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Strategies In The Design Of Antidiabetic Drugs From Terminalia Chebula Using In Silico And In Vitro Approach

Authors: Bansode, Twinkle; Salalkar, B. K.;

Strategies In The Design Of Antidiabetic Drugs From Terminalia Chebula Using In Silico And In Vitro Approach

Abstract

Diabetes mellitus is the fifth deadliest disease in the developing countries. Even with all the research and new drugs available, combating diabetes is still challenging. There are successes in finding new cost effective drugs without side effects, even if not perfect. In our investigation, we studied the in silico binding mechanism of secondary metabolites of Terminalia chebula, with the key enzymes used in the diabetes management. It was analyzed that three compounds out of 16 have a higher binding affinity for the target proteins/enzymes. Ellagic acid showed highest binding affinity with alpha amylase, beta glucosidase and alpha glucosidase with lesser binding energies -4.5 kcal/mol, -5.36 kcal/mol and -4.48 kcal/mol respectively. Arjungenin has lesser binding energy of 4.77 kcal/mol with glucokinase while luteolin has a binding energy of -7.25 kcal/mol for enzyme glycogen synthase kinase. These entire compounds interacted with non-covalent interaction. In vitro antidiabetic studies revealed that the petroleum ether extract has the significant alpha amylase inhibitory activity, i.e. 51.22% as compared to standard drug (65.99%). Further, TLC analysis revealed the presence of total 9 compounds in different plant extracts one of them might be a lead compound which could be further exploited for the development of novel, safer and potent antidiabetic drug.

Keywords

general_medical_research, Ellagic acid, Diabetes mellitus, Molecular docking, http://journals.tmkarpinski.com/index.php/mmed/article/view/524/261, Thin Layer Chromatography, Alpha amylase

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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