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A Bioinformatics Investigation into the Pharmacological Mechanisms of Sodium-Glucose Co-transporter 2 Inhibitors in Diabetes Mellitus and Heart Failure Based on Network Pharmacology
PURPOSE: Diabetes mellitus (DM) is a major risk factor for the development of heart failure (HF). Sodium-glucose co-transporter 2 (SGLT2) inhibitors have demonstrated consistent benefits in the reduction of hospitalization for HF in patients with DM. However, the pharmacological mechanism is not cle...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270285/ https://www.ncbi.nlm.nih.gov/pubmed/34028657 http://dx.doi.org/10.1007/s10557-021-07186-y |
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author | Mai, Ziling Li, Huanqiang Chen, Guanzhong Chen, Enzhao Liu, Liwei Lun, Zhubin Lai, Wenguang Zhou, Chunyun Yu, Sijia Liu, Jin Chen, Shiqun Chen, Jiyan Liu, Yong |
author_facet | Mai, Ziling Li, Huanqiang Chen, Guanzhong Chen, Enzhao Liu, Liwei Lun, Zhubin Lai, Wenguang Zhou, Chunyun Yu, Sijia Liu, Jin Chen, Shiqun Chen, Jiyan Liu, Yong |
author_sort | Mai, Ziling |
collection | PubMed |
description | PURPOSE: Diabetes mellitus (DM) is a major risk factor for the development of heart failure (HF). Sodium-glucose co-transporter 2 (SGLT2) inhibitors have demonstrated consistent benefits in the reduction of hospitalization for HF in patients with DM. However, the pharmacological mechanism is not clear. To investigate the mechanisms of SGLT2 inhibitors in DM with HF, we performed target prediction and network analysis by a network pharmacology method. METHODS: We selected targets of SGLT2 inhibitors and DM status with HF from databases and studies. The “Drug-Target” and “Drug-Target-Disease” networks were constructed using Cytoscape. Then the protein–protein interaction (PPI) was analyzed using the STRING database. Gene Ontology (GO) biological functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed to investigate using the Bioconductor tool for analysis. RESULTS: There were 125 effective targets between SGLT2 inhibitors and DM status with HF. Through further screening, 33 core targets were obtained, including SRC, MAPK1, NARS, MAPK3 and EGFR. It was predicted that the Rap1 signaling pathway, MAPK signaling pathway, EGFR tyrosine kinase inhibitor resistance, AGE-RAGE signaling pathway in diabetic complications and other signaling pathways were involved in the treatment of DM with HF by SGLT2 inhibitors. CONCLUSION: Our study elucidated the possible mechanisms of SGLT2 inhibitors from a systemic and holistic perspective based on pharmacological networks. The key targets and pathways will provide new insights for further research on the pharmacological mechanism of SGLT2 inhibitors in the treatment of DM with HF. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10557-021-07186-y. |
format | Online Article Text |
id | pubmed-9270285 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-92702852022-07-10 A Bioinformatics Investigation into the Pharmacological Mechanisms of Sodium-Glucose Co-transporter 2 Inhibitors in Diabetes Mellitus and Heart Failure Based on Network Pharmacology Mai, Ziling Li, Huanqiang Chen, Guanzhong Chen, Enzhao Liu, Liwei Lun, Zhubin Lai, Wenguang Zhou, Chunyun Yu, Sijia Liu, Jin Chen, Shiqun Chen, Jiyan Liu, Yong Cardiovasc Drugs Ther Original Article PURPOSE: Diabetes mellitus (DM) is a major risk factor for the development of heart failure (HF). Sodium-glucose co-transporter 2 (SGLT2) inhibitors have demonstrated consistent benefits in the reduction of hospitalization for HF in patients with DM. However, the pharmacological mechanism is not clear. To investigate the mechanisms of SGLT2 inhibitors in DM with HF, we performed target prediction and network analysis by a network pharmacology method. METHODS: We selected targets of SGLT2 inhibitors and DM status with HF from databases and studies. The “Drug-Target” and “Drug-Target-Disease” networks were constructed using Cytoscape. Then the protein–protein interaction (PPI) was analyzed using the STRING database. Gene Ontology (GO) biological functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed to investigate using the Bioconductor tool for analysis. RESULTS: There were 125 effective targets between SGLT2 inhibitors and DM status with HF. Through further screening, 33 core targets were obtained, including SRC, MAPK1, NARS, MAPK3 and EGFR. It was predicted that the Rap1 signaling pathway, MAPK signaling pathway, EGFR tyrosine kinase inhibitor resistance, AGE-RAGE signaling pathway in diabetic complications and other signaling pathways were involved in the treatment of DM with HF by SGLT2 inhibitors. CONCLUSION: Our study elucidated the possible mechanisms of SGLT2 inhibitors from a systemic and holistic perspective based on pharmacological networks. The key targets and pathways will provide new insights for further research on the pharmacological mechanism of SGLT2 inhibitors in the treatment of DM with HF. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10557-021-07186-y. Springer US 2021-05-24 2022 /pmc/articles/PMC9270285/ /pubmed/34028657 http://dx.doi.org/10.1007/s10557-021-07186-y Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Mai, Ziling Li, Huanqiang Chen, Guanzhong Chen, Enzhao Liu, Liwei Lun, Zhubin Lai, Wenguang Zhou, Chunyun Yu, Sijia Liu, Jin Chen, Shiqun Chen, Jiyan Liu, Yong A Bioinformatics Investigation into the Pharmacological Mechanisms of Sodium-Glucose Co-transporter 2 Inhibitors in Diabetes Mellitus and Heart Failure Based on Network Pharmacology |
title | A Bioinformatics Investigation into the Pharmacological Mechanisms of Sodium-Glucose Co-transporter 2 Inhibitors in Diabetes Mellitus and Heart Failure Based on Network Pharmacology |
title_full | A Bioinformatics Investigation into the Pharmacological Mechanisms of Sodium-Glucose Co-transporter 2 Inhibitors in Diabetes Mellitus and Heart Failure Based on Network Pharmacology |
title_fullStr | A Bioinformatics Investigation into the Pharmacological Mechanisms of Sodium-Glucose Co-transporter 2 Inhibitors in Diabetes Mellitus and Heart Failure Based on Network Pharmacology |
title_full_unstemmed | A Bioinformatics Investigation into the Pharmacological Mechanisms of Sodium-Glucose Co-transporter 2 Inhibitors in Diabetes Mellitus and Heart Failure Based on Network Pharmacology |
title_short | A Bioinformatics Investigation into the Pharmacological Mechanisms of Sodium-Glucose Co-transporter 2 Inhibitors in Diabetes Mellitus and Heart Failure Based on Network Pharmacology |
title_sort | bioinformatics investigation into the pharmacological mechanisms of sodium-glucose co-transporter 2 inhibitors in diabetes mellitus and heart failure based on network pharmacology |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9270285/ https://www.ncbi.nlm.nih.gov/pubmed/34028657 http://dx.doi.org/10.1007/s10557-021-07186-y |
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