Exploration of the mechanism of Danggui Buxue decoction (当归补血汤) for the treatment of gastric ulcer based on network pharmacology, molecular docking, and in vivo experiment

Abstract

OBJECTIVE:

To explore the mechanism of Danggui Buxue decoction (当归补血汤, DBD) for the treatment of gastric ulcer (GU), based on network pharmacology and in vivo experiments.

METHODS:

A network pharmacology strategy was used to predict the main components, candidate targets, and potential signaling pathways. Then, molecular docking was performed to further investigate the interactions and binding affinities between the main components and primary targets. Finally, a mouse model of ethanol-induced gastric ulcers was established to confirm the efficacy and potential therapeutic benefits of DBD, and candidate targets were finally identified.

RESULTS:

A total of 22 active components and 220 target genes were found to be associated with DBD. In addition, 343 GU-related target genes and 57 target genes specific to DBD treatment of GU were identified. The Gene Ontology functional enrichment analysis revealed 510 entries for biological processes, 36 entries for cell composition, and 69 entries for molecular functions. In the pathway enrichment analysis, 143 signaling pathways were identified. Additionally, the molecular docking results revealed that the main active components of DBD exhibited a strong binding capacity with key proteins, including tumor necrosis factor, AKT serine/threonine kinase 1, interleukin-6, vascular endothelial growth factor, and interleukin-1 Beta. Among these, quercetin, kaempferol, formononetin, isorhamnetin, and beta-sitosterol displayed the strongest binding affinities for these key proteins. in vivo experiments showed that DBD pretreatment effectively protected gastric mucosa, and the benefits might be attributed to the downregulation of above key proteins.

CONCLUSIONS:

Based on network pharmacology analysis and in vivo experiments, we conclude that DBD leads to the protection and healing of the gastric mucosa by targeting genes and pathways, thus effectively countering the development and progression of GU.

1. INTRODUCTION

Gastric ulcer (GU) is a prevalent gastrointestinal condition that affects approximately 2.4% of the global population, with an incidence rate ranging from 0.10% to 0.19%.^1-3 Approximately 8.1 million patients were diagnosed in 2019, representing a 25.8% increase since 1990.⁴ Several risk factors have been identified underlying the development of GU, including smoking, use of anti-inflammatory drugs, and alcohol consumption.⁵ Recent epidemiological studies have shown a potential decrease in the incidence of GU, which may be attributed to a reduction in the prevalence of Helicobacter pylori (H. pylori) infection. However, complications from peptic ulcer disease have not shown a similar reduction.^6,7 Conventional treatment regimens for GU typically involve the use of anti-secretory agents, including H2-receptors blockers and proton pump inhibitors (PPIs), alongside certain antibiotics.^8-10 However, prolonged antibiotic use and long-term reliance on PPIs could lead to an increase in complications, including impaired nutrients absorption, enteric infections, dementia, or other diseases.^11,12 Both clinical and experimental studies have demonstrated that certain herbal medicines exhibit therapeutic benefits for GU with fewer side effects.¹³ Thus, herbal medicines, either alone or in combination with conventional drugs, present a promising alternative for treating specific GU and preventing recurrence.

Danggui Buxue decoction (当归补血汤, DBD) is a classic Chinese prescription formulated by LI Dong-yuan, comprising a combination of Huangqi (Radix Astragali Mongolici) and Danggui (Radix Angelicae Sinensis) in the ratio 5:1. This herbal decoction has been traditionally used to address various health issues, such as internal injuries due to fatigue, deficiency of and blood, deficiency heat syndrome resulting from Yin vacuity with Yang floating, or the persistent ulcers.¹⁴ Clinical studies have revealed that DBD, when used in conjunction with conventional drugs for the treatment of GU, significantly enhances the therapeutic effect while reducing the incidence of adverse drug reactions compared to conventional treatment alone.^15,16 Experimental investigations have found that DBD could stimulate the proliferation of mucosal epithelial cells, thereby promoting the rapid repair of mucosal barrier damage.¹⁷ Moreover, both Huangqi (Radix Astragali Mongolici) and Danggui (Radix Angelicae Sinensis), the main components of DBD, have demonstrated remarkable efficacy in treating GU with the added benefits of few adverse reactions and low recurrence rates.¹⁸ Further research has uncovered that Huangqi (Radix Astragali Mongolici) and Danggui (Radix Angelicae Sinensis) possess mucosal protection and immune enhancement properties, which play a vital role in facilitating the healing process of GU.^19,20

H. pylori and Nonsteroidal Antiinflammatory Drugs (NSAIDs) are responsible for approximately 90%-95% of GUs, and eradication of H. pylori has been shown to reduce the recurrence rate of ulcers.^21,22 The process of ulcer repair is intricate and tightly regulated, involving various stages, such as inflammation, cell proliferation, formation of granulation tissue at the ulcer base, and angiogenesis. These events are orchestrated by cytokines and growth factors (such as epidermal growth factor (EGF), platelet-derived growth facto, keratinocyte growth factor hepatocyte growth factor, transforming growth factor beta, vascular endothelial growth factor (VEGF), and angiopoietins) as well as transcription factors, all activated in a spatially and temporally coordinated manner following tissue injury. The growth factors trigger mitogenic, motogenic and survival pathways through the activation of signaling molecules, such as Ras, mitogen-activated protein kinase (MAPK), phosphatidylinositol 3-kinase/AKT serine/threonine kinase (PI-3K/Akt), phospholipase C gamma, and Rho/ Rac/actin signaling.^23-25 Despite the progress in understanding the general mechanisms involved in ulcer repair, there remains a lack of comprehensive and systematic research concerning the specific targets and molecular mechanisms by which DBD promotes the healing of GU.

Given the potentially important role of DBD in the treatment of GU, it is imperative to explore its underlying mechanisms. To achieve this, we employed a network pharmacology method to uncover the potential active components, key targets, and pathways involved in the therapeutic effects of DBD on GU. Additionally, macromolecular docking was performed to investigate the interactions between the selected key targets and active compounds present in the DBD. Subsequently, we validated the efficacy of DBD by conducting experiments in GU mice, providing further evidence of its beneficial effects. Concurrently, experimental verification was performed to investigate the potential mechanisms by which DBD exerts its healing properties on GU.

2. MATERIALS AND METHODS

2.1. Collection of active compounds and target prediction of DBD

Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to identify active phytomolecules in DBD. The TCMSP database contains information on the absorption, distribution, metabolism, and excretion (ADME) characteristics of each compound. Oral bioavailability (OB) refers to “the rate and degree to which an active component or active moiety is absorbed from a therapeutic product that becomes accessible at the targeted site.” Drug Likeness (DL) is a qualitative paradigm for drug design that incorporates the ADME qualities of ingredients and established medications. The therapeutic compounds of DBD that satisfy the requirements of both OB ≥ 30% and DL ≥ 0.18 were collected for subsequent target prediction. Protein targets corresponding to the active compounds were obtained from TCMSP, and the UniProt website was used to match the protein targets and gene names.

2.2. Screening of disease-related genes

The GU-related genes were collected from Disgenet, Online Mendelian Inheritance in Man (OMIM), and Genecards by searching the keywords “gastric ulcer.” Then, the UniProt website was used to match gene names, and Cytoscape was used to draw active ingredient target networks.

2.3. Identification of potential anti-GU targets of DBD

The DBD- and GU-related targets were imported into the Venny 2.1.0 online platform to construct a Venn diagram of common targets of DBD and GU.

2.4. Protein-protein interaction (PPI) analysis

PPI among the potential anti-GU targets of DBD were analyzed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. The confidence score was set to > 0.4, and the species was limited to “Homo sapiens”. The results of the PPI analysis were further visualized using Cytoscape Software. The “network analysis” function in Cytoscape software (National Resource for Network Biology, Bethesda, MD, USA) was used to screen the key targets based on the standard that the values of Betweenness Centrality, Closeness, Centrality, and Degree were greater than the average value, and the STRING database was used again to obtain the PPI among the key targets.

2.5. Enrichment analysis

Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using the the Database for Annotation, Visualization and Integrated Discovery (DAVID) database for annotation, visualization, and integrated discovery. GO terms were categorized into three types: cellular components (CC), biological processes (BP), and molecular functions (MF). Bubble plots of the bioprocesses and pathways were drawn by uploading the top 20 data points to the bioinformatics platform. To analyze the interaction between the active compounds, the anti-GU targets of DBD and the compound-target-pathway networks were constructed using Cytoscape Software.

2.6. Molecular docking

Structures of active compounds were acquired from TCMSP, and their three-dimensional structures were constructed using OpenBabel 3.1.1 (OpenBabel Development Team, global open-source community) and saved in PDB format. The protein crystal structures of the key targets were obtained in PDB format from the RSCB. PyMOL 2.3.2 Software (Schrödinger, LLC, New York, NY, USA) was used for the extraction of ligands and water molecules from the crystal structure complex. The key active compounds in the PDB format were uploaded to AutoDockTools 1.5.7 (The Scripps Research Institute, La Jolla, CA, USA).

Both the proteins and key active compounds were converted into pdbqt format using AutoDockTools 1.5.7. AutoDock Vina (The Scripps Research Institute, La Jolla, CA, USA) was used to perform macromolecular docking between pdbqt-formatted proteins, and key active compounds and docked complexes were obtained. Finally, the docked complex results were visualized to estimate the binding ability of the molecules and targets using PyMOL 2.3.2 Software (Schrödinger, LLC, New York, NY, USA). A binding energy < 0 indicates that a ligand may spontaneously bind to the receptor. It is commonly recognized that the lower the energy score of the ligand- and receptor-binding configuration, the more likely it is that binding will occur.

2.7. Experiment verification

2.7.1. Preparation of DBD

Both Huangqi (Radix Astragali Mongolici) and Danggui (Radix Angelicae Sinensis) were purchased from Tianjiang Pharmaceutical co., Ltd. (Jiangyin, China), Huangqi (Radix Astragali Mongolici) and Danggui (Radix Angelicae Sinensis) were mixed in the ratio of 5:1 (dry weight) and immersed in 8 volumes of distilled water (v/m) for 0.5 h, then decocted thrice at a pressure of 0.08 MPa, each time for 1.5 h. The extracts were combined, freeze-dried, and stored at —80 ℃ until further use.

2.7.2. High-performance liquid chromatography (HPLC)

The HPLC system (Essentia LC-16, SHIMADZU-GL, Shimadzu, Japan) equipped with a WonCract ODS-2 column (SHIMADZU-GL, 4.6 mm × 150 mm) was used for sample analysis. Standards for quercetin, kaempferol, formononetin, isorhamnetin, and beta-sitosterol were dissolved in pure methanol. It was performed by gradient elution with 0.1% formic acid aqueous solution-methanol as the mobile phase. The mobile phase consisted of a mixture of 0.1% formic acid-water (A) and methanol (B) and was set in a gradient elution program: 0-4 min, 25% B; 4-8.5 min, 25%-50% B; 8.5-16 min, 50% B; 16-26 min, 50%-100% B; 26-120 min, 100% B. Detection wavelength was respectively 210, and 370 nm with 1 mL/min flow rate and 20 μL injection. Then, 100 mg of Huangqi (Radix Astragali Mongolici) or Danggui (Radix Angelicae Sinensis) was added to 20 mL of ethanol. It was stirred at 300 rpm and refluxed at 80 ℃ for 60 min. The resulting hot solution was filtered, and the filtrate was obtained for detection after concentration.

2.7.3. Animals and experimental design

Thirty-six six-week-old male C57 mice weighing 18-20 g were purchased from Chengdu Dashuo Biotechnology Co., Ltd. (Chengdu, China; license No. SCXK 2015-030). All mice were maintained on a 12/12-h light/dark cycle, allowed free access to water and food, and acclimated for at least 7 d. This study was approved by the Animal Research Ethics Committee of Chengdu University of TCM (Chengdu, China) and complied with the Guidelines for Animal Experiments (2023-kj00039).

After 1 week of adaptive feeding, 36 mice were randomly divided into six groups (n = 6). The control and model groups received distilled water. The ranitidine group was administered ranitidine (30 mg/kg body weight). The DBD groups received various doses of DBD (2.34, 1.17, 0.59 g/kg, dry weight). All substances used were dissolved in distilled water and intragastrically administered to the mice once per day for 1 week. On the 8th day, mice were stripped of food but allowed to drink water freely for 24 h. On day 9, a single dose of anhydrous ethanol (0.1 mL/10 g) was administered to all groups except the control group to establish a GU model.

One hour later, all mice were euthanized with an overdose of anesthetic. The gastric tissues of mice were carefully separated, cut along the great curvature, and flushed with cold saline. The ulcer area (mm²) of the gastric mucosa was measured using ImageJ-win64 software (Bethesda, MD, USA). The ulcer index (UI) of each animal was calculated using the following formula: UI = [ulcerated area/total stomach area] × 100.

2.7.4. Hematoxylin and eosin (HE) staining

Murine gastric tissue was collected, fixed in 4% paraformaldehyde for 48 h, dehydrated, and embedded in paraffin. The paraffin tissue blocks were cut into 4 μm-thick sections, deparaffinized with xylene and passed through graded alcohol, and stained with HE solution. Pathological changes in gastric tissues were observed under a light microscope.

2.7.5. Western blot

Total cellular protein was collected (KGP250, KeyGEN Biotech, Beijing, China) and quantified using bicinchoninic acid (cat. No. KGP902, KeyGEN Biotech, Beijing, China). Proteins were separated via sodium dodecyl sulfate-polyacrylamide gel electrophoresis and transferred through polyvinylidene fluoride membranes. After blocking the membrane with 5% bovine serum albumin for 2 h at room temperature, membranes were incubated overnight at 4 ℃ with one of the following primary antibodies: anti-TNF alpha (ab183218, Abcam, UK), anti-IL6 alpha (ab290735, Abcam, UK), anti-VEGF (ab32152, Abcam, UK), anti-TP53 (ab202026, Abcam, UK), anti-ILβ, (ab283818, Abcam, UK), anti-β-actin (bs-0061R, Bioss, China), and anti-Akt1 (CST,2938, USA). All antibodies were diluted 1:1000 in Tris-buffered saline with Tween 20 (TBST) (T1086, Solarbio, Beijing, China). After washing with PBS, the membranes were incubated with secondary antibodies, including goat anti-mouse immunoglobulin G (IgG) (bs-0296G, Bioss, Beijing, China) and goat anti-rabbit IgG (bs-0295G; Bioss, Beijing, China), and diluted to 1:4000 with TBST for 1 h at room temperature. After washing off the excess secondary antibody, protein intensity was determined using Clarity Western ECL Substrate (Bio-Rad Laboratories Co., Ltd., Hercules, CA, USA) and measured using Image Lab software (5.2.1 Version, Bio-Rad Laboratories Co., Ltd., Hercules, CA, USA). Proteins were quantified via densitometric analysis using the ImageJ software (version 1.8.0.172, Bethesda, MA, USA).

2.7.6. Real-time polymerase chain reaction (RT-PCR)

Total RNA was extracted from gastric tissue according to the Trizol instruction manual, and hereafter RNA (2 μg) was transcribed into cDNA by RevertAid First Strand cDNA Synthesis Kit (Thermo Fisher Scientific, MA, USA). Finally, the cDNA was subjected to PCR amplification with SYBR™ Select Master Mix (Applied Biosystem Inc., Carlsbad, CA, USA) by ABI 7500 Real-Time PCR machine (Applied Biosystems Inc, Carlsbad, CA, USA). All the obtained data was calculated by the 2^−△△Ct method with β-actin as an endogenous reference. The primers used for qRT-PCR were designed as follows: Tumor Necrosis Factor Alpha (TNF-α) forward primer 5’-CAGGCGGTGCCTATGTCTC-3’ and reverse primer 5’-CGATCACCCCGAAGTTCAGTAG-3’ (89 bp); Interleukin-6 (IL-6) forward 5’-TCTATACCACTTCA-CAAGTCGGA-3’ and reverse 5’-GAATTGCCAT-TGCACAACTCTTT-3’ (88 bp); VEGF forward 5’-GCACATAGAGAGAATGAGCTTCC-3’ and reverse 5’-CTCCGCTCTGAACAAGGCT-3’ (105 bp); Interleukin-1 beta (IL-1β) forward 5’-GAAATGCCA-CCTTTTGACAGTG-3’ and reverse 5’-TGGATGCTC-TCATCAGGACAG-3’ (116 bp); AKT Serine/ Threonine Kinase 1(AKT1) forward 5’-ATGAACGAC-GTAGCCATTGTG-3’ and reverse 5’-TTGTAGCCAA-TAAAGGTGCCAT-3’ (116 bp); β-actin forward 5’-GGCTGTATTCCCCTCCATCG-3’ and reverse 5’-CCAGTTGGTAACAATGCCATGT-3’ (154 bp) was included as the internal control.

2.8. Statistical analysis

Statistical analyses were performed using SPSS (version 22.0; IBM Corp., Armonk, NY, USA). All data are expressed as mean ± standard deviation. One-way analysis of variance or unpaired two-tailed Student’s t-tests were used to determine differences among groups. Differences were considered statistically significant at P≤ 0.05.

3. RESULTS

3.1. Active ingredients and targets of DBD

Through the TCMSP database setting OB ≥ 30%, DL ≥ 0.18, two active ingredients of Danggui (Radix Angelicae Sinensis) and 20 active ingredients of Huangqi (Radix Astragali Mongolici) were screened (Table 1).

Table 1.

Active ingredients of Danggui Buxue decoction

Herbs	Mol ID	Molecule name	OB (%)	DL
Danggui (Radix Angelicae Sinensis)	MOL000358	Beta-sitosterol	36.91	0.75
	MOL000449	Stigmasterol	43.83	0.76
Huangqi (Radix Astragali Mongolici)	MOL000211	Mairin	55.38	0.78
	MOL000239	Jaranol	50.83	0.29
	MOL000296	Hederagenin	36.91	0.75
	MOL000033	(3S,8S,9S,10R,13R,14S,17R)-10,13-dimethyl-17-[(2R,5S)-5-propan-2-yloctan-2-yl]-2,3,4,7,8,9,11,12,14,15,16,17-dodecahydro-1H-cyclopenta[a]phenanthren-3-ol	36.23	0.78
	MOL000354	Isorhamnetin	49.6	0.31
	MOL000371	3,9-di-O-methylnissolin	53.74	0.48
	MOL000374	5'-hydroxyiso-muronulatol-2',5'-di-O-glucoside	41.72	0.69
	MOL000378	7-O-methylisomucronulatol	74.69	0.3
	MOL000379	9,10-dimethoxypterocarpan-3-O-β-D-glucoside	36.74	0.92
	MOL000380	(6aR,11aR)-9,10-dimethoxy-6a,11a-dihydro-6H-benzofurano[3,2-c]chromen-3-ol	64.26	0.42
	MOL000387	Bifendate	31.1	0.67
	MOL000392	Formononetin	69.67	0.21
	MOL000398	Isoflavanone	109.99	0.3
	MOL000417	Calycosin	47.75	0.24
	MOL000422	Kaempferol	41.88	0.24
	MOL000433	FA	68.96	0.71
	MOL000438	(3R)-3-(2-hydroxy-3,4-dimethoxyphenyl) chroman-7-ol	67.67	0.26
	MOL000439	Isomucronulatol-7,2'-di-O-glucosiole	49.28	0.62
	MOL000442	1,7-Dihydroxy-3,9-dimethoxy pterocarpene	39.05	0.48
	MOL000098	Quercetin	46.43	0.28

Notes: OB: oral bioavailability; DL: drug likeness; FA: fulvic acid.

3.2. Target retrieval

Targets of the active ingredients were obtained from the TCMSP database. A total of 220 DBD targets were obtained after removing repetitions, and 343 GU targets were retrieved from the Disgenet, OMIM, and Genecards databases. The network diagram of the herb-active ingredient-target interactions is depicted in supplementary Figure 1. It consisted of 241 nodes (including 2 herb nodes, 19 active ingredient nodes, and 220 target nodes) and 537 edges. Among these, β-sitosterol (MOL000358) and stigmasterol (MOL000459) were identified as active compounds derived from Danggui (Radix Angelicae Sinensis), while the rest were active compounds derived from Huangqi (Radix Astragali Mongolici). Notably, quercetin (MOL000098), kaempferol (MOL000422), and formononetin (MOL000392) exhibited the highest degree values in the network.

3.3. Identification of potential anti-GU targets of DBD

Venn diagram software was employed to compare and map the predicted targets of DBD with the targets of GU, resulting in the identification of 57 potential targets associated with GU treatment (supplementary Figure 2).

3.4. PPI network for the targets

Fifty-seven potential targets were imported into the STRING database, with Homo sapiens selected as the species. A protein interaction diagram was generated (Figure 1A). The obtained data were further processed in the TSV format using Cytoscape3.8.2 software, where the network analysis function was utilized to identify key targets. The key targets were ranked based on numerical values, and the top targets included TNF, IL-6, VEGF, AKT1, tumor protein p53 (TP53), matrix metall-oproteinase 9 (MMP9), IL-1β, Caspase 3 (CASP3), RELA proto-oncogene, EGF, MYC proto-oncogene (MYC), prostaglandin-endoperoxide synthase 2 (PTGS2), and mitogen-activated protein kinase 1 (MAPK1). Moreover, to establish PPI relationships among these key targets, the STRING database was used again and a PPI relationship diagram was generated, as shown in Figure 1B and Table 2.

Figure 1. Network pharmacology analysis of DBD on GU.

A: PPI network for 57 potential targets; B: PPI network for the 14 key targets. DBD: Danggui Buxue decoction; GU: gastric ulcer; PPI: protein-protein interaction.

Table 2.

Details of the key targets

Key targets	Betweenness centrality	Closeness centrality	Degree
TNF	0.07224798	0.65882353	33
IL-6	0.06024239	0.65116279	33
VEGF	0.09232003	0.66666667	31
AKT1	0.1051178	0.64367816	28
TP53	0.08365778	0.62921348	26
MMP9	0.07389262	0.62222222	26
IL-1β	0.01989997	0.58947368	25
CASP3	0.0375621	0.57731959	21
RELA	0.03861559	0.57142857	21
EGF	0.03017289	0.56565657	20
MYC	0.05219103	0.56	17
PTGS2	0.0320954	0.54368932	17
MAPK1	0.0283965	0.54368932	16
MMP2	0.0200976	0.53846154	14

Notes: TNF: tumor necrosis factor; IL-6: interleukin-6; VEGF: vascular endothelial growth factor; AKT1: AKT serine/threonine kinase 1; TP53: tumor protein p53; MMP9: matrix metalloproteinase 9; IL-1β: interleukin-1 beta; CASP3: caspase 3; RELA: RELA proto-oncogene; EGF: epidermal growth factor; MYC: MYC proto-oncogene, PTGS2: prostaglandin-endoperoxide synthase 2; MAPK1: mitogen-activated protein kinase 1; MMP2: matrix metalloproteinase 2.

3.5. GO and KEGG pathway enrichment analyses

The DAVID database was used to perform GO functional enrichment analysis on common targets, which resulted in 510 BP entries, 36 CC entries, and 69 MF entries. The top 10 entries for each category were selected and are presented as bar charts (supplementary Figure 3). In terms of BP, enrichment analysis revealed a significant involvement in the negative regulation of the apoptotic process, positive regulation of gene expression, and positive regulation of cell proliferation. For CC, the enriched terms mainly included extracellular space, extracellular region, and cytoplasm. For MF, predominant enrichment was observed in protein binding, identical protein binding, and cytokine activity. Furthermore, 107 enrichment results were obtained from KEGG pathway analysis of common targets. To provide a comprehensive representation, the top 20 pathways were selected and are displayed in a bubble chart (supplementary Figure 4). The signaling pathways involved in regulating GU include the advanced glycation end products-receptor for advanced glycation end products (AGE-RAGE) signaling pathway in diabetes complications, lipid and atherosclerosis, cancer signaling pathway, fluid shear stress, atherosclerosis, and Interleukin-17 signaling pathway. Based on the results of the top 20 signaling pathways, active components, and corresponding targets, a network diagram was created to illustrate the association (supplementary Figure 5).

3.6. Molecular docking

The active ingredients quercetin and kaempferol, which displayed the highest degree values in the network, were selected for molecular docking studies with the five key targets, including TNF, AKT1, IL-6, VEGF, and IL-1β (Figure 2, supplementary Table 1). The results showed that both quercetin and kaempferol exhibited binding energies of ≤—5.0 kcal/mol with TNF, AKT1, IL-6, VEGF, and IL-1β. These findings indicate that quercetin and kaempferol have the potential to interact with and bind to these key targets, suggesting their possible binding activities.

Figure 2. Molecular docking: The hydrogen bond lengths, amino acid residues, and the active pockets between active components and proteins.

A: TNF-quercetin; B: TNF-kaempferol; C: IL-6-quercetin; D: VEGF-quercetin. TNF: tumor necrosis factor; IL-6: interleukin-6, VEGF: vascular endothelial growth factor.

3.7. HPLC analysis

The phytochemical composition of DBD was assessed using HPLC. As shown in supplementary Table 2, supplementary Table 3, and supplementary Figure 6, five ingredients identified from Huangqi (Radix Astragali Mongolici) or Danggui (Radix Angelicae Sinensis) were listed. In addition, these components identified by HPLC were coincident with those screened from the TCMSP database. According to the results of network pharmacological analysis, the five components were also the main active components in the network model of DBD for treating GU.

3.8. Effect of DBD on macroscopic gastric mucosal injury

As depicted in Figure 3, mice in the control group displayed no damage to the gastric mucosa. Conversely, mice in the model group that received ethanol exhibited severe gastric mucosal injury, characterized by linear or striped bleeding bands. However, the observed gastric mucosal damage was the mildest in the ranitidine group. The three groups pretreated with different doses of DBD (DBD-L, DBD-M, and DBD-H) showed varying degrees of gastric mucosal damage, ranging from moderate to mild, when compared to the model group. Notably, the DBD-H group (receiving a dosage of 2.34 g/kg body weight) exhibited the least gastric mucosal injury among all the DBD pretreatment groups.

Figure 3. Effect of DBD on gastric lesions induced by ethanol.

A: macroscopic examination of the gastric mucosa in mice of different groups; B: the average ulcer index of stomach samples in each group; C: results of HE staining of gastric mucosa (scale bar = 100 µm). A1, C1: Control group; A2, C2: Model group; A3, C3: Ranitidine group; A4, C4: DBD-H group; A5, C5: DBD-M group; A6, C6: DBD-L group. Control (distilled water, 1 week); Model (distilled water, 1 week); Ranitidine (ranitidine, 30 mg/kg body weight, 1 week); DBD-H (DBD, 2.34 g/kg, dry weight, 1 week); DBD-M (DBD, 1.17 g/kg, dry weight, 1 week); DBD-L (DBD, 0.59 g/kg, dry weight, 1 week). Statistical analyses were measured using one-way analysis of variance for multimal comparisons. Data were presented as mean ± standard deviation (n = 6). ^aP < 0.001 vs control group; ^bP < 0.001, ^cP < 0.05 vs model group. DBD: Danggui Buxue decoction.

3.9. HE staining

Histopathological characterization of the different groups illustrated microscopic alterations in the gastric tissues (Figure 3). In the control group, which had a normal gastric wall structure, the intact gastric mucosa appeared flat and smooth, and the arrangement of the glandular cells was tidy. However, in contrast to the control group, ethanol administration resulted in extensive gastric lesions characterized by intense degeneration, necrosis, and hemorrhage, including severe infiltration of inflammatory cells, cell atrophy, and cytoplasmic vacuolization, affecting almost all parts of the gastric mucosa. In contrast, pretreatment with ranitidine and DBD significantly ameliorated the exfoliation of mucosal cells, hemorrhage, necrosis, and inflammatory cell infiltration. This improvement was more pronounced in the ranitidine and DBD-H groups than that in the DBD-L and DBD-M groups.

3.10. Western blot detection of protein expression

Potential targets identified in the predictive results from network pharmacology were considered as possible mechanisms of the anti-GU effects of DBD. To further verify these results, we conducted Western blot analysis. As shown in Figure 4, it illustrated that compared to the model group, the treated groups exhibited downregulated expression of TNF-α, VEGF, IL-1β, AKT1, and IL-6 proteins (P < 0.05). This decrease was more significant in the ranitidine and DBD-H groups than that in the DBD-L and DBD-M groups.

Figure 4. Comparison of protein expression and mRNA expression levels.

A: representative results of protein phosphorylation levels in each group; B: quantitative results of protein phosphorylation levels in each group; C: relative mRNA expression of TNF-α; D: relative mRNA expression of IL-6; E: relative mRNA expression of VEGF; F: relative mRNA expression of IL-1β; G: relative mRNA expression of AKT1. Control (distilled water, 1 week); Model (distilled water, 1 week); Ranitidine (ranitidine, 30 mg/kg body weight, 1 week); DBD-H (DBD, 2.34 g/kg, dry weight, 1 week); DBD-M (DBD, 1.17 g/kg, dry weight, 1 week); DBD-L (DBD, 0.59 g/kg, dry weight, 1 week). DBD: Danggui Buxue decoction; TNF: tumor necrosis factor; AKT1: AKT serine/threonine kinase 1; IL-6: interleukin-6, VEGF: vascular endothelial growth factor; IL-1β: interleukin-1 beta. Statistical analyses were measured using one-way analysis of variance for multimal comparisons. Data were presented as mean ± standard deviation (n = 6). ^aP < 0.001 vs control group; ^bP < 0.001, ^cP < 0.01, ^dP < 0.05 vs model group.

3.11. Comparison of mRNA expression levels

RT-PCR analyses were used to determine the effect of DBD on the potential targets' mRNA expression (Figure 4). Compared with the control group, ethanol administration increased the secretion of TNF-α, VEGF, IL-1β, AKT1 and IL-6. However, pretreatment of DBD reversed the above alterations as compared with the model group, and the DBD-H group was more pronounced. These results indicate that the improvement in GU was associated with the downregulation of related target expression after treatment with different concentrations of DBD.

4. DISCUSSION

In Traditional Chinese Medicine, GU is referred to as a gastric abscess. DBD, a classic Chinese prescription, has traditionally been used to address internal injuries caused by fatigue, Qi and blood deficiencies, and persistent ulcers. Additionally, DBD has shown promise for the treatment of various gastrointestinal diseases, such as chronic gastritis, GU, dodecadactylitis, and colon cancer. However, the direct effects and underlying mechanisms of DBD in GU treatment remain unclear. To address this knowledge gap, we conducted a comprehensive study that combined predictive results from network pharmacology with in-vivo experiments for verification. Furthermore, we established an ethanol-induced gastric ulcer model and administered various doses of DBD as pretreatment. Macroscopic and histopathological examinations indicated that DBD exhibited a therapeutic effect on ethanol-induced gastric ulcers, with a stronger effect observed at higher doses. In addition to in vivo experiments, we utilized network pharmacology to identify potential active components, key targets, and pathways involved in the DBD treatment of GU. Macromolecular docking and western blot analyses were performed to validate the predicted targets and mechanisms. By integrating the findings from network pharmacology and experimental validation, we aimed to gain a comprehensive understanding of the therapeutic effects of DBD against GU.

Twenty active ingredients were identified via TCMSP analysis, and core active ingredients, including quercetin, kaempferol, formononetin, isorhamnetin, and β-stigmasterol, were identified using set analysis and pathway prediction. Quercetin is a natural flavonoid with anti-oxidant and anti-inflammatory properties. It has been shown to exert anti-inflammatory effects by inhibiting the expression of TNF-induced MMP9 in normal human gastric epithelial cells.^26,27 Similarly, kaempferol, another flavonoid with anti-inflammatory and antioxidant characteristics, mediated LR4-NF-κB signal transduction, inhibiting oxidative stress response and fibroblast cell damage.²⁸ Kaempferol has also demonstrated the ability to improve the prevention index, protect the mucosa from damage, and preserve gastric mucosal glycoproteins.²⁹ H. pylori is one of the leading causes of GU.³⁰ Interestingly, quercetin has shown significant inhibitory activity against urease, an enzyme that enables H. pylori to survive in acidic gastric juice and infect the gastric mucosa.³¹ Additionally, kaempferol has also been found to dose-dependently reduce H. pylori colonies both in vitro and in vivo. These findings highlight the inhibitory effects of quercetin and kaempferol on H. pylori. Formononetin, with an antioxidative effect, regulated the NF-κB signaling pathway, inhibiting GU inflammation and promoting gastric mucosal angiogenesis.³² In contrast, β-sitosterol, a common phytosterol, has cholesterol-lowering and tissue-repairing effects. It also increased the activity of the anti-inflammatory factor IL-10 while reducing the activity of chemokines and pro-inflammatory factors.³³ Moreover, all the active components of DBD exhibited various effects in the treatment of GU, especially quercetin and kaempferol, which is consistent with our prediction.

A total of 57 potential targets associated with the therapeutic effects of DBD in the treatment of GU were identified. The results of PPI analysis revealed key protein targets by which DBD might exert its beneficial effects on GU, including TNF, IL-6, VEGF, IL-1β, and AKT1. IL-6, L-1β, and TNF were pro-inflammatory cytokines that could play an important role in the development of gastric ulcers.³⁴ IL-6 was produced by various cells, predominantly mononuclear macrophages. It exhibits a wide range of biological activities and stimulates immune cells to produce free reactive oxygen species, lysosomal enzymes, and other inflammatory cytokines. Elevated IL-6 expression could contribute to gastric mucosal damage and the development of GU.^35,36 TNF could stimulate neutrophil infiltration and epithelial cell apoptosis, reduce gastric microcirculation around the ulcer region, and delay gastric ulcer healing.^37,38 IL-1β plays a significant role in regulating various gastric epithelial cells, and the extensive expression of IL-1β greatly contributed to ulcer formation.³⁹ Gastric mucosal inflammation caused by increased expression of these proinflammatory factors was a significant factor in the onset, exacerbation, and prolonged nonhealing of GU. This study found that TNF, IL-6, and IL-1β were all key targets of DBD in the treatment of GU and exhibited strong binding affinity with the key ingredients of DBD. Additionally, through western blotting and RT-PCR analysis, we observed a decrease in the expression of TNF, IL-1β, and IL-6 proteins and mRNA in the DBD-treated group. Notably, the inhibitory effect of high-dose DBD was more pronounced. This outcome indicated that the administration of DBD led to significant improvements in GU by downregulating the expression of these proinflammatory factors, implying that DBD was capable of reducing the inflammatory response.

AKT1 is a key regulatory kinase that transduces signals through the phosphoinositide 3-kinase (PI3K)-AKT signaling cascade to control cell growth and survival.^40,41 In this study, we found that the PI3K-AKT signaling pathway was among the top 20 enriched KEGG pathways. This indicates that DBD exerts therapeutic effects on GU via the PI3K-AKT signaling pathway. VEGF is a member of the growth factor family that promotes the proliferation, differentiation, and migration of vascular endothelial cells. Angiogenesis is crucial for the healing of gastric mucosal injuries because it facilitates the delivery of oxygen and nutrients to the healing site. Among the angiogenic factors, VEGF stood out as the most effective and fundamental regulator of angiogenesis.⁴² Consistent with our network pharmacology predictions and in vivo experimental results, both AKT1 and VEGF were key targets for DBD treatment of GU.

To further validate the relationship between active ingredients (quercetin and kaempferol) and key targets (TNF, AKT1, IL-6, VEGF, and IL-1β), we performed molecular docking experiments. The results demonstrated that the binding energies of these interactions were lower than—5.0 kJ/mol, indicating a strong potential for the formation of effective and stable complexes between the ligands and their respective receptor. To gain a deeper understanding of the interactions and action pathways of the target genes, GO and KEGG pathway analyses were utilized, resulting in 510 BP entries, 36 CC entries, 69 MF entries, and 107 pathways. GO analysis revealed that the biological processes involved in the DBD treatment of GU primarily included negative regulation of the apoptotic process, positive regulation of gene expression, and positive regulation of cell proliferation. Maintaining a balance between the proliferation and apoptosis of gastric epithelial cells is essential for the integrity of the gastric mucosa. When this balance is disrupted by various pathogenic factors, apoptosis becomes dominant, which leads to the development of gastric ulcers. Studies have shown that quercetin promotes the normal proliferation of gastric mucosa cells by inhibiting apoptosis and cell cycle arrest induced by H. pylori infection.^43,44 Among the key targets, AKT1 is closely associated with the regulation of cell cycle arrest and apoptosis. KEGG pathway analysis revealed several significant signaling pathways, including the AGE-RAGE signaling pathway in diabetic complications, lipid and atherosclerosis, cancer signaling pathway, fluid shear stress, atherosclerosis, and IL-17 signaling pathway. The AGE-RAGE signaling pathway is formed by the combination of AGE and its receptor RAGE, nicotinamide adenine dinucleotide hydrogen phosphate. This interaction enhanced oxidative stress and activated NF-κB signaling pathway, subsequently stimulating cytokines and growth factors. The NF-κB pathway played a crucial role in mediating inflammatory responses, which led to the expression of inflammatory factors, such as TNF-α, IL-6 and IL-1β, and triggered a series of non-specific inflammatory responses.⁴⁵ DBD probably generates clinical benefits by targeting any of the aforementioned molecules.

In summary, DBD pretreatment has the potential to protect the gastric mucosa from ethanol-induced injury. DBD exerts its therapeutic effects on GU by targeting TNF, VEGF, IL-1β, AKT1, and IL-6 through active ingredients, such as quercetin, kaempferol, formononetin, isorhamnetin, and β-stigmasterol. These active compounds regulate various signaling pathways, including AGE-RAGE, lipids, and atherosclerosis, to counteract the development of GU, as suggested by findings from network pharmacology and in vivo experiments. The data obtained in this study could serve as valuable references for future research and development of novel anti-GU drugs.

5. SUPPORTING INFORMATION

Supporting data to this article can be found online at http://www.journaltcm.com.

Funding Statement

Supported by the National Natural Science Foundation of China: Mechanism of Danggui Buxue Decoction in Promoting Liver Regulation by Modulating Kupffer Cell Glycolysis-Mediated Histone Lactylation in Hepatocytes (No. 82474299), and XingLin Scholars Program of Chengdu University of Traditional Chinese Medicine: Study on the Role and Mechanism of Electrospun Astragalus Polysaccharide and Angelica Polysaccharide in Promoting Liver Regeneration (No. YYZX2020036)