A Network Pharmacology to Explore the Potential Targets of Canagliflozin and Dapagliflozin in Treating Atherosclerosis
Abstract
:1. Introduction
2. Materials and Methods
2.1. Prediction of Targets for Canagliflozin and Dapagliflozin
2.2. Collection of Disease Targets of Atherosclerosis
2.3. Venn Diagram Plotting
2.4. Protein-Protein Interaction (PPI)
2.5. Gene Functions and Pathway Enrichment Analysis with Potential Targets
2.6. Construction of Target Gene-Drug Network
2.7. Molecular Docking of the Target Gene
3. Results
3.1. Network Construction of Drugs and Targets
3.2. Targets of Atherosclerosis
3.3. Prediction of Canagliflozin and Dapagliflozin Targets in Atherosclerosis
3.4. Construction of PPI Networks
3.5. GO Enrichment Analysis and KEGG Pathway Enrichment Analysis
3.5.1. KEGG Pathway Enrichment Analysis
3.5.2. Biological Process Enrichment Analysis
3.5.3. Molecular Functions Enrichment Analysis
3.5.4. Cellular Components Enrichment Analysis
3.6. Network Construction of Targets-Pathways
3.7. Molecular Docking
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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GO | Description | Gene Ratio | p | Count |
---|---|---|---|---|
hsa05200 | Pathways in cancer | 19.37 | 2.45471 × 10−28 | 37 |
hsa05205 | Proteoglycans in cancer | 12.57 | 1.51356 × 10−19 | 24 |
hsa01522 | Endocrine resistance | 8.9 | 1.44544 × 10−17 | 17 |
hsa05418 | Fluid shear stress and atherosclerosis | 8.9 | 6.76083 × 10−15 | 17 |
hsa04659 | Th17 cell differentiation | 7.85 | 3.23594 × 10−14 | 15 |
hsa04520 | Adherens junction | 6.81 | 7.58578 × 10−14 | 13 |
hsa03320 | PPAR signaling pathway | 6.28 | 1.58489 × 10−12 | 12 |
hsa05120 | Epithelial cell signaling in Helicobacter pylori infection | 5.76 | 1.86209 × 10−11 | 11 |
hsa04657 | IL-17 signaling pathway | 6.28 | 2.63027 × 10−11 | 12 |
hsa05169 | Epstein–Barr virus infection | 7.85 | 1.09648 × 10−10 | 15 |
hsa05202 | Transcriptional misregulation in cancer | 7.33 | 2.81838 × 10−10 | 14 |
hsa01524 | Platinum drug resistance | 5.24 | 6.60693 × 10−10 | 10 |
hsa05204 | Chemical carcinogenesis | 5.24 | 1.90546 × 10−9 | 10 |
hsa04211 | Longevity regulating pathway | 4.71 | 3.63078 × 10−7 | 9 |
hsa05203 | Viral carcinogenesis | 5.76 | 8.12831 × 10−7 | 11 |
hsa05206 | MicroRNAs in cancer | 6.81 | 1.14815 × 10−6 | 13 |
hsa00590 | Arachidonic acid metabolism | 3.66 | 1.14815 × 10−6 | 7 |
hsa04650 | Natural killer cell-mediated cytotoxicity | 4.71 | 1.7378 × 10−6 | 9 |
hsa04610 | Complement and coagulation cascades | 3.66 | 5.49541 × 10−6 | 7 |
hsa04215 | Apoptosis-multiple species | 2.62 | 1.25893 × 10−5 | 5 |
GO | Description | Gene Ratio | p | Count |
---|---|---|---|---|
GO:0032870 | cellular response to hormone stimulus | 20.94 | 3.71535 × 10−24 | 40 |
GO:0071396 | cellular response to lipid | 19.9 | 1.38038 × 10−22 | 38 |
GO:0033002 | muscle cell proliferation | 14.66 | 2.75423 × 10−22 | 28 |
GO:0032496 | response to lipopolysaccharide | 15.71 | 5.88844 × 10−21 | 30 |
GO:0042060 | wound healing | 16.75 | 1.07152 × 10−20 | 32 |
GO:0030335 | positive regulation of cell migration | 18.32 | 1.38038 × 10−20 | 35 |
GO:1901615 | organic hydroxy compound metabolic process | 17.8 | 3.89045 × 10−20 | 34 |
GO:0043549 | regulation of kinase activity | 19.9 | 3.71535 × 10−19 | 38 |
GO:0050727 | regulation of inflammatory response | 15.18 | 7.24436 × 10−19 | 29 |
GO:0031667 | response to nutrient levels | 16.23 | 1.02329 × 10−18 | 31 |
GO:0062197 | cellular response to chemical stress | 14.14 | 3.01995 × 10−18 | 27 |
GO:0030855 | epithelial cell differentiation | 17.28 | 5.49541 × 10−17 | 33 |
GO:0050865 | regulation of cell activation | 17.28 | 7.24436 × 10−17 | 33 |
GO:0010942 | positive regulation of cell death | 16.75 | 1.38038 × 10−16 | 32 |
GO:0050900 | leukocyte migration | 13.61 | 2.51189 × 10−16 | 26 |
GO:0036293 | response to decreased oxygen levels | 12.57 | 1.28825 × 10−15 | 24 |
GO:0042493 | response to drug | 13.61 | 1.28825 × 10−15 | 26 |
GO:0070201 | regulation of establishment of protein localization | 15.18 | 2.0893 × 10−15 | 29 |
GO:0072593 | reactive oxygen species metabolic process | 10.99 | 5.24807 × 10−15 | 21 |
GO:1902532 | negative regulation of intracellular signal transduction | 14.66 | 1.1749 × 10−14 | 28 |
GO | Description | Gene Ratio | p | Count |
---|---|---|---|---|
GO:0004879 | nuclear receptor activity | 9.95 | 3.80 × 10−25 | 19 |
GO:0016773 | phosphotransferase activity, alcohol group as acceptor | 20.42 | 1.45 × 10−21 | 39 |
GO:0031406 | carboxylic acid binding | 10.47 | 1.41 × 10−15 | 20 |
GO:0005496 | steroid binding | 7.85 | 1.26 × 10−13 | 15 |
GO:0019901 | protein kinase binding | 15.71 | 1.58 × 10−13 | 30 |
GO:0004175 | endopeptidase activity | 13.09 | 2.00 × 10−13 | 25 |
GO:0004674 | protein serine/threonine kinase activity | 10.47 | 4.47 × 10−9 | 20 |
GO:0016491 | oxidoreductase activity | 13.09 | 1.02 × 10−8 | 25 |
GO:0019902 | phosphatase binding | 6.81 | 1.91 × 10−7 | 13 |
GO:0008144 | drug binding | 4.19 | 2.57 × 10−7 | 8 |
GO:0005539 | glycosaminoglycan binding | 6.81 | 1.17 × 10−6 | 13 |
GO:0005158 | insulin receptor binding | 3.14 | 1.26 × 10−6 | 6 |
GO:0042562 | hormone binding | 4.19 | 1.48 × 10−5 | 8 |
GO:0030235 | nitric-oxide synthase regulator activity | 2.09 | 2.63 × 10−5 | 4 |
GO:0016788 | hydrolase activity, acting on ester bonds | 10.47 | 3.80 × 10−5 | 20 |
GO:0004190 | aspartic-type endopeptidase activity | 2.62 | 9.12 × 10−5 | 5 |
GO:0050294 | steroid sulfotransferase activity | 1.57 | 1.05 × 10−4 | 3 |
GO:0050661 | NADP binding | 3.14 | 1.35 × 10−4 | 6 |
GO:0016209 | antioxidant activity | 3.66 | 1.78 × 10−4 | 7 |
GO:0005126 | cytokine receptor binding | 5.76 | 2.14 × 10−4 | 11 |
GO | Description | Gene Ratio | p | Count |
---|---|---|---|---|
GO:0031983 | vesicle lumen | 12.04 | 1.32 × 10−13 | 23 |
GO:0045121 | membrane raft | 11.52 | 7.76 × 10−13 | 22 |
GO:0031012 | extracellular matrix | 12.57 | 2.95 × 10−10 | 24 |
GO:0101002 | ficolin-1-rich granule | 7.85 | 5.75 × 10−10 | 15 |
GO:0005925 | focal adhesion | 9.42 | 1.12 × 10−7 | 18 |
GO:0098552 | side of membrane | 10.99 | 2.69 × 10−7 | 21 |
GO:0043235 | receptor complex | 9.42 | 2.82 × 10−6 | 18 |
GO:1904724 | tertiary granule lumen | 3.66 | 9.55 × 10−6 | 7 |
GO:0005788 | endoplasmic reticulum lumen | 6.28 | 1.35 × 10−4 | 12 |
GO:0036021 | endolysosome lumen | 1.57 | 2.14 × 10−4 | 3 |
GO:0031234 | extrinsic component of cytoplasmic side of plasma membrane | 3.66 | 4.07 × 10−4 | 7 |
GO:0098794 | postsynapse | 6.81 | 1.95 × 10−2 | 13 |
GO:1902911 | protein kinase complex | 2.62 | 2.19 × 10−2 | 5 |
GO:0030139 | endocytic vesicle | 4.71 | 2.24 × 10−2 | 9 |
GO:0005770 | late endosome | 4.19 | 3.09 × 10−2 | 8 |
GO:0034704 | calcium channel complex | 2.09 | 3.89 × 10−2 | 4 |
GO:0030425 | dendrite | 6.28 | 5.50 × 10−2 | 12 |
GO:0048471 | perinuclear region of cytoplasm | 6.81 | 6.03 × 10−2 | 13 |
GO:0015629 | actin cytoskeleton | 5.24 | 8.71 × 10−2 | 10 |
GO:0031091 | platelet alpha granule | 2.09 | 1.07 × 10−1 | 4 |
Gene | PDB ID | Affinity (kcal/mol) |
---|---|---|
AKT1 | 6HHG | −9.22 |
EGFR | 5UG9 | −9.81 |
MAPK1 | 4XJ0 | −7.79 |
MAPK14 | 4L8M | −10.57 |
RHOA | 1A2B | −5.59 |
SRC | 2H8H | −9.22 |
Gene | PDB ID | Affinity (kcal/mol) |
---|---|---|
AKT1 | 6HHG | −7.6 |
EGFR | 5UG9 | −8.31 |
MAPK1 | 4XJ0 | −7.31 |
MAPK14 | 4L8M | −11.08 |
RHOA | 1A2B | −6.90 |
SRC | 2H8H | −8.06 |
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Wang, J.; Li, D.; Ju, W.; Wang, H. A Network Pharmacology to Explore the Potential Targets of Canagliflozin and Dapagliflozin in Treating Atherosclerosis. J. Vasc. Dis. 2022, 1, 53-70. https://doi.org/10.3390/jvd1010007
Wang J, Li D, Ju W, Wang H. A Network Pharmacology to Explore the Potential Targets of Canagliflozin and Dapagliflozin in Treating Atherosclerosis. Journal of Vascular Diseases. 2022; 1(1):53-70. https://doi.org/10.3390/jvd1010007
Chicago/Turabian StyleWang, Jin, Dongning Li, Weiwei Ju, and Hongli Wang. 2022. "A Network Pharmacology to Explore the Potential Targets of Canagliflozin and Dapagliflozin in Treating Atherosclerosis" Journal of Vascular Diseases 1, no. 1: 53-70. https://doi.org/10.3390/jvd1010007
APA StyleWang, J., Li, D., Ju, W., & Wang, H. (2022). A Network Pharmacology to Explore the Potential Targets of Canagliflozin and Dapagliflozin in Treating Atherosclerosis. Journal of Vascular Diseases, 1(1), 53-70. https://doi.org/10.3390/jvd1010007