Correlation of the α-glucosidase inhibitory activity to metabolites of tetracera scandens leaves extracts using metabolomics and molecular docking approaches

Abstract

α-Glucosidase inhibition is regarded as an efficient mechanism for management of the postprandial hyperglycemia associated with type 2 diabetes mellitus. The severe gastrointestinal adverse effects have been reported to affect patient`s compliance towards the synthetic α-glucosidase inhibitor drugs and have prompted many studies to discover natural alternatives with comparable efficiency and better tolerability. Tetracera scandens is a traditional medicinal plant, whose leaf has been used for the treatment of diabetes mellitus in Malaysia and other Southeast Asian countries. The α-glucosidase inhibitory potential of T. scandens leaf has not been assessed so far. Hence, this study was aimed to evaluate the α-glucosidase inhibitory potential of T. scandens leaf extracts. Moreover, it aimed to develop and validate a multivariate model to correlate the Fourier transform infrared (FT-IR) spectral fingerprint of the plant extracts to their α-glucosidase inhibitory activity. Another aim of this study was to characterize the putative α-glucosidase inhibitory metabolites of T. scandens extracts using metabolomics approach. Eventually, the affinity of the putative active metabolites towards α-glucosidase was to be predicted through molecular docking study. Different hydromethanolic extracts were prepared and assayed for their α-glucosidase inhibitory potential. The FT-IR spectra of T. scandens extracts were acquired and correlated to their corresponding α-glucosidase inhibitory IC50 values via the orthogonal partial least squares (OPLS) algorithm. Furthermore, the mass spectral data acquired via gas chromatography-mass spectrometry (GC-MS) analysis of the plant extracts was correlated to their α-glucosidase inhibitory IC50 values through an OPLS model, and the putative α-glucosidase inhibitory metabolites were suggested by the loading column plot of the developed model. Moreover, the 3D structures of the putative α-glucosidase inhibitory metabolites were further docked into the active site of Saccharomyces cerevisiae isomaltase in order to predict the ligand-enzyme interactions and affinities. The methanolic extracts of T. scandens leaf showed higher α-glucosidase inhibitory potential as compared to the aqueous ones. The developed OPLS model successfully predicted the α-glucosidase inhibitory potential of new independent T. scandens leaf samples given their fingerprint FT-IR spectra, therefore it can be used as a simple and rapid quality control tool. Moreover, the bands corresponding to the carbon-hydrogen bond (C-H), carbon-carbon double bond (C=C) and carbon-oxygen single bond (C-O) were determined to be positively correlated with the α- glucosidase inhibitory activity of the plant extracts. GC-MS based profiling of the α-glucosidase inhibitory metabolites led to the determination of 6 putative metabolites, namely, palmitic acid, 1-monopalmitin, stearic acid, emodin, catechin and β-sitosterol. Moreover, the metabolites malic acid, 4-hydroxybenzoic acid, xylitol, citric acid, D-fructose, D-glucose, D-mannose and myo-inositol were suggested to induce α-glucosidase activity. The results of the molecular docking study further supported the findings of the metabolite profiling study, since the putative α-glucosidase inhibitory metabolites showed predicted binding energies of -5.9 to -8.8, indicating moderate to high affinities. Conclusively, this study demonstrated the in vitro α-glucosidase inhibitory activity of T. scandens leaf. Furthermore, the metabolomics approach was successfully used to develop a rapid method for quality control of T. scandens leaf and to characterize its putative α-glucosidase inhibitory metabolites.