Abstract
Metabolomics is a technique used to compare the chemical profiles of different extracts. Natural sources like plants can be used, after being linked with metabolomics, to enhance the ability of drug discovery. A multivariate analysis and metabolomics profiling were performed on Quercus coccifera leaf extracts using LC-HRMS and NMR raw data using the SIMCA 14.0 program. All multivariate analyses were guided by the results of the α-amylase and -glucosidase inhibitory activity of the produced extracts. Both boiled water and methanolic extracts were selected to be active, with a percentage of inhibition higher than 80% upon using 1 mg/ml of each extract. The rest of the extract was found to be inactive and failed to obtain biological activity greater than 40%. Only methanolic extract was found to have a unique chemical profile and was found as an outlayer in both the supervised and unsupervised PCA scatter plots. The rest of the extracts were found to exert a known chemical profile and were found inside the domain. In addition, the OPLS-DA loading plot and heat map indicate the presence of a highly diverse chemical profile in methanol, with higher and lower chemical shifts and molecular weights. Both boiled water and methanol extracts were found to exert similar activity, but metabolomics profiling shows that methanolic extract contains a unique chemical profile and should be selected for a further fraction for the possible discovery of a new antidiabetic compound.