Abstract
Background: Polygonum cuspidatum (PC), a widely used Chinese herbal medicine (CHM), plays an important role in treating various diseases including osteoarthritis (OA). Yet, the multicomponent and multitarget characteristics of PC make deciphering the pharmacological mechanisms difficult.
Objective: The purpose of this study is to identify the core molecular mechanisms of PC against OA.
Methods: The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database was used to search for the active ingredients of PC. GeneCards was then screened to establish relevant databases for OA. A visual interactive network diagram of the relationship between the active ingredient, action target, and disease was built using Uniprot. Finally, we used STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) database to explain the interaction network of proteins and to further analyze the relationships between related proteins.
Results: PC was screened for nine potentially effective active compounds that can be used to treat OA: 6,8-Dihydroxy-7-methoxyxanthone, rhein, physovenine, beta-sitosterol, picralinal, quercetin, luteolin, catechin, and resveratrol. Using GeneCards database and TCMSP database, we obtained 149 OA-related genes after taking the intersection of OA and PC targets. Moreover, eight core target proteins were calculated by CytoNCA plugin, which is used for network centrality analysis. The enrichment analysis of the common target genes shared by PC and OA unraveled the main biological processes, such as responses to lipopolysaccharide, chemical stress, and reactive oxygen species. Previous research has demonstrated that signaling pathways related to apoptosis, inflammation, and cartilage protection are involved with those core target genes we found, like TNF and PI3K-Akt signaling pathways. The results bring that PC similarly has the potential to treat OA.
Conclusion: The main purpose of this study is to screen the active ingredients and most important target molecules of PC in treating OA. This was achieved using bioinformatic tools and databases to investigate molecular docking technology. The findings provide a theoretical foundation and potential new treatment plan for OA using PC.
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