Rapid identification of stigmastane-type steroid saponins from Vernonia amygdalina leaf based on α-glucosidase inhibiting activity and molecular networking.
10.1016/S1875-5364(22)60235-8
- Author:
Juanjuan GAO
1
;
Mengling ZHAO
1
;
Shujun SHAN
2
;
Yongyi LI
2
;
Jun LUO
2
;
Yi LI
3
Author Information
1. School of Food Science and Pharmaceutical Engineering, Testing & Analysis Center, Nanjing Normal University, Nanjing 210023, China.
2. Jiangsu Key Laboratory of Bioactive Natural Product Research and State Key Laboratory of Natural Medicines, China Pharmaceutical University, Nanjing 210009, China.
3. School of Food Science and Pharmaceutical Engineering, Testing & Analysis Center, Nanjing Normal University, Nanjing 210023, China. Electronic address: liyi16@163.com.
- Publication Type:Journal Article
- Keywords:
Diagnostic ions;
Fragmentation pathways;
Molecular networking;
Δ(7,9(11)) Stigmastane-type steroid saponins;
α-Glucosidase inhibitory activity
- MeSH:
alpha-Glucosidases/metabolism*;
Vernonia/chemistry*;
Plant Extracts/chemistry*;
Plant Leaves/chemistry*;
Saponins/chemistry*;
Steroids/chemistry*;
Diabetes Mellitus
- From:
Chinese Journal of Natural Medicines (English Ed.)
2022;20(11):846-853
- CountryChina
- Language:English
-
Abstract:
Steroid saponins are secondary metabolites with multiple medicinal values that are found in large quantities in natural medicines, especially Vernonia amygdalina, a famous nature medicine for the treatment of tonsillitis, diabetes, pneumonia. The current study was designed to combine molecular networking (MN) with diagnostic ions for rapid identification of Δ7,9(11) stigmastane-type saponins which were the α-glucosidase inhibitory active substances in V. amygdalina. First, the α-glucosidase inhibitory activities of five Δ7,9(11) stigmastane-type steroid saponins that were previously isolated were screened, which indicated that the Δ7,9(11) stigmastane-type steroid saponin was one of the active constituents responsible for ameliorating diabetes. Furthermore, a strategy was proposed to identify stigmastane-type steroid saponins and verify the plausibility of derived fragmentation pathways by applying MN, MolNetEnhancer and unsupervised substructure annotation (MS2LDA). Based on this strategy, other seven Δ7,9(11) stigmastane-type steroid saponins were identified from this plant. Our research provide scientific evidence for the antidiabetic potential of the steroid saponin-rich extract of V. amygdalina leaf.
