| کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن | 
|---|---|---|---|---|
| 5137560 | 1494530 | 2017 | 6 صفحه PDF | دانلود رایگان | 
عنوان انگلیسی مقاله ISI
												Rapid screening of potential α-amylase inhibitors from Rhodiola rosea by UPLC-DAD-TOF-MS/MS-based metabolomic method
												
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																																												کلمات کلیدی
												
											موضوعات مرتبط
												
													مهندسی و علوم پایه
													شیمی
													شیمی آنالیزی یا شیمی تجزیه
												
											پیش نمایش صفحه اول مقاله
												
												چکیده انگلیسی
												There is a growing interest in screening α-amylase inhibitors from natural products for application in the development of new anti-diabetic drugs or functional foods. In this study, an UPLC-DAD-TOF-MS/MS-based metabolomic method for rapid screening α-amylase inhibitors from Rhodiola rosea was described. First, Rhodiola rosea preparation (ligand) reacted with α-amylase (receptor) to form ligand-receptor complexes. The complexes were separated by centrifugal ultrafiltration. After that, an UPLC-DAD-TOF-MS/MS-based metabolomic method was used to measure changes in metabolome profile of Rhodiola rosea preparation before and after reaction with α-amylase. As a result, ten corresponding potential α-amylase inhibitors were obtained and identified as epigallocatechin gallate, herbacetin-3-O-d-glucopyranosyl-7-O-l-rhamnoside, kaempferol 3-xylosyl-(1 â 6)-glucoside, berbacetin-8-O-d-glucopyranoside, tricin 7-O-β-d-glucopyranoside, kaempferol 3-glucoside, tricin 5-O-β-d-glucopyranoside, herbacetin-7-O-rhamnoside, kaempferol and tricin. In conclusion, metabolomics is a promising technology to rapidly screen potential anti-α-amylase compounds from natural products.
											ناشر
												Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Functional Foods - Volume 36, September 2017, Pages 144-149
											Journal: Journal of Functional Foods - Volume 36, September 2017, Pages 144-149
نویسندگان
												Chaoyang Ma, Liming Hu, Xingran Kou, Wenping Lv, Zaixiang Lou, Hongxin Wang,