2,3,5,4'-Tetrahydroxystilbene-2-O-β-D-glucoside may be the differential material basis of raw and processed Polygoni muliflori Radix on the intervention of osteoporosis
Description
This dataset collected the original data for the manuscript, including the mass data from UPLC-IM-QTOF-MS, the the data from animal experiments. Quantitative analysis was performed with GraphPad Prism 10, and data were expressed as mean ± SD. For multiple comparison, one-way ANOVA with Tukey's post hoc test was employed, with statistical significance established at p < 0.05. Metabolomic analysis identified 23 differential components between the two forms of PMR with 2,3,5,4'-Tetrahydroxystilbene-2-O-β-D-glucoside (TSG) recognized as the principal component contributing to their differences. Network pharmacology and molecular docking analyses revealed that TSG exhibited a strong binding affinity with EGFR. In vivo experiments confirmed the distinct pharmacological efficacy of both PMRs in an osteoporosis model. Micro-CT demonstrated that processed PMR in conjunction with a high dose of TSG, significantly increased the bone mineral density, PINP levels, and ALP activity while markedly reduced the structure model index and CTX-I levels. These interventions showed potential in suppressing the expression of MMP9 and TRAP, while promoting the expression of ALP, osteopontin, and Runx2. Moreover, these treatments resulted in an upregulation of EGFR, p-PI3K, and p-AKT expression. In contrast, neither low nor high doses of raw PMR as well as a low dose of TSG demonstrated significant effects on these parameters.
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1.All MS data of detected compounds from 19 PMR samples were exported to an MSDIAL database (version 4.9.221218). Subsequently, the normalized data were subjected to further processing with UNIFI software (version 14.0) for peak picking by employing the PMR compound library, which was developed through searches online databases such as the Web of Science and SciFinder. Subsequently, the data matrix was analyzed to identify the differential components using PCA, volcano plot, and OPLS-DA via Metabo Analyst 5.0. 2.Potential target proteins of the differentiated components were identified using PubChem, STP, and Uniprot databases. Additionally, proteins targets associated with osteporosis were compiled from OMIM, GeneCards, PharmGKB, DrugBank, and DisGeNET databases. Protein-protein interaction (PPI) networks were developed utilizing the STRING database. Enrichment analysis of the PPI network was performed using degree centrality (DC) metrics obtained the CytoNCA plugin Cytoscape3.7.2. Pathway enrichment for target genes was conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases. 3.Molecular docking studies were executed using the Autodock Vina software to access the binding interactions between the target genes and the differential components. 4.Quantitative analysis of animal data was performed with GraphPad Prism 10, and data were expressed as mean ± SD. For multiple comparison, one-way ANOVA with Tukey's post hoc test was employed, with statistical significance established at p < 0.05.