Network pharmacology and experimental validation to reveal the pharmacological mechanisms of Sini decoction (四逆汤) against renal fibrosis

Abstract

OBJECTIVE:

To investigate the mechanism by which Sini decoction (四逆汤, SND) improves renal fibrosis (Rf) in rats based on transforming growth factor β1/Smad (TGF-β1/Smad) signaling pathway.

METHODS:

Network pharmacology was applied to obtain potentially involved signaling pathways in SND's improving effects on Rf. The targets of SND drug components and the targets of Rf were obtained by searching databases, such as the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCSMP) and GeenCard. The intersection targets of two searches were obtained and underwent signaling pathway analysis using a Venn diagram. Then experimental pharmacology was utilized to prove and investigate the effects of SND on target proteins in the TGF-β1/Smad signaling pathway. The Rf rat model was established by unilateral ureteral occlusion (UUO). The expression levels of transforming growth factor, matrix metalloproteinase-9 (MMP-9), matrix metal protease-2 (MMP-2), connective tissue growth factor (CTGF), and tissue inhibitor of metalloproteinase-1 (TIMP-1) were determined by Masson staining of rat renal tissue, and immunohistochemical methods. The expression levels of Smad3, Smad2, and Smad7 in renal tissue were determined by Western blotting (WB). The mechanism of the improving effects of SND on Rf was investigated based on TGF-β1/Smad signaling pathway.

RESULTS:

A total of 12 drug components of Fuzi (Radix Aconiti Lateralis Preparata), 5 drug components of Ganjiang (Rhizoma Zingiber), and 9 drug components of Gancao (Radix Glycy et Rhizoma) were obtained from the database search, and 207 shared targets were found. A total of 1063 Rf targets were found in the database search. According to the Venn diagram, in total, 96 intersection targets were found in two database searches. The metabolic pathways involved included TGF-β signaling pathway, phosphatidylinositol-3-kinase/serine-threonine protein kinase signaling (PI3K/Akt) pathway, and hypoxia-inducible factor-1 (HIF-1) signaling pathway. Masson staining analysis showed that compared with the model group, the renal interstitial collagen deposition levels in the SSN and SND groups were significantly lower (P < 0.05). Immunohistochemical analysis, compared with the control group, the positive cell area expression levels of MMP-9/TIMP-1 and MMP-2/TIMP-1 in the kidney tissue of the model group were significantly decreased (P < 0.05, P < 0.01), and the positive cell area expression levels of CTGF and TGF-β1 were significantly increased (P < 0.01). Compared with the model group, the positive cell area expression levels of MMP-9/TIMP-1 and MMP-2/TIMP-1 in the kidney tissue of the SSN and SND groups were significantly increased (P < 0.05, P < 0.01), and the positive cell area expression levels of CTGF and TGF-β1 in the kidney tissue were significantly decreased (P < 0.05, P < 0.01). WB results showed that the SSN group and the SND group could reduce the expression of Smad2 and Smad3 (P < 0.05) and increase the expression of Smad7 (P < 0.05).

1. INTRODUCTION

Renal fibrosis (Rf), mainly manifested as renal interstitial fibrosis (Rif), is commonly found in acute and chronic kidney diseases and is closely related to the deterioration of renal function. It causes necrosis, degeneration, transdifferentiation of renal tubular epithelial cells formation, and deposition of extracellular matrix.¹ The pathogenesis of Rf is a chronic and progressive process that eventually leads to end-stage renal disease.² From Traditional Chinese Medicine (TCM) perspective, Rf is considered a complex chronic process affected by multiple factors. TCM believes that kidney fibrosis is caused by congenital deficiency, poor diet, excessive fatigue, prolonged illness, or other factors, eventually leading to a deficiency of viscera Qi, blood, and Yin and Yang. And the pathogenesis of TCM is a deficiency of the spleen and kidney, and dampness stagnation. At present, western medicine has not yet had specific therapeutic drugs for Rf. At the same time, TCM pays attention to the characteristics of holistic treatment and analyzes the characteristics of treatment according to the different stages of the disease, which is the advantage of the treatment of Rf. At present, in clinical practice and experimental research, it has been found that a variety of Chinese medicine monomers or extracts can effectively improve the structure and function of kidney tissue, and a variety of Chinese medicine compound preparations can protect kidney function and delay kidney fibrosis and have fewer side effects. Experimental research showed that polydatin, astragaloside, glycyrrhizic acid, etc. have good effects on the Renal Fibrosis Model.^3,4 Shenqidihuang decoction (参芪地黄汤) and Shenlingbaizhu powder (参苓白术散) can significantly improve the renal function of patients with chronic nephritis, control the progression of renal fibrosis, enhance the curative effect, and promote the recovery of patients.^5,6 In addition, the external treatment method of TCM is widely used in clinical practice as an auxiliary means of oral medication, and internal and external treatment is used to enhance the treatment effect.⁷ For example, TCM enema, TCM colon dialysis, TCM soup bath, and other external treatments can promote the elimination of metabolites and delay the process of kidney disease more effectively.

The pathogenesis of Rf is complex, involving multiple stimuli or mediators, including growth factors, cytokines, toxins, stress molecules, and various signal transduction pathways.^8,10 Of these, transforming growth factor β (TGF-β), Wnt, Notch, and Hedgehog signaling pathways are the most important. TGF-β, Wnt, and Notch signaling pathways mainly target renal tubular epithelial cells and can indirectly induce Rf through processes such as epithelial-mesenchymal transition (EMT).¹¹ The Hedgehog signaling pathway directly acts on renal interstitial myofibroblasts.¹² TGF-β has been proven to be the main cause for the progressive development of Rf.¹³ The EMT induced by TGF-β can lead to the generation of renal interstitial fibroblasts.¹⁴ The four signal pathways mentioned above regulate the process of Rf in an independent or cooperative manner.¹⁵

Progression of Rf can result in an irreversible impairment of renal function. Therefore, it is important to find a drug that inhibits the pathogenesis of Rf, hence maintaining renal function. New drugs with high specificity are often accompanied by problems such as poor safety profiles and uncertain effectiveness in the treatment of complex diseases.¹⁶ By contrast, TCM is characterized by multiple components and multiple targets and has shown great progress in the treatment of various complex diseases.

Sini decoction (四逆汤, SND) was originally recorded in Shang Han Za Bing Lun,¹⁷ written by Zhang Zhongjing, a famous ancient Chinese medicine master. It is a Chinese medicine compound, the development of which is grounded on the etiology theory, pathogenesis, and medicinal properties of TCM.¹⁸ SND is composed of Fuzi (Radix Aconiti Lateralis Preparata), Ganjiang (Rhizoma Zingiber), and Gancao (Radix Glycy Et Rhizoma). It has the effect of restoring Yang to save inverse, breaking Yin and dissipating cold, and is mostly used to treat the syndrome of inverse Yang syncope. It is commonly used in modern clinics to treat serious diseases such as heart failure, voluntary shock, and acute myocardial infarction. Modern research shows that SND can play an anti-shock effect by dilating peripheral blood vessels. Further, it has been shown to enhance myocardial contraction, anti-oxidation, etc. Which is aimed at improving myocardial function.¹⁹

Network pharmacology has its unique advantages in the study of TCM compounds. The concept of network pharmacology was first systematically put forward by Hopkins, a pharmacologist.²⁰ It is based on the rapid development of omics and internet databases. Network pharmacology integrates a variety of biological information and other disciplines to study a variety of ideas and methods to explain the relationship between drugs and the body, and analyzes the biological system network, which makes it suitable for studying the mechanisms of action of TCM compounds. At present, the active ingredients and related targets of TCM are often obtained through databases such as Symptom Mapping,²¹ Encyclopaedia of TCM,²² TCM System Pharmacology (TCMSP),²³ etc. At the same time, disease-related targets are obtained through databases such as GeenCards,²⁴ Online Mendelian Inheritance in Man (OMIM) and Therapeutic Target Database (TTD),^25,26 and Cytoscape software is used to construct a 'Chinese medicine-component-disease-target' network diagram, to preliminarily explore the target and pathway relationship between TCM and disease, and clarify its molecular mechanism of based on it. This shows that network pharmacology is a relatively effective and easy-to-implement method for studying the molecular mechanism of TCM.

A previous study showed that SND could mitigate the pathogenesis of Rf based on animal models established by unilateral ureteral ligation. The results of the study included a reduction in 24 h urine protein, serum urea nitrogen, and creatinine levels. However, the mechanisms by which these were achieved are not known. In this study, network pharmacology was employed to filtrate the effective drug components in SND that are involved in Rf treatment, their potential targets, and signaling pathways. Additionally, pharmacological experiments were conducted to study the effects and mechanisms of action of SND in the treatment of Rf.

2. MATERIALS AND METHODS

2.1. Experimental materials and instruments

Databases and software: TCMSP (http://tcmspw.com/tcmsp.php), PubChem, TTD (http://db.idrblab.net/ttd/), Comparative Toxicogenomics Database (CTD, http://ctdbase.org/), Human Genome Number (GeenCards, https://www.geencards.org/), OMIM (https://omim.org/), DisGeNeT (https://www.disgenet.org/) databases, Cytoscape 3.9.1 (Washington, BE, USA), PyMoL2.3.0 and AutoDock vina software (La Jolla, CA, USA).

Animals: specific pathogen free Sprague-Dawley (SD) rats that were used in this experiment, were purchased from the National Institute for Food and Drug Control, Lot No. SCXK (Beijing) 2014-0013. Of these, half male. They weighed 180-200 g. The experiments were in accordance with the guidelines for animal research. As such, the study was approved by the Animal Ethics Committee of Shanxi University of TCM (Animal Ethics 2021LL1021), and the experiments were in accordance with the guidelines for animal research.

Drugs: the drugs that were used for the SND, namely; Fuzi (Radix Aconiti Lateralis Preparata), Ganjiang (Rhizoma Zingiber), and Gancao (Radix Glycy Et Rhizoma), were purchased from Beijing Tongrentang Pharmacy (Shanxi, China). The above medicinal materials were identified as authentic by Associate Professor Pei Xiangping of Shanxi University of TCM, and all medicinal materials met the standards of the 2020 edition of the Pharmacopoeia of the People's Republic of China. Shenshuaining (SSN), (Lot No. z53021547, Kunming, China), was obtained from Yunnan Ideal Pharmaceutical Company.

Reagents: the reagents that were used in the experiments included: Xylene (Lot No. 10023418), which was bought from Sinopharm Chemical Reagent Company (Shanghai, China); Tromethamine (Tris) (Lot No. A100826-0500), sodium dodecyl sulfate (SDS) (Lot No. A100227-0500), and glycine (Lot No. A100167-0500), which were purchased from Sangon Bioengineering Co., Ltd. (Shanghai, China); HE staining solution set (Lot No. G1003) was from Wuhan Sevier Biotechnology Co., Ltd. (Wuhan, China); Goat serum, goat anti-rabbit IgG-Biotin, TGF-β₁, matrix metalloproteinase-9 (MMP-9), matrix metal protease-2 (MMP-2), connective tissue growth factor (CTGF), and matrix metalloproteinase inhibitor-1 (TIMP-1) antibodies were provided by Boster Bioengineering Co., Ltd. (Wuhan, China); Secondary antibodies, goat anti-rabbit IgG (H + L) horseradish Peroxidase (HRP) (Lot No. D110058-0100), HRP-conjugated goat anti-mouse IgG (Lot No. D110087-0100), and luminescence kit (Lot No. C506668-0100), which was purchased from Sangon Bioengineering Company (Shanghai, China).

Instruments: the research instruments, were the JB-P5 embedding machine from Wuhan Junjie Electronics Company (Wuhan, China), RM2016 pathological slicer from Shanghai Leica Instrument Company (Shanghai, China), JB-L5 freezing table from Wuhan Junjie Electronics Company (Wuhan, China), Giotto staining machine from DIAPATH company (Jinan, China), Nikon Eclipse E100 type upright optical microscope, and Nikon DS-U3 imaging system from Japan Optical Industry Company (Tokyo, Japan).

2.2. Network pharmacology

2.2.1. Database search of drug components and targets

The drug components in SND were searched in TCMSP. The selected drug components that met the criteria of oral bioavailability (OB ≥ 30%) and drug-like properties (DL ≥ 0.18%), were Fuzi (Radix Aconiti Lateralis Preparata), Gancao (Radix Glycy et Rhizoma) and Ganjiang (Rhizoma Zingiber). PubChem identification (ID) or number was applied to find the simplified molecular input line entry specification (SMILE) formula of selected drug components. The SWISS TARGET PREDICTION database was employed to search related targets of selected drug components and Uniport was used to determine final targets. Components without any targets were excluded.

2.2.2. Search of disease targets and intersection targets

Targets of Rf were searched in TTD and CTD with a reference score ≥ 45 as the screening criterion; in GeenCard and DisGeNeT with Score-gad ≥ 50 and Score ≥ 0.2 as the screening criteria, respectively; and in the OMIM database. Duplicate targets obtained from these databases were removed. Venn diagram was used to obtain the intersection of target genes of drugs and disease.

2.2.3. Construction of drug-disease common targets and their protein-protein interaction (PPI) networks

The obtained drug component-disease intersection targets are used to construct a PPI network of drug-disease common targets through the String platform, the protein type is set to "Homo sapiens", and the target with a confidence score ≥ 0.4 was selected, others are default settings. Then download the tsv format file, import it into Cytoscape 3.9.1 software and evaluate the main targets according to the network node degree value. Each node represents 1 gene, and the degree value is related to the number of nodes connected to the node. The larger the degree value, the more important the node is in the network.

2.2.4. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis

KEGG pathway analysis of the intersection gene targets was performed, and the key pathways were obtained. GO and KEGG pathways were plotted by Bioinformatics (http://www.bioinformatics.com.cn/), an online platform for data analysis and visualization. Key pathways were then imported into Cytoscape to construct a ‘component-target-pathway’ interaction network. Key pathways were then imported into Cytoscape to construct a 'component-target-pathway' interaction network.

2.2.5. Molecular docking

Key targets with top-degree values were selected and input into the Protein Data Bank (PDB) database. Their 3D structures were downloaded and saved in the PDB format, and water molecules and other ligands were removed using PyMol software. The top four active ingredients in SND, according to the degree values, and the SDF format files of the active ingredients were downloaded from the PubChem database and imported into OpenBabel to be converted into PDB format. Proteins were hydrogenated using AutoDock and then derived in PDB format. The Grid Box in the Grid module was set, and the vina program was used to semi-flexible dock targets (receptors) with chemical ingredients (ligands). The combinations with the lowest binding energy were selected and visualized using PyMol software.

2.3. Experimental pharmacology

2.3.1. Preparation of SND

The SND concoction contained 1.2 g of Fuzi (Radix Aconiti Lateralis Preparata), 0.75 g of Gancao (Radix Glycy Et Rhizoma), 0.9 g of the water extract of Ganjiang (Rhizoma Zingiber), and 3 g of the volatile oil extract from Ganjiang (Rhizoma Zingiber), which was dissolved together in 100 mL of distilled water to obtain SND.

2.3.2. Animals and treatments

A total of 56 SD rats were divided into four groups, namely: control, model, SSN, and SND groups. The Rf model in the rats was established by UUO as follows. Briefly, the rats were anesthetized by intraperitoneal injection of 10% chloral hydrate (0.3 mL/100 g). They were then fixed, shaved, and disinfected. A longitudinal incision of about 1-1.5 cm in length was made under the left side of the rat's rib cage. The subcutaneous fascia was peeled off layer by layer. The muscle was incised to expose the renal pelvis. The middle part of the ureter was then ligated. After that, the abdominal cavity was sutured. In the control group, the unilateral ureter was separated without ligation, and other operations were the same as those in the model group.

Two weeks after the operation, the rats in the control and model groups were given 1 mL/100 g of distilled water through intragastric administration. The rats in the SSN group were administrated with SSN aqueous solution at a dose of 0.432 g·kg^-1·d^-1; the SND group was given 0.585 g·kg^-1·d^-1 of SND. After 2 weeks of administration, the rats were sacrificed for analysis purposes.

2.3.3. Masson staining and immunohistochemical analysis (IHC) pathological examination

The renal tissue of the rats was fixed with 10% formaldehyde for 24 h at 4 ℃, and then paraffin was embedded. After Masson staining, the pathological changes of renal tissue were observed under a light microscope.

The renal tissue was sectioned into slices with 4.0 μm thickness, dewaxed, dehydrated, antigen retrieved, and then blocked with 10% goat serum for 30 min. Subsequently, the tissue underwent incubation with different primary antibodies for 60 min, including anti-TGF-β1, MMP-9, MMP-2, CTGF, and TIMP-1 antibodies, and incubation with secondary antibodies for 10 min. Horseradish enzyme was added to renal tissues dropwise for 10 min. DAB was used to develop color. Prior to sealing with neutral gum, 5 min hematoxylin staining was conducted. The positive expression of brown cytoplasm was measured by Image J analysis software in each high power field (× 400).

2.3.4. Western blotting analysis

The levels of Smad3, Smad2, and Smad7 that were expressed in renal tissue were determined by Western blot (WB), as follows. Briefly, 30 mg of kidney tissue was homogenized. Homogenate concentration was determined using Bicinchoninic acid protein detection kit and analyzed by 5% Sodium dodecyl sulfate polyAcrylamide gel electrophoresis gel electrophoresis. For WB, proteins in the gel were transferred to polyvinylidene fluoride membrane, which was later stained with the Ponceau red staining reagent and soaked in 5% Bovine serum albumin-Tris buffered saline with tween accompanied by a gentle shake for 60 min at room temperature. Furthermore, the membrane was incubated with primary antibodies against, Smad2 (1∶1000), Smad3 (1∶1000), and Smad7 (1∶2000), at 4 ℃ overnight. Finally, the membrane was incubated with secondary antibodies HRP (1∶5000). Enhanced chemiluminescence was added. The analysis method is the same as 2.3.3.

2.4. Statistic Analysis

The SPSS software version 20 (IBM Corp. Armonk, NY, USA) was utilized for statistical analysis. Data were presented as mean ± standard deviation ($\bar{x}±s$). Singly-factor analysis and t-test were employed in group comparison, the criterion of P < 0.05 was adopted for statistical significance.

3. RESULTS

3.1. Network pharmacology

3.1.1. Search of drug components and targets

After the TCMSP database search, seven drug components were found in Fuzi (Radix Aconiti Lateralis Preparata), four in Ganjiang (Rhizoma Zingiber), and seven in Gancao (Radix Glycy et Rhizoma). Combined with the identified drug components in the 2020 edition of the Chinese Pharmacopoeia, which are five in Fuzi (Radix Aconiti Lateralis Preparata), one in Ganjiang (Rhizoma Zingiber), and two in Gancao (Radix Glycy Et Rhizoma), the total became 12, 5, and 9 drug components in Fuzi (Radix Aconiti Lateralis Preparata), Ganjiang (Rhizoma Zingiber), Gancao (Radix Glycy Et Rhizoma), respectively. A total of 207 drug targets were identified for drug components (Table 1).

Table 1.

Temperature and wildlife count in the three areas covered by the study

Herb	Number of drug components found in TCMSP	Number of drug components in Chinese Pharmacopoeia	Targets of drug components
Fuzi (Radix Aconiti Lateralis Preparata)	7	5	138
Ganjiang (Rhizoma Zingiber)	4	1	134
Gancao (Radix Glycy Et Rhizoma)	7	2	69

Notes: TCMSP: Traditional chinese medicine systems pharmacology database and analysis platform.

3.1.2. Disease targets and intersection targets

Totals of 610, 891, 261, and 22 disease targets were found in CTD, GeenCard, OMIM, and DisGeNeT, respectively, and 1063 disease-related protein targets were obtained after deduplication. According to the Venn intersection diagram, there were 96 intersection targets of the drug components and disease. Subsequently, we established the interaction network of SND targets and Rf-related targets. The network consists of 126 nodes and 694 edges and A PPI network consists of 96 nodes and 691 edges, a local clustering coefficient of 0.577. (Table 2, supplementary Figure 1).

Table 2.

Key targets of SND acting on renal tissue (top 30)

Target	Name	Degree	Betweenness centrality	Closeness centrality
EGFR	Epidermal growth factor receptor	98	0.103	0.669
HSP90AA1	Heat shock protein 90 alpha family class a member 1	96	0.117	0.650
JUN	Jun proto-oncogene, ap-1 transcription factor subunit	88	0.061	0.628
MAPK3	Mitogen-activated protein kinase 3	84	0.045	0.628
STAT3	Signal transducer and activator of transcription 3	84	0.038	0.616
ESR1	Estrogen receptor 1	78	0.058	0.616
PPARG	Peroxisome proliferator activated receptor gamma	76	0.080	0.608
MTOR	Mechanistic target of rapamycin kinase	76	0.018	0.596
PTGS2	Prostaglandin-endoperoxide synthase 2	72	0.059	0.600
MDM2	MDM2 proto-oncogene	70	0.025	0.596
BCL2L1	BCL2 like 1	68	0.019	0.581
PIK3CA	Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha	68	0.018	0.578
MMP9	Matrix metallopeptidase 9	58	0.017	0.560
KDR	Kinase insert domain receptor	54	0.022	0.560
JAK2	Janus kinase 2	54	0.008	0.544
AR	Androgen receptor	52	0.010	0.544
NR3C1	Nuclear receptor subfamily 3 group c member 1	52	0.056	0.567
GSK3B	Glycogen synthase kinase 3 beta	52	0.012	0.554
IGF1R	Insulin like growth factor 1 receptor	50	0.004	0.547
MAP2K1	Mitogen-activated protein kinase 1	48	0.004	0.538
APP	Amyloid beta precursor protein	46	0.052	0.554
MMP2	Matrix metallopeptidase 2	44	0.004	0.531
CDK2	Cyclin dependent kinase 2	44	0.003	0.520
PIK3CB	Phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit beta	40	0.005	0.482
COMT	Catechol-o-methyltransferase	38	0.026	0.482
CYP19A1	Cytochrome p450 family 19 subfamily a member 1	38	0.021	0.531
PARP1	Poly(ADP-Ribose) polymerase 1	36	0.001	0.503
TERT	Telomerase reverse transcriptase	34	0.001	0.505
JAK1	Janus kinase 1	34	0.001	0.487
ESR2	Estrogen receptor 2	34	0.022	0.528

Notes: SND: Sini decoction.

3.1.3. Go and KEGG enrichment analysis signaling

A total of 96 intersection targets were entered for signaling pathway analysis using the DAVID database. For the GO biological signaling pathways, 443 biological processes (BP), 66 cellular components (CC), 70 molecular functions (MF), 205 Wiki, and 96 KEGG pathways were found. Sorted by the enrichment of significance, the BP of SND-Rf-targets is significantly enriched in the growth hormone receptor signaling pathway via Janus kinase-signal transducer and activator of transcription (JAK-STAT), inflammatory response, regulation of killing of cells of another organism, etc. MF is mainly enriched in vascular endothelial growth factor receptor activity, protein binding, transcription factor binding, protein isomerization activity, growth hormone receptor binding, etc. CC is mainly enriched in phosphatidylinositol 3-kinase complex, class IA, phosphatidylinositol 3-kinase complex, dopaminergic synapse, etc. (Figure 1A). The top 15 pathways are listed in Figure 1B. Sorted by the value of the pathway, we select pathways with the number of genes > 0. TGF-β signaling pathway, TGF-β receptor signaling pathway, Phosphatidylinositol-3-kinase/serine-threonine protein kinase (PI3K/Akt) signaling pathway, and HIF-1 signaling pathway, et al are included.

Figure 1. GO function enrichment and KEGG signaling pathway analysis results of SND in the treatment of Rf.

A: GO function enrichment; B: KEGG signaling pathway. SND: Sini decoction; Rf: renal fibrosis. ErbB: epidermal growth factor receptor; HIF-1: hypoxiainduciblefactor-1; RAC1/pak1/p38/MMP2: ras-related C3 botulinum toxin substrate 1/p21-activated kinases 1/p38 mi‐togen-activated protein kinase; FoxO: forkhead box protein O; cAMP: cyclic adenosine monophosphate; TGF:transforming growth factor; PI3K-Akt: phosphatidylinositol-3-kinase/serine-threonine protein kinase; MAPK: mitogen-activated protein kinase.

Cell cycle-related pathways include FoxO signaling pathway. In addition, there are the mitogen-activated protein kinase (MAPK) signaling pathway, the Neurotrophin signaling pathway, the cyclic adenosine monophosphate (cAMP) signaling pathway, etc. Sorted by the value of the pathway, we select pathways with SND that may act on these pathways against Rf. TGF-β₁/signal pathway is closely related to Rf. Regulating this signal pathway may be one of the important mechanisms of SND to improve Rf. Therefore, animal experiments were conducted to verify the results.

3.1.4. Molecular docking

Key components and target proteins with the highest degree in the PPI network were docked by AutoDock software. All active components and key targets could spontaneously bind (binding free energy was less than 0 kcal/mol). The docking results are visualized by PyMol software, and some results are shown in Figure 2. The core active components (6-Gingerol, hypaconitine, aconitine, mesaconitine, etc.) were molecularly docked by AutoDock Vina (Table 3). The absolute values of the docking score indicate the affinity of the components with the targets and the stability of the conformation. An absolute value greater than 4.25 indicates a certain binding activity, greater than 5.0 indicates a good binding activity, and greater than 7.0 indicates a strong binding activity. The molecular docking results showed that the binding ability of 6-gingerol, hypaconitine, aconitine, and mesaconitine to Smad2 was stronger, and the binding energy of each active component was stronger. The binding ability of hypaconitine, aconitine, and mesaconitine active component with Smad7 is poor and weaker than 6-gingerol. Comprehensive analysis shows that the docking scores of 6-gingerol with Smad2 and Smad7 have the largest absolute value among the five targets. The targets Smad2, Smad3, Smad7, and TGF-β1 have the strongest affinity with 6-gingerol, hypaconitine, aconitine, and mesaconitine.

Figure 2. Molecular docking diagram of chemical composition to target.

A: 6-Gingerol vs Smad7; B: 6-Gingerol vs Smad2; C: 6-Gingerol vs TGF-β1; D: Hypaconitine vs Smad3; E: Aconitine vs Smad3; F: Mesaconitine vs TGF-β1. TGF-β1: transforming growth factor β1.

Table 3.

Molecular docking results of the active ingredient and the target

Active compounds	Combined energy (kcal/mol)
	Smad2	Smad3	Smad7	TGF-β1
6-Gingerol	－7.9	－7.5	－8.9	－7.8
Hypaconitine	－6.9	－7.2	－6.7	－6.9
Aconitine	－7.2	－7.4	－5.9	－6.3
Mesaconitine	－7.0	－7.2	－6.4	－7.2

Notes: TGF-β1: transforming growth factor β1.

3.2. Effect of SND on renal tissue of Rf rats

The expansion of renal tubules and renal interstitium and more green areas were observed in the model group compared with the control group in the Masson staining analysis. In contrast with the model group, the green areas in the SSN and SND groups were significantly smaller, indicating that the model was successfully established. Most importantly, this shows that SND could significantly reduce the degree of renal fibrosis in rats after UUO (Figure 3A).

Figure 3. Images of renal tissue of Rf rats, masson staining and IHC stained TGF-β1, MMP-2, MMP-9, CTGF, and TIMP-1 granules (× 400).

A: masson staining; B: expression of MMP-2; C: expression of MMP-9; D: expression of CTGF; E: expression of TIMP-1; F: expression of TGF-β1. Control: the unilateral ureter was separated without ligation (A1, B1, C1, D1, E1, F1); model: the unilateral ureter was separated and ligation (A2, B2, C2, D2, E2, F2); SSN: the unilateral ureter was separated and ligation, than gavage Shenshuaining 0.432 g·kg^-1·d^-1 2 weeks (A3, B3, C3, D3, E3, F3); SND: the unilateral ureter was separated and ligation, than gavage Sini decoction 0.585 g·kg^-1·d^-1 2 weeks (A4, B4, C4, D4, E4, F4). Rf: renal fibrosis; MMP-2: matrix metal protease-2; MMP-9: matrix metalloproteinase-9; CTGF: connective tissue growth factor; TIMP-1: tissue inhibitor of metalloproteinase-1; TGF-β1: transforming growth factor β1.

The number of expressed granules of TGF-β₁ in renal tissue of model group rats was lower than that of the control group. Compared with the model group, the number of expressed granules of TGF-β₁ in the SSN and SND groups was significantly greater.

Compared with the control group, the positive cell area expression levels of MMP-9/TIMP-1 and MMP-2/TIMP-1 in the kidney tissue of the model group were significantly decreased (P < 0.05, P < 0.01), and the positive cell area expression levels of CTGF and TGF-β1 were significantly increased (P < 0.01). Compared with the model group, the positive cell area expression levels of MMP-9/TIMP-1 and MMP-2/TIMP-1 in the kidney tissue of the SSN and SND groups were significantly increased (P < 0.05, P < 0.01 ), and the positive cell area expression levels of CTGF and TGF-β1 in the kidney tissue were significantly decreased (P < 0.05, P < 0.01), indicating that SND can inhibit the expression of TGF-β1 and CTGF, enhance the activity of MMP-9 and MMP-2, and then inhibit the inhibitor TIMP-1 of MMP-9 and MMP-2, and stimulate the degradation of extracellular matrix. Inhibit the formation of fibrosis (Figure 4A).

Figure 4. Effect of SND on TGF-β1/Smad pathway.

A: the expression of MMP-2/TIMP-1 (A1), MMP-9/TIMP-1 (A2), TGF-β1 (A3), and CTGF (A4) in renaltissue of rats with Rf (n = 6); B: expression levels of Smad2 (B1), Smad3 (B2) and Smad7 (B3) in renal tissue of four groups (n = 3). Control: the unilateral ureter was separated without ligation; model: the unilateral ureter was separated and ligation; SSN: the unilateral ureter was separated and ligation, than gavage Shenshuaining 0.432 g·kg^-1·d^-1 2 weeks; SND: the unilateral ureter was separated and ligation, than gavage Sini decoction 0.585 g·kg^-1·d^-1 2 weeks. MMP-2: matrix metal protease-2; MMP-9: matrix metalloproteinase-9; CTGF: connective tissue growth factor; TIMP-1: tissue inhibitor of metalloproteinase-1; TGF-β1: transforming growth factor β1. Data are expressed as the mean ± standard deviation; t-test, ^aP < 0.01, ^bP < 0.05 as compared to the model.

3.3. Effect of SND on Smad2, Smad3, and Smad7 expression in the Rf rats

The impact of SND on the expression of Smad2, Smad3, and Smad7 in renal tissue: the levels of Smad2 expressed in the renal tissue of rats in the model group were significantly higher than those in the control group (P < 0.05), and lower expression levels of Smad7 (P < 0.05). SND group showed significantly lower expression of Smad2 and Smad3, and higher expression levels of Smad7 (P < 0.05) (Figure 4B).

4. DISCUSSION

According to modern research, renal interstitial fibrosis, characterized by excessive deposition of the extracellular matrix, has been widely recognized as a common pathological marker of progressive chronic kidney disease with multiple etiologies. The cause of Rf is the increase in interstitial cells and collagen in renal tissue, especially the increase in stromal protein synthesis, which results in the inhibition of matrix degradation. Studies have shown that abnormal accumulation of extracellular matrix (ECM), inflammatory cell infiltration, apoptosis, oxidative stress, and other pathophysiological changes lead to fibrosis. Therefore, blocking and slowing down this process can effectively prevent the occurrence of chronic renal failure. SND is one of the classic clinical prescriptions. Therefore, the possible active ingredients and targets of SND were predicted by the network pharmacology method. GO analysis and KEGG analysis were used to predict the pathways of its possible effects, and molecular docking was used for preliminary verification. Finally, the predicted pathways were verified by in vivo experiments to provide the theoretical basis for its clinical application. In this study, UUO rats were treated with SND, and the mechanism by which SND improves Rf in UUO rats was investigated. The findings were an increase in TGF-β₁, MMP-2, MMP-9, and Smad7. However, the magnitude of the increase in Smad7 was so great. Through the analysis of the SND-compound-disease-target network, it was found that the main active components in the treatment of Rf include: possible active ingredients such as 6-gingerol, hypaconitine, aconitine, and mesaconitine obtained from SND through TCMSP, which are all active ingredients stipulated in the pharmacopeia.²⁷ Through the topological analysis of the PPI network, we found that the core targets are MAPK3, EGFR and Signal transducer and activator of transcription 3. GO analysis showed that, The BP effects of SND on Rf mainly focused on growth hormone receptor signaling pathway via JAK-STAT and cellular response to inflammation (interleukin-3) and negative regulation of synaptic transmission (glutamatergic), KEGG analysis of the network pharmacology predicts that the signaling pathways involved in alleviating Rf may be the TGF-β signaling pathway, TGF-β receptor signaling pathway, PI3K/Akt signaling pathway, hypoxia-inducible factor-1 (HIF-1) signaling pathway, etc. The PI3K/Akt signaling pathway reduces ECM secretion and inhibits the EMT process, thereby inhibiting Rf.²⁸ The cAMP signaling pathway inhibits the growth and reproduction of fibroblasts, blocks the synthesis of fibroblasts and collagen, and curbs the ECM deposition.²⁹ Renal hypoxia accelerates the progression of chronic nephropathy, which in turn exacerbates renal hypoxia. HIF mediates HIF-1, increasing the transcriptional activity of HIF-1α mRNA, allowing HIF-1α to accumulate in the cytoplasm, which leads to tubular fibrosis.^30,31 The abnormality of a variety of cytokines can also lead to Rf. According to the roles of these cytokines in the formation of Rf, they can be divided into pro-fibrosis cytokines and anti-fibrosis ones. The former type includes TGF-β, CTGF, angiotensin Ⅱ, etc., and the latter mainly includes osteogenesis protein-7, matrix metalloproteinase, and so on.

TGF-β1 is an important mediator in Rf pathophysiology. The abnormal expression of TGF-β and its family members can lead to endoplasmic reticulum stress and oxidative stress and subsequently cause kidney cell damage and fibrosis, ending up with renal dysfunction. The TGF-β superfamily contains 38 members.³² Therefore, the TGF-β1/Smad signaling pathway was selected in this study to explore the mechanism of SND in improving Rf. Through molecular docking, the key targets Smad2, Samd3, Smad7, and TGF-β in this pathway have certain binding activity with the main active components such as 6-gingerol, hypaconitine, aconitine, and mesaconitine. The main active ingredients in SND can regulate the TGF-β1/Smad signaling pathway by acting on important upstream and downstream targets such as Smad2, Samd3, Smad7, and TGF-β1 in this signaling pathway, which can improve hormone disorders, inhibit inflammation, and improve Rf. The possibility of taking SND to improve Rf disease was preliminarily verified by molecular docking. TGF-β1 upregulates CTGF expression, leading to Rf.³³ TGF-β is a well-known pro-fibrosis mediator, exerting its biological activity on different types of kidney cells during Rf through pathway downstream receptor-related Smads, including Smad2, Smad3, and Smad7.³⁴ TGF-β1 can induce phosphorylation and intranuclear transposition of Smad2/3. Phosphorylated Smad2 and Samd3 bind to Smad4, and the complex induces Rf.³⁵ Smad7, generated by TGF-β1 induction, preventing Samd2/Samd3 phosphorylation and TGF-β1 overactivation, acting as a negative feedback modulation.³⁶ TGF-β1 promotes Rf by preventing Smad7 expression and boosting Smad2/Smad3 expression.³⁷ MMP-9 and TIMP-1 play an important role in ECM metabolism,³⁸ and abnormal expression of both also leads to renal interstitial fibrosis. Abnormal expression of TIMP-1 during Rf inhibits MMP-9 activity and reduces extracellular matrix degradation, causing ECM accumulation and Rf.^39,40

Based on the results from network pharmacology, the TGF-β1/Smad signaling pathway is one of the key pathways for improving kidney, lung, and myocardial fiber diseases. Therefore, the improving effects of SND on Rf through the TGF-β1/Smad signaling pathway were studied using pharmacological experiments. Masson staining results showed that the degree of renal interstitial collagen deposition in the SND group was lower than that of the model group. IHC results showed that the expression of MMP-2/TIMP-1 and MMP-9/TIMP-1 was stronger in the SND group, and the expression levels of CTGF and TGF-β1 were reduced, suggesting that the SND had the ability to inhibit the transdifferentiation of tubular epithelial cells caused by UUO. WB results showed that the protein expression levels of Samd2 and Samd3 decreased, and the expression level of Smad7 increased, which also proves that the SND inhibited the TGF-β1/Smad signaling pathway to a certain extent, thereby inhibiting the EMT process and improving renal interstitial fibrosis. The results of this study also suggest the accuracy of target prediction in network pharmacology.

In summary, this study has demonstrated that SND can alleviate the oxidative stress damage of the Rf model animals. The mechanism is related to the intervention of the TGF-β1/Smad signaling pathway and the inhibition of the pro-fibrosis factors, CTGF and TIMP-1, and the promotion of the expression of anti-fibrosis cytokines, MMP-2 and MMP-9. In the follow-up study, we plan to design animal in vivo and in vitro pharmacological experiments to deeply observe the mechanism of SND in improving Rf. It is used to provide more references for its clinical application and development, and also provide new targets and theoretical basis for treating Rf diseases with SND.

5. SUPPORTING INFORMATION

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