3种獐牙菜属民族药UPLC指纹图谱研究

目的采用UPLC技术结合定量分析、系统聚类分析(HCA)和主成分分析(PCA),评价、鉴别3种民族药用植物川东獐牙菜Swertia davidii、狭叶獐牙菜S.angustifolia和紫红獐牙菜S.punicea Hemsl.。方法采集3种獐牙菜共27株样品色谱图,将色谱图导入中药色谱指纹图谱相似度评价系统软件,确定样品保留时间和峰面积数据,对3组样品进行相似度分析。峰面积数据导入SPSS和SIMCA-P~+软件进行HCA和PCA,从树状图和主成分得分图中判断聚类效果。结果该方法线性关系良好(R~20.999 3,仪器精密度高(RSD为0.19%~2.45%),方法重现性好(RSD为0~1.77%),加样回收率在95.8%~102.3%,RSD为0.45%~2.81%。不同物种獐牙菜植物中指示化合物的量差异大,同一物种不同个体中指示化合物量差异明显。獐牙菜苦苷在川东獐牙菜中为0.54~10.05 mg/g,狭叶獐牙菜中未检出,紫红獐牙菜中为1.76~15.62 mg/g;龙胆苦苷在川东獐牙菜中为4.27~11.18 mg/g,狭叶獐牙菜中为0.26~3.58 mg/g,紫红獐牙菜中为1.13~16.11 mg/g;当药苷在川东獐牙菜中为0.02~0.28 mg/g,狭叶獐牙菜中为0.02~0.14 mg/g,紫红獐牙菜中为0.11~44.52 mg/g;芒果苷在川东獐牙菜中为0.14~0.55 mg/g,狭叶獐牙菜中为0.03~0.04 mg/g,紫红獐牙菜中为0.01~13.49 mg/g。HCA树状图分类准确率为85.2%,误判的紫红獐牙菜样品中化合物量较低。PCA得分图可以区分3种獐牙菜,紫红獐牙菜聚类效果分散,个体之间差异较大。结论采用UPLC技术分析指示化合物的量,结合化学计量学能够评价和鉴别3种獐牙菜属药用植物。在本研究中,紫红獐牙菜表现出更高的药用价值。

UPLC fingerprint for three species of folk medicine in Swertia L.

Objective To accelerate the development of nation medicine, ultra-high performance liquid chromatography (UPLC) combined with content analysis of index compound, cluster analysis (HCA), and principal component analysis (PCA) was used to evaluate and discriminate three kinds of national folk medicinal plants, Swertia davidi, S. punicea, and S. angustifolia. Methods The chromatograms of 27 samples from three kinds of Swertia L. were collected. The chromatograms were imported in Similarity Evaluation System for Chromatographic Fingerprint of Chinese Materia Medica 2004A to obtain data retention time and peak area of samples. Three sets of samples of similarity were analyzed. The peak area data were imported in SPSS and SIMCA-P⁺ software for cluster analysis and principal component analysis, dendrogram and principal component scores were obtained, and the clustering effect was observed. Results The line relationship of this way was good (R² > 0.999 3), with high precision instrument (RSD of 0.19%-2.45%), the method had good reproducibility (RSD of 0-1.77%), recovery was between 95.8% and 102.3% (RSD of 0.45%-2.81%). Three kinds of Swertia L. medicinal plants were different in the contents of index compounds, and the contents of index compounds in the same species were different. Swertiamarin:S.davidi (0.54-10.05 mg/g), S.angustifolia (undetectable), S.punicea (1.76-15.62 mg/g); gentiopicroside:S.davidi (4.27-11.18 mg/g), S.angustifolia (0.26-3.58 mg/g), S.punicea (1.13-16.11 mg/g); sweroside:S.davidi (0.02-0.28 mg/g), S.angustifolia (0.02-0.14 mg/g), S.punicea (0.11-44.52 mg/g); mangiferin:S.davidi (0.14-0.55 mg/g), S.angustifolia (0.03-0.04 mg/g), S.punicea (0.01-13.49 mg/g). The accuracy of dendrogram classification was 85.2%. The contents of index compounds of three false anomalies were less than the remaining nine samples of S.punicea. The effect of discrimination by PCA scores plot of three Swertia L. plants was good, and S. punicea with dispersive distribution indicated that the individuals were significant difference. Conclusion The method to evaluate and discriminate three Swertia L. medicinal plants is feasible by UPLC combined with analysis of index compound HCA and PCA. In this article, S.punicea is more valuable compared S.davidi and S.angustifolia.