Investigating the potential anti-inflammatory mechanism of benzophenone compounds from the leaves of Aquilaria sinensis (Lour.) Gilg based on network pharmacology and molecular docking strategies.

ABSTRACT

BACKGROUND: Aquilaria sinensis (Lour.) Gilg (ASG) has been used as traditional medicine for centuries. However, the active ingredients from leaves and their anti-inflammatory mechanism are rarely reported. The network pharmacology and molecular docking strategies were applied to explore the potential mechanisms of Benzophenone compounds from the leaves of ASG (BLASG) against inflammation. METHODS: BLASG-related targets were obtained from the SwissTargetPrediction and PharmMapper databases. Inflammation-associated targets were retrieved from GeneGards, DisGeNET, and CTD databases. Cytoscape software was used to draw a network diagram of BLASG and its corresponding targets. DAVID database was applied for enrichment analyses. A protein-protein interaction (PPI) network was constructed to identify the hub targets of BLASG. Molecular docking analyses were performed by AutoDockTools 1.5.6. Moreover, we used ELISA and qRT-PCR assays to validate the anti-inflammatory effects of BLASG by cell experiments. RESULTS: Four BLASG were extracted from ASG, and corresponding 225 potential targets were identified. PPI network analysis indicated that SRC, PIK3R1, AKT1, and other targets were the core therapeutic targets. Enrichment analyses revealed that the effects of BLASG are regulated by targets associated with apoptosis and inflammation-related pathways. In addition, molecular docking revealed that BLASG combined well with PI3K and AKT1. Furthermore, BLASG significantly decreased the inflammatory cytokines levels and down-regulated PIK3R1 and AKT1 gene expression in RAW264.7 cells. CONCLUSION: Our study predicted the potential targets and pathways of BLASG against inflammation, which offered a promising strategy to reveal the therapeutic mechanism of natural active components in the treatment of diseases.