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Title: Rapid profiling and structural characterization of bioactive compounds and their distribution in different parts of Berberis petiolaris Wall. ex G. Don applying hyphenated mass spectrometric techniques. Author: Singh A, Bajpai V, Srivastava M, Arya KR, Kumar B. Journal: Rapid Commun Mass Spectrom; 2014 Oct 15; 28(19):2089-100. PubMed ID: 25156599. Abstract: RATIONALE: Berberis petiolaris Wall. is a lesser known medicinal plant, belonging to the family Berberidaceae. The genus Berberis is known for many biological activities such as anti-microbial, anti-inflammatory and anti-diarrheal, etc. There are not many reports of the isolation of components from Berberis petiolaris. This study aims to seek identification, characterization and quantification of components. METHODS: A method was developed for rapid screening of phytochemicals using high-pressure liquid chromatography hyphenated with quadrupole time-of-flight mass spectrometry (HPLC/ESI-QTOF-MS/MS). Suitable collision-induced dissociation mass spectrometry (CID-MS/MS) methods were developed for structural investigation of alkaloids, flavanoids and other classes of compounds using nine reference standards for authentication. Multiple reaction monitoring (MRM) methods were developed for quantitative study of five constituents using triple quadrupole-linear ion trap mass spectrometry (UPLC/QqLIT-MS/MS). RESULTS: On the basis of HPLC retention behavior and fragmentation pathways obtained by high-resolution MS and MS/MS, 32 compounds were identified and characterized in different parts of Berberis petiolaris. Quantitative studies of chlorogenic acid, magnoflorine, jatrorrhizine, palmatine and berberine were also completed successfully. CONCLUSIONS: Rapid and accurate HPLC/ESI-QTOF-MS/MS and UPLC/ESI-QqLIT-MS/MS methods were established for identification, characterization and quantification of phytochemicals in the ethanolic extract of Berberis petiolaris. These methods, therefore, can be used for studies on phytochemical variation in different parts of the plant. Principle components analysis (PCA) may be used for plant part discrimination.[Abstract] [Full Text] [Related] [New Search]