Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Sep 22;11(10):649.
doi: 10.3390/metabo11100649.

Identification of α-Glucosidase Inhibitors from Leaf Extract of Pepper (Capsicum spp.) through Metabolomic Analysis

Affiliations

Identification of α-Glucosidase Inhibitors from Leaf Extract of Pepper (Capsicum spp.) through Metabolomic Analysis

Samuel Tilahun Assefa et al. Metabolites. .

Abstract

Metabolomics and in vitro α-glucosidase inhibitory (AGI) activities of pepper leaves were used to identify bioactive compounds and select genotypes for the management of type 2 diabetes mellitus (T2DM). Targeted metabolite analysis using UPLC-DAD-QToF-MS was employed and identified compounds that belong to flavone and hydroxycinnamic acid derivatives from extracts of pepper leaves. A total of 21 metabolites were detected from 155 samples and identified based on MS fragmentations, retention time, UV absorbance, and previous reports. Apigenin-O-(malonyl) hexoside, luteolin-O-(malonyl) hexoside, and chrysoeriol-O-(malonyl) hexoside were identified for the first time from pepper leaves. Pepper genotypes showed a huge variation in their inhibitory activity against α-glucosidase enzyme(AGE) ranging from 17% to 79%. Genotype GP38 with inhibitory activity of 79% was found to be more potent than the positive control acarbose (70.8%.). Orthogonal partial least square (OPLS) analyses were conducted for the prediction of the AGI activities of pepper leaves based on their metabolite composition. Compounds that contributed the most to the bioactivity prediction model (VIP >1.5), showed a strong inhibitory potency. Caffeoyl-putrescine was found to show a stronger inhibitory potency (IC50 = 145 µM) compared to acarbose (IC50 = 197 µM). The chemometric procedure combined with high-throughput AGI screening was effective in selecting polyphenols of pepper leaf for T2DM management.

Keywords: capsicum; flavones; metabolomics; pepper leaves extract; polyamines; α-glucosidase inhibition.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Representative chromatograms of the 21 detected compounds from pepper leaves extract. Compounds: (1), N-cis caffeoyl putrescine; (2), N-trans caffeoyl putrescine; (3), feruloyl putrescine; (4), coumaroyl putrescine; (5), 5 caffeoylquinci acid (5CQA); (6), luteolin 7-O-(2”-O-apiosyl)glucoside; (7), luteolin7-O-glucoside; (8), luteolin-O-(-apiosyl malonyl) hexoside; (9), apigenin 7-O-(2”-O-apiosyl)glucoside; (10), apigenin 7-O-glucoside; (11), luteolin-O-(apiosylmalonyl); (12), chrysoeriol-O-(apiosyl) hexoside; (13), Luteolin 7-O-(2”-O-apiosyl-6”-O-malonyl) glucoside; (14), luteolin-O-(malonyl) hexoside; (15), apigenin-O-(apiosylmalonyl) hexoside; (16), apigenin-O-(apiosylmalonyl) hexoside; (17), chrysoeriol-O-(apiosylmalonyl) hexoside; (18), apigenin 7-O-(2”-O-apiosyl-6”-O-malonyl) glucoside; (19), chrysoeriol-O-(-O-apiosylmalonyl) hexoside; (20), apigenin-O-(malonyl) hexoside; (21), chrysoeriol-O-(malonyl) hexoside.
Figure 2
Figure 2
MS fragmentation patterns of metabolites identified from pepper leaf in positive mode ionization.
Figure 3
Figure 3
In vitro α-glucosidase inhibitory activities of pepper leaf extracts. The result is presented as mean ± SD (n = 3).
Figure 4
Figure 4
IC50 values of pepper leaf extracts and acarbose against α-glucosidase enzyme. The result is presented as mean ± SD (n = 3).
Figure 5
Figure 5
PCA score plot showing pepper genotypes: (A) OPLS loading plot (B) and VIP plot (C) showing the contribution of metabolites to the AGI activity, and S-plot (D).
Figure 6
Figure 6
Observed and predicted AGI activities of the training set (A); prediction plot using separate test samples (B).
Figure 7
Figure 7
Displayed VIP Plot, and S-plot from OPLS-class analysis showing the contribution of metabolites to the AGI activity in class-1 (A,B), class-2 (C,D), and class-3 (E,F).
Figure 8
Figure 8
Dose-dependent inhibition of α-glucosidase enzyme using the caffeoyl-putrescine and acarbose.

Similar articles

Cited by

References

    1. Reinehr T. Type 1 diabetes mellitus in children and adolescents. World J. Diabetes. 2013;4:270–281. doi: 10.4239/wjd.v4.i6.270. - DOI - PMC - PubMed
    1. Lankatillake C., Huynh T., Dias D.A. Understanding glycaemic control and current approaches for screening antidiabetic natural products from evidence-based medicinal plants. Plant Methods. 2019;15:1–35. doi: 10.1186/s13007-019-0487-8. - DOI - PMC - PubMed
    1. Xiao J., Kai G., Yamamoto K., Chen X. Advance in Dietary Polyphenols as α-Glucosidases Inhibitors: A Review on Structure-Activity Relationship Aspect. Crit. Rev. Food Sci. Nutr. 2013;53:818–836. doi: 10.1080/10408398.2011.561379. - DOI - PubMed
    1. Hakamata W., Kurihara M., Okuda H., Nishio T., Oku T. Design and Screening Strategies for α-Glucosidase Inhibitors Based on Enzymological Information. Curr. Top. Med. Chem. 2009;9:3–12. doi: 10.2174/156802609787354306. - DOI - PubMed
    1. Pyner A., Nyambe-Silavwe H., Williamson G. Inhibition of human and rat sucrase and maltase activities to assess antiglycemic potential: Optimization of the assay using acarbose and polyphenols. J. Agric. Food Chem. 2017;65:8643–8651. doi: 10.1021/acs.jafc.7b03678. - DOI - PubMed

LinkOut - more resources