中国药物警戒 ›› 2026, Vol. 23 ›› Issue (7): 733-738.
DOI: 10.19803/j.1672-8629.20250732

• 脓毒症中医药机制与临床用药研究专栏 • 上一篇    下一篇

基于数据挖掘与网络药理学探讨β-Sitosterol治疗脓毒症性凝血病的作用机制

李雅静1,2, 陈腾飞3, 王雪蕊4,5, 徐霄龙4,5, 刘清泉1,3,4,5,*   

  1. 1内蒙古医科大学中医学院,内蒙古 呼和浩特 010110;
    2包头市中心医院中医科,内蒙古 包头 014040;
    3北京中医医院重症医学科,北京 100010;
    4北京市中医研究所,北京 100010;
    5中医疫病化瘀解毒理论创新研究北京市重点实验室,北京 100010
  • 收稿日期:2025-10-17 出版日期:2026-07-15 发布日期:2026-07-16
  • 通讯作者: *刘清泉,男,主任医师,教授·博导,中医结合急诊与危重症。E-mail: liuqingquan_2003@126.com
  • 作者简介:李雅静,女,在读博士,中医药防治急危重症。
  • 基金资助:
    国家自然科学基金资助项目（82474428、82575023）; 中医药国家多学科创新团队项目（ZYYCXTD-D-202201）

Mechanisms of β-Sitosterol against sepsis-induced coagulopathy based on data mining and network pharmacology

Li Yajing1,2, Chen Tengfei3, Wang Xuerui4,5, Xu Xiaolong4,5, Liu Qingquan1,3,4,5,*   

  1. 1School of Traditional Chinese Medicine, Inner Mongolia Medical University, Hohhot Inner Mongolia 010110, China;
    2Department of Traditional Chinese Medicine, Baotou Central Hospital, Baotou Inner Mongolia 014040, China;
    3Department of Critical Care Medicine, Beijing Hospital of Traditional Chinese Medicine, Beijing 100010, China;
    4Beijing Institute of Traditional Chinese Medicine, Beijing 100010, China;
    5Beijing Key Laboratory of Theory Innovation and Application on Traditional Chinese Medicine for Resolving Blood Stasis and Detoxification in Epidemic Diseases, Beijing 100010, China
  • Received:2025-10-17 Online:2026-07-15 Published:2026-07-16

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摘要： 目的 挖掘含β-Sitosterol中药的性味归经特点,整合网络药理学和分子动力学阐述其治疗脓毒症性凝血病（Sepsis-Induced Coagulopathy, SIC）的潜在作用机制,为SIC的防治提供参考。方法 通过公共数据库筛选含β-Sitosterol的中药信息及其作用靶点,分析药物性味归经规律;从GeneCards、OMIM、TTD数据库获取SIC相关靶点,取两者交集后获得作用靶点。利用蛋白质相互作用网络识别关键靶点,并进行GO和KEGG富集分析。通过分子对接验证两者的亲和力,并利用分子动力学模拟评价β-Sitosterol与核心靶点结合的稳定性。结果 数据挖掘显示含β-Sitosterol的中药多为清热药、性味苦寒,归肝经。共筛选出其与SIC的交集靶点14个。通路富集分析表明,其机制主要涉及T细胞受体信号通路、FOXO信号通路等。分子对接结果显示,β-Sitosterol与核心靶点结合良好;分子动力学模拟进一步表明,β-Sitosterol 能与TNF、SHH等靶蛋白形成稳定的蛋白质配体复合物。结论 初步阐明β-Sitosterol可能通过作用于TNF、SHH等多个靶点,调控T细胞受体、FOXO等信号通路,发挥治疗SIC的作用。

关键词: β-Sitosterol, 脓毒症性凝血病, TNF, SHH, T细胞受体, FOXO信号通路, 数据挖掘, 网络药理学, 分子动力学模拟

Abstract: Objective To explore the properties, flavors, and channel tropism of traditional Chinese medicines (TCMs) containing β-Sitosterol, and to study the potential molecular mechanisms of β-Sitosterol against sepsis-induced coagulopathy (SIC) by integrating network pharmacology and molecular dynamics (MD) in order to provide data for the prevention and treatment of SIC. Methods We screened TCMs containing β-Sitosterol and identified their potential targets via databases before analyzing the taste, property and meridian tropism of related herbs. SIC-related targets were retrieved from the GeneCards, OMIM, and TTD databases while the intersection of these targets was identified using Venny 2.1.0. Protein-protein interaction (PPI) networks were used to identify key targets, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Molecular docking was used to validate the affinity between β-Sitosterol and core targets, and molecular dynamics simulations were performed to evaluate the stability of β-Sitosterol binding to these targets. Results Data mining found that β-Sitosterol-containing TCMs were predominantly categorized as “heat-clearing” drugs, which were bitter in flavor and cold in nature and belonged to the liver meridian. A total of 14 intersection targets between β-Sitosterol and SIC were identified. Pathway enrichment analysis suggested that the underlying mechanisms involved the T-cell receptor signaling pathway and the FOXO signaling pathway. Molecular docking results showed strong binding affinity between β-Sitosterol and the core targets. MD simulations confirmed that β-Sitostero formed stable protein-ligand complexes with target proteins such as TNF and SHH. Conclusion This study finds that β-Sitosterol may exert therapeutic effects against SIC by targeting multiple proteins, including TNF and SHH, and modulating signaling pathways such as the T-cell receptor and FOXO.

Key words: β-Sitosterol, Sepsis-Induced Coagulopathy, TNF, SHH, T-Cell Receptor, FOXO Signaling Pathways, Data Mining, Network Pharmacology, Molecular Dynamics Simulation

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