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Determination of metabolites in Uncaria sinensis by HPLC and GC-MS after green solvent microwave-assisted extraction
Authors:Tan Swee Ngin  Yong Jean Wan Hong  Teo Chin Chye  Ge Liya  Chan Yee Wen  Hew Choy Sin
Institution:a Natural Sciences and Science Education Academic Group, Nanyang Technological University, 1 Nanyang Walk, Singapore 637616, Singapore
b Institute of Advanced Studies, Nanyang Technological University, Nanyang Executive Centre #02-18, 60 Nanyang View, Singapore 639673, Singapore
Abstract:Uncaria sinensis (Oliv.) Havil (Rubiaceae) has been used as an important Traditional Chinese Medicine (TCM) herb for the treatment of fevers and various nervous disorders. The major bioactive secondary metabolites from different classes of chemical compounds, i.e. organic acid, flavonoid and alkaloid, present in this TCM herb, namely catechin, caffeic acid, epicatechin and rhynchophylline, were extracted by microwave-assisted extraction (MAE) method with ultra-pure water as the extraction solvent. The optimal extraction conditions for this green solvent MAE method were found to be 100 °C for 20 min. The recoveries of the compounds were found to be comparable to that of heating under reflux using ultra-pure water for 60 min. The method precision (RSD, n = 6) was found to vary from 0.19% to 5.60% for the proposed method on different days for the secondary metabolites. Simultaneously, the key primary metabolites such as sucrose and phenylalanine for the biosynthesis of bioactive secondary metabolites were successfully characterized by GC-MS. Furthermore, an approach using the combination of primary and secondary metabolite profiling based on their chemical fingerprints with Principal Component Analysis (PCA) was successfully developed to evaluate the quality of U. sinensis obtained from different sources. This approach was shown to be feasible in discriminating U. sinensis from different origins and thus a potential application for the quality control of other medicinal herbs.
Keywords:Uncaria sinensis  Green solvent  Microwave-assisted extraction  Metabolites profiling  Principal Component Analysis
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