Analysis of the biological mechanism of Gurigumu-13 in the treatment of non-alcoholic fatty liver disease based on network pharmacology
Jie Zhang, Ying Wei, Xuan Li, Liya Su, Haifeng Zhang
TL;DR
This study explores how a traditional Mongolian medicine called Gurigumu-13 treats non-alcoholic fatty liver disease by identifying its active compounds and biological mechanisms.
Contribution
The paper introduces a network pharmacology-based approach to uncover the therapeutic mechanisms of Gurigumu-13 in non-alcoholic fatty liver disease.
Findings
GR reduces liver fat accumulation and oxidative stress in NAFLD rat models and HepG2 cells.
GR modulates key signaling pathways like PI3K/AKT/mTOR and STAT3 to improve lipid metabolism and insulin resistance.
Active compounds ellagic acid and terchebin are likely responsible for GR's therapeutic effects.
Abstract
Gurigumu-13 (GR) was a classical Mongolian medicinal compound widely used in clinical practice for the treatment of non-alcoholic fatty liver disease (NAFLD). This study aimed to investigate the underlying mechanism by which GR exerted its therapeutic effects against NAFLD. The main active components of GR were identified using high-resolution mass spectrometry. Using network pharmacology approaches, key targets and potential pathways of GR against NAFLD were predicted and preliminarily validated through molecular docking. Furthermore, transcriptomic sequencing analysis, combined with in vivo and in vitro experiments was performed to elucidate the efficacy and mechanism of GR in alleviating NAFLD. In vivo, a rat model of NAFLD was established by feeding Wistar rats a methionine-choline deficient (MCD) diet. Serum levels of AST, ALT, TC, TG, MDA, GSH, SOD, HDL-C, and LDL-C were…
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Figure 8- —Inner Mongolia Medical University Science and Technology Million Project
- —https://doi.org/10.13039/501100004763Natural Science Foundation of Inner Mongolia Autonomous Region
- —General project of universities directly under Inner Mongolia Autonomous Region
- —Key Laboratory Open Fund Project of Affiliated Hospital of Inner Mongolia Medical University
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Taxonomy
TopicsLiver Disease Diagnosis and Treatment · Pharmacological Effects of Natural Compounds · Alcohol Consumption and Health Effects
Introduction
Non-alcoholic fatty liver disease (NAFLD) is a clinicopathological syndrome characterized primarily by excessive lipid accumulation in hepatocytes, which represents a condition of considerable public health importance [1, 2]. Although independent of alcohol consumption, NAFLD has emerged as a global health challenge, affecting approximately 25% of the adult population worldwide [3]. In China, epidemiological data from 2008 to 2018 revealed a particularly severe situation, with NAFLD prevalence reaching 29.2% and accounting for nearly half of all chronic liver disease cases [4]. While a substantial proportion of patients follow a non-progressive disease course, a significant subset experiences progressive liver injury, inflammation, and fibrosis, which may ultimately advance to cirrhosis or even hepatocellular carcinoma. Current clinical management strategies for NAFLD focus predominantly on lifestyle interventions—including dietary modification, physical exercise, and weight loss—supplemented by adjunctive pharmacotherapy such as hepatoprotective, lipid-lowering, antioxidant, anti-inflammatory agents, and vitamin E [5]. However, existing drugs are often associated with varying degrees of adverse effects, which limit their long-term applicability and therapeutic efficacy. Consequently, the exploration of safer and more effective treatment approaches represents an urgent and unmet clinical need.
Mongolian medicine has demonstrated distinct value in the prevention and treatment of NAFLD. Numerous clinical and experimental studies indicate that Mongolian medicinal therapies offer advantages such as proven efficacy, minimal adverse effects, relatively low cost, and ease of implementation [6]. Their mechanisms of action involve harmonizing systemic balance, protecting hepatocyte function, promoting digestion and absorption, and regulating hepatic metabolism, while also safely modulating patients’ overall constitution [7]. Gurigumu-13 (GR), also known as Honghua Qinggan Thirteen Ingredients Pills, is a classical Mongolian medicinal compound included in the Drug Standards of the Ministry of Health of the People’s Republic of China (Mongolian Medicine Volume) and is commonly used in the treatment of liver diseases including NAFLD [8]. This formulation consists of thirteen medicinal components—Crocus sativus L., Ophiopogon japonicus (Thunb.) Ker Gawl., Syringa oblata Lindl., Nelumbo nucifera Gaertn., Dolomiaea costus (Falc.) Kasana & A.K.Pandey, Terminalia chebula Retz., Melia azedarach L., Gardenia jasminoides J.Ellis, Pterocarpus indicus Willd., Rengong Shuiniujiao, Rengong Niuhuang, Yinzhu, and Rengong Shexiang—combined in specific proportions. Modern research confirms that several of these components, such as Crocus sativus L., Ophiopogon japonicus, Syringa oblata Lindl., and Terminalia chebula Retz., possess therapeutic potential for liver diseases including NAFLD [9–12]. Clinically, GR is used to clear liver toxins, reduce blood viscosity, and moisten the intestines. It can effectively improve liver function indicators, alleviate NAFLD-related symptoms, and exhibits a favorable safety profile, representing a beneficial adjunct to existing treatment regimens [13]. However, current research on GR remains largely based on clinical experience summaries, and a systematic, in-depth experimental elucidation of its precise molecular mechanisms of action is still lacking.
Based on this, we hypothesize that GR exerts hepatoprotective effects against NAFLD through modulation of the PI3K/AKT/mTOR pathway and attenuation of oxidative stress. To verify this hypothesis, this study will adopt modern pharmacological research strategies by constructing an in vivo model of NAFLD in Wistar rats induced by methionine-choline deficiency (MCD) feed, as well as an in vitro model of steatosis in HepG2 cells induced by a mixture of oleic acid (OA) and palmitic acid (PA) [14–17]. This study aims to systematically evaluate the impact of GR on the NAFLD model and deeply explore its mechanism of improving lipid deposition in vivo and in vitro. The technical route of this study is shown in Fig. 1.
Fig. 1. Workflow for discovery of the potential mechanisms of GR against NAFLD
Materials and methods
Drugs
Gurigumu-13 (GR, Inner Mongolia Mongolian Medicine Co., Ltd., China; product number: Z15020395) was ground into powder and set aside for use. Accurately weighed 0.38 g of the powder, was dissolved it in 20mL of deionized water, thoroughly mixed, and then filtered through a 0.22 μm filter membrane. The resulting solution was aliquot and stored at 4 °C for future use. The positive control drug, polyene phosphatidylcholine Capsules, was purchased from Sanofi (Beijing) Pharmaceutical Co., Ltd. (China, Product number: H20059010).
High performance liquid chromatography-mass spectrometry
After filtering the above-mentioned GR solution through a 0.22 μm nylon filter membrane (ThermoFisher Scientific, USA), the liquid chromatography-mass spectrometry (LC-MS) system composed of ACQUITY UPLC^®^ HSS T3 chromatographic column and Q-TOF synapt G2 si MS mass spectrometer (Waters) was adopted for analysis. The specific methodology was adapted from reference [18].
Network pharmacology analysis
Potential active components of GR were screened from the TCMSP, SYMMAP, and TCMID databases using the criteria of oral bioavailability ≥ 30% and drug-likeness ≥ 0.18. The molecular structures of the selected components were downloaded from the PubChem database. Putative targets of these components were predicted using the Swiss Target Prediction database and the Pharm Mapper platform. All retrieved targets were standardized and duplicates were removed using the UniProt database. Meanwhile, disease targets related to non‑alcoholic fatty liver disease (NAFLD) were collected by searching the GeneCards and OMIM databases using the keywords “non‑alcoholic fatty liver disease” and “NAFLD.” A Venny diagram was generated using the Venny 2.1 online tool to identify the intersection between GR active‑component targets and NAFLD‑related targets.
The intersection targets were imported into the STRING database to construct a protein–protein interaction (PPI) network, which was then visualized and topologically analyzed using Cytoscape software. Core targets were screened according to node degree centrality values. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for the intersection targets were performed with the R package clusterProfiler. Using the above results, an integrated “drug–component–target–pathway–disease” network was built. Integrating the KEGG enrichment analysis and PPI network findings, key targets were selected for molecular docking validation. The three‑dimensional structures of these target proteins were obtained from the RCSB PDB database. Molecular docking simulations with the major active components of GR were performed using AutoDockTools software to evaluate binding affinity.
In vivo experiments
Modeling and grouping
All animal procedures were approved by the Medical Ethics Committee of Inner Mongolia Medical University (Ethics approval No. YKD202102054) and were conducted in accordance with both the ARRIVE 2.0 guidelines and the EU Directive 2010/63/EU. Forty healthy male Wistar rats (initial body weight 180–200 g) were randomly divided into five groups: control, model, high‑dose GR, medium‑dose GR, and low‑dose GR. After one week of acclimatization, the model and treatment groups were fed a MCD diet to induce NAFLD, whereas the control group continued to receive standard chow. GR doses for each treatment group were calculated by converting the human equivalent dose based on body surface area. Beginning in the fifth week, the respective GR solutions were administered daily by oral gavage to the treatment groups; the control and model groups received an equal volume of phosphate‑buffered saline (PBS) for 8 weeks. Throughout the experiment, general condition, body weight, and food intake were monitored and recorded regularly. It should be noted that the MCD diet model does not fully recapitulate key metabolic features of human NAFLD, as it primarily induces steatosis without consistently developing the accompanying insulin resistance or systemic metabolic dysfunction. Furthermore, a positive control group was not included due to limitations of the selected positive control drug.
Sample collection and indicator detection
Following the 8‑week experimental period, rats were fasted for 12 h and anesthetized by intraperitoneal injection of sodium pentobarbital. Blood was collected by cardiac puncture and allowed to stand at room temperature before centrifugation to separate serum. Serum levels of alanine aminotransferase (ALT, catalog number: C009-3-1), aspartate aminotransferase (AST, C010-2-1), total cholesterol (TC, A111-1-1), triglycerides (TG, A110-1-1), high‑density lipoprotein cholesterol (HDL‑C, A112-1-1), low‑density lipoprotein cholesterol (LDL‑C, A113-1-1), and reduced glutathione (GSH, A005-1-2) were determined using commercially available assay kits (Nanjing Jiancheng Bioengineering Institute, China). Livers were promptly excised, weighed, and the liver index (liver weight / body weight × 100%) was calculated. Portions of liver tissue were divided into aliquots and stored at − 80 °C for subsequent measurement of superoxide dismutase (SOD) activity (Beijing Solarbio Science & Technology Co., Ltd., China; catalog number: BC5165) and malondialdehyde (MDA) content (catalog number: BC6410).
Histopathological analysis
After the experiment, the body weight and liver wet weight of all rats were measured, and the liver index was calculated. Liver tissue samples were fixed in 4% paraformaldehyde (Wuhan Servicebio Technology Co., Ltd, China; catalog number, G1101) for 24 h, dehydrated through a graded ethanol series, embedded in paraffin, and sectioned. Sections were dewaxed, rehydrated, and stained with hematoxylin and eosin (H&E) (Gibco Life Technologies, USA, catalog number: 7231). Morphological structure and lipid droplet deposition in liver tissue were examined under an optical microscope, and representative images were acquired for analysis.
In vitro experiment
Cell culture and treatment
HepG2 cells were kindly provided by the Clinical Medical Research Center of Inner Mongolia Medical University (Zhejiang Meisen Cell Technology Co., Ltd., China; catalogue number: SCC249; species: Homo sapiens; CVCL accession: CVCL_L855). Cells were maintained in complete DMEM medium (Gibco Life Technologies, USA; catalog number: 11965092) supplemented with 10% fetal bovine serum (Gibco Life Technologies, USA; catalog number: A5670701) and 1% penicillin‑streptomycin (Beijing Solarbio Science & Technology Co., Ltd., China; catalog number: P1400) at 37 °C in a humidified 5% CO₂ incubator. Prior to experiments, cells were serum‑starved for 12 h. A cellular steatosis model was established by treating HepG2 cells with a mixture of 0.245 mM oleic acid (OA; Sigma-Aldrich, USA; catalog number: 112-80-1) and 0.1225 mM palmitic acid (PA; Sigma-Aldrich, USA; catalog number: 57-10-3) for 24 hours. During the induction period, cells were simultaneously treated with different concentrations of GR.
Cell viability assay
HepG2 cells were seeded into 96‑well plates (Corning Incorporated, USA; catalog number: 3635) at a density of 5 × 10³ cells per well. After 24 h of culture, the medium was replaced with fresh medium containing varying concentrations of GR (0, 0.594, 1.19, 2.38, 4.75, 9.50, 19.0 mg/mL) together with the fatty acid mixture, and cells were incubated for an additional 24 h. Cell viability was dynamically monitored and quantified using the IncuCyte Live‑Cell Analysis System (Essen Bio-Science, USA).
Determination of intracellular lipid content
Intracellular lipid droplet morphology and distribution were visualized by Oil Red O (Beijing Solarbio Science & Technology Co., Ltd., China; catalog number: G1262) staining. In parallel, the intracellular triglyceride (TG) content was quantitatively measured in cell lysates using a commercial triglyceride assay kit (Nanjing Jiancheng Bioengineering Institute, China; catalog number: A110-1-1).
Quantitative real-time polymerase chain reaction (qRT-PCR) analysis
Total RNA was extracted from cells using TRIzol reagent, and cDNA was synthesized with a commercial reverse transcription kit (Sangon Biotech Co., Ltd., Shanghai, China; catalog number: 3300). Amplification reactions were performed using SYBR Green Premix on a QuantStudio™ real-time fluorescence quantitative PCR system (Thermo Fisher, USA). β‑actin was used as the internal reference gene, and the relative mRNA expression levels of target genes were calculated with the 2^(−ΔΔCt) method. Primer sequences used in this study are listed in Table S1.
Western blot analysis
Total cellular proteins were extracted with RIPA lysis buffer containing protease and phosphatase inhibitors. Protein concentrations were determined using the bicinchoninic acid (BCA) assay. A prestained protein molecular weight marker (Lanjie Ke Technology Co., Ltd., China; catalog number: BL741A) was used. Equal amounts of protein samples were separated by SDS‑PAGE and transferred onto polyvinylidene difluoride (PVDF) membranes (Bio-Rad Laboratories, Inc, USA; catalog number: 1620177). Membranes were blocked in 5% (w/v) non-fat milk at room temperature for 1 h, followed by incubation with corresponding primary antibodies overnight at 4 °C. After washing, membranes were incubated with horseradish peroxidase‑conjugated secondary antibodies (1:5000) for 1 h at room temperature. Protein bands were visualized using a chemiluminescence imaging system (ChemiDoc MP, Bio-Rad, USA), and band intensities were quantified with ImageJ software (National Institutes of Health, USA). β-actin served as the loading control for calculating relative target protein expression levels. Antibody information is provided in Table S2.
Statistical analysis
All data were presented as mean ± standard deviation and were analyzed using GraphPad Prism 8.0 software. The homogeneity of variances was verified using the Brown-Forsythe test. Data were analyzed using one-way ANOVA followed by Tukey’s post hoc test (for normally distributed data) or Kruskal–Wallis test for nonparametric data. Data are derived from at least three independent experiments. Statistical significance was set at P < 0.05.
Results
Identification of the major chemical composition of GR
The chemical constituents of GR were analyzed by liquid chromatography–mass spectrometry (Fig. 2). A total of 151 major bioactive compounds were identified, ranked by response value (see Table S3 for details). Among these, ellagic acid, terchebin, berberine, baicalin, and others were characterized as the primary components of GR.
Fig. 2. Liquid chromatography-mass spectrometry (LC-MS) metabolic fingerprinting total ion chromatogram (TIC) of GR. A Positive ions. B Negative ions
Network pharmacology analysis: protein interaction, GO, and KEGG enrichment of target genes
By integrating data from multiple databases, including TCMSP, SYMMAP, PubChem, and PharmMapper, a total of 406 potential active ingredients and 1,012 related targets of GR were screened (Table 1). A “component–target” network was constructed and visualized using Cytoscape software, consisting of 238 nodes (11 compounds and 30 genes) and 237 interaction edges (Fig. 3A). Additionally, 2,376 and 528 NAFLD-related targets were retrieved from the GeneCards and OMIM databases, respectively. After removing duplicates, 1,927 unique targets were obtained. A Venn diagram then revealed 329 overlapping targets between GR and NAFLD (Fig. 3B), suggesting that these common targets may mediate the therapeutic effects of GR on NAFLD.
Table 1. The active ingredient in GRGR componentsActive compoundsPotential gene targetsChuanlizi4230Clove128295Hezi27122Safflower125337Lianzi320Maidong1263Muxiang99152Niuhuang14140Musk7457Buffalo horn429Gardenia64315
Fig. 3. Network pharmacology to predict the mechanism of action of GR on NAFLD. A Potential targets of GR in the treatment of NAFLD. The color of the target ranges from dark to light according to its importance in the prescription. B Venn analysis of GR targets and NAFLD targets. C GO enrichment analysis. D KEGG enrichment analysis. E PPI network of GR-NAFLD interactions
The 329 common targets were imported into the STRING database to construct a protein–protein interaction (PPI) network. The resulting network comprised 327 nodes and 1,062 edges (Fig. 3E). The PPI network enrichment analysis yielded a P‑value of less than 1.0 × 10⁻¹⁶, indicating statistically significant interactions among the nodes and supporting the reliability of the predicted targets. Using the CytoHubba plugin in Cytoscape, topological analysis using node degree as the criterion identified the following core targets: TNF, STAT3, AKT, IL6, VEGFA, PTGS2, IL1B, MMP9, CASP3, INS, JUN, and IL10 (Fig. 3E).
Subsequently, Gene Ontology (GO) and KEGG pathway enrichment analyses were performed on the common targets. GO analysis yielded 2,936 terms, including 2,542 biological processes (BP), 126 cellular components (CC), and 268 molecular functions (MF). The top 10 entries from each category are displayed in Fig. 3C. Biological processes were primarily enriched in oxidative stress response, reactive oxygen species response, and response to oxygen levels. Cellular components were mainly associated with vesicle lumen, membrane microdomains, and endoplasmic reticulum lumen. Molecular functions were related to nuclear receptor activity, RNA polymerase ii specific DNA binding transcription factor binding, and cytokine receptor binding, among others. KEGG pathway enrichment analysis identified 188 pathways, with the top 10 listed in Table S4. The top 39 pathways, ranked by P‑value, were selected for visualization in a bubble chart (Fig. 3D). These significantly enriched pathways were primarily associated with lipid metabolism and atherosclerosis, inflammation‑related pathways (e.g., the TNF signaling pathway), glucose metabolism processes (e.g., insulin resistance), and stress response pathways (e.g., the FoxO signaling pathway). Based on the integration of the above findings, a comprehensive “drug–disease–pathway–target” network was constructed (Figure S1). This network suggests that pathways related to lipids and atherosclerosis, the PI3K/AKT signaling pathway, and the insulin resistance pathway may play key roles in the treatment of NAFLD with GR.
Molecular docking verification
Based on mass spectrometry analysis and network pharmacology results, and in accordance with the traditional Chinese medicine principle of “sovereign, minister, assistant, and envoy,” the main active components from safflower, Ophiopogon japonicus, and artificial bezoar were selected as ligands. Meanwhile, through the combination of KEGG pathway enrichment analysis (P < 0.001) and node degree‑based screening, eight core target proteins were identified: PIK3R1, AKT, GSK3B, mTOR, STAT3, AMPK, PGC‑1α, and PPAR‑α. Molecular docking simulations were performed using AutoDock Vina. The binding energy analysis suggested that the active components could bind stably to the target proteins (binding energy data are provided in Table S5). The eight complexes with the lowest binding energies were selected for visualization (Fig. 4), which further confirmed the favorable binding potential between the active ingredients of GR and the key target proteins.
Fig. 4. Molecular docking results of GR and key target proteins. A Heat map of binding energy activity. B molecular docking model of Terchebin and GSK-3β; C molecular docking model of Terchebin and mTOR; D molecular docking model of Terchebin and STAT3; E molecular docking model of Terchebin and AKT. F molecular docking model of Terchebin and PPAR-α; G molecular docking model of Terchebin and AMPK; H molecular docking model of Bilobalide and STAT3; I molecular docking model of Terchebin and PI3K
GR ameliorates lipid metabolism disorders in MCD diet-induced NAFLD rats
Feeding with the MCD diet significantly increased the liver index and induced characteristic pathological changes in rats. After 8 weeks, the body weight of rats in the model group increased from 189.6 ± 1.7 g to 330.7 ± 10.1 g, whereas in the control group it increased only to 267.7 ± 2.1 g. The weight gain in the model group was approximately 1.82 times that of the control group (n = 8, P < 0.05; Fig. 5A, B). Treatment with high- and medium-dose GR significantly attenuated this weight increase (high-dose group: 288.3 ± 8.5 g; medium-dose group: 281.3 ± 3.2 g). The liver index was also significantly elevated in the model group (6.68% ± 0.09%) compared with the control group (4.36% ± 0.15%), and both high- and medium-dose GR treatment significantly reduced it (high-dose group: 5.76% ± 0.29%; medium-dose group: 5.57% ± 0.27%; n = 8, P < 0.05; Fig. 5C). H&E staining of liver tissues (Fig. 5D) revealed clear lobular architecture and normal cellular morphology in the control group. In contrast, the model group exhibited marked hepatic steatosis characterized by macrovesicular fat vacuoles (indicated by arrows) and cellular swelling. Following intervention with high and medium doses of GR, the extent of hepatic steatosis and vacuolization was substantially reduced. Quantitative assessment using the NAFLD Activity Score (NAS) confirmed these observations, with the model group scoring 7.33 ± 0.57, while the scores in the high- and medium-dose GR groups decreased to 1.67 ± 0.58 and 2.00 ± 0.56, respectively (n = 8, P < 0.05; Fig. 5G).
Fig. 5. Effect of GR on obesity and hepatic steatosis in NAFLD rats. A Weight change in rats within 8 weeks. B Initial and final body weight of rats. C Liver index. D HE staining of liver. E Serum lipid TC and TG. F LDL-C and HDL-C. G NAFLD Activity Score. H ALT and AST. I GSH and SOD. J MDA. ^^P < 0.05, ^^P < 0.01, ^^P < 0.001 and ^****^P < 0.0001
Serum biochemical analysis (Fig. 5E, F) demonstrated that rats fed the MCD diet exhibited marked dyslipidemia and liver injury compared with controls. Specifically, serum levels of TC, TG and LDL‑C were elevated approximately 1.9‑fold (2.43 ± 0.06 vs. 1.28 ± 0.13 mmol/L), 2.4‑fold (1.22 ± 0.12 vs. 0.51 ± 0.02 mmol/L), and 3.6‑fold (1.15 ± 0.08 vs. 0.32 ± 0.04 mmol/L), respectively (n = 8, P < 0.05). Liver injury markers ALT and AST also rose significantly by about 2.5‑fold (24.51 ± 0.99 vs. 9.81 ± 0.23 U/L) and 1.73‑fold (97.36 ± 0.73 vs. 56.24 ± 0.40 U/L), while HDL‑C was reduced by approximately 43.4% (0.85 ± 0.05 vs. 1.33 ± 0.12 mmol/L) (n = 8, P < 0.05 for all comparisons). Treatment with high‑ and medium‑dose GR significantly reversed these alterations. Both doses significantly lowered TC, TG, LDL‑C, ALT and AST levels (TC: 2.25 ± 0.05 and 2.20 ± 0.01 mmol/L; TG: 1.01 ± 0.07 and 0.98 ± 0.02 mmol/L; LDL‑C: 0.97 ± 0.07 and 0.90 ± 0.01 mmol/L; ALT: 21.80 ± 1.19 and 16.30 ± 2.08 U/L; AST: 83.91 ± 0.28 and 68.02 ± 0.06 U/L; n = 8, all P < 0.05 vs. model) while elevating HDL‑C (1.21 ± 0.07 and 1.26 ± 0.06 mmol/L; n = 8, P < 0.05). These data indicate that GR ameliorates MCD diet-induced dyslipidemia and hepatic injury. GR intervention also enhanced antioxidant capacity. Hepatic SOD activity (117.2 ± 9.6 and 125.9 ± 4.2 vs. 77.6 ± 0.66 U/g prot in the model) and serum GSH levels (332.6 ± 15.1 and 330.5 ± 29.7 vs. 249.7 ± 1.37 µg/mL in the model) were significantly increased compared with the model group (n = 8, P < 0.05). Concurrently, the hepatic lipid peroxidation product MDA was reduced (2.16 ± 0.07 and 1.99 ± 0.02 vs. 2.67 ± 0.08 mmol/g prot in the model; n = 8, P < 0.05) (Fig. 5H, I). Collectively, these findings indicate that GR attenuates oxidative stress and lipid peroxidation in vivo.
GR alleviates lipid accumulation and oxidative stress in steatotic HepG2 cells
Based on cell viability assays (Figure S2), GR was used at concentrations of GR were determined as 0.594 mg/mL (L), 1.19 mg/mL (M), and 2.38 mg/mL (H). In the OA/PA-induced HepG2 cell model of steatosis, intracellular TG levels were significantly elevated by approximately 5.1‑fold compared to the control group (model: 0.56 ± 0.05 mmol/g vs. control: 0.11 ± 0.04 mmol/g; n = 3, P < 0.05). GR intervention dose‑dependently reduced TG accumulation (H: 0.17 ± 0.03 mmol/g; M: 0.19 ± 0.01 mmol/g; L: 0.22 ± 0.01 mmol/g; n = 3, P < 0.05; Fig. 6A). Oil Red O staining revealed extensive cytoplasmic lipid droplet accumulation in the model group, which was markedly attenuated by GR treatment (Fig. 6B). GR also enhanced glucose uptake in steatotic cells, as evidenced by reduced glucose concentration in the culture medium (model: 11.6 ± 1.1 mmol/L vs. control: 6.2 ± 0.16 mmol/L; H: 8.7 ± 0.37 mmol/L; M: 9.5 ± 0.17 mmol/L; L: 6.3 ± 0.29 mmol/L; n = 3, P < 0.05; Fig. 6C).
Fig. 6. Effects of GR on lipid accumulation and oxidative stress in adipose HepG2 cells. A TG levels. B Oil red O staining. C Glucose content in culture medium of HepG2 cells. D SOD activity. E MDA content. F ROS content in HepG2 cells treated with GR. P < 0.05, ^^P < 0.01, ^^P < 0.001 and ^****^P < 0.0001
GR also mitigated oxidative stress. Compared to the control, SOD activity was decreased in the model group (model: 1.57 ± 0.02 U/g prot vs. control: 2.37 ± 0.06 U/g prot; n = 3, P < 0.05), whereas levels of MDA and reactive oxygen species (ROS) were significantly increased (MDA: model 0.30 ± 0.03 mmol/g prot vs. control 0.18 ± 0.01 mmol/g prot; ROS: model 0.72 ± 0.01 vs. control 0.23 ± 0.04; n = 3, P < 0.05). GR intervention elevated SOD activity (H: 2.04 ± 0.03 U/g prot; M: 1.73 ± 0.01 U/g prot; L: 1.53 ± 0.01 U/g prot; n = 3, P < 0.05; Fig. 6D) and reduced both MDA (H: 0.20 ± 0.01 mmol/g prot; M: 0.22 ± 0.02 mmol/g prot; L: 0.23 ± 0.01 mmol/g prot; n = 3, P < 0.05; Fig. 6E) and ROS levels (H: 0.42 ± 0.02; n = 3, P < 0.05; Fig. 6F). These results demonstrate that GR mitigates lipid accumulation and alleviates oxidative stress in HepG2 cells.
GR increases PI3K and AKT phosphorylation to ameliorate hepatic steatosis in HepG2 cells
Transcriptomic sequencing was performed on control, model (OA/PA-induced), and GR-treated HepG2 cells. Principal component analysis demonstrated clear separation between groups with good intra-group sample aggregation (Fig. 7A). The Pearson correlation coefficient (r) between biological replicates exceeded 0.92 in all cases (Fig. 7B), indicating high reproducibility. Cluster analysis of differentially expressed genes revealed that GR treatment substantially altered the cellular transcriptional profile (Fig. 7C). GO enrichment analysis suggested that GR may function through modulating biological processes related to lipid metabolism, triglyceride catabolism, and adipocyte differentiation (Fig. 7D). KEGG pathway analysis further identified the PI3K/AKT signaling pathway and the insulin resistance pathway as key candidates mediating the effects of GR (Fig. 7E), consistent with prior network pharmacology predictions.
Fig. 7. Effect of GR on fatty HepG2 cells was analyzed by transcriptome sequencing. A PCA analysis. B Correlation analysis. C Differential gene cluster analysis heat map. D GO enrichment analysis. E KEGG enrichment analysis
To validate these findings, qPCR and Western blot analyses were conducted on key targets. qPCR results confirmed that GR intervention significantly regulated the expression of multiple lipid metabolism-associated genes (Fig. 8A, P < 0.05). Examination of key nodes in the PI3K/AKT/mTOR and STAT3 pathways showed that in steatotic HepG2 cells, levels of phosphorylated PI3K and AKT proteins as well as the p-AKT/AKT ratio were decreased, while mTOR and STAT3 protein levels were elevated (P < 0.05; Fig. 8J). GR treatment reversed these alterations, significantly increasing p-PI3K and p-AKT protein levels and the p-AKT/AKT ratio, while downregulating mTOR and STAT3 expression (Fig. 8K–T, P < 0.05). qPCR results further corroborated these protein-level trends (Fig. 8B–I, P < 0.05). In summary, GR treatment promoted the phosphorylation of PI3K and AKT while inhibiting STAT3 activity, thereby restoring lipid and energy homeostasis.
Fig. 8. Effect of GR on expression of key targets in HepG2 cells. A Transcriptomic analysis of the mRNA expression profiles of differentially expressed genes. B-I The mRNA expression profiles of GSK-3β, PPAR-α, PGC-1α, AMPK, STAT3, PI3K, AKT and mTOR. J-T p-mTOR, mTOR, p-PI3K, PI3K, p-AKT, AKT and STAT3 protein expression in HepG2 cells. ^^P < 0.05, ^^P < 0.01, ^^P < 0.001 and ^****^P < 0.0001
Discussion
In this study, we employed network pharmacology as the core strategy to systematically investigate the potential material basis and mechanism of action of the Mongolian medicine compound GR in the treatment of NAFLD. Network pharmacology, which analyzes relationships by constructing drug–target–disease networks, aligns with the holistic perspective of traditional medicine [19, 20]. We preliminarily validated the effects of active components in GR such as ellagic acid and terchebin on NAFLD, and further verified their binding potential to core targets through molecular docking simulations. Unlike silymarin, which directly protects hepatocytes, the active ingredients of GR resemble those of berberine and similar agents that exert indirect hepatoprotective effects via metabolic regulation. This multi-component, multi-target synergy suggests that GR could alleviate liver injury while modulating glucose and lipid metabolism and reducing hepatic lipid accumulation, highlighting its potential as a hepatoprotective agent.
By constructing a protein–protein interaction network, we identified core targets including AKT and STAT3, which closely interact with proteins such as PI3K and mTOR. GO and KEGG enrichment analyses suggest that GR may regulate oxidative stress and inflammatory responses, and inhibit lipid accumulation, by activating the PI3K/AKT signaling pathway. In animal experiments, MCD diet effectively induced marked hepatic steatosis in Wistar rats, with histological features consistent with simple steatosis (NAFL) [21–24]. Serum levels of TC, TG, ALT, and AST were significantly elevated in model rats, alongside decreased hepatic antioxidant capacity (SOD, GSH) and increased lipid peroxidation products (MDA). These changes indicate the presence of lipid metabolic disorder, liver injury, and oxidative stress. Intervention with GR effectively reversed these pathological and biochemical abnormalities and significantly alleviated hepatic steatosis, suggesting a mitigating effect on MCD diet-induced liver injury and oxidative stress.
To further elucidate the underlying mechanisms, we established a steatosis model in HepG2 cells using oleic acid (OA) and palmitic acid (PA). Cellular experiments confirmed that GR significantly reduced intracellular lipid and triglyceride accumulation, improved glucose uptake, and enhanced antioxidant defenses, as evidenced by increased SOD activity and decreased levels of MDA and ROS. At the molecular level, the PI3K/AKT signaling pathway, a key regulator of cellular metabolism, proliferation, and survival [25–30], was found to be suppressed in lipid‑loaded HepG2 cells, as indicated by reduced phosphorylation of PI3K and AKT as well as downregulated expression of downstream mTOR. Treatment with GR reversed these changes, markedly elevating the levels of p-PI3K and p-AKT, increasing the p-AKT/AKT ratio, and upregulating mTOR expression. Furthermore, expression of STAT3 protein was notably increased in model cells, and GR effectively inhibited its upregulation. Considering the strong correlation between STAT3 and key nodes of the PI3K/AKT/mTOR pathway predicted by network pharmacology, we speculate that GR may exert synergistic regulation of lipid metabolism and attenuation of oxidative stress through concurrent modulation of the PI3K/AKT/mTOR and STAT3 signaling axes.
However, this study has several limitations. First, although the MCD diet-induced rat model effectively elicits hepatic steatosis, it does not fully recapitulate the insulin resistance and systemic metabolic dysregulation characteristic of human NAFLD. GR treatment promoted the phosphorylation of PI3K and AKT while inhibiting STAT3 activity, thereby restoring lipid and energy homeostasis. Second, although multiple concentrations were tested in vitro, further dose–response analyses and functional validation using pathway‑specific inhibitors (e.g., PI3K/AKT blockers) are needed to more precisely delineate GR’s mode of action. Finally, while evidence from whole‑animal to cellular‑molecular levels supports the efficacy of GR, systematic pharmacokinetic studies and long‑term safety assessments are still lacking. The clinical translational potential of GR therefore remains at an exploratory stage and warrants more in-depth investigation in the future.
Conclusion
In conclusion, this study demonstrates that the Mongolian medicine compound GR elicits a protective effect against NAFLD, likely through active components including ellagic acid and terchebin, by modulating the PI3K/AKT/mTOR and STAT3 signaling pathways. Specifically, GR enhances the phosphorylation of PI3K and AKT while suppressing STAT3 overexpression, thereby improving hepatocellular lipid metabolism and mitigating oxidative stress. These findings provide experimental support for the potential clinical application of GR and reveal its multi-target mechanism of action, underscoring the compound’s promise as a candidate hepatoprotective agent. Notwithstanding these promising findings, the precise mechanistic details and translational potential of GR require further verification through comprehensive pharmacological and clinical studies.
Supplementary Information
Supplementary Material 1.
Supplementary Material 2.
Supplementary Material 3.