Uncovering Active Ingredients and Mechanisms of Spica Prunellae in the Treatment of Colon Adenocarcinoma: A Study Based on Network Pharmacology and Bioinformatics

Background: As a well-known herb used in the treatment of colon adenocarcinoma (COAD), Spica Prunellae (SP) shows favorable clinical effect and safety in China for many years, but its active ingredients and therapeutic mechanisms against COAD remain poorly understood. Therefore, this study aims to uncover active ingredients and mechanism of SP in the treatment of COAD using a combined approach of network pharmacology and bioinformatics. Methods: A comprehensive approach mainly comprised of target prediction, network construction, pathway and functional enrichment analysis, and hub genes verification was adopted in the current study. Results: We collected 102 compounds-related genes and 3549 differently expressed genes (DEGs) following treatment with SP, and 64 disease-drug target genes between them were recognized. In addition, a total of 25 active ingredients in SP were identified.Pathway and functional enrichment analyses suggested that the mechanisms of SP against COAD might be to induce apoptosis of colon cancer cells by regulating PI3K-Akt and TNF signaling pathway. Recognition of hub genes and core functional modules was performed by constructing protein-protein interaction (PPI) network, from whichTP53, MYC, MAPK8 and CASP3 were found as the hub target genes that might play an important part in therapy for COAD. Subsequently we further compared differential expression level and assessed prognostic value of these four hub genes. These result of verification suggested that SP exerted therapeutic effects against COAD via a PPI network involving TP53, MYC, MAPK8 and CASP3. Conclusion: In this study, active ingredients and mechanism of SPin the treatment of COAD were systematically dis-cussed, which providedthe foundation for further experimental studies and mightact to promote its appropriate clinical application.

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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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Potential mechanisms of Guizhi decoction against hypertension based on network pharmacology and Dahl salt-sensitive rat model

Chinese Medicine ◽

10.1186/s13020-021-00446-x ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Jiye Chen ◽

Yongjian Zhang ◽

Yongcheng Wang ◽

Ping Jiang ◽

Guofeng Zhou ◽

...

Keyword(s):

Signaling Pathway ◽

Rat Model ◽

Experimental Studies ◽

Matrix Metalloproteinase 2 ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Therapeutic Effects ◽

Active Ingredients ◽

Active Compounds ◽

Guizhi Decoction

Abstract Background Guizhi decoction (GZD), a classical Chinese herbal formula, has been widely used to treat hypertension, but its underlying mechanisms remain elusive. The present study aimed to explore the potential mechanisms and therapeutic effects of GZD on hypertension by integrating network pharmacology and experimental validation. Methods The active ingredients and corresponding targets were collected from the Traditional Chinese Medicine Systems Pharmacology database and Analysis Platform (TCMSP). The targets related to hypertension were identified from the CTD, GeneCards, OMIM and Drugbank databases. Multiple networks were constructed to identify the key compounds, hub targets, and main biological processes and pathways of GZD against hypertension. The Surflex-Dock software was used to validate the binding affinity between key targets and their corresponding active compounds. The Dahl salt-sensitive rat model was used to evaluate the therapeutic effects of GZD against hypertension. Results A total of 112 active ingredients, 222 targets of GZD and 341 hypertension-related targets were obtained. Furthermore, 56 overlapping targets were identified, five of which were determined as the hub targets for experimental verification, including interleukin 6 (IL-6), C–C motif chemokine 2 (CCL2), IL-1β, matrix metalloproteinase 2 (MMP-2), and MMP-9. Pathway enrichment analysis results indicated that 56 overlapping targets were mainly enriched in several inflammation pathways such as the tumor necrosis factor (TNF) signaling pathway, Toll-like receptor (TLR) signaling pathway and nuclear factor kappa-B (NF-κB) signaling pathway. Molecular docking confirmed that most active compounds of GZD could bind tightly to the key targets. Experimental studies revealed that the administration of GZD improved blood pressure, reduced the area of cardiac fibrosis, and inhibited the expression of IL-6, CCL2, IL-1β, MMP-2 and MMP-9 in rats. Conclusion The potential mechanisms and therapeutic effects of GZD on hypertension may be attributed to the regulation of cardiac inflammation and fibrosis.

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Integrated Analyses Identify Immune-Related Signature Associated with Qingyihuaji Formula for Treatment of Pancreatic Ductal Adenocarcinoma Using Network Pharmacology and Weighted Gene Co-Expression Network

Journal of Immunology Research ◽

10.1155/2020/7503605 ◽

2020 ◽

Vol 2020 ◽

pp. 1-17

Author(s):

Xiang Qian ◽

Zhuo Chen ◽

Sha Sha Chen ◽

Lu Ming Liu ◽

Ai Qin Zhang

Keyword(s):

Expression Profiles ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Ductal Adenocarcinoma ◽

Network Pharmacology ◽

Active Ingredients ◽

Kaplan Meier ◽

Human Protein Atlas

The study aimed to clarify the potential immune-related targets and mechanisms of Qingyihuaji Formula (QYHJ) against pancreatic cancer (PC) through network pharmacology and weighted gene co-expression network analysis (WGCNA). Active ingredients of herbs in QYHJ were identified by the TCMSP database. Then, the putative targets of active ingredients were predicted with SwissTargetPrediction and the STITCH databases. The expression profiles of GSE32676 were downloaded from the GEO database. WGCNA was used to identify the co-expression modules. Besides, the putative targets, immune-related targets, and the critical module genes were mapped with the specific disease to select the overlapped genes (OGEs). Functional enrichment analysis of putative targets and OGEs was conducted. The overall survival (OS) analysis of OGEs was investigated using the Kaplan-Meier plotter. The relative expression and methylation levels of OGEs were detected in UALCAN, human protein atlas (HPA), Oncomine, DiseaseMeth version 2.0 and, MEXPRESS database, respectively. Gene set enrichment analysis (GSEA) was conducted to elucidate the key pathways of highly-expressed OGEs further. OS analyses found that 12 up-regulated OGEs, including CDK1, PLD1, MET, F2RL1, XDH, NEK2, TOP2A, NQO1, CCND1, PTK6, CTSE, and ERBB2 that could be utilized as potential diagnostic indicators for PC. Further, methylation analyses suggested that the abnormal up-regulation of these OGEs probably resulted from hypomethylation, and GSEA revealed the genes markedly related to cell cycle and proliferation of PC. This study identified CDK1, PLD1, MET, F2RL1, XDH, NEK2, TOP2A, NQO1, CCND1, PTK6, CTSE, and ERBB2 might be used as reliable immune-related biomarkers for prognosis of PC, which may be essential immunotherapies targets of QYHJ.

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Identification of Potentially Therapeutic Target Genes of Hepatocellular Carcinoma

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17031053 ◽

2020 ◽

Vol 17 (3) ◽

pp. 1053

Author(s):

Chengzhang Li ◽

Jiucheng Xu

Keyword(s):

Gene Expression ◽

Target Genes ◽

Expression Profiles ◽

Differential Expression Analysis ◽

Gene Expression Profiles ◽

Functional Enrichment ◽

Ppi Network ◽

Hub Genes ◽

Gene Differential Expression ◽

Oncomine Database

Background: Hepatocellular carcinoma (HCC) is a major threat to public health. However, few effective therapeutic strategies exist. We aimed to identify potentially therapeutic target genes of HCC by analyzing three gene expression profiles. Methods: The gene expression profiles were analyzed with GEO2R, an interactive web tool for gene differential expression analysis, to identify common differentially expressed genes (DEGs). Functional enrichment analyses were then conducted followed by a protein-protein interaction (PPI) network construction with the common DEGs. The PPI network was employed to identify hub genes, and the expression level of the hub genes was validated via data mining the Oncomine database. Survival analysis was carried out to assess the prognosis of hub genes in HCC patients. Results: A total of 51 common up-regulated DEGs and 201 down-regulated DEGs were obtained after gene differential expression analysis of the profiles. Functional enrichment analyses indicated that these common DEGs are linked to a series of cancer events. We finally identified 10 hub genes, six of which (OIP5, ASPM, NUSAP1, UBE2C, CCNA2, and KIF20A) are reported as novel HCC hub genes. Data mining the Oncomine database validated that the hub genes have a significant high level of expression in HCC samples compared normal samples (t-test, p < 0.05). Survival analysis indicated that overexpression of the hub genes is associated with a significant reduction (p < 0.05) in survival time in HCC patients. Conclusions: We identified six novel HCC hub genes that might be therapeutic targets for the development of drugs for some HCC patients.

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Xiaoyu Xiezhuo Drink Protects against Ischemia-Reperfusion Acute Kidney Injury in Aged Mice through Inhibiting the TGF-β1/Smad3 and HIF1 Signaling Pathways

BioMed Research International ◽

10.1155/2021/9963732 ◽

2021 ◽

Vol 2021 ◽

pp. 1-19

Author(s):

Qingqing Ye ◽

Hongbo Chen ◽

Hongzhen Ma ◽

Xiaojun Xiang ◽

Shouci Hu ◽

...

Keyword(s):

Drug Targets ◽

Ischemia Reperfusion ◽

Kidney Injury ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Ppi Network ◽

Hub Genes ◽

Aged Mice ◽

Tgf Β1

Acute kidney injury (AKI) is responsible for significant mortality among hospitalized patients that is especially troubling aged people. An effective self-made Chinese medicine formula, Xiaoyu Xiezhuo Drink (XXD), displayed therapeutic effects on AKI. However, the compositions and underlying mechanisms of XXD remain to be elucidated. In this study, we used the ultra-high-performance liquid chromatography method coupled with hybrid triple quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) to investigate the chemical components in XXD. Then, the absorbable components of XXD were identified based on the five principles and inputted into the SwissTargetPrediction and STITCH databases to identify the drug targets. AKI-related targets were collected from the GenCLiP 3, GeneCards, and DisGeNET databases. The crossover genes of XXD and AKI were identified for functional enrichment analysis. The protein-protein interaction (PPI) network of crossover genes was constructed, followed by the identification of hub genes. Subsequently, the effects and potential mechanisms of XXD on AKI predicted by the network pharmacology and bioinformatics analyses were experimentally validated in ischemia-reperfusion (I/R) injury-induced AKI aged mouse models. A total of 122 components in XXD were obtained; among them, 58 components were found that could be absorbed in the blood. There were 800 potential drug targets predicted from the 58 absorbable components in AKI which shared 36 crossover genes with AKI-related targets. The results of functional enrichment analysis indicated that crossover genes mostly associated with the response to oxidative stress and the HIF1 signaling pathway. In the PPI network analysis, 12 hub genes were identified, including ALB, IL-6, TNF, TP53, VEGFA, PTGS2, TLR4, NOS3, EGFR, PPARG, HIF1A, and HMOX1. In AKI aged mice, XXD prominently alleviated I/R injury-induced renal dysfunction, abnormal renal pathological changes, and cellular senescence, inflammation, and oxidative damage with a reduction in the expression level of the inflammatory mediator, α-SMA, collagen-1, F4/80, TP53, VEGFA, PTGS2, TLR4, NOS3, EGFR, PPARG, HIF1A, ICAM-1, TGF-β1, Smad3, and p-Smad3 and an increase of nephridial tissue p-H3, Ki67, HMOX1, MMP-9, and Smad7 levels. In summary, our findings suggest that XXD has renoprotective effects against AKI in aged mice via inhibiting the TGF-β1/Smad3 and HIF1 signaling pathways.

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Identification of potential key genes and pathway linked with sporadic Creutzfeldt-Jakob disease based on integrated bioinformatics analyses

10.1101/2020.12.21.20248688 ◽

2020 ◽

Author(s):

Basavaraj Vastrad ◽

Chanabasayya Vastrad ◽

Iranna Kotturshetti

Keyword(s):

Regulatory Network ◽

Molecular Mechanisms ◽

Target Genes ◽

Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Hub Genes ◽

Bioinformatics Analyses ◽

Go Enrichment ◽

Jakob Disease

AbstractSporadic Creutzfeldt-Jakob disease (sCJD) is neurodegenerative disease also called prion disease linked with poor prognosis. The aim of the current study was to illuminate the underlying molecular mechanisms of sCJD. The mRNA microarray dataset GSE124571 was downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were screened. Pathway and GO enrichment analyses of DEGs were performed. Furthermore, the protein-protein interaction (PPI) network was predicted using the IntAct Molecular Interaction Database and visualized with Cytoscape software. In addition, hub genes and important modules were selected based on the network. Finally, we constructed target genes - miRNA regulatory network and target genes - TF regulatory network. Hub genes were validated. A total of 891 DEGs 448 of these DEGs presented significant up regulated, and the remaining 443 down regulated were obtained. Pathway enrichment analysis indicated that up regulated genes were mainly linked with glutamine degradation/glutamate biosynthesis, while the down regulated genes were involved in melatonin degradation. GO enrichment analyses indicated that up regulated genes were mainly linked with chemical synaptic transmission, while the down regulated genes were involved in regulation of immune system process. hub and target genes were selected from the PPI network, modules, and target genes - miRNA regulatory network and target genes - TF regulatory network namely YWHAZ, GABARAPL1, EZR, CEBPA, HSPB8, TUBB2A and CDK14. The current study sheds light on the molecular mechanisms of sCJD and may provide molecular targets and diagnostic biomarkers for sCJD.

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Using Weighted Gene Co-Expression Network Analysis to Identify Key Genes Related to the Onset of Preeclampsia

10.21203/rs.3.rs-87182/v1 ◽

2020 ◽

Author(s):

Xinyang Shen ◽

Zhijian Wang ◽

Zhirui Zeng ◽

Zhenqin Huang ◽

Xiaowei Huang ◽

...

Keyword(s):

Enrichment Analysis ◽

Diagnostic Value ◽

Functional Enrichment ◽

Immune Response Gene ◽

Control Group ◽

Ppi Network ◽

Hub Genes ◽

Ontology Term ◽

Gene Data ◽

Core Genes

Abstract Background: Preeclampsia is a form of hypertension in pregnancy, which induced by complicated factors. However, the pathogenesis of the disease is unclear. The present study was aimed to discover the critical biomarkers associated with the occurrence and development of preeclampsia. Methods：Gene data profile GSE75010 was downloaded from the Gene Expression Omnibus (GEO) database and used as discovery cohort to establish a WGCNA network determining significant modules which associated with clinical traits. Subsequently, functional enrichment analysis, pathway analysis and protein-protein interaction (PPI) network construction were performed on the core genes in significant modules to identify hub genes. Then, gene data profile GSE25906 was used as verified cohort to determine their diagnostic value of hub genes. The protein expression levels of these hub genes in preeclampsia and control placental tissues were verified using immunohistochemistry method. Finally, GSEA was performed to analyze their enrichment pathways. Results: Total 33 co-expression modules were identified after the establishment of WGCNA, of which 4 gene modules were identified as significant modules because they were related to multiple (>3) clinical traits. Total 75 core genes in significant modules were analyzed, and results showed that they were mainly enriched in adaptive immune response (Gene Ontology term) and platelet activation (Kyoto Encyclopedia of Genes and Genomes term). Finally, a total of 5 genes including TYROBP, PLEK, LCP2, HCK, ITGAM were identified as hub genes which scored high in PPI network and had high diagnostic value. Furthermore, the protein level of these 5 genes in placental tissues of preeclampsia was lower than that of the control group. Moreover, these 5 genes were all enriched in 17 pathways, including autoimmunity pathway. Conclusions：These 5 genes (TYROBP, PLEK, LCP2, HCK, ITGAM) may be closely related to the pathogenesis of preeclampsia, which may also help the diagnosis and therapy of preeclampsia.

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Network pharmacology-based elucidation of the molecular mechanism underlying the anti-migraine effect of Asari Radix et Rhizoma

Tropical Journal of Pharmaceutical Research ◽

10.4314/tjpr.v18i10.10 ◽

2021 ◽

Vol 18 (10) ◽

pp. 2067-2074

Author(s):

Yun-Bin Jiang ◽

Mei Zhong ◽

Ting Huang ◽

Zhong-Hua Dai ◽

Xing-Bao Tao ◽

...

Keyword(s):

Molecular Mechanism ◽

Target Genes ◽

Enrichment Analysis ◽

Scientific Basis ◽

Network Pharmacology ◽

Overlapping Genes ◽

Hub Genes ◽

Gene Enrichment Analysis ◽

Gene Enrichment ◽

Tnf Gene

Purpose: To determine the molecular mechanism involved in the anti-migraine effect of Asari Radix et Rhizoma (ARR) using network pharmacology. Methods: The compounds present in ARR were identified through information retrieval from literature and public databases, and were screened based on absorption, distribution, metabolism, excretion and toxicity. Target genes related to the selected compounds and migraine were identified or predicted from public databases. Hub genes in ARR against migraine were identified through analysis of interactions in overlapping genes between compounds and migraine target genes, based on STRING database. Gene enrichment analysis of overlapping genes was performed using Database for Annotation, Visualization and Integrated Discovery. Results: A total of 138 compounds were selected as potential bioactive compounds in ARR. Target genes related to the selected compounds (611 genes) and migraine (278 genes) were obtained, including 71 overlapping genes. The hub genes in the anti-migraine effect of ARR were BDNF, IL6, COMT, APP and TNF. Gene enrichment analysis showed the top 10 biological processes or pathways involved in the mechanism of anti-migraine action of ARR. The tissue source of the overlapping genes was not limited to the brain. The results from gene enrichment analysis revealed that the effect of ARR on migraine was holistic, which is characteristic of traditional Chinese medicines. Conclusion: Network pharmacology has been used to decipher the molecular mechanism involved in the action of ARR against migraine. The results provide a scientific basis for the clinical effect of ARR on migraine.

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Construction of Circular RNA–MicroRNA–Messenger RNA Regulatory Network of Recurrent Implantation Failure to Explore Its Potential Pathogenesis

Frontiers in Genetics ◽

10.3389/fgene.2020.627459 ◽

2021 ◽

Vol 11 ◽

Author(s):

Jiahuan Luo ◽

Li Zhu ◽

Ning Zhou ◽

Yuanyuan Zhang ◽

Lirong Zhang ◽

...

Keyword(s):

Messenger Rna ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Differentially Expressed ◽

Implantation Failure ◽

Ppi Network ◽

Recurrent Implantation Failure ◽

Hub Genes ◽

Hub Gene ◽

Gene Regulatory

Background: Many studies on circular RNAs (circRNAs) have recently been published. However, the function of circRNAs in recurrent implantation failure (RIF) is unknown and remains to be explored. This study aims to determine the regulatory mechanisms of circRNAs in RIF.Methods: Microarray data of RIF circRNA (GSE147442), microRNA (miRNA; GSE71332), and messenger RNA (mRNA; GSE103465) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed circRNA, miRNA, and mRNA. The circRNA–miRNA–mRNA network was constructed by Cytoscape 3.8.0 software, then the protein–protein interaction (PPI) network was constructed by STRING database, and the hub genes were identified by cytoHubba plug-in. The circRNA–miRNA–hub gene regulatory subnetwork was formed to understand the regulatory axis of hub genes in RIF. Finally, the Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the hub genes were performed by clusterProfiler package of Rstudio software, and Reactome Functional Interaction (FI) plug-in was used for reactome analysis to comprehensively analyze the mechanism of hub genes in RIF.Results: A total of eight upregulated differentially expressed circRNAs (DECs), five downregulated DECs, 56 downregulated differentially expressed miRNAs (DEmiRs), 104 upregulated DEmiRs, 429 upregulated differentially expressed genes (DEGs), and 1,067 downregulated DEGs were identified regarding RIF. The miRNA response elements of 13 DECs were then predicted. Seven overlapping miRNAs were obtained by intersecting the predicted miRNA and DEmiRs. Then, 56 overlapping mRNAs were obtained by intersecting the predicted target mRNAs of seven miRNAs with 1,496 DEGs. The circRNA–miRNA–mRNA network and PPI network were constructed through six circRNAs, seven miRNAs, and 56 mRNAs; and four hub genes (YWHAZ, JAK2, MYH9, and RAP2C) were identified. The circRNA–miRNA–hub gene regulatory subnetwork with nine regulatory axes was formed in RIF. Functional enrichment analysis and reactome analysis showed that these four hub genes were closely related to the biological functions and pathways of RIF.Conclusion: The results of this study provide further understanding of the potential pathogenesis from the perspective of circRNA-related competitive endogenous RNA network in RIF.

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Exploring the Pharmacological Mechanism of the modified Chinese medicine formulas “Shenfu-Linguizhugan decoction” treating Dilated cardiomyopathy Based on Network Pharmacology

10.21203/rs.3.rs-19020/v1 ◽

2020 ◽

Author(s):

Wuxia Quan ◽

Yandong Miao

Keyword(s):

Gene Expression ◽

Chinese Medicine ◽

Dilated Cardiomyopathy ◽

Target Genes ◽

Muscle Disease ◽

Network Pharmacology ◽

Therapeutic Effects ◽

Bioactive Components ◽

Ppi Network ◽

Compound Target

Abstract Background: Dilated cardiomyopathy (DCM) is a non-ischaemic cardiac muscle disease with structural and functional myocardial aberration can lead to extensive morbidity and mortality due to complications in particular heart failure and arrhythmia. Two classic Chinese medicine formulas, Shenfu decoction and Linguizhugan decoction, were both shown to exert therapeutic effects on heart disease. Thus, modified Shenfu and Linguizhugan decoction (SFLGZGD) is recommended for treatment DCM. However, its chemical and pharmacological characteristics remain to be elucidated. In the current study, a network pharmacology approach was applied to characterize the action mechanism and target genes of SFLGZGD on DCM.Methods: The gene expression of DCM was obtained from the Gene Expression Omnibus (GEO). All compounds were obtained from the correlative databases, and active mixture were selected according to their oral bioavailability (OB) and drug-likeness (DL) index. The potential targets of SFLGZGD were obtained from the traditional Chinese medicine systems pharmacology (TCMSP) database. The compound-target and target-pathway networks were constructed. The protein-protein interactive (PPI) network generated by R software was visualized by Cytoscape, and the topology scores, functional regions, and gene annotations were analyzed using plugins of Bisogenet and CytoNCA. The potential pathways related to target genes were determined by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses.Results: A total of 963 differentially expressed genes (DEGs), including 538 upregulated genes and 425 downregulated, were obtained from GSE19303. A total of 636 ingredients in SFLGZGD were obtained, among which, 93 were chosen as bioactive components. The compound-target network included 10 bioactive components and 18 potential targets and a total of 1939 genes obtained in the PPI network, among them, a total of 16 genes were screened out. Moreover,129 terms on the GO analysis and six pathways obtained. Among these potential targets, EGFR, CDKN1A, MMP1, COL1A1, COL3A1, MMP3, ICAM1, and HSPB1 were identified as relatively high-degree targets.Conclusions: The network pharmacology-based approach in the current study has shown promising potential in identifying major therapeutic targets from TCM formulations. Besides, our study suggested that network pharmacology prediction may provide a useful tool for describing the molecular mechanism of SFLGZGD on DCM.

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