Use of network pharmacology and molecular docking to explore the mechanism of action of curcuma in the treatment of osteosarcoma

Abstract

Curcuma has been used as an adjuvant treatment for osteosarcoma (OS) due to its anticancer compounds. However, the underlying mechanism remains unclear. Therefore, this study aimed to explore the mechanism of action of curcuma in the treatment of OS using network pharmacology and molecular docking. In this study, anticancer compounds were obtained from relevant literature, and curcuma-related targets and OS treatment targets were obtained from public databases. Protein‒protein interaction networks were constructed to screen out the hub genes using the STRING database and Cytoscape software. Cluster analysis of the protein modules was then performed using the Cytoscape MCODE plugin. Furthermore, Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses were performed for common targets among curcuma targets and OS-related targets using the DAVID database. Finally, molecular docking was performed, and the results were verified by Auto dock Tool and PyMOL software. Our research identified 11 potential active compounds, 141 potential therapeutic targets and 14 hub genes for curcuma. AKT1, TNF, STAT3, EGFR, and HSP90AA1 were the key targets closely related to the PI3K/Akt signaling pathways, HIF-1 signaling pathways, ErbB signaling pathways, and FOXO signaling pathways, which are involved in angiogenesis, cancer cell proliferation, metastasis, invasion, and chemotherapy resistance in the microenvironment of OS. Molecular docking suggested that the core compound had a strong affinity for key targets, with a binding energy of less than – 5 kJ/mol. The study showed that curcuma-mediated treatment of OS was a complex process involving multiple compounds, targets, and pathways. This study will enhance the understanding of how curcuma affects the proliferation and invasion of OS cells and reveal the potential molecular mechanism underlying the effect of curcuma on OS lung metastasis and chemotherapy resistance.

Potential Utilization of Phenolic Acid Compounds as Anti-Inflammatory Agents through TNF-α Convertase Inhibition Mechanisms: A Network Pharmacology, Docking, and Molecular Dynamics Approach

“…PTGS2 follows with centrality values of 0.336, 15, and 0.552, respectively. In our experimental study, “degree” represents the number of direct neighbors of a node, where a greater number of direct connections signifies a more influential role within the network . “Betweenness centrality” quantifies the shortest paths between all node pairs, with an emphasis on specific nodes that facilitate communication within the network. , “Closeness centrality” is defined as the reciprocal of the average shortest path distance between a node and all other nodes in the network, with higher values indicating greater centrality and faster signal transmission to other nodes in the network …”

Uncovering Naringin’s Anticancer Mechanisms in Glioblastoma via Molecular Docking and Network Pharmacology Approaches

“…Researchers can examine complicated interactions at several levels to understand the combined impacts and fundamental mechanisms of various drugs. 20 . The current research employed a network pharmacology approach to investigate naringin's pivotal targets, biological functions, and related pathways to treat GBM.…”