| Literature DB >> 25169722 |
Cai Huang1, Qiongming Xu2, Chang Chen1, Chengwu Song1, Yong Xu3, Yi Xiang1, Yulin Feng4, Hui Ouyang4, Yang Zhang5, Hongliang Jiang6.
Abstract
Physalins, uniquely discovered from genus physalis, showed significant bioactivities in many aspects. It is therefore very important for the exploration of natural resources rich of physalins. However, there is no efficient approach for rapid discovery and identification of this class of compounds due to their structural complexity. To address the issue, the fragmentation pathways and correspondingly fragmentation rules of physalins in negative MS/MS mode were thoroughly investigated in this study using seven physalin standards. As a result, diagnostic ions for the rapid screening of physalins and classification of different types of physalins were determined based on their MS/MS fragmentation patterns. On top of that, an integrated approach using UHPLC-QTOF-MS/MS together with a novel three-step data mining strategy was developed for the systematic analysis of physalins in complex samples. Consequently, 46 physalins including 20 novel ones were efficiently discovered and identified from the crude extracts of Ph. alkekengi calyx. The present study laid a foundation for future study of different parts of Ph. alkekengi and other physalis species with regard to rapid discovery of novel physalins. In addition, this study provided a base for establishing a quality control method of the raw materials of Ph. alkekengi according to the profile of physalins.Entities:
Keywords: Data mining strategy; Physalins; Physalis alkekengi L.var.franchetii (Mast.) Makino; QTOF-MS/MS; Structural identification; UHPLC
Mesh:
Year: 2014 PMID: 25169722 DOI: 10.1016/j.chroma.2014.08.004
Source DB: PubMed Journal: J Chromatogr A ISSN: 0021-9673 Impact factor: 4.759