Literature DB >> 32059529

Investigation of α-Glucosidase Inhibitory Metabolites from Tetracera scandens Leaves by GC-MS Metabolite Profiling and Docking Studies.

Ahmed Nokhala1, Mohammad Jamshed Siddiqui1,2, Qamar Uddin Ahmed1,2, Muhammad Safwan Ahamad Bustamam3, And Zainul Amiruddin Zakaria4,5.   

Abstract

Stone leaf (Tetracera scandens) is a Southeast Asian medicinal plant that has been traditionally used for the management of diabetes mellitus. The underlying mechanisms of the antidiabetic activity have not been fully explored yet. Hence, this study aimed to evaluate the α-glucosidase inhibitory potential of the hydromethanolic extracts of T. scandens leaves and to characterize the metabolites responsible for such activity through gas chromatography-mass spectrometry (GC-MS) metabolomics. Crude hydromethanolic extracts of different strengths were prepared and in vitro assayed for α-glucosidase inhibition. GC-MS analysis was further carried out and the mass spectral data were correlated to the corresponding α-glucosidase inhibitory IC50 values via an orthogonal partial least squares (OPLS) model. The 100%, 80%, 60% and 40% methanol extracts displayed potent α-glucosidase inhibitory potentials. Moreover, the established model identified 16 metabolites to be responsible for the α-glucosidase inhibitory activity of T. scandens. The putative α-glucosidase inhibitory metabolites showed moderate to high affinities (binding energies of -5.9 to -9.8 kcal/mol) upon docking into the active site of Saccharomyces cerevisiae isomaltase. To sum up, an OPLS model was developed as a rapid method to characterize the α-glucosidase inhibitory metabolites existing in the hydromethanolic extracts of T. scandens leaves based on GC-MS metabolite profiling.

Entities:  

Keywords:  GC–MS metabolomics; Tetracera scandens; metabolite profiling; molecular docking; orthogonal partial least squares; α-glucosidase inhibition

Year:  2020        PMID: 32059529     DOI: 10.3390/biom10020287

Source DB:  PubMed          Journal:  Biomolecules        ISSN: 2218-273X


  4 in total

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Journal:  Heliyon       Date:  2022-07-09

2.  Characterization of α-Glucosidase Inhibitors from Psychotria malayana Jack Leaves Extract Using LC-MS-Based Multivariate Data Analysis and In-Silico Molecular Docking.

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Journal:  Molecules       Date:  2020-12-12       Impact factor: 4.411

3.  In Vitro and In Vivo Antidiabetic Activity, Phenolic Content and Microscopical Characterization of Terfezia claveryi.

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4.  Exploring potential antidiabetic and anti-inflammatory flavonoids from Euphorbia humifusa with an integrated strategy.

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  4 in total

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