromatography-mass spectrometry(LC-MS). The targets of these small molecules were obtained from the BATMAN-TCM database to construct a “component-target-disease” network. Lung cancer-related disease targets were retrieved from the GeneCard and Malacard databases followed by Gene Ontology (GO) functional and KEGG pathway enrichment analyses of potential pharmacological targets. A protein-protein interaction (PPI) network was constructed using the STRING database. The molecular docking was employed to screen small molecules with potential anti-cancer activity, and their potential inhibition to proliferation of human non-small cell lung cancer cell line A549 and human large cell lung cancer cell line H460. Results A total of 37 active components and 429 targets were identified in tea, with 182 overlapping targets associated with lung cancer. GO analysis revealed that these targets were primarily involved in biological processes such as cell proliferation, response to stimuli, and metabolic processes. KEGG pathway analysis indicated that these targets were mainly enriched in the p53 signaling pathway, ErbB signaling pathway, and PI3K-Akt signaling pathway. PPI network analysis identified key targets including MAPK1, AKT1, SRC, MAPK3, and p53. Molecular docking screened coumestrol as a molecule capable of binding to human estrogen receptor 2 (ESR2), and its inhibitory effect on the proliferation of A549 and H460 cells was experimentally validated(P<0.000 1). Conclusions The active components in tea may intervene in the development and progression of lung cancer through a multi-component, multi-target, and multi-pathway mechanism, The results suggests potential components against lung cancer in tea, which may be applied in the prevention of human lung cancer.

Key words: tea, lung cancer, network pharmacology, protein-protein interaction network

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