Comprehensive metabolic profiling of Zanthoxylum armatum and Zanthoxylum acanthopodium leaves, bark, flowers and fruits using ultra high performance liquid chromatography. Issue 5 (23rd April 2018)

• Record Type: Journal Article
• Authors: Bhatt, Vinod; Kumar, Neeraj; Sharma, Upendra; Singh, Bikram
• Is Part Of: Separation science plus. Volume 1:Issue 5(2018)
• Page Start: 311
• Page End: 324
• Publication Date: 2018-04-23
• Subjects: folk medicine -- metabolic profiling -- principal component analysis -- ultra high performance liquid chromatography; Chromatographic analysis -- Periodicals; 543.8
• DOI: 10.1002/sscp.201800004
• Languages: English
• ISSNs: 2573-1815

Abstract

Abstract: Zanthoxylum armatum and Z. acanthopodium belong to the Rutaceae family, are extensively used in traditional folk medicine and possess anti‐inflammatory, antibacterial, hepatoprotecive and antidiabetic properties. However, the comprehensive phytochemical studies of these species in order to explain medicinal properties are still not clear. In the present study, a new ultra high performance liquid chromatography method has been developed for the determination of the biologically important compounds in the different parts (leaves, bark, flowers and fruits) of Z. armatum and Z. acanthopodium . The results revealed that lignans and flavonoids are the principal components in leaves samples while aporphine alkaloids, lignans and amides are the major constituents in bark samples of Z. armatum . None of the analyzed compounds were detected in bark and leaves of Z. acanthopodium except catechin. In contrast, the fruit pericarp was characterized by the sanshool analogues, especially hydroxy‐α‐sanshool. In addition, the method was also applied for identification of 27 metabolites in the different parts of Z. armatum and Z. acanthopodium using ultra high performance liquid chromatography with tandem mass spectrometry. The identification of eight compounds in Z. armatum and metabolic profiling of Z. acanthopodium is reported here for the first time. The results obtained were also analyzed by principal component analysis to discriminate the similarity and differences among the samples.