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Centella asiatica is a medicinal plant widely used as a traditional medicine due to several biological activities, such as antioxidants in Indonesia. This study aims to identify the active antioxidant compounds of C. asiatica leaves extract using a liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS)-based metabolomics approach. Extracts were prepared using different concentrations of ethanol p.a., i.e. 70% ethanol, 50% ethanol, 30% ethanol, and water. Antioxidant activity was tested using the 2,2-diphenyl-1-picrylhydrazyl method. The results showed the highest antioxidant activity was C. asiatica extracted by 70% ethanol with IC50 of 72.48 ± 2.42 µg/mL. The positive control was ascorbic acid, having an IC50 value of 3.38 ± 0.04 µg/mL. Ascorbic acid and 70% ethanol extract have strong antioxidant activity. Metabolite profiling using LC-MS/MS could identify 35 metabolites consisting of flavonoids, fatty acids, phenolics, terpenes, and several other groups of compounds. Orthogonal partial least squares-discriminant analysis classified the metabolites into active (ethanol 70% and ethanol 50%) and inactive (ethanol p.a., ethanol 30%, and water) antioxidants. Five metabolites have potential as antioxidants, namely 4,5-dicaffeoylquinic acid (11), kaempferol (13), and three unknown compounds.

Centella asiatica, or pegagan in Indonesia, is a perennial plant used in Indonesian traditional medicine (jamu) and functional food with many biological activities. Those biological activities come from the bioactive metabolites present in C. asiatica. Differences in metabolite pathways in each part of the plant affect the accumulation of metabolites contained, thus impacting its biological activity. Therefore, this study aims to identify and evaluate differences in the distribution of metabolites in each part of C. asiatica, namely leaves, stems, stolons, and roots. Each plant part was extracted using methanol and sonicated for 30 minutes. The metabolites in the samples were separated and detected using UHPLC-Q-Orbitrap HRMS. Differences in the distribution of metabolites in each part of the plant were evaluated using chemometrics analysis. UHPLC-Q-Orbitrap HRMS analysis could positively identify 37 metabolites, most of which belong to the phenylpropanoid, triterpenoid, triterpenoid saponin, and flavonoid groups. Principal component analysis was able to clearly distinguish each part of the plant using the peak intensity of the overall chromatogram and the peak area of the identified metabolites. The different biosynthetic pathways of metabolites in plants could cause a difference in the distribution of metabolites in each plant.

Ebony (Diospyros celebica Bakh) is an endemic forest tree species found in Sulawesi whose basic information on its metabolite profile is still lacking. The objective of this research was to separate and identify putatively metabolite present in the leaves and wood of ebony across Sulawesi. Separation and identification of ebony metabolites were carried out using UHPLC-Q-Orbitrap HRMS analysis. Using ultrasonication with ethanol as the extracting solvent, we used powdered ebony leaves and wood. The results showed that the metabolites contained in the leaves and wood of ebony were 59 metabolites. About 14 compounds were found in the leaves and wood, 21 compounds in the wood, and 24 compounds in the leaves. The identified metabolites are flavonoids, terpenoids, amino aldehydes, alkaloids, quinones, steroids, amino acids, fatty acids, and saccharides. Clustering of ebony using principal component analysis obtained leaves and wood groups using peak area of known compounds as the variable.

Sida rhombifolia, also known as sidaguri in Indonesia, is a medicinal plant commonly used as a herbal medicine because of its metabolite and biological activities. One of the several factors that affect plant metabolite composition and concentration is the use of plant parts. In this study, the experiment aimed to identify the metabolite profile in the leaves and stem extracts of S. rhombifolia using UHPLC-Q-Orbitrap HRMS-based untargeted metabolomics. The samples were distinguished by principal component analysis (PCA). Extraction of metabolites was conducted by sonication for approximately 30 min with 70% ethanol as the extraction solvent; 28 metabolites were identified. Seven metabolites were identified only in the leaves, three were identified only in the stems, and 18 other metabolites were identified in both the leaves and stems. These metabolites were categorized as flavonoids, triterpenoids, alkaloids, coumarins, phenolic aldehydes, phenolic acids, ecdysteroids, fatty acids, and monoterpene lactones. Based on the classification results, PCA grouped the leaves and stem extracts of S. rhombifolia using the peak area variables of the identified metabolites.

Kaempferia angustifolia also known as kunci pepet in Indonesia, has been widely used as a traditional medicine to treat cold, cough, stomachache, diarrhea, fever, and dysentery, also used as a slimming agent. The level of biological activity depends on the composition and concentration of bioactive compounds present in the plants. In addition, extraction solvents affects the composition and concentration of bioactive compounds. Therefore, this study aimed at identifying the metabolite profile of K. angustifolia and to evaluate the inhibitory potential of their various solvent extracts towards lipase enzyme. Extracts were prepared using water and different concentration of ethanol (30–99%) and then analyzed their metabolite profile using LC-MS/MS. Lipase inhibitory activity was assessed using in vitro enzymatic inhibition assay. In this study, profile of K. angustifolia was shown to be rich in terpenoids (monoterpenoids, sesquiterpenoids, diterpenoids), and phenolics (carboxylic acid and phenolic acid). Most of the identified compounds were detected in ethanol extract of K. angustifolia. The ethanol extract at 100 μg/mL displayed 59.82% inhibitory activity towards lipase and was found to have the highest inhibitory activity compared to the other extracts. A partial least square-discriminant analysis (PLS-DA) was performed for clustering the extracts based on the peak area of 53 putatively identified compounds. Based on the result obtained, 50% ethanol extract is the best extract that gives the highest inhibition results and 15 metabolites were identified, mainly from the carboxylic acid and terpenoid groups.

The potential application of Xylocarpus granatum, a mangrove species, as traditional medicine has been widely linked to its high secondary metabolite and antioxidant contents. However, few studies have been reported to identify and classify active metabolites responsible for such excellent biological activities. Therefore, the aim of this work was to determine the antioxidant activity, identify the metabolite profiles, and predict the metabolites acting as antioxidants in X. granatum extract using a gas chromatography–mass spectrometry (GC-MS)-based metabolomics approach. The seeds, stems, fruit peel, pulp, leaves, and twigs of X. granatum were macerated with ethanol. Each extract was analyzed with GC-MS, and the data were processed using mass spectrometry data-independent analysis (MS-DIAL) software to identify the metabolites. The IC50 value of plant parts of X. granatum ranged from 7.73 to 295 ppm. A total of 153 metabolites were identified and confirmed in the X. granatum extracts. Among the identified metabolites, epicatechin and epigallocatechin were the two most abundant in the stem extracts and are expected to have the greatest potential as antioxidants. Principal component analysis (PCA) succeeded in grouping all parts of the plant into three groups based on the composition of the metabolites: group 1 (stems, fruit peel, and twigs), group 2 (seeds and pulp), and group 3 (leaves).