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Erschienen in:
01.12.2020 | Original Article
Molecular docking and ADMET-based mining of terpenoids against targets of type-II diabetes
Erschienen in: Network Modeling Analysis in Health Informatics and Bioinformatics | Ausgabe 1/2020
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Abstract
Despite the availability of various medicines for the treatment of diabetes, plant-based drugs draw special attention due to their low cost and lesser side effects. The rhizomes of plant Hedychium coronarium have been reported for its anti-diabetic activity previously. In the present study, docking and computational ADME parameters of a few terpenoid ligands isolated from the above-mentioned plant against two control molecules (Sitagliptin, Metformin) were compared. The retrieved docked images indicated the docking sites in the target protein. Out of the five compounds, Digoxigenin monodigitoxoside has shown the best docking result. The LD50 of this compound is very similar to control and lower than others. This in silico study confirmed that terpenoids present in the plant rhizome are a potent drug candidate for the treatment of type-II diabetes. We have identified a few best-fit terpenoid molecules against identified targets using in silico studies, which may give new drugs to combat type-II diabetes after wet-lab validation.