Department of Analytical Chemistry and Pharmaceutical Technology, Center for Pharmaceutical Research-CePhaR, Vrije Universiteit Brussel-VUB, Laarbeeklaan 103, B-1090 Brussels, Belgium.
J Chromatogr B Analyt Technol Biomed Life Sci. 2012 Dec 1;910:114-21. doi: 10.1016/j.jchromb.2012.06.025. Epub 2012 Jun 28.
The genera of Mallotus and Phyllanthus contain several species that are commonly used as traditional medicines in oriental countries. Some species show interesting pharmaceutical activities, such as an antioxidant activity. To produce clinically useful medicines or food supplements (nutraceuticals) from these herbs, the species should be identified and a thorough quality control should be implemented. Nowadays, the integration of chromatographic and chemometric approaches allows a high-throughput identification and activity prediction of medicinal plants. In this study, Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were applied and compared to distinguish Mallotus and Phyllanthus species. Moreover, peaks from their chromatographic fingerprints, which were responsible for their antioxidant activity were assigned. For the latter purpose, the relevant information was extracted from the chromatographic fingerprints using linear multivariate calibration techniques, i.e., Partial Least Squares (PLS) and Orthogonal Projections to Latent Structures (O-PLS). Results reveal that exploratory analysis using PCA shows somewhat diverging clustering tendencies between Mallotus and Phyllanthus samples than HCA. However, both approaches mainly confirm each other. Concerning the multivariate calibration techniques, both PLS and O-PLS models demonstrate good predictive abilities. By comparing the regression coefficients of the models with the chromatographic fingerprints, the peaks that are potentially responsible for the antioxidant activity of the extracts could be confirmed.
藤桔属和叶下珠属的一些种通常被用作东方国家的传统药物。有些种具有有趣的药物活性，如抗氧化活性。为了从这些草药中生产出具有临床应用价值的药物或食品补充剂（营养保健品），应该对其进行鉴定，并实施全面的质量控制。如今，色谱和化学计量学方法的结合可以实现高通量的鉴定和药用植物的活性预测。在本研究中，应用主成分分析（PCA）和层次聚类分析（HCA）来区分藤桔属和叶下珠属的种。此外，还对其色谱指纹图谱中的峰进行了分配，这些峰与它们的抗氧化活性有关。为了达到后者的目的，使用线性多元校正技术，即偏最小二乘法（PLS）和正交投影到潜结构（O-PLS），从色谱指纹图谱中提取相关信息。结果表明，使用 PCA 的探索性分析显示出藤桔属和叶下珠属样品之间聚类趋势有些不同，而 HCA 则主要相互印证。然而，这两种方法都主要相互印证。关于多元校正技术，PLS 和 O-PLS 模型都表现出良好的预测能力。通过比较模型的回归系数与色谱指纹图谱，可以确认可能对提取物的抗氧化活性负责的峰。
