Metabolome Mining of Curcuma longa L. Using HPLC-MS/MS and Molecular Networking.

Turmeric, Curcuma longa L., is a type of medicinal plant characterized by its perennial nature and rhizomatous growth. It is a member of the Zingiberaceae family and is distributed across the world's tropical and subtropical climates, especially in South Asia. Its rhizomes have been highly valued for food supplements, spices, flavoring agents, and yellow dye in South Asia since ancient times. It exhibits a diverse array of therapeutic qualities that encompass its ability to combat diabetes, reduce inflammation, act as an antioxidant, exhibit anticancer properties, and promote anti-aging effects. In this study, organic extracts of C. longa rhizomes were subjected to HPLC separation followed by ESI-MS and low-energy tandem mass spectrometry analyses. The Global Natural Product Social Molecular Networking (GNPS) approach was utilized for the first time in this ethnobotanically important species to conduct an in-depth analysis of its metabolomes based on their fragments. To sum it up, a total of 30 metabolites including 16 diarylheptanoids, 1 diarylpentanoid, 3 bisabolocurcumin ethers, 4 sesquiterpenoids, 4 cinnamic acid derivatives, and 2 fatty acid derivatives were identified. Among the 16 diarylheptanoids identified in this study, 5 of them are reported for the first time in this species.

Metabolomics and molecular networking approach for exploring the anti-diabetic activity of medicinal plants.

Metabolomics and molecular networking approaches have expanded rapidly in the field of biological sciences and involve the systematic identification, visualization, and high-throughput characterization of bioactive metabolites in natural products using sophisticated mass spectrometry-based techniques. The popularity of natural products in pharmaceutical therapies has been influenced by medicinal plants with a long history of ethnobotany and a vast collection of bioactive compounds. Here, we selected four medicinal plants Cleistocalyx operculatus, Terminalia chebula, Ficus lacor, and Ficus semicordata, the biochemical characteristics of which remain unclear owing to the inherent complexity of their plant metabolites. In this study, we aimed to evaluate the potential of these aforementioned plant extracts in inhibiting the enzymatic activity of α-amylase and α-glucosidase, respectively, followed by the annotation of secondary metabolites. The methanol extract of Ficus semicordata exhibited the highest α-amylase inhibition with an IC50 of 46.8 ± 1.8 µg mL-1, whereas the water fraction of Terminalia chebula fruits demonstrated the most significant α-glucosidase inhibition with an IC50 value of 1.07 ± 0.01 µg mL-1. The metabolic profiling of plant extracts was analyzed through Liquid Chromatography-Mass Spectrometry (LC-HRMS) of the active fractions, resulting in the annotation of 32 secondary metabolites. Furthermore, we applied the Global Natural Product Social Molecular Networking (GNPS) platform to evaluate the MS/MS data of Terminalia chebula (bark), revealing that there were 205 and 160 individual ion species observed as nodes in the methanol and ethyl acetate fractions, respectively. Twenty-two metabolites were tentatively identified from the network map, of which 11 compounds were unidentified during manual annotation.