Abstract graphic file with name ao3c08968_0009.jpg Nonalcoholic fatty liver disease (NAFLD) is a prevalent global liver disorder, posing substantial health risks. Britanin, a bioactive sesquiterpene lactone extracted from Inula japonica, has demonstrated antidiabetic, hypolipidemic, and hepatoprotective attributes. Nonetheless, the precise impact of Britanin on NAFLD and the intricate biological mechanisms underpinning this interaction remain unexplored. We integrated computer-aided methods to unearth shared biological targets and signaling pathways associated with both Britanin and NAFLD. A network was constructed by compiling putative targets associated with Britanin and NAFLD, followed by a stringent screening of key targets and mechanisms through protein–protein interaction analysis along with GO and KEGG pathway enrichment analyses. Molecular docking was integrated as an evaluation tool, culminating in the identification of HO-1 as the pivotal therapeutic target, showcasing a satisfactory binding affinity. The primary mechanism was ascribed to biological processes and pathways linked to oxidative stress, as evidenced by the outcomes of enrichment analyses. Of these, the AMPK/SREBP1c pathway assumed centrality in this mechanism. Furthermore, in vivo experiments substantiated that Britanin effectively curtailed NAFLD development by ameliorating liver injury, modulating hyperlipidemia and hepatic lipid accumulation, and alleviating oxidative stress and apoptosis. In summary, this study demonstrates the potential of Britanin as a promising therapeutic drug against NAFLD. Introduction Nonalcoholic fatty liver disease (NAFLD) is a prevalent liver disease worldwide, affecting approximately 25% of the population.^[32]1,[33]2 Initially regarded as a benign condition primarily associated with obesity, recent research has revealed the intricate nature of NAFLD. Numerous studies have demonstrated an elevated risk of mortality associated with NAFLD.^[34]3,[35]4 Furthermore, even the presence of simple steatosis can ultimately lead to increased all-cause mortality due to the progressive nature of the disease over long-term follow-up periods.^[36]5,[37]6 NAFLD encompasses a spectrum of clinical manifestations, ranging from simple steatosis (referred to as fatty liver) to hepatic fibrosis and nonalcoholic steatohepatitis.^[38]7,[39]8 These conditions are associated with an increased risk of liver-related complications including hepatocellular carcinoma, liver failure, and cirrhosis. Additionally, NAFLD is closely linked to significant extra-hepatic manifestations, such as diabetes, dyslipidemia, and cardiovascular disease, further exacerbating its disease burden.^[40]9−[41]14 Consequently, it is imperative to recognize that the effective treatment of this disease would yield substantial benefits for healthcare. Recently, growing interest in Oriental medicine has prompted a surge in research on natural compounds that exhibit potential for treating inflammatory diseases. Inula japonica Thunb, a frequently utilized medicinal plant in traditional Chinese medicine, has gained recognition for its ability to regulate spleen, liver, lung, and stomach function, as well as its potential in preventing abortion.^[42]15,[43]16 Britanin (Bri) is a bioactive sesquiterpene lactone mainly found in plants like Inula britannica, Inula japonica, and Inula lineariifolia Turcz., and it belongs to the category of pharmacologically active phytochemicals.^[44]17,[45]18Inula britannica extract has shown antioxidant and hepatoprotective properties in vitro.^[46]19 Moreover, Wu et al. reported that Britanin functions as a protective phytochemical against ischemic brain injury in a rat model of middle cerebral artery occlusion-reperfusion (MCAO/R).^[47]20 Kim et al. demonstrated that Britanin mitigates airway inflammation induced by ovalbumin in a murine model of asthma.^[48]21 In addition, contemporary pharmacological investigations have revealed its multifaceted effects, encompassing antidiabetic, hypolipidemic, and hepatoprotective activities. In detail, Britanin exhibited antiadipogenic properties by reducing intracellular lipid accumulation and modulating the expression of markers associated with lipogenesis and adipogenesis.^[49]22 Britanin, when administered orally, notably decreased blood lipid and glucose levels in diabetic mice, suggesting the antidiabetic and hypolipidemic effects of Britanin.^[50]23 Nevertheless, the potential of Britanin in alleviating NAFLD has yet to be elucidated. Hence, the objective of this study is to investigate the potential protective effect of Britanin against NAFLD and elucidate the underlying mechanism using a combination of pharmaco-bioinformatics approaches and experimental verification. Materials and Methods Screening and Identification of Britanin Targets The potential targets of Britanin were obtained using SymMap, TCMID, and TCMSP databases. The PubChem database ([51]https://pubchem.ncbi.nlm.nih.gov/) was utilized to acquire single large flowers, inula Britanin 2d structure. The SwissTargetPrediction database ([52]http://www.swisstargetprediction.ch/) was further used to predict the potential targets of Britanin. In the SwissTargetPrediction tool, it is hypothesized that the top 15% of results carry a 75% likelihood of representing the compound’s target. Consequently, the initial 15 results from SwissTargetPrediction were chosen. The Z-score for network proximity was derived from the mean and standard deviation of random distances. Comparing results from the PharmMapper database, the Z-score exhibits a superior confidence interval and statistical significance compared to the ‘Fit score’, aligning with it. Results with Z-score > 0 was considered significant, while a negative Z-score indicated insignificance. Additionally, a higher Z-score correlates with a more favorable combination of compound molecules and protein targets. Within TargetNet, outcomes with a probability (Prob) ≥ 0.9 ([53]http://targetnet.scbdd.com) were deemed reliable targets for active ingredients. Hence, to enhance result confidence, Prob ≥ 0.9 and Z-score > 0 were chosen as effective criteria in this study. Acquisition of Disease Targets In gene expression omnibus (GEO) databases ([54]https://www.ncbi.nlm.nih.gov/geo/), the transcriptome chip data related to “nonalcoholic fatty liver disease” was downloaded, and the screening criteria were as follows: The key word is “nonalcoholic fatty liver disease” and “human beings”. Then, the bioconductor R package in R software was used to rectify the background, normalize, and calculate the expression value of the chip data. The differentially expressed mRNAs between the two groups were calculated using the limma package. The P value < 0.05 and (|log2 FC| ≥ 0.58) variation range ≥ 1.50 were set as the criteria for screening differential genes in which log2FC ≥ 0.58 represented upregulated mRNA expression, and log2FC ≤ −0.58 represented downregulated mRNA expression. Subsequently, differentially expressed genes (DEGs) related to NAFLD were obtained. The DEGs obtained from screening were used to generate a heatmap and perform clustering analysis using the heatmap package. The P-values in the differentially processed data were transformed to −log10 scale, and based on the log2FC values, the −log10 (P-value) was grouped into upregulated DEGs, downregulated DEGs, and DEGs with no statistical significance. The processed data was then imported into R to create a volcano plot. Additionally, by searching the “nonalcoholic fatty liver disease” in the Genecards ([55]https://www.genecards.org/) database, disease targets related to NAFLD were obtained. The acquired targets were merged and deduplicated and then matched with validated human target gene names using the Uniprot database. Gene Set Enrichment Analysis Using the clusterprofiler R package, gene set enrichment analysis (GSEA) was performed on the gene sets from the aforementioned NAFLD data set. The “hallmark gene sets” were selected for comparison, aiming to explore the biological functions played by the gene sets between NAFLD and normal tissues. Identification of Common Targets between Britanin and NAFLD and Construction of a PPI Network To elucidate the interactions between NAFLD-related targets and the potential targets of Britanin, the R language ([56]https://www.r-project.org/) software and the Perl programming language were utilized. The disease targets and Britanin targets were intersected using Venny 2.1 software ([57]http://bioinfogp.cnb.csic.es/tools/venny/index.html) to generate a Venn diagram. The STRING database ([58]https://string-db.org/) was used to construct separate protein–protein interaction (PPI) networks for the shared targets. To ensure data reliability, we specifically chose PPI data related to “Homo sapiens” with a confidence score equal to or greater than 0.7 (classified as highest confidence: ≥ 0.9, high: ≥ 0.7, medium: 0.4–0.7, low: < 0.4). These data were utilized for constructing the PPI network, and subsequently, we extracted the largest connected component. Finally, the acquired data set was imported into the Cytoscape software for the purpose of visualizing and analyzing key targets. GO Biological Function and KEGG Pathway Enrichment Analysis The shared targets between Britanin and NAFLD were subjected to gene ontology (GO) analysis using the clusterProfilerGO.R package in R language ([59]https://www.r-project.org/) and Perl programming language. We established a threshold of an adjusted P-value < 0.05, and the ggplot2 package was employed to visualize the outcomes of significant enrichment. GO analysis serves as the primary method for characterizing the functions of gene products, encompassing biological process (BP), molecular function (MF), and cellular component (CC). Additionally, the clusterProfilerKEGG.R package was employed for KEGG pathway enrichment analysis. Furthermore, the pathview package was utilized to visualize the corresponding signaling pathways. By analyzing the enrichment factor values, the extent of enrichment in key pathways was determined, aiming to explore the potential biological functions and signaling pathway mechanisms of Britanin in treating NAFLD. Core Target Relative Expression and ROC Evaluation The expression matrix data related to NAFLD was retrieved and downloaded from the GEO database. This data set encompasses the transcriptome expression matrix file specifically for NAFLD. Subsequently, utilizing the ggpubr package, perform an analysis of the relative expression levels of the core target genes within the NAFLD expression data, previously selected during the preliminary screening. Additionally, a boxplot represents the relative expression levels of these core target genes. Next, the standardized NAFLD-core target gene expression data are merged with the clinical data of NAFLD. Finally, R language packages such as survival, caret, glmnet, survminer, and survival receiver operating characteristic (ROC) are utilized to construct ROC curves for the core genes associated with NAFLD. Molecular Docking Verification To validate the interaction between Britanin and the core proteins, we performed molecular docking was performed. The chemical structures of active compounds were downloaded from the PubChem database ([60]https://pubchem.ncbi.nlm.nih.gov/). Using Chem3D software, corresponding 3D structures were created and exported in the mol2 format. The protein structures of the core proteins were obtained from the PDB database ([61]http://www.rcsb.org/). The protein was processed by using PyMOL software by removing water molecules and phosphate groups. AutoDockTools 1.5.6 software was used to convert the drug’s active compounds and the protein gene files from the pdb format to pdbqt format and identify the active binding site. Finally, the Vina script was executed to calculate the molecular binding energy and display the results of molecular docking. Discovery Studio 2019 was also used to identify the docking sites and calculate the flexible binding LibDockScore. The output of the molecular docking results was imported into PyMOL software for visualization of the molecular docking conformations. A binding energy less than 0 indicates spontaneous binding between the ligand and receptor. When Vina binding energy is ≤ −5.0 kcal mol^–1 and LibDockScore >100, it suggests a stable docking interaction. The 3D and 2D representation of the ligand–receptor complex was displayed to assess the reliability of the bioinformatics analysis prediction. Animal Experiments A total of 32 six-week-old C57BL/6J mice were used as animal models, purchased from Changzhou Cavens Experimental Animals Co., Ltd. They were housed in the SPF-grade barrier system at the Animal Facility of the University of south China. After 1 week of acclimatization, the mice were randomly divided into four groups, with eight mice per group, as follows: (1) control group: fed with regular diet; (2) model group: fed with a high-fat diet; (3) low-dose drug group: fed with a high-fat diet + Bri (10 mg/kg); (4) high-dose drug group: fed with a high-fat diet + Bri (20 mg/kg). After 8 weeks of high-fat diet feeding, the mice in the drug groups were subjected to gavage administration of Bri for 6 weeks. After completion of drug administration, the mice were euthanized for sample collection. First, the animals were monitored daily, and when they reached specific humane end points, they were euthanized using pentobarbital sodium. These humane end points included signs such as nose bleeding, skin lesions, breathing difficulties, prostration, considerable loss in body weight, rotational movement, and a decrease in body temperature. Then, blood samples were obtained, and the abdominal cavity was opened to collect liver samples from the mice. All procedures were carried out in conformity with the Animal Care Guidelines of the University of South China and the Institutional Animal Ethics Committee for the use of experimental animals. Biochemical Analysis Blood samples were collected from the mice and centrifuged at 3000g for 15 min to obtain serum for analysis of four lipid parameters (total cholesterol, triglycerides, HDL cholesterol, and LDL cholesterol) and two liver function markers (ALT and AST) levels. The lipid and liver function assay kits were purchased from Solaibao Biotechnology Co., Ltd., and the measurements were conducted following the instructions provided in the kit manuals. Determination of Body Weight, Food Intake, and Liver Fat Weight in Mice After the intervention with Britanin, the body weight and food intake of the mice were measured and recorded every 2 days. After the mice were euthanized, the livers were extracted, photographed, and weighed using an analytical balance. Histopathological Examination To observe pathological changes in the liver tissue of mice, we performed histological staining. The liver tissues were fixed and embedded in the OCT compound for frozen sectioning using a cryostat. Oil Red O staining was performed to assess lipid accumulation in the liver. Additionally, the liver tissues were fixed in paraformaldehyde, embedded in paraffin, and sectioned. Hematoxylin and eosin (HE) staining and Masson’s trichrome staining were conducted to evaluate general tissue morphology and fibrosis, respectively. Detection of Oxidative Stress-Related Indexes Mouse serum was collected, and the levels of malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) in the serum were measured following the instructions provided in the assay kit. Immunohistochemistry After fixation of the liver tissue with paraformaldehyde, paraffin sections were prepared. Immunohistochemical staining was performed using the corresponding primary antibodies, followed by incubation with horseradish peroxidase (HRP)-conjugated secondary antibodies. 3, 3′-diaminobenzidine (DAB) staining was conducted using a DAB kit, followed by counterstaining with hematoxylin. The stained sections were observed under a microscope. Western Blot Assay 100 mg portion of liver tissue was homogenized in a lysis buffer to obtain a protein extraction. The total protein extract was obtained after centrifugation. The protein concentration was measured by using a BCA assay kit. SDS-PAGE was employed for protein electrophoresis. Subsequently, the proteins were transferred to a PVDF membrane by using the wet transfer method. The membrane was then blocked and incubated with the primary antibody overnight on a shaker at 4 °C. After the membrane was washed, it was incubated with the secondary antibody and finally visualized. Primary antibodies include AMPK (dilution ratio 1:1000, ab3759, Abcam), pAMPK (dilution ratio 1:1000, ab92701, Abcam), SREBP-1c (dilution ratio 1:1000, ab28481, Abcam), HO-1 (dilution ratio 1:1000, ab13243, Abcam), Caspase3 (dilution ratio 1:1000, ab32351, Abcam), Bcl-2 (dilution ratio 1:1000, ab32124, Abcam), Bax (dilution ratio 1:1000, ab32503, Abcam), and β-actin (dilution ratio 1:2000, ab8227, Abcam). Secondary antibodies were HRP-labeled Goat Anti-Mouse IgG (H + L) (dilution ratio of 1:1000, ab150116, Abcam) and HRP-labeled Goat Anti-Rabbit IgG (H + L) (dilution ratio of 1:1000, ab6721, Abcam). The protein bands were visualized by a Tanon 5500 Imaging System (Tanon Technology Co. Ltd., Shanghai, China). Statistical Analysis All experimental data are presented as mean ± standard deviation (mean ± SD). Student’s t test was used for data comparison between two groups, and P < 0.05 was considered statistically significant. In the realm of network pharmacology and bioinformatics analysis, R software was utilized to handle extensive data sets. GraphPad Prism 8.01 and SPSS 24.0 software were used for data visualization and statistical analysis. Results Identification of Potential Targets for Britanin By searching the SymMap, TCMID, and TCMSP databases, a total of seven target proteins corresponding to the drug were identified. In addition, SwissTargetPrediction predicted 108 potential target proteins for Britanin. Combining these results were combined, a total of 112 potential target proteins for Britanin were identified. Target Screening for NAFLD The filtering criteria were set as follows: (1) NAFLD and (2) human. Our study originated from the [62]GSE63067 chip data set, which included 99 patients with NAFLD and 7 healthy adults. After data background correction and normalization, the sample distribution is shown in [63]Figure [64]1 A. Based on the criteria of P-value (<0.05) and expression fold change (≥1.50 or |log2FC| ≥ 0.58), a total of 270 differentially expressed mRNAs were identified in the [65]GSE63067 data set, including 202 upregulated mRNAs and 68 downregulated mRNAs. As shown in [66]Figure [67]1B, heatmaps of the differentially expressed coding RNAs were generated, with red indicating upregulated gene expression and blue indicating downregulated gene expression. The P-values from the differential analysis of the chip data were transformed into −log10 scale, and based on log2FC, the −log10 (P-value) was grouped into upregulated DEGs, downregulated DEGs, and nonsignificant DEGs. The processed data was imported into R to generate a volcano plot, as shown in [68]Figure [69]1C. By sorting the DEGs in NAFLD according to log2FC, GSEA analysis revealed significant enrichments. As shown in [70]Figure [71]1D, the upregulated gene set in NAFLD, compared to healthy adults, showed significant enrichment in pathways such as inflammatory bowel disease, legionellosis, leishmaniasis, terpenoid backbone biosynthesis, and the TNF signaling pathway. The downregulated gene set exhibited significant enrichment in pathways including hepatitis B, N-glycan biosynthesis, protein processing in the endoplasmic reticulum, ribosome, and various types of N-glycan biosynthesis ([72]Figure [73]1E). Figure 1. [74]Figure 1 [75]Open in a new tab Target selection for NAFLD. (A) Distribution of standardized samples from the [76]GSE63067 data set. (B) Heatmap of DEGs in [77]GSE63067. (C) Volcano plot illustrating DEGs in [78]GSE63067. (D) Gene set enrichment analysis (GSEA) of the upregulated gene set in [79]GSE63067. (E) Gene set enrichment analysis (GSEA) of the downregulated gene set in [80]GSE63067. Screening of Common Targets By searching the Genecards database with a relevance score threshold of ≥10 for “nonalcoholic fatty liver disease”, a total of 544 proteins associated with NAFLD-related diseases were obtained. The 112 potential target proteins of the active compounds were separately compared with 270 NAFLD-related targets and 544 proteins associated with NAFLD-related diseases. Using the online Venn diagram tool InteractiVenn, the matched mappings identified 24 potential targets for the treatment of NAFLD by Britanin. These include LRRK2, CXCR2, DPP4, HO-1, MAPK8, and MAPK14. As shown in [81]Figure [82]2 A, the Venn diagram illustrates the intersection of the active compound and disease targets. Furthermore, the Cytoscape 3.7.2 software results showed a common target network for Britanin and NAFLD. The top 10 core targets were selected based on Degree, Closeness, and Betweenness values ([83]Figure [84]2B–D). These core targets included LRRK2, ESR1, AR, MAPK8, MAPK14, HO-1, EGFR, MMP1, NFE2L2, and DPP4. Figure 2. [85]Figure 2 [86]Open in a new tab Core gene network. (A) Venn diagram depicting potential core targets of Britanin in NAFLD treatment. (B) Distribution of core targets based on degree centrality. (C) Distribution of core targets based on closeness centrality. (D) Distribution of core targets based on betweenness centrality. Results of GO and KEGG Enrichment Analysis The bioconductor and clusterProfiler packages in R were used to perform GO and KEGG enrichment analysis on the 24 potential targets of Britanin for the treatment of NAFLD. The results of the GO analysis revealed that the potential target genes were primarily enriched in BPs, such as cellular response to chemical stress, response to metal ion, and cellular response to oxidative stress. In terms of CCs, the enrichment was observed in the membrane raft, membrane microdomain, and caveola, among others. The MFs were predominantly associated with transcription cofactor binding, transcription coactivator binding, and virus receptor activity ([87]Figure [88]3 A,B). Furthermore, the KEGG analysis identified significant enrichment in pathways such as endocrine resistance, the relaxin signaling pathway, fluid shear stress and atherosclerosis, and the IL-17 signaling pathway ([89]Figure [90]3C,D). Figure 3. [91]Figure 3 [92]Open in a new tab Enrichment analysis. (A) Bar chart depicting GO functional analysis results. (B) Chord diagram illustrating enriched GO terms. (C) Chord diagram illustrating enriched KEGG pathways. (D) Schematic representation of the endocrine resistance signaling pathway. ROC Curve Construction To further elucidate the expression changes of the 24 intersecting genes in NAFLD, we downloaded relevant gene expression data for NAFLD from GEO. Using the ggpubr package, we analyzed the relative expression levels of the 24 DEGs and generated a boxplot ([93]Figure [94]4 A). The results showed that LRRK2, CXCR2, DPP4, HO-1, MAPK8, and MAPK14 exhibited significantly higher expression in NAFLD tissues from the [95]GSE63067 data set (P < 0.05). Therefore, we performed ROC curve analysis for these six target genes to evaluate their sensitivity and specificity in diagnosing NAFLD. As shown in [96]Figure [97]4B, the area under the curve values for LRRK2, CXCR2, DPP4, HO-1, MAPK8, and MAPK14 in the [98]GSE63067 data set were all greater than 0.80, suggesting good diagnostic significance. Figure 4. [99]Figure 4 [100]Open in a new tab Relative gene expression and ROC model construction. (A) Relative expression levels of core genes in [101]GSE63067 data set. (B) ROC model for core DEGs in [102]GSE63067 samples. Results of Molecular Docking Based on the network pharmacology and bioinformatics analysis, the interaction between Britanin and the core targets of NAFLD, including LRRK2, CXCR2, DPP4, HO-1, MAPK8, and MAPK14, was validated through molecular docking. The 3D structure of Britanin was generated using Chem3D software and saved in mol*2 format. The 3D structures of the core proteins, LRRK2, CXCR2, DPP4, HO-1, MAPK8, and MAPK14, were downloaded from the PDB database and saved in a pdb format. The AutoDockTools 1.5.6 software was used to convert the ligand and target proteins into pdbqt format, and active pockets (binding sites formed by hydrogen bonds, H−π bonds, or π–π bonds with one or more amino acid residues) were identified. The Vina script was executed to calculate the binding energies of the ligand–receptor complexes. The results, presented in [103]Table [104]1 , demonstrated that the binding energies between Britanin and the core proteins LRRK2, HO-1, and MAPK8 were all below −5.0 kcal·mol^–1, with RMSD values less than 2.00, indicating stable binding. Additionally, using Discovery Studio 2019 software, molecular docking was performed between the active compound and its corresponding target proteins, and LibDockScores were calculated ([105]Table [106]1). Based on [107]Table [108]1, Britanin formed semiflexible docking with the respective core proteins LRRK2, CXCR2, DPP4, HO-1, MAPK8, and MAPK14, and docking sites were successfully identified. Among them, the docking model between the active compound and the core protein HO-1 had a LibDockScore greater than 100. Considering the RMSD, chemical energy, and docking scores, the docking complex formed between Britanin and the core protein HO-1 was the most stable, followed by the complex with the core protein MAPK8. Different core proteins and different active molecules form distinct docking complexes due to the formation of different hydrogen bonds and hydrophobic interactions at specific amino acid residues. Finally, the compound results obtained from Vina were imported into PyMOL and Discovery Studio 2019 software for 3D and 2D molecular docking visualizations, as shown in [109]Figure [110]5. Table 1. Results of Molecular Docking Using Autodock-Vina and Discovery Studio 2019. structural domain compound Vina (kcal mol^–1) RMSD DS (LibDockScore) LRRK2(5OP4) Britanin –7.3 1.957 92.8351 CXCR2(6KVA) Britanin –1.5 2.151 87.7261 DPP4(4L72) Britanin –7.2 30.245 67.1245 HMOX1(1DVE) Britanin –7.6 1.613 103.552 MAPK8(4G1W) Britanin –7.4 1.862 95.0942 MAPK14(6SFO) Britanin –7.7 4.504 95.0706 [111]Open in a new tab Figure 5. [112]Figure 5 [113]Open in a new tab Molecular docking models. (A1) Macroscopic 3D molecular docking model of LRRK2-Britanin. (A2) Microscopic 3D molecular docking model of LRRK2-Britanin. (A3) 2D molecular docking model of LRRK2-Britanin. (B1) Macroscopic 3D molecular docking model of CXCR2-Britanin. (B2) Microscopic 3D molecular docking model of CXCR2-Britanin. (B3) 2D molecular docking model of CXCR2-Britanin. (C1) Macroscopic 3D molecular docking model of DPP4-Britanin. (C2) Microscopic 3D molecular docking model of DPP4-Britanin. (C3) 2D molecular docking model of DPP4-Britanin. (D1) Macroscopic 3D molecular docking model of HMOX1-Britanin. (D2) Microscopic 3D molecular docking model of HMOX1-Britanin. (D3) 2D molecular docking model of HMOX1-Britanin. (E1) Macroscopic 3D molecular docking model of MAPK8-Britanin. (E2) Microscopic 3D molecular docking model of MAPK8-Britanin. (E3) 2D molecular docking model of MAPK8-Britanin. (F1) Macroscopic 3D molecular docking model of MAPK14-Britanin. (F2) Microscopic 3D molecular docking model of MAPK14-Britanin. (F3) 2D molecular docking model of MAPK14-Britanin. Britanin Protects against NAFLD in High-Fat Diet-Fed Mice by Attenuating Liver Injury Next, we explored the in vivo effects of Britanin on NAFLD. Compared to the normal control group, mice in the high-fat group showed significant increases in body weight, liver weight, and liver index, indicating successful modeling of NAFLD. Importantly, compared to the high-fat group, the mice in the treatment group (Britanin) exhibited significant reductions in body weight, liver weight, and liver index ([114]Figure [115]6 A–C). Furthermore, liver function indicators were examined, and the results showed that compared to the control group, the levels of serum ALT and AST were significantly increased in the high-fat group ([116]Figure [117]6D,E). However, after Britanin treatment, the levels of AST and ALT were significantly decreased. Histological examination of liver tissue sections stained with HE demonstrated that Britanin treatment effectively alleviated the hepatic steatosis induced by a high-fat diet. These results collectively indicate that Britanin can ameliorate liver injury in mice with high-fat diet-induced NAFLD. Figure 6. [118]Figure 6 [119]Open in a new tab Effects of Britanin on hepatic injury in a high-fat diet-induced NAFLD mouse model. (A) Body weight (n = 8). (B) Liver weight (n = 8). (C) Liver index (n = 8). (D) Serum AST activity (n = 8). (E) Serum ALT activity (n = 8). (F) Liver H&E staining. Typical images were chosen from each experimental group. Data are shown as mean ± SD. *P < 0.05 vs HFD. Britanin Inhibits NAFLD in High-Fat Diet-Fed Mice by Reducing Hyperlipidemia and Hepatic Lipid Accumulation To assess the effect of Britanin on hyperlipidemia in mice with NAFLD, we first examined the levels of TC, TG, HDL-c, and LDL-c in the serum. The results showed that after Britanin treatment, the levels of TC, TG, and LDL-c in the serum were significantly decreased ([120]Figure [121]7 A–D). Conversely, the level of HDL-c was significantly increased, suggesting that Britanin decreased the serum lipid profiles in NAFLD mice. Furthermore, we performed Oil Red O staining on mouse liver tissue ([122]Figure [123]7E) and found that Britanin could alleviate lipid accumulation in the liver. Numerous studies demonstrated that the AMPK/SREBP1c pathway plays a key role in the regulation of hepatic lipid accumulation in NAFLD mice.^[124]24,[125]25 To further investigate the inhibitory effect of Britanin on hepatic lipid accumulation, we examined the phosphorylation levels of AMPK and the expression levels of SREBP1c. The results demonstrated that Britanin inhibited AMPK phosphorylation and reduced SREBP1c expression ([126]Figure [127]7F,G). These findings suggest that Britanin suppresses hepatic lipid accumulation in NAFLD mice through the modulation of AMPK phosphorylation and SREBP1c expression. Figure 7. [128]Figure 7 [129]Open in a new tab Effects of Britanin on lipid accumulation in a high-fat diet-induced NAFLD mouse model. (A) Serum TC levels (n = 8). (B) Serum TG levels (n = 8). (C) Serum LDL-c levels (n = 8). (D) Serum HDL-c levels (n = 8). (E) Liver Oil Red O staining. Typical images were chosen from each experimental group. (F) Hepatic protein expression of p-AMPK and AMPK (n = 8). (G) Hepatic protein expression of SREBP-1c (n = 8). Data are shown as mean ± SD. *P < 0.05 vs HFD. Britanin Suppresses NAFLD in High-Fat Diet-Fed Mice by Alleviating Oxidative Stress and Apoptosis Preliminary network pharmacology results indicate that Britanin is involved in oxidative stress responses. Therefore, we next investigated the effect of Britanin on oxidative stress in a NAFLD mouse model. By measuring relevant oxidative stress markers in the serum, we observed that Britanin mitigated the oxidative stress ([130]Figure [131]8 A,B). The results of network pharmacology showed that Britanin and hemeoxygenase-1 (HO-1) were the most stable. It has been reported that enhanced HO-1 expression is involved in the alleviation of oxidative stress during NAFLD progression.^[132]26,[133]27 Therefore, the WB assay was used to detect the level of HO-1, and it was found that the level of HO-1 protein increased significantly after Britanin treatment ([134]Figure [135]8C). It has been shown that inhibition of apoptosis can alleviate the progression and development of NAFLD. The GO enrichment analysis suggested that Britanin is involved in regulating apoptosis. Further investigation through Western blotting and immunohistochemistry confirmed ([136]Figure [137]8D,E) that Britanin inhibits the levels of Caspase3 and Bax while upregulating the level of Bcl2. These findings collectively suggest that Britanin ameliorates the development of NAFLD by attenuating hepatic oxidative stress and apoptosis. Figure 8. [138]Figure 8 [139]Open in a new tab Effects of Britanin on oxidative stress and apoptosis in a high-fat diet-induced NAFLD mouse model. (A) Serum MDA activity (n = 8). (B) Serum SOD activity (n = 8). (C) Hepatic protein expression of HO-1 (n = 8). (D) Liver immunohistochemistry staining. (E) Hepatic protein expression of Caspase3, Bax, and Bcl2. Data are shown as mean ± SD. *P < 0.05 vs HFD. Discussion Recently, a rising number of interconnected investigations and inquiries have focused on conventional pharmacological methods. Although traditional pharmacological approaches have unveiled the pharmacology and mechanisms of drugs, they face challenges in elucidating the intricate interactions and molecular processes occurring between pharmaceuticals and the human body.^[140]28,[141]29 Leveraging the advancements in systems biology and multidimensional pharmacology, network pharmacology amalgamates biological networks with drug actions. It scrutinizes the correlation between drugs and nodes or network modules within the network, employing a multicomponent and multitarget action approach. The current study demonstrated the effects of Britanin on the treatment of NAFLD and revealed the underlying mechanism by integrating pharmaco-bioinformatics approaches and experimental verification. Our findings showed that Britanin had a high affinity for HO-1, according to network pharmacology and molecular docking assays. Moreover, Britanin significantly alleviated oxidative stress by inhibiting HO-1 expression in NAFLD mice. Besides, we also found that Britanin inhibited the development of NAFLD in high-fat diet-fed mice by attenuating liver damage and hepatic lipid accumulation through decreasing serum ALT and AST levels and suppressing the AMPK/SREBP1c pathway. Additionally, Britanin protected against NAFLD via inhibiting apoptosis by downregulating Caspase3 and the Bax/Bcl2 ratio. NAFLD, a prevalent chronic liver disorder, is intricately linked to dyslipidemia, insulin resistance, obesity, and metabolic syndrome.^[142]30 Although the exact pathogenesis and progression of NAFLD remain elusive, the accumulation of excess lipids in the liver acts as a precursor to steatosis. This, in turn, triggers the generation of lipid peroxidation and engenders lipid-induced toxicity within hepatocytes.^[143]31 Ongoing drug development endeavors predominantly revolve around modulating lipid and glucose metabolism while mitigating oxidative stress damage to the liver.^[144]32 Nevertheless, a universally sanctioned drug for NAFLD treatment has yet to emerge. Although there is currently no specific effective treatment for NAFLD, some traditional Chinese medicine, such as curcumin,^[145]33 Lingguizhugan Decoction,^[146]34 and spleen-strengthening and liver-draining formula,^[147]35 have been in clinical trials. In this study, experimental NAFLD was induced in mice through a high-fat diet. The administration of Britanin was found to attenuate oxidative stress, ameliorate liver injury, and curtail hepatic lipid accumulation in mice subjected to a high-fat diet. These findings unequivocally underscore the potential of Britanin as a promising and novel candidate for NAFLD therapy. Of note, positive drugs are required in animal biological effect experiments. Despite the current constraint on including positive drugs in our experiments, we will conduct positive drug studies to further verify the effect of Britanin on NAFLD in future studies. Grounded in the concept of component synergy, Traditional Chinese medicine employs a therapeutic approach that spans multiple effects, pathways, and targets, closely aligning with the principles of network pharmacology theory and methodology.^[148]36 Recently, the exploration of Traditional Chinese medicine has significantly embraced network pharmacology to anticipate biologically active constituents and elucidate intricate molecular targets.^[149]37,[150]38 Also, Britanin plays a protective role in liver diseases. For example, Britanin induces apoptosis of hepatocellular carcinoma cells via downregulating the antiapoptotic protein Bcl-2 expression, upregulating the pro-apoptotic protein Bax expression, and suppressing the activation of NF-κB.^[151]39 Consequently, our study harnessed network pharmacology to forecast potential molecular targets and dissect the conceivable mechanism through which Britanin mitigates NAFLD. The network pharmacology and molecular docking results identified HO-1 as the most key target for Britanin against NAFLD. Decreased hepatic HO-1 expression was reported to improve oxidative stress in the liver and ameliorate the development of NAFLD.^[152]40,[153]41 Importantly, our findings showed that Britanin inhibited oxidative stress by downregulating the level of HO-1 expression. Moreover, the AMPK/SREBP1c pathway that is correlated with lipid metabolism was shown to participate in the Britanin-provided alleviation on NAFLD. In addition, our studies also showed that Britanin decreased Caspase3 expression and the Bax/Bcl2 ratio, thereby inhibiting apoptosis. Taken together, these studies suggest that Britanin has great therapeutic potential and benefits for NAFLD. Conclusions In conclusion, our investigation employed a multifaceted approach encompassing molecular docking, experimental validation, and pharmaco-bioinformatics techniques to corroborate the targets of Britanin and elucidate its potential mechanisms in effectively suppressing NAFLD. Our findings demonstrate that Britanin exerts its influence on NAFLD by mitigating liver injury, curbing hyperlipidemia and hepatic lipid accumulation, and alleviating oxidative stress and apoptosis. This comprehensive methodology underpins the current study, presenting a promising alternative therapeutic avenue characterized by low toxicity. This approach holds the potential for stand-alone use or synergistic integration with other medications for the treatment of NAFLD. Acknowledgments