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An In Ovo Model for Testing Insulin-mimetic Compounds
Published on: April 23, 2018
An in silico study on antidiabetic activity of bioactive compounds in Euphorbia thymifolia Linn
T Hoang Nguyen Vo1, Ngan Tran1, Dat Nguyen1
1International University - Vietnam National University - HCMC, Quarter 6, Linh Trung Ward, Thu Duc District, Ho Chi Minh City, Vietnam.
Abstract:
Herbal medicines have become strongly preferred treatment to reduce the negative impacts of diabetes mellitus (DM) and its severe complications due to lesser side effects and low cost. Recently, strong anti-hyperglycemic effect of Euphorbia thymifolia Linn. (E. thymifolia) on mice models has reported but the action mechanism of its bioactive compounds has remained unknown. This study aimed to evaluate molecular interactions existing between various bioactive compounds in E. thymifolia and targeted proteins related to Type 2 DM. This process involved the molecular docking of 3D structures of those substances into 4 targeted proteins: 11-β hydroxysteroid dehydrogenase type 1, glutamine: fructose-6-phosphate amidotransferase, protein-tyrosine phosphatase 1B and mono-ADP-ribosyltransferase sirtuin-6. In the next step, LigandScout was applied to evaluate the bonds formed between 20 ligands and the binding sites of each targeted proteins. The results identified seven bioactive compounds with high binding affinity (<-8.0 kcal/mol) to all 4 targeted proteins including β-amyrine, taraxerol, 1-O-galloyl-β-d-glucose, corilagin, cosmosiin, quercetin-3-galactoside and quercitrin. The pharmacophore features were also explained in 2D figures which indicated hydrophobic interactions, hydrogen bond acceptors and hydrogen bond donors forming between carbonyl oxygen molecules of those ligands and active site residues of 4 targeted protein.Graphical abstract Euphorbia thymifolia Linn. is a small prostrate herbaceous annual weed that can positively impact on reducing hyperglycemic effect. In order to clearly understand about molecular level of the its bioactive compounds, in silico approach is performed.
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