文章摘要
李晴,朱香梅,石雨荷,朱珏,王智,刘湘丹,周日宝,童巧珍.基于指纹图谱和网络药理学的白术质量标志物预测分析[J].中国药事,2022,36(4):404-416
基于指纹图谱和网络药理学的白术质量标志物预测分析
Prediction and Analysis of Quality Markers of Atractylodis Macrocephalae Rhizoma Based on Fingerprints, and Network Pharmacology
  
DOI:10.16153/j.1002-7777.2022.04.006
中文关键词: 白术  质量标志物  指纹图谱  网络药理学  白术内酯Ⅰ  白术内酯Ⅱ  白术内酯Ⅲ  苍术酮
英文关键词: Atractylodis Macrocephalae Rhizoma  quality markers  fingerprints  network pharmacology  AtractylenolideⅠ  AtractylenolideⅡ  AtractylenolideⅢ  Atractylolone
基金项目:湖南省科技厅中央引导地方科技发展专项资金项目(编号 2019XF5069);湖南省科技厅科技特派员服务乡村振兴项目(编号2021NK4240);湘产大宗道地药材平术高品质生态种植及精准扶贫示范研究(编号 19A367)
作者单位
李晴 湖南中医药大学药学院,长沙 410208 
朱香梅 湖南中医药大学药学院,长沙 410208 
石雨荷 湖南中医药大学药学院,长沙 410208 
朱珏 湖南中医药大学药学院,长沙 410208 
王智 湖南中医药大学药学院,长沙 410208 湘产大宗道地药材种质资源及规范化种植重点研究室,长沙 410208 湖南省普通高等学校中药现代化研究重点实验室,长沙 410208 
刘湘丹 湖南中医药大学药学院,长沙 410208 湘产大宗道地药材种质资源及规范化种植重点研究室,长沙 410208 湖南省普通高等学校中药现代化研究重点实验室,长沙 410208 
周日宝 湖南中医药大学药学院,长沙 410208 湘产大宗道地药材种质资源及规范化种植重点研究室,长沙 410208 湖南省普通高等学校中药现代化研究重点实验室,长沙 410208 
童巧珍 湖南中医药大学药学院,长沙 410208 湘产大宗道地药材种质资源及规范化种植重点研究室,长沙 410208 湖南省普通高等学校中药现代化研究重点实验室,长沙 410208 
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中文摘要:
      目的:基于指纹图谱和网络药理学分析白术中潜在质量标志物(Q-Marker)并测定其含量。方法:采用 Waters Sun Fire C18 色谱柱(250 mm×4.6 mm,5 μm),以水(A)-乙腈(B)为流动相,梯度洗脱,流速1 mL·min-1,检测波长切换测定,柱温30 ℃,进样量 10 μL,建立白术药材指纹图谱, 对32批白术药材进行相似度评价,确认共有峰并进行指认,再通过网络药理学方法构建“活性成分-靶点-通路”网络图,预测 Q-Marker,并测定其含量。结果:建立了32批白术药材指纹图谱,确认了 28 个共有峰,通过白术对照品指认4个色谱峰,分别为白术内酯Ⅰ、白术内酯Ⅱ、白术内酯Ⅲ、苍术酮; 经网络药理学确认以上 4 种成分为活性成分,可作用于 16个核心靶点、20 条关键通路发挥抗癌、抗炎、改善胃肠道疾病作用,初步预测白术内酯Ⅰ、白术内酯Ⅱ、白术内酯Ⅲ、苍术酮为潜在Q-Marker, 白术药材中其总质量分数不低于1.79 mg·g-1结论:白术潜在Q-Marker预测分析为建立一整套质量控制评价体系提供参考,为阐明其药效物质基础的作用机制奠定基础。
英文摘要:
      Objective: To analyze the potential quality marker (Q-Marker) in Atractylodis Macrocephalae Rhizoma and determine its content based on fingerprints and network pharmacology. Methods: Waters Sun Fire C18 chromatographic column (250 mm×4.6 mm, 5 μm) was used with water (A)-acetonitrile (B) as mobile phase, gradient elution, flow rate of 1 mL·min-1, detection wavelength switching measurement, column temperature of 30 ℃ and injection volume of 10 μL to establish the fingerprints of Atractylodis Macrocephalae Rhizoma. of 32 batches of Atractylodis Macrocephalae Rhizoma were evaluated, the common peaks were confirmed and identified, and the“active ingredient-target-pathway”network was subsequently constructed with network pharmacological method to predict Q-Marker and determine its content. Results: The fingerprints of 32 batches of Atractylodis Macrocephalae Rhizoma were established, and 28 common peaks were confirmed. Four chromatographic peaks were identified by comparing the reference substances of Atractylodis Macrocephalae Rhizoma, which were AtractylenlolideⅠ, AtractylenolideⅡ, AtractylenolideⅢand Atractylone, respectively; It is also confirmed by network pharmacology that the above four components are active components, that can act on 16 core targets and 20 key pathways to play the roles of anti-cancer, anti-inflammatory and improving gastrointestinal conditions. It is preliminarily predicted that AtractylenolideⅠ, AtractylenolideⅡ, AtractylenolideⅢand Atractylolone are potential Q-Markers, and the total mass fraction of Atractylodis Macrocephalae Rhizoma is not less than 1.79 mg·g-1. Conclusion: The prediction and analysis to potential Q-Markers of Atractylodis Macrocephalae Rhizoma will provide references for the establishment of a set of quality control evaluation system and will lay a foundation for clarifying the material basis and mechanism of its efficacy.
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