1HNMR-Based Discriminatory Analysis of Eurycoma longifolia from Different Locations and Establishing a Profile for Primary Metabolites Identification and Quassinoids Quantification

Quassinoids, the major secondary metabolites of Eurycoma longifolia roots, improve male fertility. Hence, it is crucial to investigate their quantitative level in E. longifolia extracts. A profile was established to identify the primary metabolites and major quassinoids, and quantify quassinoids using external calibration curves. Furthermore, the metabolic discrimination of E. longifolia roots from different regions was investigated. The (1)H-NMR spectra of the quassinoids, eurycomanone, eurycomanol, 13,21-dihydroeurycomanone, and eurycomanol-2-O-β-D-glycopyranoside were obtained. The (1)H-NMR profiles of E. longifolia root aqueous extracts from Perak (n = 30) were obtained and used to identify primary metabolites and the quassinoids. Selangor, Kedah, Terengganu (n = 5 for each), and Perak samples were checked for metabolic discrimination. Hotelling's T(2) plot was used to check for outliers. Orthogonal partial least-squares discriminant analysis was run to reveal the discriminatory metabolites. Perak samples contained formic, succinic, methylsuccinic, fumaric, lactic, acetic and syringic acids as well as choline, alanine, phenylalanine, tyrosine, α-glucose, eurycomanone, eurycomanol, 13,21-dihydroeurycomanone, and eurycomanol-2-O-β-D-glycopyranoside. The extracts from other locations contained the same metabolites. The limit of quantification values were 1.96 (eurycomanone), 15.62 (eurycomanol), 3.91 (13,21-dihydroeurycomanone), and 31.25 (eurycomanol-2-O-β-D-glycopyranoside) ppm. The Hotelling's T(2) plot revealed no outlier. The orthogonal partial least-squares discriminant analysis model showed that choline, eurycomanol, eurycomanol-2-O-β-D-glycopyranoside, and lactic and succinic acid levels were different among regions. Terengganu and Perak samples contained higher amounts of eurycomanol and eurycomanol-2-O-β-D-glycopyranoside, respectively. The current approach efficiently detected E. longifolia root metabolites, quantified the quassinoids, and discriminated E. longifolia roots from different locations. These findings could be applicable to future research on E. longifolia where the higher content of quassinoids is required.