scholarly journals Investigating the Mechanisms of Pollen Typhae in the Treatment of Diabetic Retinopathy Based on Network Pharmacology and Molecular Docking

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Rongrong Zhou ◽  
De Jin ◽  
Yuqing Zhang ◽  
Liyun Duan ◽  
Yuehong Zhang ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Genes ◽  
Network Pharmacology ◽  
Docking Analysis ◽  
Pathway Network ◽  
Gene Pathway ◽  
Vegf Signaling ◽  
Vegf Signaling Pathway

Objective. To explore the main bioactive compounds and investigate the underlying mechanism of Pollen Typhae (PT) against diabetic retinopathy (DR) by network pharmacology and molecular docking analysis. Methods. Bioactive ingredients and the target proteins of PT were obtained from TCMSP, and the related target genes were acquired from the SwissTargetPrediction database. The target genes of DR were obtained from GeneCards, TTD database, DisGeNET database, and DrugBank. The compound-target interaction network was established based on Cytoscape 3.7.2. The protein-protein interaction (PPI) network was constructed via STRING database and Cytoscape 3.7.2. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were visualized through DAVID database and Bioinformatics. Ingredient-gene-pathway network analysis was conducted to further screen the ingredients, target proteins, and pathways closely related to the biological mechanism on PT for DR, and molecular docking analysis was performed by SYBYL-X 2.1.1 software. Finally, the mechanism and underlying targets of PT in the treatment of DR were predicted. Results. A total of 8 compounds and 171 intersection targets were obtained based on the online network database. 7 main compounds were screened from compound-target network, and 53 targets including the top six key targets (PTGS2, AKT1, VEGFA, MAPK3, TNF, and EGFR) were further acquired from PPI analysis. The 53 key targets covered 80 signaling pathways, among which PI3K-Akt signaling pathway, focal adhesion, Rap1 signaling pathway, VEGF signaling pathway, and HIF-1 signaling pathway were closely connected with the biological mechanism involved in the alleviation of DR by PT. Ingredient-gene-pathway network shows that AKTI, EGFR, and VEGFA were core genes, kaempferol and isorhamnetin were pivotal ingredients, and VEGF signaling pathway and Rap1 signaling pathway were closely involved in anti-DR. The docking results indicated that five main compounds (arachidonic acid, isorhamnetin, quercetin, kaempferol, and (2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one) had good binding activity with EGFR and AKT1 targets. Conclusion. The active ingredients in PT may regulate the levels of inflammatory factors, suppress the oxidative stress, and inhibit the proliferation, migration, and invasion of retinal pericytes by acting on PTGS2, AKT1, VEGFA, MAPK3, TNF, and EGFR targets through VEGF signaling pathway, PI3K-Akt signaling pathway, Rap1 signaling pathway, and HIF-1 signaling pathway to play a therapeutic role in diabetic retinopathy.

The Mechanism of Compound Danshen Dripping Pills in the Treatment of Diabetic Retinopathy Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xuedong An ◽  
LiYun Duan ◽  
YueHong Zhang ◽  
De Jin ◽  
Shenghui Zhao ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Cell Proliferation ◽  
Diabetic Retinopathy ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Active Ingredient ◽  
Network Pharmacology ◽  
Asiatic Acid ◽  
Active Components ◽  
The Core

Abstract BackgroundOur previous randomized, double-blind, placebo-controlled, multi-center clinical study showed that Compound Danshen Dripping Pills (CDDP) had a significant and safe effect in the treatment of diabetic retinopathy (DR), but its mechanism is still unclear, which we would explain based on network pharmacology and molecular docking.MethodThe active ingredients of CDDP (composed of Panax notoginseng, Salvia miltiorrhiza Bge., and Borneol) were searched in the TCMSP database. The validated target and Smiles number of the active ingredient are queried through the PubChem database, and the predicted target of the active ingredient is obtained through the Swisstarget Prediction database. The Drugbank, TTD, and DisGeNET databases were retrieved to obtain the related targets of DR. The core targets were obtained by the cluster analysis function of Cytoscape, and then the Protein-Protein Interaction was performed. The GO and KEGG signal pathways were enriched and clustered in David database. The potential active components and targets were docking with Autodock Vina, and the results were visualized by PyMOL.Result51 active components and 922 validation and prediction targets of CDDP, 715 targets of DR and 154 co-targets were obtained. Cluster analysis showed that there were two clusters, a total of 64 targets. Go and KEGG signal pathway enrichment analysis showed that the top 20 mainly included TNF and HIF-1 signaling pathway. In GO analysis, BP mainly includes positive regulation of smooth muscle cell proliferation and response to hypoxia, CC mainly includes extracellular space and extracellular domain, MF mainly includes protein binding and protein binding recognition. In KEGG database, the key genes in the TNF signaling pathway were TNF, NFkB and VEGF, in HIF-1 signaling pathway were the IL-6, STAT3, HIF1A and VEGF. Molecular docking results showed that all components of CDDP had a certain docking ability with TNF, NFkB, VEGF, IL-6, STAT3 and HIF1A, which of Asiatic acid and Salvianolic acid j was the strongest.Conclusion Based on the network pharmacology and molecular docking, the core active components of CDDP, mainly including Asiatic acid and Salvianolic acid j, which may play a role in regulating cell proliferation and response to inflammation and hypoxia by regulating the binding and recognition of intracellular and extracellular proteins, that is, mainly through TNF signaling pathway and HIF-1 signaling pathway.

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

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.

scholarly journals Elucidation of the Mechanisms and Molecular Targets of Lianhuaqingwen for Treatment of COVID-19 Based on Network Pharmacology

2021 ◽  
Vol 9 (4) ◽  
pp. 111-122
Author(s):  
Yan Luo ◽  
Si-ting Gao ◽  
Jun-xiong Cheng ◽  
Wei-jian Xiong ◽  
Wen-Fu Cao
Keyword(s):  
Target Genes ◽  
Molecular Targets ◽  
Core Gene ◽  
Mechanisms Of Action ◽  
Network Pharmacology ◽  
Pathway Network ◽  
Functional Annotations ◽  
Gene Pathway ◽  
Protein Protein Interaction ◽  
Ppi Networks

Lianhuaqingwen (LH) is the widely used in the treatment of Coronavirus disease 2019 (COVID-19). However, its mechanisms of action and molecular targets for treatment of COVID-19 are not clear. The active compounds of LH were collected and their targets were identified through the network pharmacology. The mechanism of compound multi components and multi targets and its relationship with disease are analyzed. COVID-19 targets were obtained by analyzing with TCMSP. In total, 282 active ingredients and 510 targets of LH were identified. Twenty-one target genes associated with LH and COVID-19. Protein-protein interaction (PPI) data were then obtained and PPI networks of LH putative targets and COVID-19-related targets were visualized and merged to identify the candidate targets for LH against COVID-19. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis were carried out. The gene-pathway network was constructed to screen the crucial target genes. The functional annotations of target genes were found to be related to immune regulation, host defense, inflammatory reaction and autoimmune diseases and so on. Twenty pathways including immunology, cancer, and cell processing were significantly enriched. Quercetin and luteolin might be the crucial ingredients. IL6 was the core gene and other several genes including IL1B, STAT1, IFNGR1, and NCF1 were the key genes in the gene-pathway network of LH for treatment of COVID-19. The results indicated that LH’s effects against COVID-19 might relate to regulation of immunological function through the specific biological processes and the related pathways. This study demonstrates the application of network pharmacology in evaluating mechanisms of action and molecular targets of complex herbal formulations.

scholarly journals Investigation of Active Ingredients and Mechanism of Sanao Decoction in the Treatment of Chronic Cough by Network Pharmacology

2020 ◽  
Author(s):  
Mengke Sheng ◽  
Xing Liu ◽  
Qingsong Qu ◽  
Xiaowen Wu ◽  
Yuyao Liao ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Chronic Cough ◽  
Fluid Shear Stress ◽  
Oxidant Stress ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Ingredients ◽  
Active Components ◽  
Pathway Network

Abstract Background: Chronic cough significantly affects human health and quality of life. Studies have shown that Sanao Decoction（SAD）can clinically treat chronic cough. To investigate its mechanisms, we used the method of network pharmacology to conduct research at the molecular level.Methods: The active ingredients and their targets were screened by pharmacokinetics parameters from the traditional Chinese medicine system pharmacology analysis platform (TCMSP). The relevant targets of chronic cough were obtained from two databases: GeneCards and DrugBank. Take the intersection to get potential targets of SAD to treat chronic cough and establish the component-target regulatory network by CytoScape3.7.2 and protein-protein interaction (PPI) network by STRING 1.0. The function of the target gene and related pathways were analyzed by the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) in the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The significant pathways and their relevant targets were obtained and the target-pathway network was established by CytoScape3.7.2. Finally, molecular docking of the core active components and relevant targets was performed.Results: A total of 98 active components, 113 targets were identified. The component-target and target-pathway network of SAD and PPI network were established. Enrichment analysis of DAVID indicated that 2062 terms were in biological processes, 77 in cellular components, 142 in molecular functions and 20 significant pathways. In addition, the molecular docking showed that quercetin and luteolin had a good combination with the corresponding targets.Conclusions: It indicates that the active compounds of SAD, such as quercetin, luteolin, may act on AKT1, MAPK1, RELA, EGFR, BCL2 and regulate PI3K-Akt signaling pathway, AGE-RAGE signaling pathway in diabetic complications and Fluid shear stress and atherosclerosis pathway to exert the effects of anti-inflammatory, anti-airway remodeling, anti-oxidant stress and repair airway damage to treat chronic cough.

scholarly journals Network Pharmacology‐Based Study on the Active Component and Mechanism of the Anti-Gastric-Cancer Effect of Herba Sarcandrae

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Li Han ◽  
Ying Han
Keyword(s):  
Gastric Cancer ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Target Genes ◽  
Scientific Basis ◽  
Gene Expression Omnibus ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Pathway Network

Background. Herba Sarcandrae is used in the clinical practice of traditional Chinese medicine to deal with gastric cancer. However, there are few studies on its precise mechanism. Method. In this study, a network pharmacological approach was utilized to construct a molecular/target/pathway molecular regulatory network for the anti-gastric-cancer effect of Herba Sarcandrae. The active components of Herba Sarcandrae and their potential mechanisms were explored. Chemical components of the Herba Sarcandrae were identified through a database, and they were evaluated and screened based on oral bioavailability and drug similarity. Results. Genes related to gastric cancer were found in the Gene Expression Omnibus (GEO) database, and gene targets related to anti-gastric-cancer were chosen by comparison. Using annotation, visualization, and a comprehensive discovery database, the function and related pathways of target genes were analyzed and screened. Cytoscape software was utilized to construct a component/target/pathway network for the antitumor effect of Herba Sarcandrae. Finally, 6 drug ingredients and 29 target genes related to gastric cancer were detected. IL-17 signaling pathway, NF-kappa B signaling pathway, and other signaling pathways were significantly enriched. Many signaling pathways that directly act on tumors and indirect pathways inhibit the development of gastric cancer. Conclusion. This study provides a scientific basis for further elucidating the mechanism of the anti-gastric-cancer effect of Herba Sarcandrae.

Systematic evaluation of the mechanisms of Mulberry leaf (Morus alba Linne) acting on diabetes based on network pharmacology and molecular docking

2020 ◽  
Vol 23 ◽  
Author(s):  
Qiguo Wu ◽  
Yeqing Hu
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Active Compounds ◽  
Pathway Network ◽  
Pathway Enrichment ◽  
Mulberry Leaves ◽  
Mulberry Leaf

Background: Diabetes mellitus is one of the most common endocrine metabolic disorder diseases. The application of herbal medicine to control glucose levels and improve insulin action might be a useful approach in the treatment of diabetes. Mulberry leaves (ML) has been reported to exert important activities of anti-diabetic. Objective: In this work, we aimed to explore the multi-targets and multi-pathways regulatory molecular mechanism of Mulberry leaves (ML, Morus alba Linne) acting on diabetes. Methods: Identification of active compounds of Mulberry leaves using Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Bioactive components were screened by FAF-Drugs4 website (Free ADME-Tox Filtering Tool). The targets of bioactive components were predicted from SwissTargetPrediction website, and the diabetes related targets were screened from GeneCards database. The common targets of ML and diabetes are used for Gene Ontology (GO) and pathway enrichment analysis. The visualization networks were constructed by Cytoscape 3.7.1 software. The construction of biological networks were performed to analyze the mechanisms as follows: (1) Compound-Target network; (2) Common target-Compound network; (3) Common targets protein interaction network; (4) Compound-Diabetes protein-protein interactions (PPI) network; (5) Target-Pathway network; (6) Compound-Target-Pathway network. At last, the prediction results of network pharmacology were verified by molecular docking method. Results: 17 active components were obtained by TCMSP database and FAF-Drugs4 website. 51 potential targets (11 common targets and 40 associated indirect targets) were obtained and used to build the PPI network by String database. Furthermore, the potential targets were used to GO and pathway enrichment analysis. 8 key active compounds (quercetin, Iristectorigenin A, 4-Prenylresveratrol, Moracin H, Moracin C, Isoramanone, Moracin E and Moracin D) and 8 key targets (AKT1, IGF1R, EIF2AK3, PPARG, AGTR1, PPARA, PTPN1 and PIK3R1) were obtained to play major roles in Mulberry leaf acting on diabetes. And the signal pathways involved in the mechanisms mainly include AMPK signaling pathway, PI3K-Akt signaling pathway, mTOR signaling pathway, insulin signaling pathway and insulin resistance. The molecular docking results show that the 8 key active compounds have good affinity with the key target of AKT1, and the 5 key targets (IGF1R, EIF2AK3, PPARG, PPARA and PTPN1) have better affinity than AKT1 with the key compound of quercetin. Conclusion: Based on network pharmacology and molecular docking of this work provided an important systematic and visualized basis for further understanding the synergy mechanism of ML acting on diabetes.

scholarly journals MicroRNA-183 inhibition exerts suppressive effects on diabetic retinopathy by inactivating BTG1-mediated PI3K/Akt/VEGF signaling pathway

2019 ◽  
Vol 316 (6) ◽  
pp. E1050-E1060 ◽  
Author(s):  
Zhen-Zhen Zhang ◽  
Xiu-Hong Qin ◽  
Jing Zhang
Keyword(s):  
Endothelial Cells ◽  
Diabetic Retinopathy ◽  
Cell Growth ◽  
Signaling Pathway ◽  
Cell Apoptosis ◽  
Vascular Endothelial Cells ◽  
Tube Formation ◽  
Vascular Endothelial ◽  
Vegf Signaling ◽  
Vegf Signaling Pathway

Diabetic retinopathy (DR) is a serious diabetic complication caused by both environmental and genetic factors. Molecular mechanisms of DR may lead to the discovery of reliable prognostic indicators. The current study aimed to clarify the mechanism of microRNA-183 (miR-183) in DR in relation to the PI3K/Akt/VEGF signaling pathway. Microarray-based gene expression profiling of DR was used to identify the differentially expressed genes. Sprague-Dawley rats were used for the establishment of DR models, and then miR-183 was altered by mimic or inhibitor or BTG1 was downregulated by siRNA to explore the regulatory mechanism of miR-183 in DR. Furthermore, the expression of miR-183, CD34, endothelial nitric oxide synthase (eNOS), BTG1 and the PI3K/Akt/VEGF signaling pathway-related genes as well as reactive oxygen species (ROS) level was determined, and the relationship between miR-183 and BTG1 was also verified. Cell growth, cell apoptosis, and angiogenesis were determined. Microarray analysis revealed the involvement of miR-183 in DR via the PI3K/Akt/VEGF signaling pathway by targeting BTG1. Upregulated miR-183 and downregulated BTG1 were observed in retinal tissues of DR rats. miR-183 overexpression activated the PI3K/Akt/VEGF signaling pathway, upregulated CD34, eNOS, and ROS, and inhibited BTG1. BTG1 was confirmed as a target gene of miR-183. miR-183 overexpression or BTG1 knockdown promoted cell growth and tube formation while it suppressed cell apoptosis of vascular endothelial cells in DR rats. In this study, we demonstrated that miR-183 silencing inhibiting cell growth and tube formation in vascular endothelial cells of DR rats via the PI3K/Akt/VEGF signaling pathway by upregulating BTG1.

scholarly journals Deciphering the Molecular Targets and Mechanisms of HGWD in the Treatment of Rheumatoid Arthritis via Network Pharmacology and Molecular Docking

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Wei Liu ◽  
Yihua Fan ◽  
Chunying Tian ◽  
Yue Jin ◽  
Shaopeng Du ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Differentially Expressed Genes ◽  
Target Genes ◽  
Differentially Expressed ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Target Proteins ◽  
Target Network

Background. Huangqi Guizhi Wuwu Decoction (HGWD) has been applied in the treatment of joint pain for more than 1000 years in China. Currently, most physicians use HGWD to treat rheumatoid arthritis (RA), and it has proved to have high efficacy. Therefore, it is necessary to explore the potential mechanism of action of HGWD in RA treatment based on network pharmacology and molecular docking methods. Methods. The active compounds of HGWD were collected, and their targets were identified from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and DrugBank database, respectively. The RA-related targets were retrieved by analyzing the differentially expressed genes between RA patients and healthy individuals. Subsequently, the compound-target network of HGWD was constructed and visualized through Cytoscape 3.8.0 software. Protein-protein interaction (PPI) network was constructed to explore the potential mechanisms of HGWD on RA using the plugin BisoGenet of Cytoscape 3.8.0 software. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed in R software (Bioconductor, clusterProfiler). Afterward, molecular docking was used to analyze the binding force of the top 10 active compounds with target proteins of VCAM1, CTNNB1, and JUN. Results. Cumulatively, 790 active compounds and 1006 targets of HGWD were identified. A total of 4570 differentially expressed genes of RA with a p value <0.05 and log 2fold change > 0.5 were collected. Moreover, 739 GO entries of HGWD on RA were identified, and 79 pathways were screened based on GO and KEGG analysis. The core target gene of HGWD in RA treatment was JUN. Other key target genes included FOS, CCND1, IL6, E2F2, and ICAM1. It was confirmed that the TNF signaling pathway and IL-17 signaling pathway are important pathways of HGWD in the treatment of RA. The molecular docking results revealed that the top 10 active compounds of HGWD had a strong binding to the target proteins of VCAM1, CTNNB1, and JUN. Conclusion. HGWD has important active compounds such as quercetin, kaempferol, and beta-sitosterol, which exert its therapeutic effect on multiple targets and multiple pathways.

scholarly journals Elucidation of the Mechanisms and Molecular Targets of Sanhuang Xiexin Decoction for Type 2 Diabetes Mellitus Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Manman Xu ◽  
Zhonghao Li ◽  
Lu Yang ◽  
Wujianwen Zhai ◽  
Nina Wei ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Signaling Pathway ◽  
Protein Interactions ◽  
Network Pharmacology ◽  
Pathway Network ◽  
Gene Pathway ◽  
The Core ◽  
Key Genes ◽  
Differential Expressed Genes

Sanhuang Xiexin Decoction (SXD) is commonly used to treat type 2 diabetes mellitus (T2DM) in clinical practice of traditional Chinese medicine (TCM). In order to elucidate the specific analysis mechanisms of SXD for T2DM, the method of network pharmacology was applied to this article. First, the effective ingredients of SXD were obtained and their targets were identified based on the TCMSP database. The T2DM-related targets screened from the GEO database were also collected by comparing the differential expressed genes between T2DM patients and healthy individuals. Then, the common targets in SXD-treated T2DM were obtained by intersecting the putative targets of SXD and the differential expressed genes of T2DM. And the protein–protein interaction (PPI) network was established using the above common targets to screen key genes through protein interactions. Meanwhile, these common targets were used for GO and KEGG analyses to further elucidate how they exert antidiabetic effects. Finally, a gene pathway network was established to capture the core one in common targets enriched in the major pathways to further illustrate the role of specific genes. Based on the data obtained, a total of 67 active compounds and 906 targets of SXD were identified. Four thousand one hundred and seventy-six differentially expressed genes with a P value < 0.005 and ∣log2fold change∣>0.5 were determined between T2DM patients and control groups. After further screening, thirty-seven common targets related to T2DM in SXD were finally identified. Through protein interactions, the top 5 genes (YWHAZ, HNRNPA1, HSPA8, HSP90AA1, and HSPA5) were identified. It was found that the functional annotations of target genes were associated with oxygen levels, protein kinase regulator, mitochondria, and so on. The top 20 pathways including the PI3K-Akt signaling pathway, cancers, HIF-1 signaling pathway, and JAK-STAT signaling pathway were significantly enriched. CDKN1A was shown to be the core gene in the gene-pathway network, and other several genes such as CCND1, ERBB2, RAF1, EGF, and VEGFA were the key genes for SXD against T2DM. Based on the network pharmacology approach, we identified key genes and pathways related to the prognosis and pathogenesis of T2DM and also provided a feasible method for further studying the chemical basis and pharmacology of SXD.

Sign in / Sign up

Export Citation Format

Share Document