| Literature DB >> 29966279 |
Van Bon Nguyen1,2, San-Lang Wang3,4, Ngu Truong Nhan5,6, Thi Hanh Nguyen7, Nguyen Phuong Dai Nguyen8, Do Huu Nghi9,10, Nguyen Manh Cuong11,12.
Abstract
Alpha-glucosidase inhibitory activity has been commonly used for the evaluation of antidiabetic property in vitro. The aim of this study is to investigate and characterize Dalbergia tonkinensis as a potential source of antidiabetic compounds. The screening of the active parts used, such as trunk bark, heartwood, and the leaves of Dalbergia tonkinensis indicated that all these extracted parts used with methanol demonstrated potent α-glucosidase inhibitory activity. The in vitro antidiabetic property of Dalbergia tonkinensis was notably recorded for the first time and showed activity (EC50 = 0.17⁻0.78 mg/mL) comparable to those of reported potent herbal extracts (EC50 = 0.25⁻4.0 mg/mL) and higher activity than that of acarbose, a commercial antidiabetic drug (EC50 = 1.21 mg/mL). The stability tests revealed that the heartwood of Dalbergia tonkinensis extract (HDT) possesses high pH stability with relative activity in the range of 80⁻98%. Further bioassay-guided purification led to the isolation of 2 active compounds identified as sativanone and formononetin from the ethyl acetate fraction and water fraction of HDT, respectively. These α-glucosidase inhibitors (aGIs) show promising inhibition against various types of α-glucosidases. Remarkably, these inhibitors were determined as new mammalian aGIs, showing good effect on rat α-glucosidase. The results suggest that Dalbergia tonkinensis is a potent source of aGIs and suggest promise in being developed as functional food with antidiabetic efficacy. The results of this study also enrich our knowledge concerning current biological activity and constituents of Dalbergia tonkinensis species.Entities:
Keywords: Dalbergia tonkinensis; diabetes; formononetin; heartwood; inhibitors; sativanone
Mesh:
Substances:
Year: 2018 PMID: 29966279 PMCID: PMC6099635 DOI: 10.3390/molecules23071589
Source DB: PubMed Journal: Molecules ISSN: 1420-3049 Impact factor: 4.411
α-glucosidase inhibition of some potential extract of medicinal plants collected in Dak Lak.
| No. | Scientific Name of Medicinal Plants | Part Used | EC50 (mg/mL) | References |
|---|---|---|---|---|
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| Heartwood | 0.17 ± 0.013 | This study |
| 1.21 ± 0.103 | ||||
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| Trunk bark | ≥4 | Nguyen et al., 2016 [ |
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| Trunk bark | 0.41 ± 0.03 | Nguyen et al., 2016 [ |
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| Trunk bark | 1.42 ± 0.02 | Nguyen et al., 2016 [ |
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| Trunk bark | 0.360 ± 0.03 | Nguyen et al., 2017 [ |
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| Leaves | 0.67 | Nguyen et al., 2017 [ |
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| Trunk bark | 1.08 | Nguyen et al., 2017 [ |
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| Leaves | 0.66 | Nguyen et al., 2017 [ |
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| Leaves | 0.25 ± 0.01 | Nguyen et al., 2018 [ |
All the samples were extracted with methanol as the method described in the material and method section; their inhibition against α-glucosidase was tested and expressed as EC50 value.
Figure 1The inhibition of different Dalbergia tonkinensis parts used and expressed as aGI % (A) and EC50 values (B); results are means ± SD of multi tests (n = 3).
Figure 2The pH stability of HDT. The sample was treated in the range of pH 2–13 at 37 °C for 30 min. The α-glucosidase inhibitory activity was then tested and expressed as relative activity (%). Yeast α-glucosidase was used for the enzymatic inhibition assay. Results are means ± SD of multi tests (n = 3).
Figure 3Flowchart for the isolation and identification of active inhibitors from the heartwood of Dalbergia tonkinensis (HDT); Fr. (fraction).
α-glucosidase inhibition of HDT and its fractions after partition.
| Samples | Yield (g) | α-Glucosidase Inhibition | ||
|---|---|---|---|---|
| EC50 (mg/mL) | Inhibition (%) * | |||
| HDT |
| 60.3 | 0.172 ± 0.011 | 98 ± 3.2 |
| HDT-1 |
| 1.6 | 1.712 ± 0.210 | 73 ± 4.1 |
| HDT-2 |
| 27.2 | 0.124 ± 0.003 | 90 ± 2.5 |
| HDT-3 |
| 11.1 | 0.069 ± 0.001 | 95 ± 3.7 |
| HDT-4 |
| 12.0 | 0.513 ± 0.051 | 82 ± 2.3 |
| Acarbose |
| 1.357 ± 0.03 | 62 ± 1.8 | |
*: the inhibition of acarbose and fractions were detected at their concentration range of 0.1–5 mg/mL; results are means ± SD of multi tests (n = 3).
Figure 4Inhibitory activity (%) of sub-fractions of HDT-3 (A) and HDT-4 (C) after separation by silica opened column (first time). aGI (%) of components of HDT-31 (B) and HDT-4.3 (D) after further separation by silica open column (second time). aGI (%) of isolated compounds and acarbose (E). Results are means ± SD of multi tests (n = 3).
Specific inhibitory activity of Sativanone, Formononetin, and Acarbose.
| No. | Enzyme Source | Inhibition Expressed as EC50 (mg/mL) | ||
|---|---|---|---|---|
| Sativanone | Formononetin | Acarbose | ||
| 1 | Yeast α-glucosidase | 0.23 ± 0.012 | 0.06 ± 0.002 | 1.321 ± 0.048 |
| 2 | Rat α-glucosidase | 0.37 ± 0.022 | 0.23 ± 0.037 | 0.121 ± 0.001 |
| 3 | Bacterial α-glucosidase | 0.07 ± 0.001 | 0.03 ± 0.002 | 0.001 ± 0.000 |
| 4 | Rice α-glucosidase | 0.81 ± 0.023 | 0.98 ± 0.029 | 0.031 ± 0.005 |
All tests were performed in triplicate; results are means ± SD of multi tests (n = 3).
Rat α-glucosidase inhibitory activity of crude extracts, fractions, sub-fractions, and isolated compounds from Dalbergia tonkinensis extract.
| Components | Rat α-glucosidase Inhibitory Activity | |
|---|---|---|
| EC50 (mg/mL) | Max Inhibition (%) | |
|
| 1.72 ± 0.116 | 61 ± 3.46 |
| Trunk bark extract | 2.91 ± 0.289 | 51 ± 4.62 |
| Leaves extract | 2.78 ± 0.173 | 54 ± 4.60 |
| HDT-3 | 1.31 ± 0.057 | 68 ± 5.77 |
| HDT-3.1 | 1.13 ± 0.058 | 75 ± 5.20 |
| HDT-3.1.2 | 0.92 ± 0.023 | 77 ± 5.18 |
|
| 0.357 ± 0.006 | 91 ± 4.61 |
| HDT-4 | 1.43 ± 0.115 | 67 ± 2.89 |
| HDT-4.3 | 0.87 ± 0.035 | 78 ± 4.61 |
| HDT-4.3.3 | 0.55 ± 0.012 | 84 ± 4.62 |
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| 0.251 ± 0.006 | 94 ± 5.11 |
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| Coefficient of variation | 12.50026 | 1.853018 |
The samples and acarbose were tested at their concentration range of 0.05–3.2 mg/mL; results are means ± SD of multi tests (n = 3); the means of EC50 and max inhibition values with the different letter in the same column are significantly different in comparison based on Duncan’s multiple range test (alpha = 0.01) using SAS version 9.4, Statistical Analysis Software analysis.