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Exploring the mechanism of metformin action in Alzheimer’s disease and type 2 diabetes based on network pharmacology, molecular docking, and molecular dynamic simulation

BACKGROUND: Metformin, which has been shown to be highly effective in treating type 2 diabetes (T2D), is also believed to be valuable for Alzheimer’s disease (AD). Computer simulation techniques have emerged as an innovative approach to explore mechanisms. OBJECTIVE: To study the potential mechanism...

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Autores principales: Shi, Xin, Li, Lingling, Liu, Zhiyao, Wang, Fangqi, Huang, Hailiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540612/
https://www.ncbi.nlm.nih.gov/pubmed/37780174
http://dx.doi.org/10.1177/20420188231187493
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author Shi, Xin
Li, Lingling
Liu, Zhiyao
Wang, Fangqi
Huang, Hailiang
author_facet Shi, Xin
Li, Lingling
Liu, Zhiyao
Wang, Fangqi
Huang, Hailiang
author_sort Shi, Xin
collection PubMed
description BACKGROUND: Metformin, which has been shown to be highly effective in treating type 2 diabetes (T2D), is also believed to be valuable for Alzheimer’s disease (AD). Computer simulation techniques have emerged as an innovative approach to explore mechanisms. OBJECTIVE: To study the potential mechanism of metformin action in AD and T2D. METHODS: The chemical structure of metformin was obtained from PubChem. The targets of metformin were obtained from PubChem, Pharm Mapper, Batman, SwissTargetPrediction, DrugBank, and PubMed. The pathogenic genes of AD and T2D were retrieved from the GeneCards, OMIM, TTD, Drugbank, PharmGKB, and DisGeNET. The intersection of metformin with the targets of AD and T2D is represented by a Venn diagram. The protein-protein interaction (PPI) and core targets networks of intersected targets were constructed by Cytoscape 3.7.1. The enrichment information of GO and Kyoto Encyclopedia of Gene and Genomics (KEGG) pathways obtained by the Metascape was made into a bar chart and a bubble diagram. AutoDockTools, Pymol, and Chem3D were used for the molecular docking. Gromacs software was used to perform molecular dynamics (MD) simulation of the best binding target protein. RESULTS: A total of 115 key targets of metformin for AD and T2D were obtained. GO analysis showed that biological process mainly involved response to hormones and the regulation of ion transport. Cellular component was enriched in the cell body and axon. Molecular function mainly involved kinase binding and signal receptor regulator activity. The KEGG pathway was mainly enriched in pathways of cancer, neurodegeneration, and endocrine resistance. Core targets mainly included TP53, TNF, VEGFA, HIF1A, IL1B, IGF1, ESR1, SIRT1, CAT, and CXCL8. The molecular docking results showed best binding of metformin to CAT. MD simulation further indicated that the CAT-metformin complex could bind well and converge relatively stable at 30 ns. CONCLUSION: Metformin exerts its effects on regulating oxidative stress, gluconeogenesis and inflammation, which may be the mechanism of action of metformin to improve the common pathological features of T2D and AD.
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spelling pubmed-105406122023-09-30 Exploring the mechanism of metformin action in Alzheimer’s disease and type 2 diabetes based on network pharmacology, molecular docking, and molecular dynamic simulation Shi, Xin Li, Lingling Liu, Zhiyao Wang, Fangqi Huang, Hailiang Ther Adv Endocrinol Metab Original Research BACKGROUND: Metformin, which has been shown to be highly effective in treating type 2 diabetes (T2D), is also believed to be valuable for Alzheimer’s disease (AD). Computer simulation techniques have emerged as an innovative approach to explore mechanisms. OBJECTIVE: To study the potential mechanism of metformin action in AD and T2D. METHODS: The chemical structure of metformin was obtained from PubChem. The targets of metformin were obtained from PubChem, Pharm Mapper, Batman, SwissTargetPrediction, DrugBank, and PubMed. The pathogenic genes of AD and T2D were retrieved from the GeneCards, OMIM, TTD, Drugbank, PharmGKB, and DisGeNET. The intersection of metformin with the targets of AD and T2D is represented by a Venn diagram. The protein-protein interaction (PPI) and core targets networks of intersected targets were constructed by Cytoscape 3.7.1. The enrichment information of GO and Kyoto Encyclopedia of Gene and Genomics (KEGG) pathways obtained by the Metascape was made into a bar chart and a bubble diagram. AutoDockTools, Pymol, and Chem3D were used for the molecular docking. Gromacs software was used to perform molecular dynamics (MD) simulation of the best binding target protein. RESULTS: A total of 115 key targets of metformin for AD and T2D were obtained. GO analysis showed that biological process mainly involved response to hormones and the regulation of ion transport. Cellular component was enriched in the cell body and axon. Molecular function mainly involved kinase binding and signal receptor regulator activity. The KEGG pathway was mainly enriched in pathways of cancer, neurodegeneration, and endocrine resistance. Core targets mainly included TP53, TNF, VEGFA, HIF1A, IL1B, IGF1, ESR1, SIRT1, CAT, and CXCL8. The molecular docking results showed best binding of metformin to CAT. MD simulation further indicated that the CAT-metformin complex could bind well and converge relatively stable at 30 ns. CONCLUSION: Metformin exerts its effects on regulating oxidative stress, gluconeogenesis and inflammation, which may be the mechanism of action of metformin to improve the common pathological features of T2D and AD. SAGE Publications 2023-09-27 /pmc/articles/PMC10540612/ /pubmed/37780174 http://dx.doi.org/10.1177/20420188231187493 Text en © The Author(s), 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Shi, Xin
Li, Lingling
Liu, Zhiyao
Wang, Fangqi
Huang, Hailiang
Exploring the mechanism of metformin action in Alzheimer’s disease and type 2 diabetes based on network pharmacology, molecular docking, and molecular dynamic simulation
title Exploring the mechanism of metformin action in Alzheimer’s disease and type 2 diabetes based on network pharmacology, molecular docking, and molecular dynamic simulation
title_full Exploring the mechanism of metformin action in Alzheimer’s disease and type 2 diabetes based on network pharmacology, molecular docking, and molecular dynamic simulation
title_fullStr Exploring the mechanism of metformin action in Alzheimer’s disease and type 2 diabetes based on network pharmacology, molecular docking, and molecular dynamic simulation
title_full_unstemmed Exploring the mechanism of metformin action in Alzheimer’s disease and type 2 diabetes based on network pharmacology, molecular docking, and molecular dynamic simulation
title_short Exploring the mechanism of metformin action in Alzheimer’s disease and type 2 diabetes based on network pharmacology, molecular docking, and molecular dynamic simulation
title_sort exploring the mechanism of metformin action in alzheimer’s disease and type 2 diabetes based on network pharmacology, molecular docking, and molecular dynamic simulation
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540612/
https://www.ncbi.nlm.nih.gov/pubmed/37780174
http://dx.doi.org/10.1177/20420188231187493
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