{"title":"基于网络药理学、分子对接和分子动力学模拟,探索二甲双胍在阿尔茨海默病和2型糖尿病中的作用机制。","authors":"Xin Shi, Lingling Li, Zhiyao Liu, Fangqi Wang, Hailiang Huang","doi":"10.1177/20420188231187493","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>To study the potential mechanism of metformin action in AD and T2D.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/02/5e/10.1177_20420188231187493.PMC10540612.pdf","citationCount":"0","resultStr":"{\"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.\",\"authors\":\"Xin Shi, Lingling Li, Zhiyao Liu, Fangqi Wang, Hailiang Huang\",\"doi\":\"10.1177/20420188231187493\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>To study the potential mechanism of metformin action in AD and T2D.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2023-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/02/5e/10.1177_20420188231187493.PMC10540612.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/20420188231187493\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2023/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/20420188231187493","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
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 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.