Objective To explore the potential molecular mechanism of Rhodiola crenulata (RC) for type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD) by network pharmacology and molecular docking. Methods The target genes of T2DM and AD, the effective active components and targets of RC were identified through multiple public databases during March to August, 2022. The main active components and core genes of RC anti T2DM-AD were screened. The key genes were enrichment analyzed by gene ontology function and Kyoto gene and Kyoto Encyclopedia of Genes and Genomes. AutoDock Vina was used for molecular docking and binding energy calculation. Results A total of 5189 T2DM related genes and 1911 AD related genes were obtained, and the intersection result showed that there were 1418 T2DM-AD related genes. There were 48 active components of RC and 617 corresponding target genes. There were 220 crossing genes between RC and T2DM-AD. The main active components of RC anti T2DM-AD included kaempferol, velutin, and crenulatin. The key genes for regulation include ESR1, EGFR, and AKT1, which were mainly enriched in the hypoxia-inducible factor-1 signal pathway, estrogen signal pathway, and vascular endothelial growth factor signal pathway. The docking binding energies of the main active components of RC and key gene molecules were all less than −1.2 kcal/mol (1 kcal=4.2 kJ). Conclusions RC may play a role in influencing T2DM and AD by regulating the hypoxia-inducible factor-1 signaling pathway, estrogen signaling pathway, and vascular endothelial growth factor signaling pathway.
ObjectiveTo explore the metabolic changes during the differentiation of 3T3-L1 adipocytes caused by the treatment of the transient receptor potential vanilloid 4 (TRPV4)-specific agonist GSK1016790A basing on ultra-performance liquid chromatography-mass spectrometry technology. MethodsMouse 3T3-L1 cells were treated with GSK1016790A at different concentrations (0.1, 1, and 10 μmol/L), and the effect of drugs on cell proliferation was detected by cell counting kit-8 method. A mature adipocyte model was constructed, and GSK1016790A was used to activate TRPV4 channel protein activity and verify the expression levels of TRPV4 and triglycerides. Cell metabolites were collected for metabolomic studies, differential metabolites were screened between groups, and related metabolic pathways were analyzed. Results After GSK1016790A intervened in mature adipocytes, the expression levels of TRPV4 mRNA and triglycerides in cells were significantly upregulated (P<0.05). Metabolomics detection found that GSK1016790A screened a total of 45 differential metabolites such as 2-amino-1,3,4-octadecanetriol, linoleic acid, sphingosine, sphinganine, sn-glycerol-3-phosphate and uridine, mainly involving 13 possible metabolic pathways such as sphingolipid metabolism and biosynthesis of unsaturated fatty acids. Conclusion GSK1016790A may promote adipogenesis in adipocytes by activating TRPV4 channel protein activity, and at the same time participate in regulating metabolic pathways such as the biosynthesis of unsaturated fatty acids pathway and sphingolipid metabolism pathway, affecting lipid metabolism in adipocytes.