Exploration of the Mechanism of Valsartan Treatment in Chronic Renal Failure: Network Pharmacology and Experimental Validation

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Introduction
Kidney disease and associated complications have now become an important global public health problem.In recent years, the number of patients with end-stage renal disease in China has increased rapidly and will continue to increase in the next few years [1,2].Tough chronic kidney disease (CKD) is caused by many factors, good blood pressure control prevents progression of CKD [3], which is closely related to the incidence of end-stage renal disease (ESRD) and the mortality of cardiovascular disease (CVD) [4,5].With an increasing prevalence of CKD and a lack of efective treatment, this has caused serious health problems worldwide [6,7].
Studies found that valsartan has a lasting and stable blood pressure efect and few toxic side efects, especially for secondary hypertension caused by renal damage, and can reduce the mortality of heart patients with left ventricular dysfunction [8].In addition, valsartan can weaken platelet activity by attenuated COX-2/TXA2 expression through p38-MAPK and NF-κB pathways and reduce cardio thrombotic events in elderly hypertensive patients [9].Since there is no specifc clinical treatment plan for CKD, it is urgent to improve patients' symptoms and fnd efective and safe therapeutic drugs for them.As such, in this study, the network pharmacology method was used to predict potential key targets and related molecular pathways of valsartan in treating chronic renal failure, which were validated by animal experiments, as well as clarifying the role of valsartan in improving the development of chronic renal failure, and fnding preventive and treatment drugs for treatment of hypertension combined with chronic renal failure.We elucidated the role of valsartan in improving chronic renal failure to then fnd efective prevention drugs for clinical treatment of hypertension, combined with chronic renal failure.

(i)
(iv) GO and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses: In R studio software, we set "p value � 0.05" and "q value � 0.05" and assessed GO and KEGG enrichment for common targets of valsartan/chronic renal failure, drawing corresponding bar or bubble plots.
(v) Molecular docking: Te process involved selecting the top 10 active targets based on the degree values from the "valsartan-potential targets-chronic kidney failure" network diagram.Te drug compound's sdf format was exported from the Pub-Chem database and subsequently converted to mol2 format using the Open Babel GUI software.Te AutoDock software was employed for molecular processing of relevant molecules, encompassing the addition of hydrogens, designation as ligands, torsion angle detection, and torsion bond selection.Te crystal protein structures of the top 10 core targets in the protein-protein interaction 2 Journal of Clinical Pharmacy and Terapeutics (PPI) network were retrieved from the RCSB PDB database (https://www.rcsb.org).Subsequently, the Pymol software was utilized to remove water molecules, clear ligands, and save the structures in pdb format.Te protein was subjected to hydrogenation using the AutoDock software and then exported in the pdbqt format.Te docking parameters and computational methods were set to default values, and the AutoDock program was executed to perform molecular docking, followed by an examination of the docking outcomes.Te docking efcacy between active compound ligands and core target protein receptors was evaluated based on their binding energy.Te molecular docking outcomes were visualized once more using Pymol.Notably, a higher binding activity between the active compound ligands and the core target protein receptors corresponded to lower binding energy values.
(vi) Laboratory animal modeling and group random number method: Te C57BL/6 mice were divided into 5 groups (n � 5): the sham group, the model group, the valsartan low-dose group (10 mg•kg −1 ), the valsartan medium-dose group (20 mg•kg −1 ), and the valsartan high-dose group (50 mg•kg −1 ).In the established model of chronic renal failure (CRF), mice in the sham group only exposed the kidney and resutured the wound, while remaining mice used the internationally recognised 5/6 kidney resection surgery (plot method).One week after mold-making, each group of mice received drug gavage as per the experimental protocol.Te sham and model groups were given equal volume of CMC-Na solution once a day for 4 consecutive weeks.Mice in each group fasted with water 12 h before specimen collection.After intraperitoneal injection of 3% sodium pentobarbital, blood was collected from the eyes and centrifuged at 5000 r•min −1 for 15 min, and the supernatant was removed and kept in a −80 °C refrigerator.Bloodcollected mice were fxed on a sterile operating table, and kidney tissues were harvested, fxed in 4% neutral formaldehyde, dehydrated, and embedded in parafn, as other tissues were kept in a −80 °C refrigerator.
(vii) Te histopathological changes in the kidney were observed by hematoxylin•eosin (H&E) and Masson staining.Fixed liver tissues were dehydrated with gradient alcohol and embedded in parafn.
Following the preparation of 3 μm continuous sections, the samples were dewaxed using xylene, subjected to gradient alcohol hydration, and then rinsed with distilled water.Subsequently, conventional H&E and Masson staining were applied.Te glomerular disintegration atrophy, infammatory cell infltration, renal tubule deformation, collagen deposition, and renal fbrosis of mice renal tissue sections were observed under an optical microscope.We randomly observed 20 felds of each section at high magnifcation (20x) under a light microscope.(viii) Serum BUN, Cre, MDA, and T-SOD levels of mice in each group were detected as per the reagent kit (Nanjing Jiancheng Biological Engineering Institute) instructions.(ix) Te mRNA expression levels of related genes in kidney tissue were detected by quantitative realtime polymerase chain reaction (RT-qPCR).We collected partial kidney tissue from mice in each experimental group, performed total mRNA extraction using the Trizol method, employing β-actin as an internal reference gene, and conducted amplifcation reactions utilizing the Applied Biosystems QuantStudio 3 system.All primer sequences are shown in Table 1.(x) Western blotting was used to detect expression levels of related proteins in the kidney tissue of each group.Partial mice kidney tissue in each group was added with appropriate RIPA (strong) lysate and homogenized at 60 Hz for 60 s.Total protein in the supernatant was obtained after centrifugation (12,000 rpm) for 10 min.Total protein concentration was determined with an enhanced BCA protein assay kit.Ten, 5× protein loading bufer was added, heated at 95 °C for 10 min for denaturation, and stored at −20 °C.Moreover, 10% SDS-PAGE separation gel was prepared according to the kit.Electrophoresis (constant pressure) was performed at 80 V for 30 min and 120 V for 60 min.Transfer at 300 mA for 90 minutes.We used 5% skim milk powder to prevent nonspecifc binding with antibodies (room temperature shaker for 2 h) and washed with 0.1% TBST 3 × 5 min.A primary antibody was incubated at 4 °C (1 : 1000) overnight.After washing with TBST 3 times for 5 min per wash, blots were incubated with a horseradish peroxidase-labeled secondary antibody, prepared by adding 5% skim milk powder (1 : 10000) at room temperature for 60 min.Wash 3 times with 0.1% TBST for 5 min each.Labeled bands underwent a chromogenic reaction using ECL detection reagent and were visualised with a WB luminometer (5,200 multi, Tanon, China).ImageJ software was used for protein gray value analysis.
2.3.Statistical Analysis.SPSS13.0 software was used for statistical analysis.Measurement data were expressed as (x ± s).Te t-test compared diferences between the two groups, as one-way analysis of variance (ANOVA) was used for comparison between multiple groups.P < 0.05 was considered statistically diferent, P < 0.01 was considered a signifcant statistical diference, and P < 0.001 was considered a remarkable statistical diference.

Network Pharmacology Results
(i) Prediction of potential targets for valsartan action: Trough the SwissTargetPrediction and TargetNet databases, 25 and 98 potential action targets of valsartan were obtained, respectively.After gene names were unifed in a UniProt database, and all chemical components and targets were standardised and merged, with deleted duplicates, a total of 115 efective target genes were obtained.(ii) Chronic renal failure disease and drug-disease intersection targets: By searching GeneCards, PharmGKB, DrugBank, and TTD, 5,018 human targets related to chronic renal failure were found.
After removing duplicate values, a total of 4,901 human targets of chronic renal failure disease were obtained.Moreover, 66 targets common to valsartan and chronic renal failure were extracted using Venny2.1.0and considered potential core targets for valsartan to treat chronic renal failure (Figure 1 3).

Results of Animal Experiments
(i) Histopathological observation of the mouse kidney in each group: To validate results of network pharmacology, C57BL/6 mice were used to investigate the ameliorating efect of valsartan on chronic renal failure.Compared to the model group, the kidney tissue structure of the valsartan-dose group was basically restored to normal, as the glomerulus and renal interstitium were signifcantly improved, infammatory infltrates and vacuoles decreased signifcantly, renal collagen fbers decreased, and the degree of fbrosis was signifcantly improved.In addition, serum creatinine (Cre), urea nitrogen (BUN), and malondialdehyde (MDA) contents were signifcantly decreased, and total superoxide dismutase (T-SOD) was signifcantly higher, with statistically signifcant diferences (P < 0.05) (Figure 4).(ii) Analysis of real-time-per results: Compared to the model group, the mRNA expression levels of TNFα, IL-1β, and IL-6 signifcantly decreased in renal tissue at each dose of valsartan.Te mRNA expression level of IL-10 signifcantly increased, and the diference was statistically signifcant (P < 0.05) (Figure 5).(iii) Western blot analysis of results: To further validate the KEGG enrichment analysis, we detected proteins related to the calcium ion signaling pathway.
Western blot results showed that protein expression of CALM, PKCα, and CaMKIV in renal tissue of valsartan-dose mice increased signifcantly (P < 0.01 or P < 0.001) (Figure 6).

Discussion
With acceleration of the aging process in China's population, the number of chronic diseases and deaths is increasing, which threatens the health of our residents [10].

Journal of Clinical Pharmacy and Terapeutics
Hypertension is one of the most common chronic diseases, accompanied by organ function or organic damage, such as the heart, brain, and kidney, and is the main risk factor of cardio-cerebrovascular disease [11,12].It interacts with renal diseases.On the one hand, when the patient's blood pressure is not controlled and treated in a timely and correct   6 Journal of Clinical Pharmacy and Terapeutics manner, it leads to insufcient blood supply to the kidneys, causing damage to renal function and creating chronic renal failure [13,14].On the other hand, renal parenchymal lesions and renal artery lesions can increase blood pressure, forming hypertension [15,16].Terefore, attention must be paid to the interaction between hypertension and renal function damage, which is of great signifcance to formulate a reasonable and efective treatment plan.
Various studies have shown that the progression of CKD from the mild to terminal stage can be delayed by controlling hypertension and proteinuria [17,18], and valsartan can reduce blood pressure and aldosterone levels by blocking angiotensin II, reducing blood volume and sodium content in blood, improving renal function of CKD patients, and slowing disease progression [19][20][21][22], but the mechanism of valsartan in improving renal function has not been clarifed.
In recent years, network pharmacology has been applied more and more in drug development, which checks predicted targets of compounds with predicted targets of disease, along with further analyses of the potential mechanism of this compound in treating disease by constructing a network map of "drug-key target-disease" [23,24].In this study, we conducted a systematic analysis of the potential mechanism of valsartan in treating chronic renal failure using a network pharmacology approach.We identifed 10 key genes afected by valsartan in chronic renal failure, including epidermal growth factor receptor (EGFR), cyclooxygenase 2 (PTGS2), peroxisome proliferator-activated receptor γ (PPARG), tyrosine kinase receptor 2 (ERBB2), angiotensin-converting enzyme (ACE), signal transduction and transcription activator protein 3 (STAT3), matrix metalloproteinase 9 (MMP9), peroxisome proliferator-activated receptor α (PPARA), protein tyrosine   [25].In addition, PTGS2 as an enzyme complex plays an important role in the conversion of arachidonic acid to prostaglandins, and some research shows that CaMKII acts as an upstream cascade to facilitate its transcription and expression; it indicates that PTGS2 may be related to the calcium signaling pathway [26].Given the complexity of the hub target molecular docking results and KEGG enrichment analysis, the subsequent experiments in this study verifed the mechanism of valsartan in treating chronic renal failure through the calcium signaling pathway.Tis study showed that valsartan, compared with the model group, signifcantly improved the glomerular and renal interstitial structure, reduced renal collagen fber deposition, alleviated the degree of renal fbrosis, and significantly reduced serum Cre, BUN, and MDA while increasing T-SOD in mice with chronic renal failure (P < 0.05) (Figure 4).In addition, it can improve the degree of infammation in the kidneys and reduce the mRNA expression levels of TNF-α, IL-1β, IL-6, and elevated IL-10 (P < 0.05) in mouse kidney tissue (Figure 5).Te WB assay showed that valsartan could signifcantly upregulate protein expression levels of CALM, PKCα, and CaMKIV in renal tissue (P < 0.01 or P < 0.001) (Figure 6), as valsartan could improve chronic renal failure through activation of calcium ion signaling along with dose dependence.
In conclusion, by combining network pharmacology methods and construction of the "valsartan-target-chronic renal failure" network, specifc targets and mechanisms of valsartan on chronic renal failure were obtained.Te possible mechanism of valsartan in improving chronic renal failure was preliminarily explored, which may provide a new solution to treat chronic renal failure.Yet, due to numerous pathways and complex mechanisms in chronic renal failure, this must be further studied to learn if valsartan also improves chronic renal failure through other action mechanisms.
(a)).(iii) Te establishment of PPI network and screening of key targets: Te 66 common targets were imported into the STRING11.5database to obtain the PPI network maps (Figure 1(b)).Results exported in TSV format were imported into the Cytoscape software, and key targets were screened according to the degree value, as the top 10 were key targets (Figures 1(c) and 1(d)).(iv) GO and KEGG pathway enrichment analysis: By GO analysis of the gene ontology database, 1,482 cell components (CC), molecular function (MF), and biological processes (BPs) were enriched for key target genes.Tey were ranked as per the corrected P value, with the top 8 bars selected for bar chart display (Figure 2(a)).A total of 76 enriched pathways were obtained from the top 20 pathways (Figure 2(b)

Figure 1 :Figure 2 :
Figure 1: Te network pharmacology target search.(a) Te target of valsartan and chronic renal failure intersect; (b) the PPI network of valsartan targets for chronic renal failure; (c) core target map of valsartan to treat chronic renal failure; (d) the heat map of the core target in valsartan treated chronic renal failure.

Table 1 :
Primer sequence of real-time PCR.
a role in enhancing proliferative capacity and promoting cell survival.ErbB receptors could interact with the Ca 2+ -sensor and transducer protein calmodulin (CaM) directly, by phosphorylation of the receptors via CaM-dependent kinases, and regulate their activity and functions