Search

Objective To investigate the potential mechanism of osteoking in the treatment of type 2 diabetic osteoporosis by inhibiting osteoblast ferroptosis from the perspective of network pharmacology and molecular docking.Methods TCMSP database and BATMAN-TCM database were used to retrieve the components and targets of traditional Chinese medicine, and GeneCards and OMIM database were used to obtain the disease targets of osteoporosis in type 2 diabetes.The PPI protein interaction network was constructed with STRING11.0 database, and topological analysis was performed to screen important targets in the network. The potential therapeutic targets were imported into the DAVID online database for gene ontology(GO) enrichment analysis and gene and genome encyclopedia(KEGG) pathway enrichment analysis.Finally, molecular docking simulation was performed to verify the results of network pharmacology.Results A total of 223 potential therapeutic targets were obtained through network pharmacology screening.The key active substances of osteoking in the treatment of type 2 diabetic osteoporosis are luteolin, 20(R)-ginsenoside Rh2, kaempferol, baicalein, beta-sitosterol, etc.The key targets are IL-6, Akt, TNF, MAPK3, HIF-1A, etc.The results of GO and KEGG analysis showed that the treatment of osteoporosis in type 2 diabetes by osteoking mainly included biological processes such as lipopolysaccharide response, hypoxia response, and inflammatory response, and regulated HIF-1A, TNF, IL-17, PI3K/Akt and other signaling pathways.The results of molecular docking showed that 7-O-methylisoprostol, baicalein, kaempferol, and quercetin had good binding activity with HIF-1A.Conclusion Through network pharmacology and molecular docking technology, it is found that osteoking may treat type 2 diabetic osteoporosis through multiple targets, and may reduce oxidative stress and inhibit osteoblast ferroptosis through HIF-1A signaling pathway to treat type 2 diabetic osteoporosis. [ABSTRACT FROM AUTHOR]

OBJECTIVE: The aim of this study was to predict the mechanism of Osteoking in preventing deep vein thrombosis (DVT) of the lower limb by network pharmacology and molecular docking. MATERIALS AND METHODS: The relevant active components and targets of Osteoking were collected through the TCMSP database, and the relevant disease targets of DVT were collected through the GeneCards, OMIM, and DisGeNET databases. The intersecting gene targets of Osteoking and DVT were obtained using Venny 2.1.0 software. PPI network construction and core target selection using Cytoscape 3.9.0 software. The Metascape database was used for GO and KEGG enrichment analysis of relevant targets. Finally, the molecular docking of the main active components and key targets was carried out. RESULTS: There are 361 potential targets and 71 core targets of Osteoking in preventing deep vein thrombosis of the lower limb. Signal pathways are involved in various diseases such as cancer, diabetic complications, atherosclerosis, and more. Some of the most common pathways include AGE-RAGE signaling pathway and Calcium signaling pathway. Molecular docking results showed that the main active components of Osteoking had relatively stable binding activities with the key targets. CONCLUSIONS: Osteoking can play a role through multiple targets and multiple signal pathways to prevent the formation of deep venous thrombosis of the lower limb after fracture. [ABSTRACT FROM AUTHOR]

Objective To explore the potential mechanism of Osteoking （OK） in the treatment of Osteoarthritis （OA） and preliminarily verify it with DMM rats. Methods TCMSP database was used to collect potential targets of OK, GeneCards database and OMIM were used to screen target genes related to OA, and Cytoscape 3.8.2 software was used to establish a regulatory network for interaction between OK Active ingredient and OA target genes. The STRING database was used to construct protein interaction maps and GO and KECG were analyzed. In addition, OA rats were constructed using medial meniscus instability surgery （DMM） to observe knee joint cartilage lesions, and ELISA was used to detect inflammation and oxidative stress levels after OK treatment. Results Network pharmacology results showed that 80 core genes were involved in OK therapy for OA, including serum albumin （ALB） and interleukin-6 （IL6), mainly involving biological processes such as immunity, inflammatory response, oxidative stress, and metabolism. Animal experiments showed that compared with the model group, the surface structure of the articular cartilage in the OK group of rats tended to be normal, with less detachment of chondrocytes; OK reduced serum inflammatory factors IL-6 （P < 0.01), VEGF （P < 0.01), and oxidative stress factor MDA （P < 0.05), improved ALB levels and SOD activity （P < 0.01). Conclusion OK can alleviate OA cartilage tissue damage, enhance immunity, and inhibit inflammation and oxidative stress reactions, preliminarily verifying the results of network pharmacology. [ABSTRACT FROM AUTHOR]