Network Pharmacology-Based Approach to Investigate the Mechanisms ofHedyotis diffusaWilld. in the Treatment of Gastric Cancer

Background.Hedyotis diffusaWilld. (HDW) is one of the renowned herbs often used in the treatment of gastric cancer (GC). However, its curative mechanism has not been fully elucidated.Objective. To systematically investigate the mechanisms of HDW in GC.Methods. A network pharmacology approach mainly comprising target prediction, network construction, and module analysis was adopted in this study.Results. A total of 353 targets of the 32 bioactive compounds in HDW were obtained. The network analysis showed that CA isoenzymes, p53, PIK3CA, CDK2,P27Kip1, cyclin D1, cyclin B1, cyclin A2, AKT1, BCL2, MAPK1, and VEGFA were identified as key targets of HDW in the treatment of GC. The functional enrichment analysis indicated that HDW probably produced the therapeutic effects against GC by synergistically regulating many biological pathways, such as nucleotide excision repair, apoptosis, cell cycle, PI3K/AKT/mTOR signaling pathway, VEGF signaling pathway, and Ras signaling pathway.Conclusions. This study holistically illuminates the fact that the pharmacological mechanisms of HDW in GC might be strongly associated with its synergic modulation of apoptosis, cell cycle, differentiation, proliferation, migration, invasion, and angiogenesis.

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Based on Network Pharmacology to Explore the Molecular Mechanism of Buzhong Yiqi Decoction for the Treatment of Gastric Cancer

10.21203/rs.3.rs-1098024/v1 ◽

2021 ◽

Author(s):

Ruiping Yang ◽

Xiaojing Lin ◽

Chunhui Tao ◽

Ruixue Jiang

Keyword(s):

Gastric Cancer ◽

Molecular Dynamics ◽

Molecular Docking ◽

Signaling Pathway ◽

Molecular Mechanism ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Dynamics Simulation ◽

Network Pharmacology ◽

Active Ingredients

Abstract BackgroundBuzhong Yiqi Decoction (BZYQD) has been widely accepted as an alternative treatment for gastric cancer (GC) in China. The present study set out to determine the potential molecular mechanism of BZYQD in the treatment of GC by means of network pharmacology, molecular docking, and molecular dynamics simulation.MethodsThe potential active ingredients and targets of BZYQD were screened out through the Traditional Chinese Medicine Systems Pharmacology (TCMSP). GC-related targets were screened out through the GeneCards database, and the intersection targets of BZYQD and GC were obtained by using the Venn diagram online tool. Then, the TCM-Active Ingredient-Target network was constructed by using the Cytoscape, and the protein-protein interaction (PPI) network was constructed by using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the effective targets of BZYQD in GC were performed through the Metascape platform. Finally, the molecular docking between the compounds and the target proteins was performed by using the AutoDock Vina software. The simulation of molecular dynamics was conducted for the optimal protein-ligand complex obtained by molecular docking using the Amber18 software.ResultsA total of 150 active ingredients of BZYQD were retrieved, corresponding to 136 targets of GC. The key active ingredients were quercetin, kaempferol, nobiletin, naringenin, and formononetin. The core targets were AKT1, STAT3, TP53, MAPK1, and MAPK3. GO functional enrichment analysis showed that BZYQD treated GC by affecting various biological processes such as oxidative stress, chemical stress, lipopolysaccharide reaction, and apoptosis. KEGG pathway enrichment analysis indicated that the apoptosis signaling pathway, PI3K/Akt signaling pathway, proteoglycan in cancer, IL-17 signaling pathway, TNF signaling pathway, and HIF-1 signaling pathway were involved. Molecular docking results revealed the highest binding energy for MAPK3 and naringenin. The stable binding of MAPK3 and naringenin was also demonstrated in the molecular dynamics simulation test, with the binding free energy of -25kcal/mol.ConclusionThis study preliminarily revealed the multi-component, multi-target, and multi-pathway characteristics of BZYQD against GC, laying a scientific basis for further research on the molecular mechanism of BZYQD.

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Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207322666190717124507 ◽

2019 ◽

Vol 22 (6) ◽

pp. 411-420 ◽

Cited By ~ 5

Author(s):

Xian-Jun Wu ◽

Xin-Bin Zhou ◽

Chen Chen ◽

Wei Mao

Keyword(s):

Cardiovascular Disease ◽

Cardiovascular Diseases ◽

Signaling Pathway ◽

Kegg Pathway ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Therapeutic Effects ◽

Pathway Enrichment ◽

Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

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Exploring the Potential of Capsaicin Against Cancer Metastasis Based on TGF-β Signaling Modulation Through Module-based Network Pharmacology Approach

Current Drug Discovery Technologies ◽

10.2174/1570163816666190515104041 ◽

2020 ◽

Vol 17 (5) ◽

pp. 647-660 ◽

Cited By ~ 1

Author(s):

Shivananda Kandagalla ◽

Sharath Belenahalli Shekarappa ◽

Gollapalli Pavan ◽

Umme Hani ◽

Manjunatha Hanumanthappa

Keyword(s):

Amino Acid ◽

Amino Acid Composition ◽

Signaling Pathway ◽

Acid Composition ◽

Protein Interaction ◽

Cancer Metastasis ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Mode Analysis ◽

Network Pharmacology

Background: Capsaicin is an active alkaloid /principal component of red pepper responsible for the pungency of chili pepper. Capsaicin by changing the intracellular redox homeostasis regulate a variety of signaling pathways ultimately producing a divergent cellular outcome. Several reports showed the potential of capsaicin against cancer metastasis, however unexplored molecular mechanism is still an active part of the research. Several growth factors have a critical role during cancer metastasis among them TGF- β signaling play a vital role. Methods: The present study aimed at analyzing capsaicin modulation of TGF-β signaling using network pharmacology approach. The chemical and protein interaction data of capsaicin was curated and abstracted using STITCH4.0, PubChem and ChEMBL database. Further, the compiled data set was subjected to the pathway and functional enrichment analysis using Protein Analysis THrough Evolutionary Relationship (PANTHER) and, Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. Meanwhile, the pattern of amino acid composition across the capsaicin targets was analyzed using the EMBOSS Pepstat tool. Capsaicin targets involved in TGF- β were identified and their Protein-Protein Interaction (PPI) network constructed using STRING v10 and Cytoscape (v 3.2.1). From the above-constructed network, the clusters were mined using the MCODE clustering algorithm and finally binding affinity of capsaicin with its targets involved in TGF-β signaling pathway was analyzed using Autodock Vina. Results: The analysis explored capsaicin targets and, their associated functional and pathway annotations. Besides, the analysis also provides a detailed distinct pattern of amino acid composition across the capsaicin targets. The capsaicin targets described as MAPK14, JUN, SMAD3, MAPK3, MAPK1 and MYC involved in TGF-β signaling pathway through pathway enrichment analysis. The binding mode analysis of capsaicin with its targets has shown high affinity with MAPK3, MAPK1, JUN and MYC. Conclusion: The study explores the potential of capsaicin as a potent modulator of TGF-β signaling pathway during cancer metastasis and proposes new methodology and mechanism of action of capsaicin against TGF- β signaling pathway.

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The Mechanism Study of Xiao-Xian-Xiong Decoction in the Treatment of Atherosclerosis with Network Pharmacology

10.21203/rs.3.rs-73640/v1 ◽

2020 ◽

Author(s):

Liucheng Xiao ◽

Zonghuan Li ◽

Chongyuan Fan ◽

Chenggong Zhu ◽

Xingyu Ma ◽

...

Keyword(s):

Cell Proliferation ◽

Signaling Pathway ◽

Mapk Pathway ◽

Enrichment Analysis ◽

Foam Cells ◽

Functional Enrichment ◽

Network Pharmacology ◽

Mechanism Study ◽

Ppi Networks

Abstract Background: Xiao-Xian-Xiong decoction is a useful formula in the treatment of atherosclerosis in traditional Chinese medicine. In this study, we aimed to investigate the function of Xiao-Xian-Xiong decoction in the treatment of atherosclerosis. Methods: In this study, we conducted the method of network pharmacology and molecular docking to discover the mechanism of Xiao-Xian-Xiong decoction against atherosclerosis. Then, we validated the function of Xiao-Xian-Xiong decoction in atherosclerosis in vitro. We investigated the function and mechanism of Xiao-Xian-Xiong decoction in RAW264.7 macrophage-derived foam cells.Results: We identified 213 targets of Xiao-Xian-Xiong decoction and 331 targets of atherosclerosis. The PPI networks of Xiao-Xian-Xiong decoction and atherosclerosis were constructed. Furthermore, the two PPI networks were merged and the core PPI network was obtained. Then, functional enrichment analysis was conducted with GO and KEGG signaling pathway analysis. KEGG analysis indicated Xiao-Xian-Xiong decoction was correlated with ubiquitin mediated proteolysis pathway, PI3K-AKT pathway, MAPK pathway, Notch signaling pathway, and TGF-β signaling pathway. At last, we validated the function of Xiao-Xian-Xiong decoction with atherosclerosis in vitro. Xiao-Xian-Xiong decoction reduced lipid accumulation and promoted the outflow of cholesterol in RAW264.7-derived foam cells. Xiao-Xian-Xiong decoction increased the expression of ABCA1 and ABCG1 protein in foam cells. ABCA1 and ABCG1 were related with regulation of the inflammatory pathway and cell proliferation in atherosclerosis.Conclusions: Combined the mechanism of available treatments of atherosclerosis, we inferred Xiao-Xian-Xiong decoction could alleviate atherosclerosis by inhibiting inflammatory response and cell proliferation.

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Network pharmacology, molecular docking, and experimental study for the mechanisms of Qishen Yiqi Pills against Cardiovascular Diseases

10.21203/rs.3.rs-889464/v1 ◽

2021 ◽

Author(s):

Jie-wen Zhao ◽

Hai-dong Liu ◽

Ming-yin Man ◽

Lv-ya Wang ◽

Ning Li ◽

...

Keyword(s):

Molecular Docking ◽

Cardiovascular Diseases ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Network Pharmacology ◽

Literature Mining ◽

Therapeutic Effects ◽

Active Components

Abstract Background Qishen Yiqi Pills (QSYQP) is a traditional Chinese compound recipe. However, our understanding of its mechanism has been hindered due to the complexity of its components and targets. In this work, the network pharmacology-based approaches were used to explore QSYQP’s pharmacological mechanism on treating cardiovascular diseases (CVD). Results From ETCM and TCM MESH databases we collected QSYQP’s 333 active components and their 674 putative targets. We constructed the sub-network influence by CVD genes and found that 40% QSYQP targets appeared in 20 modules, in which QSYQP’s targets and CVD genes co-existed as hub nodes in the sub-network. Functional enrichment analysis suggested that the 42 key targets were mainly expressed in platelets, blood vessels, cardiomyocytes, and other tissues. The main signaling pathways regulated and controlled by the key targets were inflammation, immunity, blood coagulation and energy metabolism. Network and pathway analysis identified 7 key targets, which were regulated by 7 compounds of QSYQP. 26 of the 42 important targets, including the 7 key targets were verified by literature mining. Twelve pairs of interactions between key targets and QSYQP’s compounds were validated by molecular docking. Further validation experiments suggested that QSYQP suppressed H/R induced apoptosis and cytoskeleton disruption of cardiomyocytes. Western blotting showed that the expression of cardiovascular diseases-related genes including ACTC1, FoxO1 and DIAPH1 was significantly decreased by establishing the hypoxia-reoxygenation model in vitro, while the protein expression of experimental group was significantly increased by adding QSYQP or its ingredients. Conclusion These results indicated the correlation of QSYQP treatment to the therapeutic effects of CVD. At the molecular level, this study revealed the multicomponent and multitargeting mechanisms of QSYQP in the regulation and treatment of cardiovascular diseases, potentially providing a reference for the further utilization of QSYQP.

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Molecular Mechanism of Gelsemium elegans (Gardner and Champ.) Benth. Against Neuropathic Pain Based on Network Pharmacology and Experimental Evidence

Frontiers in Pharmacology ◽

10.3389/fphar.2021.792932 ◽

2022 ◽

Vol 12 ◽

Author(s):

Wancai Que ◽

Zhaoyang Wu ◽

Maohua Chen ◽

Binqing Zhang ◽

Chuihuai You ◽

...

Keyword(s):

Molecular Dynamics ◽

Neuropathic Pain ◽

Molecular Dynamics Simulation ◽

Experimental Evidence ◽

Signaling Pathway ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Dynamics Simulation ◽

Network Pharmacology ◽

Holistic View

Gelsemium elegans (Gardner and Champ.) Benth. (Gelsemiaceae) (GEB) is a toxic plant indigenous to Southeast Asia especially China, and has long been used as Chinese folk medicine for the treatment of various types of pain, including neuropathic pain (NPP). Nevertheless, limited data are available on the understanding of the interactions between ingredients-targets-pathways. The present study integrated network pharmacology and experimental evidence to decipher molecular mechanisms of GEB against NPP. The candidate ingredients of GEB were collected from the published literature and online databases. Potentially active targets of GEB were predicted using the SwissTargetPrediction database. NPP-associated targets were retrieved from GeneCards, Therapeutic Target database, and DrugBank. Then the protein-protein interaction network was constructed. The DAVID database was applied to Gene Ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis. Molecular docking was employed to validate the interaction between ingredients and targets. Subsequently, a 50 ns molecular dynamics simulation was performed to analyze the conformational stability of the protein-ligand complex. Furthermore, the potential anti-NPP mechanisms of GEB were evaluated in the rat chronic constriction injury model. A total of 47 alkaloids and 52 core targets were successfully identified for GEB in the treatment of NPP. Functional enrichment analysis showed that GEB was mainly involved in phosphorylation reactions and nitric oxide synthesis processes. It also participated in 73 pathways in the pathogenesis of NPP, including the neuroactive ligand-receptor interaction signaling pathway, calcium signaling pathway, and MAPK signaling pathway. Interestingly, 11-Hydroxyrankinidin well matched the active pockets of crucial targets, such as EGFR, JAK1, and AKT1. The 11-hydroxyrankinidin-EGFR complex was stable throughout the entire molecular dynamics simulation. Besides, the expression of EGFR and JAK1 could be regulated by koumine to achieve the anti-NPP action. These findings revealed the complex network relationship of GEB in the “multi-ingredient, multi-target, multi-pathway” mode, and explained the synergistic regulatory effect of each complex ingredient of GEB based on the holistic view of traditional Chinese medicine. The present study would provide a scientific approach and strategy for further studies of GEB in the treatment of NPP in the future.

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Mechanisms of Compound Kushen Injection for Treatment of Bladder Cancer Based on Bioinformatics and Network Pharmacology With Experimental Validation

10.21203/rs.3.rs-71493/v1 ◽

2020 ◽

Author(s):

Lihui Zhang ◽

Wanying Zhang ◽

Jiaming Xiong ◽

Xiumei Duan ◽

Lina Hai ◽

...

Keyword(s):

Bladder Cancer ◽

Target Genes ◽

Medicinal Preparation ◽

Malignant Neoplasm ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Bladder Cancer Cell Line ◽

Network Pharmacology ◽

Therapeutic Effects ◽

Gene And Protein Expression

Abstract Background: Bladder cancer is the most common malignant neoplasm of the urinary system. CompoundKushen injection (CKI) is a Chinese medicinal preparation that has been used clinically to treat varioustypes of cancers for more than 20 years. However, the pharmacological effect of CKI on bladder cancerrequires further clarification.Methods: Network pharmacology combined with bioinformatics was used to elucidate the therapeuticmechanism and potential targets of CKI in bladder cancer. The mechanism by which CKI is effective againstbladder cancer was further verified in vitro using the human bladder cancer cell line T24.Results: Network pharmacology analysis identified 35 active compounds and 268 target genes of CKI.Bioinformatics data mining revealed 5500 differentially expressed genes associated with bladder cancer.Common genes of CKI and bladder cancer suggested that CKI exerts anti-bladder cancer effects byregulating genes such as MMP-9, JUN, EGFR, and ERK1. Functional enrichment analysis indicated thatCKI has a therapeutic effect on bladder cancer by synergistically regulating certain biological processes,including cell proliferation, cell migration, and cell apoptosis. In addition, Kyoto Encyclopedia of Genes andGenomes enrichment analysis implicated pathways related to cancer, bladder cancer, and the PI3K-Aktsignaling pathway. Consistently, cell experiments indicated that CKI could inhibit proliferation andmigration of T24 bladder cancer cells, and induce their apoptosis. Moreover, RT-qPCR and western blotresults indicated that CKI may treat bladder cancer by downregulating gene and protein expression levels,respectively of MMP-9, JUN, EGFR, and ERK1.Conclusions: CKI can inhibit proliferation and migration, and induce apoptosis of T24 bladder cancer cellsthrough multiple biological pathways and targets. CKI also has significant effects on regulation of key genesand proteins associated with bladder cancer. Overall, our findings provide solid evidence and deepen currentunderstanding of the therapeutic effects of CKI for bladder cancer, and further support its clinical use.

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Uncovering the Key miRNAs and Targets of the Liuwei Dihuang Pill in Diabetic Nephropathy-Related Osteoporosis based on Weighted Gene Co-Expression Network and Network Pharmacology Analysis

Endocrine Metabolic & Immune Disorders - Drug Targets ◽

10.2174/1871530321666210215161921 ◽

2021 ◽

Vol 21 ◽

Author(s):

Ming Ming Liu ◽

Nan Ning Lv ◽

Rui Geng ◽

Zhen Hua ◽

Yong Ma ◽

...

Keyword(s):

Diabetic Nephropathy ◽

Network Analysis ◽

Signaling Pathway ◽

Diabetic Complications ◽

Cellular Response ◽

Mapk Signaling ◽

Functional Enrichment ◽

Network Pharmacology ◽

Integrated Analysis ◽

Therapeutic Effects

Background: Diabetic nephropathy-related osteoporosis (DNOP) is the most common comorbid bone metabolic disorder associated with diabetes mellitus (DM). The Liuwei Dihuang Pill (LWD) is a traditional Chinese herbal medicine widely used to treat diabetic complications, including diabetic nephropathy (DN). This study aimed to identify the biomarkers of the mechanisms of DNOP in LWD with systems biology approaches. Methods: Herein, we performed an integrated analysis of the GSE51674 and GSE63446 datasets from the GEO database via weighted gene co-expression network and network pharmacology (WGCNA) analysis. In addition, a network pharmacology approach, including bioactive compounds, was used with oral bioavailability (OB) and drug-likeness (DL) evaluation. Next, target prediction, functional enrichment analysis, network analysis, and virtual docking were used to investigate the mechanisms of LWD in DNOP. Results : WGCNA successfully identified 63 DNOP-related miRNAs. Among them, miR-574 was significantly upregulated in DN and OP samples. A total of 117 targets of 22 components associated with LWD in DNOP were obtained. The cellular response to nitrogen compounds, the AGE-RAGE signaling pathway in diabetic complications, and the MAPK signaling pathway were related to the main targets. Network analysis showed that kaempferol and quercetin were the most significant components. MAPK1 was identified as a potential target of miR-574 and the hub genes in the protein-protein interaction (PPI) network. The docking models demonstrated that kaempferol and quercetin had a strong binding affinity for Asp 167 of MAPK1. Conclusion: This study demonstrated that miR-574 may play important roles in DNOP, and the therapeutic effects of kaempferol and quercetin on LWD in DNOP might be mediated by miR-574 by targeting MAPK1. Our results provide new perspectives for further studies on the anti-DNOP mechanism of LWD.

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Network pharmacology and molecular docking approaches to investigating the mechanism of action of Zanthoxylum bungeanum in the treatment of oxidative stress-induced diseases

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207323999201117112316 ◽

2020 ◽

Vol 23 ◽

Author(s):

Rong Zhao ◽

Meng-Meng Zhang ◽

Dan Wang ◽

Wei Peng ◽

Qing Zhang ◽

...

Keyword(s):

Oxidative Stress ◽

Molecular Docking ◽

Signaling Pathways ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Network Pharmacology ◽

Therapeutic Effects ◽

Active Components ◽

Active Compounds ◽

Zanthoxylum Bungeanum

Background: Zanthoxylum bungeanum Maxim., a traditional Chinese herbal medicine, has been reported to possess therapeutic effects on diseases induced by oxidative stress (DOS), such as atherosclerosis and diabetes complication. However, the active components and its related mechanisms are still not systematically reported. Objective: The current study was aimed to explore the main active ingredients and its molecular mechanisms of Z. bungeanum for treating DOS using network pharmacology combined with molecular docking simulation. Methods: The active components of Z. bungeanum pericarps, in addition to the interacting targets, were identified from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. These components were filtered using the parameters of oral bioavailability and drug-likeness, and the targets related to DOS were obtained from the Genecards and OMIM database. Furthermore, the overlapping genes were obtained, and a protein-protein interaction was visualized using the STRING database. Next, the Cytoscape software was employed to build a disease/drug/component/target network, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using R software. Finally, the potential active compounds and their related targets were validated using molecular docking technology. Results: A total of 61 active compounds, 280 intersection genes, and 105 signaling pathways were obtained. Functional enrichment analysis suggested that DOS occurs possibly through the regulation of many biological pathways, such as AGERAGE and HIF-1 signaling pathways. Thirty of the identical target genes showed obvious compact relationships with others in the STRING analysis. Three active compounds, quercetin, diosmetin, and beta-sitosterol, interacting with the four key targets, exhibited strong affinities. Conclusion: The findings of this study not only indicate the main mechanisms involving in the oxidative stress-induced diseases, but also provide the basis for further research on the active components of Z. bungeanum for treating DOS.

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Network Pharmacology-Based Prediction of Mechanism of Shenzhuo Formula for Application to DKD

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/6623010 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Xinmiao Wang ◽

Haoyu Yang ◽

Lili Zhang ◽

Lin Han ◽

Sha Di ◽

...

Keyword(s):

Rna Polymerase Ii ◽

Signaling Pathway ◽

Topological Analysis ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Regulation Of Transcription ◽

Therapeutic Effects ◽

Active Ingredients ◽

Go Analysis

Background. Shenzhuo formula (SZF) is a traditional Chinese medicine (TCM) prescription which has significant therapeutic effects on diabetic kidney disease (DKD). However, its mechanism remains unknown. Therefore, this study aimed to explore the underlying anti-DKD mechanism of SZF. Methods. The active ingredients and targets of SZF were obtained by searching TCMSP, TCMID, SwissTargetPrediction, HIT, and literature. The DKD target was identified from TTD, DrugBank, and DisGeNet. The potential targets were obtained and PPI network were built after mapping SZF targets and DKD targets. The key targets were screened out by network topology and the “SZF-key targets-DKD” network was constructed by Cytoscape. GO analysis and KEGG pathway enrichment analysis were performed by using DAVID, and the results were visualized by Omicshare Tools. Results. We obtained 182 potential targets and 30 key targets. Furthermore, a “SZF-key targets-DKD” network topological analysis showed that active ingredients like M51, M21, M5, M71, and M28 and targets like EGFR, MMP9, MAPK8, PIK3CA, and STAT3 might play important roles in the process of SZF treating in DKD. GO analysis results showed that targets were mainly involved in positive regulation of transcription from RNA polymerase II promoter, inflammatory response, lipopolysaccharide-mediated signaling pathway, and other biological processes. KEGG showed that DKD-related pathways like TNF signaling pathway and PI3K-Akt signaling pathway were at the top of the list. Conclusion. This research reveals the potential pharmacological targets of SZF in the treatment of DKD through network pharmacology and lays a foundation for further studies.

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