| Literature DB >> 31652794 |
Ting-Hsu Chen1, May-Jywan Tsai2, Yaw-Syan Fu3,4, Ching-Feng Weng5,6.
Abstract
Approximately 400 Garcinia species are distributed around the world. Previous studies have reported the extracts from bark, seed, fruits, peels, leaves, and stems of Garcinia mangostana, G. xanthochymus, and G. cambogia that were used to treat adipogenesis, inflammation, obesity, cancer, cardiovascular diseases, and diabetes. Moreover, the hypoglycemic effects and underlined actions of different species such as G. kola, G. pedunculata, and G. prainiana have been elucidated. However, the anti-hyperglycemia of G. linii remains to be verified in this aspect. In this article, the published literature was collected and reviewed based on the medicinal characteristics of the species Garcinia, particularly in diabetic care to deliberate the known constituents from Garcinia and further focus on and isolate new compounds of G. linii (Taiwan distinctive species) on various hypoglycemic targets including α-amylase, α-glucosidase, 5'-adenosine monophosphate-activated protein kinase (AMPK), insulin receptor kinase, peroxisome proliferator-activated receptor gamma (PPARγ), and dipeptidyl peptidase-4 (DPP-4) via the molecular docking approach with Gold program to explore the potential candidates for anti-diabetic treatments. Accordingly, benzopyrans and triterpenes are postulated to be the active components in G. linii for mediating blood glucose. To further validate the potency of those active components, in vitro enzymatic and cellular function assays with in vivo animal efficacy experiments need to be performed in the near future.Entities:
Keywords: Garcinia linii; benzopyran; bioflavonoid; hypoglycemia; in silico; phenolic; triterpene
Year: 2019 PMID: 31652794 PMCID: PMC6920772 DOI: 10.3390/biom9110641
Source DB: PubMed Journal: Biomolecules ISSN: 2218-273X
Summary of the Garcinia species on specific targets of anti-diabetes with basic findings.
| Species. | Molecular Targets | Basic Findings |
|---|---|---|
|
| α-Glucosidase, PPARγ, DPP4 | Small intestinal exposure to HCA resulted in a modest reduction in glycemia of healthy individuals [ |
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| α-Amylase, α-Glucosidase, AMPK, IRK | Activated PI3K/PKB/Akt signaling pathway and AMPK signaling pathway, resulting in the translocation of GLUT4 in L6 myotubes without affecting the expression of GLUT4 [ |
|
| α-Amylase, IRK | KV offered significant anti-diabetic relief via reduction of FBG, α-amylase and HbA1c [ |
|
| α-Amylase, IRK | MVR from |
|
| IRK | Elevated insulin levels of rats [ |
|
| IRK | Increased insulin sensitivity of 3T3-L1 adipocytes [ |
G. cambogia extract (GE); (−)-hydroxycitric acid (HCA); Pear pomace extract (PE), CCAAT-enhancer binding protein alpha (C/EBP-α); Peroxisome proliferator-activated receptor gamma (PPARγ); fatty acid synthase (FAS); insulin receptor kinase (IRK); phosphatidylinositol-3 kinase (PI3K)/the serine/threonine kinase protein kinase B (PKB/Akt); AMP-activated protein kinase (AMPK); fasting blood glucose (FBG); kolaviron (KV); mangosteen vinegar rind (MVR); Super CitriMax hydroxycitric acid (HCA-SX), a novel calcium/potassium salt; G. mangostana pericarp ethanolic extract (GME); glycated hemoglobin (HbA1c); Streptozotocin (STZ).
Figure 1The binding affinity of benzopyrans, triterpenes, stigmastane, biflavonoid, and phenolic on α-amylase, α-glucosidase, AMPK, insulin receptor kinase, PPARγ, and DPP4. Molecular docking was performed by Gold program. Ranking/ChemPLP score presents the order of score value. The model setup was genetic algorithms (GA) run 10 times, a GA search efficiency 200%, removal of water and hydrogen, and ChemPLP scoring. ChemPLP used hydrogen bonding and multiple linear potentials to model Van der Waals and repulsive terms. α-Tocopherolquinone (a kind of benzopyrans) and squalene (a kind of triterpenes) had a higher binding affinity than the reference drug, Acarbose with α-amylase and α-glucosidase prolonging the carbohydrates hydrolyzed to reduce the absorption of glucose and regulate blood glucose levels. Interestingly, α-tocopherolquinone also had a higher binding affinity than reference drugs (Metformin, Chaetochromin, and GW9662) with AMPK1, AMPK2, PPARγ, and IRK templates, respectively; and binding signals would stimulate insulin secretion in contrast to Squalene, which only had a binding affinity with AMPK1. However, α-tocopherolquinone and Squalene still had a stronger binding affinity than Sitagliptin (reference drug) with DDP4 template that could prevent incretins from being digested by DDP4 and promote skeletal cells’ uptake of glucose from the blood.