Phytochemical screening and metabolomic approach based on Fourier transform infrared (FTIR): Identification of a-amylase inhibitor metabolites in Vernonia amygdalina leaves
Context: Vernonia amygdalina has been reported as a potential antidiabetic agent. One of the mechanisms in diabetes mellitus treatment is the inhibition of the α-amylase enzyme's action. Objective: This study is aimed to identify the presence of secondary metabolites in Vernonia amygdalina leaf...
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Main Authors: | , , , |
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Format: | Other NonPeerReviewed |
Language: | English |
Published: |
Journal of Saudi Chemical Society
2022
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Subjects: | |
Online Access: | https://repository.ugm.ac.id/284485/1/50.pdf https://repository.ugm.ac.id/284485/ https://www.sciencedirect.com/journal/journal-of-saudi-chemical-society/vol/26/issue/6 |
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Institution: | Universitas Gadjah Mada |
Language: | English |
Summary: | Context: Vernonia amygdalina has been reported as a potential antidiabetic agent. One of the mechanisms in diabetes mellitus treatment is the inhibition of the α-amylase enzyme's action. Objective: This study is aimed to identify the presence of secondary metabolites in Vernonia amygdalina leaf extract, which has the potential as α-amylase inhibitors through phytochemical screening combined with metabolomic analysis. Materials and methods: Methanol extract from Vernonia amygdalina leaf was partitioned into n-hexane, dichloromethane (DCM), and ethyl acetate. From this process, methanol, hexane, DCM, and ethyl acetate extracts were obtained. These extracts were then being tested for phytochemical screening, α-amylase inhibition, and FTIR. Then FTIR data were used for metabolomic analysis (PCA and PLS). Results: The results of the α-amylase inhibition test showed that the ethyl acetate extract had the smallest IC50 average value, which was 3.00 μg/mL. Based on the phytochemical screening test results, the extract showed positive for the presence of compounds such as flavonoids, phenols, tannins, alkaloids, and saponins. From the PCA analysis (Bi-plot), the wavenumbers that were influential in the ethyl acetate extract were 1436 to 1681 and 3341 to 3348 cm−1. In theory, functional groups such as C[sbnd]H, C[dbnd]C, C[dbnd]O, N[sbnd]H, and O[sbnd]H appeared on the absorption. From the PLS analysis, these wavenumbers affected the activity. Conclusion: The most potential extract as an α-amylase inhibitor was the ethyl acetate extract. Based on phytochemical screening tests and metabolomic analysis, it was proven that this extract contained compounds as hypoglycemic agents |
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