Litcius/Paper detail

A novel antidiabetic peptide GPAGAP from <i>Andrias davidianus</i> collagen hydrolysates: screening, action mechanism prediction and improving insulin resistance in HepG2 cells

Zi-Han Dong, Ruo-Yao Pan, Guoyan Ren, Ming Zhou, Bin Zhang, Jinling Fan, Zhijun Qiu

2024Food & medicine homology.32 citationsDOIOpen Access PDF

Abstract

In this study, a novel hypoglycemic peptide Gly-Pro-Ala-Gly-Ala-Pro (GPAGAP) was screened from skin collagen hydrolysates of <i>Andrias davidianus</i> by network pharmacology and bioinformatics, and its hypoglycemic mechanism was predicted. Meanwhile, the improvement of insulin resistance (IR) in HepG2 cells were detected. Through network pharmacology screening, GPAGAP had good drug-like properties, and 105 targets of GPAGAP overlap with diabetes mellitus type 2 (T2DM) targets. These targets were mainly enriched in the PI3K-Akt signaling pathway, TNF signaling pathway, IR and other signaling pathways related to T2DM. The results of IR-HepG2 cell model experiments showed that GPAGAP could reduce IR of HepG2 cells induced by high-glucose and high-insulin, and improve glucose consumption of IR-HepG2 cells. GPAGAP could increase the glycogen content, hexokinase (HK) and pyruvate kinase (PK) activities of IR-HepG2 cells, inhibit the accumulation of triglyceride (TG) and total cholesterol (TC) in IR-HepG2 cells, and enhance the activity of superoxide dismutase (SOD) in IR-HepG2 cells, reduce the content of malondialdehyde (MDA) and reactive oxygen species (ROS) in IR-HepG2 cells. The above results suggested that GPAGAP could through multi-target and multi-pathway to improve the glucose metabolism, lipid metabolism and oxidative stress response of IR-HepG2 cells. It has the potential effect of improving insulin resistance in T2DM.

Topics & Concepts

HydrolysateMechanism (biology)PeptideMechanism of actionInsulin resistanceChemistryInternal medicineEndocrinologyInsulinPharmacologyBiochemistryMedicineIn vitroPhysicsHydrolysisQuantum mechanicsProtein Hydrolysis and Bioactive PeptidesNatural Antidiabetic Agents StudiesMachine Learning in Bioinformatics