فهرست نشریات علمی دسترسی آزاد ایران

The objective of this study was to utilize network pharmacology and bioinformatics tools to identify and assess bioactive compounds derived from Artemisia vestita for their potential therapeutic use in osteoarthritis (OA). The IMPPAT and KNApSAcK databases were used to identify the bioactive compounds of A. vestita. SwissADME and ProTox 3.0 evaluated the drug-likeness and bioavailability of the material. SwissTargetPrediction was used to identify protein targets. Genes associated with OA were included in the GeneCards database. Compound target and OA-related gene commonalities were found using a Venn diagram. Protein-protein interaction (PPI) networks were constructed using STRING and evaluated using Cytoscape. Hub genes were found with the CytoHubba plugin. CB-DOCK2 was used for molecular docking, while ShinyGO was utilized for enrichment analysis. Root mean square fluctuation was computed using CABS-flex molecular modeling, and docking results were validated with redocking using AutoDock Vina. Molecular dynamics was simulated via the iMODS platform. Out of the 28 bioactive compounds found, eight satisfied the criterion for drug-likeness and bioavailability. 89 target genes are interacting with quercetin. The signalling pathways PI3K-Akt and ErbB were identified by the enrichment analysis. Quercetin has a high binding to OA proteins, including AKT1, EGFR, SRC, MMP9, and IGF1R, according to molecular docking study. Molecular dynamics simulations confirmed the strong interactions and durability of the protein-ligand complexes. An MTT assay was used to validate the DCM/ethanol extract of A. vestita aerial parts against synovial cells (SW-982) and its toxicity on normal cartilage cells (CHON-001). OA cells had significant suppression, whereas normal cells were unaltered. The utilization of network pharmacology and bioinformatics tools in this study has identified quercetin as a highly promising bioactive compound in A. vestita, with potential applications in OA therapy. This research provides a significant understanding of the molecular pathways involved in OA.