Uncovering the Mechanisms and Molecular Targets of Weibing Formula 1 against Gastritis: Coupling Network Pharmacology with GEO Database

Weibing Formula 1, a classic traditional formula, has been widely used clinically to treat gastritis in recent years. However, the potential pharmacological mechanism of Weibing Formula 1 is still unclear to date. A network pharmacology-based strategy was performed to uncover the underlying mechanisms of Weibing Formula 1 against gastritis. Furthermore, we structured the drug-active ingredients-genes–disease network and PPI network of shared targets, and function enrichment analysis of these targets was carried out. Ultimately, Gene Expression Omnibus (GEO) datasets and real-time quantitative PCR were used to verify the related genes. We found 251 potential targets corresponding to 135 bioactive components of Weibing Formula 1. Then, 327 gastritis-related targets were known gastritis-related targets. Among which, 60 common targets were shared between potential targets of Weibing Formula 1 and known gastritis-related targets. The results of pathway enrichment analysis displayed that 60 common targets mostly participated in various pathways related to Toll-like receptor signaling pathway, MAPK signaling pathway, cytokine-cytokine receptor interaction pathway, chemokine signaling pathway, and apoptosis. Based on the GSE60427 dataset, 15 common genes were shared between differentially expressed genes and 60 candidate targets. The verification results of the GSE5081 dataset showed that except for DUOX2 and VCAM1, the other 13 genes were significantly upregulated in gastritis, which was consistent with the results in the GSE60427 dataset. More importantly, real-time quantitative PCR results showed that the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly upregulated and NOS2, EGFR, and IL-10 were downregulated in gastritis patients, while the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly downregulated and NOS2, EGFR, and IL-10 were upregulated after the treatment of Weibing Formula 1. PTGS2, NOS2, EGFR, MMP9, CXCL2, CXCL8, and IL-10 may be the important direct targets of Weibing Formula 1 in gastritis treatment. Our study revealed the mechanism of Weibing Formula 1 in gastritis from an overall and systematic perspective, providing a theoretical basis for further knowing and application of this formula in the future.

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Network Pharmacology-Based Study on the Mechanism of Pinellia ternata in Asthma Treatment

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/9732626 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Yanmin Lyu ◽

Xiangjing Chen ◽

Qing Xia ◽

Shanshan Zhang ◽

Chengfang Yao

Keyword(s):

Candidate Genes ◽

Signaling Pathway ◽

Expression Profiles ◽

Animal Experiments ◽

Enrichment Analysis ◽

Th2 Cells ◽

Network Pharmacology ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Pinellia Ternata

Background. Pinellia ternata (PT), a medicinal plant, has had an extensive application in the treatment of asthma in China, whereas its underlying pharmacological mechanisms remain unclear. Methods. Firstly, a network pharmacology method was adopted to collect activated components of PT from Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Targets of PT were assessed by exploiting the PharmMapper website; asthma-related targets were collected from the OMIM website, and target-target interaction networks were built. Secondly, critical nodes exhibiting high possibility were identified as the hub nodes in the network, which were employed to conduct Gene Ontology (GO) comment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway enrichment analysis. Finally, the tissue expression profiles of key candidate genes were identified by the Gene Expression Omnibus (GEO) database, and the therapeutic effect of PT was verified by an animal experiment. Results. 57 achievable targets of PT on asthma were confirmed as hub nodes through using the network pharmacology method. As revealed from the KEGG enrichment analysis, the signaling pathways were notably enriched in pathways of the T-cell receptor signaling pathway, JAK-STAT signaling pathway, and cytokine-cytokine receptor interaction. The expression profiles of candidate genes including Mmp2, Nr3c1, il-10, il-4, il-13, il-17a, il-2, tlr4, tlr9, ccl2, csf2, and vefgα were identified. Moreover, according to transcriptome RNA sequencing data from lung tissues of allergic mice compared to normal mice, the mRNA level of Mmp2 and il-4 was upregulated ( P < 0.001 ). In animal experiments, PT could alleviate the allergic response of mice by inhibiting the activation of T-helper type 2 (TH2) cells and the expression of Mmp2 and il-4. Conclusions. Our study provides candidate genes that may be either used for future studies related to diagnosis/prognosis or as targets for asthma management. Besides, animal experiments showed that PT could treat asthma by regulating the expression of Mmp2 and il-4.

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Exploring the Pharmacological Mechanism of Duhuo Jisheng Decoction in Treating Osteoporosis Based on Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/5510290 ◽

2021 ◽

Vol 2021 ◽

pp. 1-21

Author(s):

Zhencheng Xiong ◽

Can Zheng ◽

Yanan Chang ◽

Kuankuan Liu ◽

Li Shu ◽

...

Keyword(s):

Molecular Docking ◽

Signaling Pathway ◽

Enrichment Analysis ◽

Mapk Signaling ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Active Compounds ◽

Treatment Of Osteoporosis ◽

Target Proteins

Objective. The purpose of this work is to study the mechanism of action of Duhuo Jisheng Decoction (DHJSD) in the treatment of osteoporosis based on the methods of bioinformatics and network pharmacology. Methods. In this study, the active compounds of each medicinal ingredient of DHJSD and their corresponding targets were obtained from TCMSP database. Osteoporosis was treated as search query in GeneCards, MalaCards, DisGeNET, Therapeutic Target Database (TTD), Comparative Toxicogenomics Database (CTD), and OMIM databases to obtain disease-related genes. The overlapping targets of DHJSD and osteoporosis were identified, and then GO and KEGG enrichment analysis were performed. Cytoscape was employed to construct DHJSD-compounds-target genes-osteoporosis network and protein-protein interaction (PPI) network. CytoHubba was utilized to select the hub genes. The activities of binding of hub genes and key components were confirmed by molecular docking. Results. 174 active compounds and their 205 related potential targets were identified in DHJSD for the treatment of osteoporosis, including 10 hub genes (AKT1, ALB, IL6, MAPK3, VEGFA, JUN, CASP3, EGFR, MYC, and EGF). Pathway enrichment analysis of target proteins indicated that osteoclast differentiation, AGE-RAGE signaling pathway in diabetic complications, Wnt signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway, JAK-STAT signaling pathway, calcium signaling pathway, and TNF signaling pathway were the specifically major pathways regulated by DHJSD against osteoporosis. Further verification based on molecular docking results showed that the small molecule compounds (Quercetin, Kaempferol, Beta-sitosterol, Beta-carotene, and Formononetin) contained in DHJSD generally have excellent binding affinity to the macromolecular target proteins encoded by the top 10 genes. Conclusion. This study reveals the characteristics of multi-component, multi-target, and multi-pathway of DHJSD against osteoporosis and provides novel insights for verifying the mechanism of DHJSD in the treatment of osteoporosis.

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Bioinformatics Analysis of the Regulatory lncRNA-miRNA-mRNA Network in Patients with Neuropathic Pain

10.21203/rs.3.rs-54799/v1 ◽

2020 ◽

Author(s):

Huai-Gen Zhang ◽

Li Liu ◽

Zhi-Ping Song ◽

Da-Ying Zhang

Keyword(s):

Neuropathic Pain ◽

Signaling Pathway ◽

Interaction Analysis ◽

Enrichment Analysis ◽

Mapk Signaling ◽

Biological Information ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Protein Protein Interaction ◽

Potential Therapeutic Application

Abstract Background: Neuropathic pain (NP) is the main form of chronic pain, caused by damage to the nervous system and dysfunction. Methods: Here, we explore the key molecules involved in the development of NP condition via identification of lncRNA-miRNA-mRNA expression pattern of patients with NP. We identified differentially expressed miRNAs, lncRNA and mRNA through a comprehensive analysis strategy. Subsequently, we used bioinformatics approach to perform pathway enrichment analysis on DEGs and protein-protein interaction analysis. Combined with the three datasets, the lncRNA-miRNA-mRNA network was constructed. It will then be used as targets for drug prediction. Results: The results showed that a total of 8,251 DEGs (4,193 upregulated and 4,058 downregulated) were identified from the three microarray datasets, 959 DEmiRs (455 upregulated and 504 downregulated), 2,848 DElncs (1,324 upregulated and 1,524 downregulated). GO analysis showed that DEGs are mainly enriched in blood circulation, regulation of membrane potential and regulation of ion transmembrane transport. KEGG results showed that DEGs are enriched in neuroactive ligand-receptor interaction, PI3K-Akt signaling pathway and MAPK signaling pathway. When the correlation is set to above 0.8, a total of 31 lncRNAs, 36 miRNAs and 24 mRNAs were screened in the lncRNA-miRNA-mRNAs network. The results of drug prediction indicated the targeted drugs mainly include INDOMETHACIN, GLUTAMIC ACID and PIRACETAM. Conclusion: The lncRNA-miRNA-mRNA network has been carried out a comprehensive biological information analysis and predicted the potential therapeutic application of drugs in patients with NP. The corresponding data has a certain reference for studying the pathological mechanism of NP.

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Network Pharmacology Reveals That Resveratrol Can Alleviate COVID-19-Related Hyperinflammation

Disease Markers ◽

10.1155/2021/4129993 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Zijian Xiao ◽

Qing Ye ◽

Xiaomei Duan ◽

Tao Xiang

Keyword(s):

Signaling Pathway ◽

Antiviral Agent ◽

Interaction Network ◽

Enrichment Analysis ◽

Bioinformatic Analysis ◽

Gene Expression Omnibus ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Kegg Pathways ◽

Go Terms

Hyperinflammation is related to the development of COVID-19. Resveratrol is considered an anti-inflammatory and antiviral agent. Herein, we used a network pharmacological approach and bioinformatic gene analysis to explore the pharmacological mechanism of Resveratrol in COVID-19 therapy. Potential targets of Resveratrol were obtained from public databases. SARS-CoV-2 differentially expressed genes (DEGs) were screened out via bioinformatic analysis Gene Expression Omnibus (GEO) datasets GSE147507, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis; then, protein-protein interaction network was constructed. The common targets, GO terms, and KEGG pathways of Resveratrol targets and SARS-CoV-2 DEGs were confirmed. KEGG Mapper queried the location of common targets in the key pathways. A notable overlap of the GO terms and KEGG pathways between Resveratrol targets and SARS-CoV-2 DEGs was revealed. The shared targets between Resveratrol targets and SARS-CoV-2 mainly involved the IL-17 signaling pathway, NF-kappa B signaling pathway, and TNF signaling pathway. Our study uncovered that Resveratrol is a promising therapeutic candidate for COVID-19 and we also revealed the probable key targets and pathways involved. Ultimately, we bring forward new insights and encourage more studies on Resveratol to benefit COVID-19 patients.

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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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Anticancer Effects of Emodin on HepG2 Cell: Evidence from Bioinformatic Analysis

BioMed Research International ◽

10.1155/2019/3065818 ◽

2019 ◽

Vol 2019 ◽

pp. 1-14 ◽

Cited By ~ 3

Author(s):

Rui-sheng Zhou ◽

Xiong-Wen Wang ◽

Qin-feng Sun ◽

Zeng Jie Ye ◽

Jian-wei Liu ◽

...

Keyword(s):

Signaling Pathway ◽

Hepg2 Cells ◽

Molecular Mechanisms ◽

Mapk Signaling ◽

Ion Concentration ◽

Receptor Interaction ◽

Pathway Enrichment Analysis ◽

Mrna Levels ◽

Hub Genes ◽

Positive Regulation

Hepatocellular carcinoma (HCC) is a primary cause of cancer-related death in the world. Despite the fact that there are many methods to treat HCC, the 5-year survival rate of HCC is still at a low level. Emodin can inhibit the growth of HCC cells invitroand invivo. However, the gene regulation of emodin in HCC has not been well studied. In our research, RNA sequencing technology was used to identify the differentially expressed genes (DEGs) in HepG2 cells induced by emodin. A total of 859 DEGs were identified, including 712 downregulated genes and 147 upregulated genes in HepG2 cells treated with emodin. We used DAVID for function and pathway enrichment analysis. The protein-protein interaction (PPI) network was constructed using STRING, and Cytoscape was used for module analysis. The enriched functions and pathways of the DEGs include positive regulation of apoptotic process, structural molecule activity and lipopolysaccharide binding, protein digestion and absorption, ECM-receptor interaction, complement and coagulation cascades, and MAPK signaling pathway. 25 hub genes were identified and pathway analysis revealed that these genes were mainly enriched in neuropeptide signaling pathway, inflammatory response, and positive regulation of cytosolic calcium ion concentration. Survival analysis showed that LPAR6, C5, SSTR5, GPR68, and P2RY4 may be involved in the molecular mechanisms of emodin therapy for HCC. A quantitative real-time PCR (qRT-PCR) assay showed that the mRNA levels of LPAR6, C5, SSTR5, GPR68, and P2RY4 were significantly decreased in HepG2 cells treated with emodin. In conclusion, the identified DEGs and hub genes in the present study provide new clues for further researches on the molecular mechanisms of emodin.

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Integrating Network Pharmacology with Molecular Docking to Unravel the Active Compounds and Potential Mechanism of Simiao Pill Treating Rheumatoid Arthritis

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/5786053 ◽

2020 ◽

Vol 2020 ◽

pp. 1-16

Author(s):

Mengshi Tang ◽

Xi Xie ◽

Pengji Yi ◽

Jin Kang ◽

Jiafen Liao ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Molecular Docking ◽

Signaling Pathway ◽

Target Genes ◽

Enrichment Analysis ◽

Binding Activity ◽

New Combination ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Potential Mechanism

Objective. To explore the main components and unravel the potential mechanism of simiao pill (SM) on rheumatoid arthritis (RA) based on network pharmacological analysis and molecular docking. Methods. Related compounds were obtained from TCMSP and BATMAN-TCM database. Oral bioavailability and drug-likeness were then screened by using absorption, distribution, metabolism, and excretion (ADME) criteria. Additionally, target genes related to RA were acquired from GeneCards and OMIM database. Correlations about SM-RA, compounds-targets, and pathways-targets-compounds were visualized through Cytoscape 3.7.1. The protein-protein interaction (PPI) network was constructed by STRING. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed via R packages. Molecular docking analysis was constructed by the Molecular Operating Environment (MOE). Results. A total of 72 potential compounds and 77 associated targets of SM were identified. The compounds-targets network analysis indicated that the 6 compounds, including quercetin, kaempferol, baicalein, wogonin, beta-sitosterol, and eugenol, were linked to ≥10 target genes, and the 10 target genes (PTGS1, ESR1, AR, PGR, CHRM3, PPARG, CHRM2, BCL2, CASP3, and RELA) were core target genes in the network. Enrichment analysis indicated that PI3K-Akt, TNF, and IL-17 signaling pathway may be a critical signaling pathway in the network pharmacology. Molecular docking showed that quercetin, kaempferol, baicalein, and wogonin have good binding activity with IL6, VEGFA, EGFR, and NFKBIA targets. Conclusion. The integrative investigation based on bioinformatics/network topology strategy may elaborate on the multicomponent synergy mechanisms of SM against RA and provide the way out to develop new combination medicines for RA.

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Network Pharmacology of Yougui Pill Combined with Buzhong Yiqi Decoction for the Treatment of Sexual Dysfunction

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2019/1243743 ◽

2019 ◽

Vol 2019 ◽

pp. 1-10 ◽

Cited By ~ 2

Author(s):

Yangyun Wang ◽

Wandong Yu ◽

Chaoliang Shi ◽

Wei Jiao ◽

Junhong Li ◽

...

Keyword(s):

Sexual Dysfunction ◽

Signaling Pathway ◽

Herbal Medicines ◽

Mapk Signaling ◽

Glycyrrhetinic Acid ◽

Network Pharmacology ◽

Receptor Interaction ◽

Chemical Components ◽

Target Proteins ◽

Yougui Pill

Purpose. We aimed to find the possible key targets of Yougui pill and Buzhong Yiqi decoction for the treatment of sexual dysfunction. Materials and Methods. The composition of Yougui pill combined with Buzhong Yiqi decoction was obtained, and its effective components of medicine were screened using ADME; the component target proteins were predicted and screened based on the TCMSP and BATMAN databases. Target proteins were cross-validated using the CTD database. We performed gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses for target proteins using the Cytoscape plugin ClueGO + CluePedia and the R package clusterProfiler, respectively. Subsequently, protein-protein interaction (PPI) analyses were conducted using the STRING database. Finally, a pharmacological network was constructed. Results. The pharmacological network contained 89 nodes and 176 relation pairs. Among these nodes, there were 12 for herbal medicines (orange peel, licorice, Eucommia, Aconite, Astragalus, Chinese wolfberry, yam, dodder seed, ginseng, Cornus officinalis, Rehmannia, and Angelica), 9 for chemical components (18-beta-glycyrrhetinic acid, carvacrol, glycyrrhetinic acid, higenamine, nobilin, quercetin, stigmasterol, synephrine, and thymol), 62 for target proteins (e.g., NR3C1, ESR1, PTGS2, CAT, TNF, INS, and TP53), and 6 for pathways (MAPK signaling pathway, proteoglycans in cancer, dopaminergic synapse, thyroid hormone signaling pathway, cAMP signaling pathway, and neuroactive ligand-receptor interaction). Conclusion. NR3C1, ESR1, PTGS2, CAT, TNF, INS, and TP53 may be important targets for the key active elements in the decoction combining Yougui pill and Buzhong Yiqi. Furthermore, these target proteins are relevant to the treatment of sexual dysfunction, probably via pathways associated with cancer and signal transduction.

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Ganghuo Kanggan Decoction in Influenza: Integrating Network Pharmacology and In Vivo Pharmacological Evaluation

Frontiers in Pharmacology ◽

10.3389/fphar.2020.607027 ◽

2020 ◽

Vol 11 ◽

Author(s):

Yanni Lai ◽

Qiong Zhang ◽

Haishan Long ◽

Tiantian Han ◽

Geng Li ◽

...

Keyword(s):

Signaling Pathway ◽

Influenza A ◽

Target Prediction ◽

Enrichment Analysis ◽

New Drugs ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Active Components ◽

Compound Screening

Background: Ganghuo Kanggan decoction (GHKGD) is a clinical experience prescription used for the treatment of viral pneumonia in the Lingnan area of China, and its clinical effect is remarkable. However, the mechanism of GHKGD in influenza is still unclear.Objective: To predict the active components and signaling pathway of GHKGD and to explore its therapeutic mechanism in influenza and to verified it in vivo using network pharmacology.Methods: The potential active components and therapeutic targets of GHKGD in the treatment of influenza were hypothesized through a series of network pharmacological strategies, including compound screening, target prediction and pathway enrichment analysis. Based on the target network and enrichment results, a mouse model of influenza A virus (IAV) infection was established to evaluate the therapeutic effect of GHKGD on influenza and to verify the possible molecular mechanism predicted by network pharmacology.Results: A total of 116 candidate active compounds and 17 potential targets were identified. The results of the potential target enrichment analysis suggested GHKGD may involve the RLR signaling pathway to reduce inflammation in the lungs. In vivo experiments showed that GHKGD had a protective effect on pneumonia caused by IAV-infected mice. Compared with the untreated group, the weight loss in the GHKGD group in the BALB/c mice decreased, and the inflammatory pathological changes in lung tissue were reduced (p < 0.05). The expression of NP protein and the virus titers in lung were significantly decreased (p < 0.05). The protein expression of RIG-I, NF-kB, and STAT1 and the level of MAVS and IRF3/7 mRNA were remarkably inhibited in GHKGD group (p < 0.05). After the treatment with GHKGD, the level of Th1 cytokines (IFN-γ, TNF-α, IL-2) was increased, while the expression of Th2 (IL-5, IL4) cytokines was reduced (p < 0.05).Conclusion: Through a network pharmacology strategy and in vivo experiments, the multi-target and multi-component pharmacological characteristics of GHKGD in the treatment of influenza were revealed, and regulation of the RLR signaling pathway during the anti-influenza process was confirmed. This study provides a theoretical basis for the research and development of new drugs from GHKGD.

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A Network Pharmacology Approach to Uncover the Mechanisms of Shen-Qi-Di-Huang Decoction against Diabetic Nephropathy

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2018/7043402 ◽

2018 ◽

Vol 2018 ◽

pp. 1-14 ◽

Cited By ~ 9

Author(s):

Sha Di ◽

Lin Han ◽

Qing Wang ◽

Xinkui Liu ◽

Yingying Yang ◽

...

Keyword(s):

Diabetic Nephropathy ◽

Signaling Pathway ◽

Molecular Mechanisms ◽

Interaction Network ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Protein Protein Interaction ◽

Regulation Of Blood Pressure ◽

Protein Protein Interaction Network

Shen-Qi-Di-Huang decoction (SQDHD), a well-known herbal formula from China, has been widely used in the treatment of diabetic nephropathy (DN). However, the pharmacological mechanisms of SQDHD have not been entirely elucidated. At first, we conducted a comprehensive literature search to identify the active constituents of SQDHD, determined their corresponding targets, and obtained known DN targets from several databases. A protein-protein interaction network was then built to explore the complex relations between SQDHD targets and those known to treat DN. Following the topological feature screening of each node in the network, 400 major targets of SQDHD were obtained. The pathway enrichment analysis results acquired from DAVID showed that the significant bioprocesses and pathways include oxidative stress, response to glucose, regulation of blood pressure, regulation of cell proliferation, cytokine-mediated signaling pathway, and the apoptotic signaling pathway. More interestingly, five key targets of SQDHD, named AKT1, AR, CTNNB1, EGFR, and ESR1, were significant in the regulation of the above bioprocesses and pathways. This study partially verified and predicted the pharmacological and molecular mechanisms of SQDHD on DN from a holistic perspective. This has laid the foundation for further experimental research and has expanded the rational application of SQDHD in clinical practice.

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