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DOI 10.1002/pmic.201400258

Медицинская библиотека · Proteomics · 2015

Improved metabolites of pharmaceutical ingredient grade Ginkgo biloba and the correlated proteomics analysis.

Zheng Wen, Li Ximin, Zhang Lin, Zhang Yanzhen, Lu Xiaoping, Tian Jingkui

СтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

Ginkgo biloba is an attractive and traditional medicinal plant, and has been widely used as a phytomedicine in the prevention and treatment of cardiovascular and cerebrovascular diseases. Flavonoids and terpene lactones are the major bioactive components of Ginkgo, whereas the ginkgolic acids (GAs) with strong allergenic properties are strictly controlled. In this study, we tested the content of flavonoids and GAs under ultraviolet-B (UV-B) treatment and performed comparative proteomic analyses to determine the differential proteins that occur upon UV-B radiation. That might play a crucial role in producing flavonoids and GAs. Our phytochemical analyses demonstrated that UV-B irradiation significantly increased the content of active flavonoids, and decreased the content of toxic GAs. We conducted comparative proteomic analysis of both whole leaf and chloroplasts proteins. In total, 27 differential proteins in the whole leaf and 43 differential proteins in the chloroplast were positively identified and functionally annotated. The proteomic data suggested that enhanced UV-B radiation exposure activated antioxidants and stress-responsive proteins as well as reduced the rate of photosynthesis. We demonstrate that UV-B irradiation pharmaceutically improved the metabolic ingredients of Ginkgo, particularly in terms of reducing GAs. With high UV absorption properties, and antioxidant activities, the flavonoids were likely highly induced as protective molecules following UV-B irradiation.

Для цитирования: Zheng Wen, Li Ximin, Zhang Lin, Zhang Yanzhen, Lu Xiaoping, Tian Jingkui. Improved metabolites of pharmaceutical ingredient grade Ginkgo biloba and the correlated proteomics analysis.. Proteomics. 2015. DOI: 10.1002/pmic.201400258.

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