基于HPLC-Q-Exactive Orbitrap MS与化学计量法的香青兰质量标志物预测

    Predictive Analysis on Q-markers of Dracocephalum Moldavica L. Based on HPLC-Q-Exactive Orbitrap MS and Chemometrics

    • 摘要:
      目的 基于HPLC-Q-Exactive Orbitrap MS与化学计量法明确香青兰化学成分,预测其质量标志物。
      方法 采用HPLC-Q-Exactive Orbitrap MS分析不同产地香青兰的化学成分,并采用HPLC建立10批不同产地香青兰药材的指纹图谱,基于共有峰的峰面积,使用SPSS 27.0.1和SIMCA 14.1软件进行聚类分析(cluster analysis,CA)、主成分分析(principal component analysis,PCA)和正交偏最小二乘法判别分析(orthogonal partial least squares discriminant analysis,OPLS-DA),筛选出能够代表不同产地香青兰差异性的化学成分,并与香青兰现代药理学作用及传统疗效关联找出其质量标志物。
      结果 共分析鉴定出30个化合物,10批香青兰HPLC指纹图谱共标定了20个共有峰,相似度在0.922~0.990,根据CA、PCA及OPLS-DA分析结果将10批香青兰分为3类,并最终筛选出差异较大的4个标志性成分,且药理作用已明确,可作为香青兰质量标志物。
      结论 研究通过HPLC-Q-Exactive Orbitrap MS快速全面分析香青兰化学成分,并结合指纹图谱和化学计量法预测其质量标志物,可为香青兰质量评价研究提供参考。

       

      Abstract:
      OBJECTIVE To identify the chemical components and predict the Q-markers of Dracocephalum moldavica L. based on HPLC-Q-Exactive Orbitrap MS and chemometrics.
      METHODS The chemical components of Dracocephalum moldavica L. from different origins were analyzed using HPLC-Q-Exactive Orbitrap MS. Additionally, HPLC was employed to establish fingerprint chromatograms for 10 batches of the herb from different areas. Based on the peak areas of the common peaks, cluster analysis(CA), principal component analysis(PCA), and orthogonal partial least squares discriminant analysis(OPLS-DA) were conducted using SPSS 27.0.1 and SIMCA 14.1 software. Chemical components that could represent the differences in Dracocephalum moldavica L. from different regions were screened out and associated with the modern pharmacological effects and traditional therapeutic effects of Dracocephalum moldavica L. to identify their Q-markers.
      RESULTS A total of 30 compounds were identified. A total of 20 common peaks were identified in the HPLC fingerprint chromatograms of 10 batches of Dracocephalum moldavica L., with a similarity ranging from 0.922 to 0.990. The results of CA, PCA, and OPLS-DA analysis divided the 10 batches of Dracocephalum moldavica L. into 3 categories and ultimately screened 4 characteristic components that caused differences in the quality of medicinal materials from different habitats. Their pharmacological effects had been clarified, and these could be used as Q-markers for Dracocephalum moldavica L.
      CONCLUSION The study utilizes HPLC-Q-Exactive Orbitrap MS to quickly and comprehensively analyze the chemical components of Dracocephalum moldavica L., combining fingerprint analysis and chemometrics to predict its Q-markers. It can provide a reference for the quality evaluation of Dracocephalum moldavica L.

       

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