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.


Introduction
Over the last decade, numerous new studies have demonstrated the importance of inflammation in the progression of chronic conditions such as inflammatory bowel disease, cardiovascular disease, diabetes, cancer, and neurodegeneration (Yeung et al. 2018).Therefore, screening compounds with anti-inflammatory activity from traditional Chinese Medicine will facilitate the development of novel drugs.Aquilaria sinensis (Lour.)Gilg (ASG), a member of the Thymelaeaceae family, has been used as traditional medicine in China for centuries (Yuan H-W et al. 2018).The resinous wood of ASG, locally named Chinese agarwood, has been used as a folk medicine in the treatment of diseases, including dyspnea, vomiting, and abdominal pain (Wang SL et al. 2015).In addition, a large member of experimental studies has found that dried ASG leaf extract has significant anti-inflammatory, analgesic, antitumor, and immunomodulatory pharmacological activities (Zhou et al. 2008;Hsiao et al. 2021).However, the study on the anti-inflammatory activity of ASG leaf remains in the stage of efficacy evaluation, and the material basis and mechanism of its anti-inflammatory effect have not yet been studied in depth.Our previous study showed that the extract of n-butanol from ASG leaf was the anti-inflammatory effective fraction, and 6 compounds with anti-inflammatory effects were separated, of which 4 components had benzophenone mother nucleus structure, which was: 2-O-a-L-rhamnopyranosy-4,6,4,-TrihydroxylbenzoPhenone (RTP), 3.5-C-glucoside-2,4,6,4 0 -Tetrahydroxybenzophenone (3.5GTP), 3-C-glucoside-2,4,6,4 0 -Tetrahydroxybenzophenone (3GTP), mangiferin (MAN).Benzophenones from the leaves of ASG (BLASG) are a class of compounds with special structures widely present in natural plants, which consist of two benzene rings connected by a carbonyl group to constitute a backbone mother nucleus containing 13 carbon atoms, and are connected with major substituents such as hydroxyl, methoxy, glycosyl, and prenyl groups.At present, the antiinflammatory effects of benzophenones have only been reported for MAN.A recent study showed that MAN exerted a regulation effect on pyroptosis and inflammation by inactivating the NF-rB pathway in LPS-induced bone-marrowderived macrophages (Feng M et al. 2022).MAN also inhibited 7,12-dimethylbenz(a)anthracene-induced mammary carcinogenesis via positive regulation of apoptotic pathways and NF-rB inhibition (Wang X et al. 2021).Other benzophenones have not been investigated in depth and systematically for pharmacodynamic studies, and no molecular mechanism has been reported regarding their anti-inflammatory effects.
Professor Hopkins originally proposed the concept of 'network pharmacology' in 2007 (Hopkins 2007).This newly developed approach changed the mechanisms by which researchers used to study the potential pharmacological effects of drugs on diseases.In recent years, traditional Chinese Medicine has benefited from this new research tool (Lin et al. 2021;Wang Y et al. 2022;Yuan ZZ et al. 2022).In our study, we combined network pharmacology, molecular docking, and cell experiment to investigate the potential targets and signaling pathways of BLASG in the treatment of inflammation.Our findings further elucidated the molecular mechanism action of the anti-inflammatory effects of BLASG.This is not only of great significance for the further development and utilization of ASG leaf, but also will provide a new class of lead compounds for the development of anti-inflammatory new drugs, and provide new research directions and ideas for the development of innovative drugs from traditional Chinese Medicine.

Screening of compounds-disease mapped targets
The GeneCards (https://www.genecards.org/)database, DisGeNET (https://https://www.disgenet.org/)database, and CTD (http://ctdbase.org/)database were used to obtain all inflammation-related targets with the keyword 'inflammation'.On this basis, Venny online analysis tool was used to map the BLASG target of action with inflammationrelated targets to obtain the mapped targets of compounddisease.

Construction and analysis of protein-protein interaction (PPI) network
The resulting Gene List of mapped targets was imported into the STRING (https://cn.string-db.org/)database to obtain protein interaction data.This data was imported into Cytoscape (3.7.2) software to visualize the results of the PPI network.The cytoHubba plugin was used to screen the Top 10 key genes using the MCC algorithm.The major clusters of the PPI network were identified using the Cytoscape plugin MCODE.

Functional enrichment analysis
KEGG enrichment analysis can identify the signal pathways enriched by the intersection of genes between BLASG and inflammation.Gene Ontology (GO) functional analysis was performed to describe the function of genes, including molecular function (MF), cellular component (CC), and biological process (BP).The collective genes were subjected to GO and KEGG enrichment analyses using the DAVID (http:// david.abcc.ncifcrf.gov/)database.The results were visualized using the 'clusterProfiler' package.A p-value <0.05 was considered statistically significant.

Molecular docking analysis
We performed molecular docking to interpret the potential binding mode of active ingredients to a macromolecular receptor.The 3D structures of targets protein (AKT and PI3K) were downloaded from PDB (https://www.rcsb.org)databases, and the 3D conformations of proteins with a crystal resolution <3 Å, as measured by X crystal diffraction, were chosen.First, we used PyMOL software to remove the solvent and organic of the protein conformations.Then, AutoDock software (1.5.6) was used to perform molecular docking analysis, and the results of molecular docking were visualized using the PyMOL software.

Cells culture and treatment
RAW264.7, a mouse macrophage cell line was obtained from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China).The cells were incubated in high-glucose Dulbecco's modified Eagle's medium containing 10 U/mL penicillin, 10 mg/mL streptomycin, and 10% fetal bovine serum and maintained in an incubator supplemented with 5% CO2 at 37 C. RTP, 3.5GTP, 3GTP, and MAN were separated from ASG. LPS (Escherichia coli) and dexamethasone (DEX) were obtained from Sigma-Aldrich and dissolved in DMSO.DEX was used as a positive control.Cells from the sixth passage were used in the next experiments.RAW264.7 cells were treated or not treated with BLASG (20 mM) or DEX (20 mM) in the presence of LPS (1 mg/ml) for 24 h.Then, the MTT solution (20 mL) was added to each well and cultured for 4 h at 37 C.The model of inflammation induced by LPS was established based on a previous report (Cao et al. 2019).

Measurement of inflammatory cytokine
After the RAW264.7 cells were pretreated with BLASG (20 mM) for 1 h and LPS for an additional 24 h.We collected the culture supernatant, and the IL-10, IL-6 and TNF-a level was measured using enzyme-linked immunosorbent assay (ELISA) based on the manufacturer's protocols (ThermoFisher, MA, USA).

Quantitative real-time polymerase chain reaction
Total RNA was extracted from RAW264.7 cells using TRIzol Reagent (Invitrogen, CA, USA) based on the manufacturer's protocols.2 mg of purified RNA was synthesized into the cDNA using the cDNA synthesis kits (Invitrogen, CA, USA).Then, the Quantitative real-time polymerase chain reaction (qRT-PCR) was performed on a StepOne Real-time PCR system (Applied Biosystems, CA, USA).The 2 -DDCt method was used to measure the mRNA expression levels.The primers were presented in Table S1.

Statistical analysis
GraphPad Prism software was used to conduct all statistical analyses.Data were expressed as the means ± SD.Statistical differences between the two groups were compared using an analysis of variance followed by Tukey's comparison test.Statistical difference was set at p < 0.05.

Screening of anti-inflammatory targets of 4 BLASG
Four BLASG including RTP, 3.5GTP, 3GTP, and MAN were extracted and purified from ASG.A total of 406 BLASG-related targets were obtained after removing duplicates from Swiss Target Prediction and Pharm Mapper databases.We used the GeneCards, DisGeNET, and CTD databases, and a total of 3129 inflammation-related targets were identified after deleting the reappeared targets.Then, we ultimately identified 222 potential targets of BLASG against inflammation by overlapping the screened targets of BLASG and inflammation with a Venn tool (Figure 1(A)).
As presented in Figure 1(B), the 222 targets screened by the intersection described above were imported into Cytoscape software to construct a target network of BLASG associated with inflammation.The PPI network was topologically analyzed using Analyze Network tool, which involved a total of 204 nodes and 1433 edges.Four green diamond nodes represent each of the four BLASG.Light blue rectangular nodes represent the overlapping targets between BLASG and inflammation.Dark blue rectangular nodes represent common targets of four BLASG.

Enrichment analysis of 222 common targets
As shown in Figure 2(A), the top 10 GO analyses of BP, CC, and MF were presented as a histogram.The results showed that the main BP terms were a response to oxygen-containing compound, response to stress, cellular response to chemical stimulus, response to organic substance, etc; and the main MF term was catalytic activity.As shown in Figure 2(B), the top 10 KEGG pathways were presented as bubble diagrams.The results showed that the main KEGG pathways were pathways in cancer, PI3K-Akt signaling pathway, MAPK signaling pathway, proteoglycans in cancer, focal adhesion, etc.

Analysis of common genes among four BLASG
As shown in Figure 3(A), we identified 36 common genes for four BLASG using a Venn tool.We further identified the core networks using the MCODE plug-in (Figure 3(B)).The results showed that the functional network main composed of SRC, PIK3R1, EGFR, HARS, AKT1, HSP90AA1, LCK, and JAK2 was its core subnetwork (Table S2), suggesting that BLASG may be closely related to the interaction of the above targets during the intervention of inflammatory response.
Further enrichment analysis of these 36 targets, the results showed that the main BP terms were a cellular response to chemical stimulus, regulation of biological quality, response to chemical, response to external stimulus, etc; the main CC term was extracellular space; and the main MF terms were catalytic activity and identical protein binding (Figure 4(A)).As shown in Figure 4(B and C), the top 10 KEGG pathways were presented as bubble diagrams.The results indicated that the main KEGG pathways were pathways in cancer, PI3K-Akt signaling pathway, Ras signaling pathway, prostate cancer, endocrine resistance, FoxO signaling pathway, estrogen signaling pathway, etc.We further analyzed the inflammatory pathways with the higher association in KEGG enrichment analysis results.The findings showed that the anti-inflammatory effect-related targets were widely distributed in classical inflammatory signaling pathways, such as the PI3K-AKT signaling pathway (Figure 5).
The above signaling axis pointed to the apoptosis-regulating gene BCL-2 and its related genes.Therefore, it is speculated that BLASG may regulate immune cell apoptosis through the above signaling pathways and thus intervene in the inflammatory response.

Molecular docking analysis
As shown in Figures 6 and 7, the molecular docking of four BLASG with PI3K and AKT1 receptors showed that the binding energy of each receptor-ligand complex was 5kcal/mol after docking (Table S3), indicating that all four compounds could actively bind to the receptor with high-affinity activity.The molecular docking results verified that all four BLASG had good binding properties to PI3K and AKT1 receptor molecules.In general agreement with the results of KEGG analysis, it was further verified that the BLASG could regulate immune cell apoptosis through the classical PI3K-AKT signaling pathway and thus interfere with the inflammatory response.

BLASG inhibits LPS-evoked inflammation in RAW264.7 cells
As shown in Figure 8(A), our findings showed that treatment with RTP (20 mM), 3.5GTP (20 mM), 3GTP (20 mM), MAN (20 mM), and DEX (20 mM) had no cytotoxicity on the cell viability of RAW264.7 cells.Thus, the concentrations of 20 mM for BLASG were selected in the next study.To validate the potential mechanism of BLASG as predicated on network pharmacology and molecular docking results, we measured the levels of the pro-inflammatory cytokine in different groups.Compared to the Con group, the IL-6 and TNF-a levels were significantly increased in the LPS group, which were inhibited by treatment with RTP (20 mM), 3.5GTP (20 mM), 3GTP (20 mM), and MAN (20 mM), respectively (Figures 8(B  and C).To further confirm the anti-inflammatory effects of BLASG, we conducted additional research on the alterations in IL-10 production.Compared to the LPS group, the IL-10 level was significantly increased in the treatment groups (Figure 8(D)).
Moreover, we detected the expression of genes (PIK3R1 and AKT1) related to the PI3K-AKT signaling pathway and the anti-inflammatory-related gene (IL-10) using PCR analysis.Compared with the Con group, the expression levels of PIK3R1 (Figure 9(A)) and AKT1 (Figure 9(B)) were significantly up-regulated in the LPS group, which were down-regulated by treatment with RTP (20 mM), 3.5GTP (20 mM), 3GTP (20 mM), MAN (20 mM), and DEX (20 mM), respectively.In addition, compared to the LPS group, the IL-10 gene expression level was significantly increased in the treatment groups (Figures 9(C)).Our findings showed that BLASG had a promising antiinflammatory effect via the PI3K-AKT signaling pathway.

Discussion
Previous studies on the development and utilization of ASG resources have been limited to medicinal parts (wood parts containing resins) in the traditional sense, completely ignoring other parts of ASG with medicinal development potential, such as branches and leaves (Wang S et al. 2018;Li W et al. 2021;Alamil et al. 2022).Therefore, if we can conduct comprehensive research on the development of the nonmedicinal part resources of ASG, mainly the leaves, and expand the range of medicinal uses of ASG, we can provide a theoretical basis and research foundation for the further development and utilization of the ASG leaves and their series of related products while making full use of the rare plant resources.Previous studies have revealed blood glucose regulatory activities (Jiang and Tu 2011), antitumor effects (Cheng JT et al. 2013;Yang et al. 2018), the a-glucosidase inhibitory effect (Feng J et al. 2011), and analgesic and antiinflammatory effects of active extracts and ingredients of ASG leaves (Qi et al. 2009).Given the above studies, ASG  leaves may have potential pharmacological applications.Our preliminary study found that ASG leaves have significant anti-inflammatory potency and the n-butanol extraction fraction is the effective anti-inflammatory fraction of ASG leaves.On this basis, we finally identified four BLASG compounds with high correlation with in vitro anti-inflammatory activity from this fraction, namely: RTP, 3.5GTP, 3GTP, and MAN.Consistent with our findings, a previous study showed that MAN suppressed inflammatory cytokine-related gene expression via inhibition of the NF-jB pathway in collageninduced arthritis (Tsubaki et al. 2015).MAN prevented NLRP3 inflammasome activation in LPS-induced lung injury (Li N et al. 2021).
Our study applied a network pharmacology approach to identify the core targets and potential pharmacodynamic pathways of BLASG in the treatment of inflammation.The results of PPI and topological analyses indicated that there were eight core targets (SRC, PIK3R1, EGFR, HARS, AKT1,  HSP90AA1, LCK, and JAK2) of the BLASG against inflammation.In addition, the results of the KEGG enrichment analysis revealed that the PI3K-Akt signaling pathway was likely the relevant pathway for inflammation.Furthermore, molecular docking and in vitro experiments have demonstrated this finding.PI3K-Akt signaling pathway, as one of the important intracellular signaling pathways, plays a key role in a variety of cellular biological processes by influencing the activation status of various downstream effector molecules (Ersahin et al. 2015).The PI3K-Akt signaling pathway was important in the pathogenesis of inflammation-related disorders, such as ulcerative colitis, arthritis, idiopathic pulmonary fibrosis, and chronic sinusitis (Sun et al. 2020;Cheng KJ et al. 2022;Dong et al. 2022;Wang J et al. 2022).Activation of the PI3K-Akt signaling pathway participated in IL-6 trans-signaling induced inflammatory response in human vascular endothelial cells (Zegeye et al. 2018).LY294002, an inhibitor of PI3K, was shown to suppress the inflammatory response in endotoxin-evoked uveitis by inhibiting the PI3K-Akt signaling pathway (Wu et al. 2022).In addition, lots of active compounds exerted anti-inflammatory effects via the inactivation of PI3K-Akt signaling pathway (Harikrishnan et al. 2018;Zhang et al. 2019;Fan et al. 2020;Gao et al. 2020;Zhang et al. 2021).In our study, the molecular docking results indicated that the binding between the four BLASG compounds and AKT and PI3K is good.Furthermore, the four BLASG compounds exerted a significant inhibition effect on the PIK3R1 and AKT1 expression levels in LPS-treated RAW264.7 cells, resulting in a significant decline in the secretion of IL-6 and TNF-a.These findings implied that BLASG could inhibit inflammation via the regulation of the PI3K-Akt signaling pathway.

Conclusion
The results of network pharmacology and molecular docking showed that four BLASG compounds may have participated in interaction with primary proteins (AKT and PI3K) in the PI3K-Akt signaling pathway.Further cell experiments demonstrated that BLASG suppressed LPS-induced inflammation by down-regulating the expression of PIK3R1 and AKT1.All these findings showed that BLASG was a potent anti-inflammatory agent for inflammation-associated disorders.However, further studies are needed regarding the exact anti-inflammatory mechanism of BLASG.

Figure 1 .
Figure 1.Identification of potential genes associated with the anti-inflammation effects of BLASG.(A) Venn diagram of shared genes between BLASG and inflammation.(B) BLASG compound-target network diagram.Green diamond nodes represent each of the four BLASG.Light blue rectangular nodes represent the overlapping targets between BLASG and inflammation.Dark blue rectangular nodes represent common targets of four BLASG.

Figure 2 .
Figure 2. GO and KEGG enrichment analysis of 222 genes.(A) Histogram showed the top 10 GO analyses of BP, CC, and MF.(B) Bubble diagrams showed the top 10 KEGG pathways.

Figure 4 .
Figure 4. GO and KEGG enrichment analysis of 36 genes.(A) Histogram showed the top 10 GO analyses of BP, CC, and MF.Bubble (B) and circle (C) plots showed the top 10 KEGG pathways.

Figure 5 .
Figure 5. Therapeutic effects of BLASG compounds against inflammation involved in PI3K-Akt signaling pathway.

Figure 6 .
Figure 6.Molecular docking analysis of BLASG compounds binding to AKT. (A) Molecular docking simulation between RTP and AKT.(B) Molecular docking simulation between 3.5GTP and AKT.(C) Molecular docking simulation between 3GTP and AKT.(D) Molecular docking simulation between MAN and AKT.The left side shows the 3D surface structure of the AKT receptor and the small molecule ligand.The right side shows the binding pattern of the small molecule ligand to the AKT protein.

Figure 7 .
Figure 7. Molecular docking analysis of BLASG compounds binding to PI3K.(A) Molecular docking simulation between RTP and PI3K.(B) Molecular docking simulation between 3.5GTP and PI3K.(C) Molecular docking simulation between 3GTP and PI3K.(D) Molecular docking simulation between MAN and PI3K.The left side shows the 3D surface structure of the PI3K receptor and the small molecule ligand.The right side shows the binding pattern of the small molecule ligand to the PI3K protein.

Figure 8 .
Figure 8. BLASG compounds inhibited pro-inflammatory cytokines and increased anti-inflammatory cytokines in LPS-stimulated RAW264.7 cells.RAW264.7 cells were treated or not treated with BLASG compounds (20 mM) or DEX (20 mM) in the presence of LPS (1 mg/ml) for 24 h.(A) Effects of BLASG compounds and LPS on cell viability.The level of IL-6 (B), TNF-a (C), and IL-10 (D) was measured by the ELISA method.# p < 0.001 compared with the Con group; ÃÃ p < 0.01 compared with LPS-stimulated group; ÃÃÃ p < 0.001 compared with LPS-stimulated group.