Glycolipids Derived from the Korean Endemic Plant Aruncus aethusifolius Inducing Glucose Uptake in Mouse Skeletal Muscle C2C12 Cells.
Jong Gwon BaekDo Hwi ParkNgoc Khanh VuCharuvaka MuvvaHoseong HwangSungmin SongHyeon-Seong LeeTack-Joong KimHak-Cheol KwonKeunwan ParkKi Sung KangJaeyoung KwonPublished in: Plants (Basel, Switzerland) (2024)
Aruncus spp. has been used as a traditional folk medicine worldwide for its anti-inflammatory, hemostatic, and detoxifying properties. The well-known species A. dioicus var. kamtschaticus has long been used for multifunctional purposes in Eastern Asia. Recently, it was reported that its extract has antioxidant and anti-diabetic effects. In this respect, it is likely that other Aruncus spp. possess various biological activities; however, little research has been conducted thus far. The present study aims to biologically identify active compounds against diabetes in the Korean endemic plant A. aethusifolius and evaluate the underlying mechanisms. A. aethusifolius extract enhanced glucose uptake without toxicity to C2C12 cells. A bioassay-guided isolation of A. aethusifolius yielded two pure compounds, and their structures were characterized as glycolipid derivatives, gingerglycolipid A, and (2 S )-3-linolenoylglycerol- O -β-d-galactopyranoside by an interpretation of nuclear magnetic resonance and high-resolution mass spectrometric data. Both compounds showed glucose uptake activity, and both compounds increased the phosphorylation levels of insulin receptor substrate 1 (IRS-1) and 5'-AMP-activated protein kinase (AMPK) and protein expression of peroxisome proliferator-activated receptor γ (PPARγ). Gingerglycolipid A docked computationally into the active site of IRS-1, AMPK1, AMPK2, and PPARγ (-5.8, -6.9, -6.8, and -6.8 kcal/mol).
Keyphrases
- protein kinase
- skeletal muscle
- anti inflammatory
- induced apoptosis
- oxidative stress
- type diabetes
- magnetic resonance
- high resolution
- insulin resistance
- cell cycle arrest
- blood glucose
- cardiovascular disease
- glycemic control
- cell death
- machine learning
- blood pressure
- south africa
- magnetic resonance imaging
- signaling pathway
- electronic health record
- cell proliferation
- pi k akt
- adipose tissue
- deep learning
- cancer therapy
- wound healing
- artificial intelligence
- weight loss