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In Silico Analysis of Ferroptosis-Related Genes and Its Implication in Drug Prediction against Fluorosis
Fluorosis is a serious global public health problem. Interestingly, so far, there is no specific drug treatment for the treatment of fluorosis. In this paper, the potential mechanisms of 35 ferroptosis-related genes in U87 glial cells exposed to fluoride were explored by bioinformatics methods. Sign...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9961266/ https://www.ncbi.nlm.nih.gov/pubmed/36835629 http://dx.doi.org/10.3390/ijms24044221 |
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author | Liu, Bin Fu, Xiaoli Du, Yuhui Feng, Zichen Liu, Xiaoxue Li, Zhiyuan Yu, Fangfang Zhou, Guoyu Ba, Yue |
author_facet | Liu, Bin Fu, Xiaoli Du, Yuhui Feng, Zichen Liu, Xiaoxue Li, Zhiyuan Yu, Fangfang Zhou, Guoyu Ba, Yue |
author_sort | Liu, Bin |
collection | PubMed |
description | Fluorosis is a serious global public health problem. Interestingly, so far, there is no specific drug treatment for the treatment of fluorosis. In this paper, the potential mechanisms of 35 ferroptosis-related genes in U87 glial cells exposed to fluoride were explored by bioinformatics methods. Significantly, these genes are involved in oxidative stress, ferroptosis, and decanoate CoA ligase activity. Ten pivotal genes were found by the Maximal Clique Centrality (MCC) algorithm. Furthermore, according to the Connectivity Map (CMap) and the Comparative Toxicogenomics Database (CTD), 10 possible drugs for fluorosis were predicted and screened, and a drug target ferroptosis-related gene network was constructed. Molecular docking was used to study the interaction between small molecule compounds and target proteins. Molecular dynamics (MD) simulation results show that the structure of the Celestrol–HMOX1 composite is stable and the docking effect is the best. In general, Celastrol and LDN-193189 may target ferroptosis-related genes to alleviate the symptoms of fluorosis, which may be effective candidate drugs for the treatment of fluorosis. |
format | Online Article Text |
id | pubmed-9961266 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99612662023-02-26 In Silico Analysis of Ferroptosis-Related Genes and Its Implication in Drug Prediction against Fluorosis Liu, Bin Fu, Xiaoli Du, Yuhui Feng, Zichen Liu, Xiaoxue Li, Zhiyuan Yu, Fangfang Zhou, Guoyu Ba, Yue Int J Mol Sci Article Fluorosis is a serious global public health problem. Interestingly, so far, there is no specific drug treatment for the treatment of fluorosis. In this paper, the potential mechanisms of 35 ferroptosis-related genes in U87 glial cells exposed to fluoride were explored by bioinformatics methods. Significantly, these genes are involved in oxidative stress, ferroptosis, and decanoate CoA ligase activity. Ten pivotal genes were found by the Maximal Clique Centrality (MCC) algorithm. Furthermore, according to the Connectivity Map (CMap) and the Comparative Toxicogenomics Database (CTD), 10 possible drugs for fluorosis were predicted and screened, and a drug target ferroptosis-related gene network was constructed. Molecular docking was used to study the interaction between small molecule compounds and target proteins. Molecular dynamics (MD) simulation results show that the structure of the Celestrol–HMOX1 composite is stable and the docking effect is the best. In general, Celastrol and LDN-193189 may target ferroptosis-related genes to alleviate the symptoms of fluorosis, which may be effective candidate drugs for the treatment of fluorosis. MDPI 2023-02-20 /pmc/articles/PMC9961266/ /pubmed/36835629 http://dx.doi.org/10.3390/ijms24044221 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Liu, Bin Fu, Xiaoli Du, Yuhui Feng, Zichen Liu, Xiaoxue Li, Zhiyuan Yu, Fangfang Zhou, Guoyu Ba, Yue In Silico Analysis of Ferroptosis-Related Genes and Its Implication in Drug Prediction against Fluorosis |
title | In Silico Analysis of Ferroptosis-Related Genes and Its Implication in Drug Prediction against Fluorosis |
title_full | In Silico Analysis of Ferroptosis-Related Genes and Its Implication in Drug Prediction against Fluorosis |
title_fullStr | In Silico Analysis of Ferroptosis-Related Genes and Its Implication in Drug Prediction against Fluorosis |
title_full_unstemmed | In Silico Analysis of Ferroptosis-Related Genes and Its Implication in Drug Prediction against Fluorosis |
title_short | In Silico Analysis of Ferroptosis-Related Genes and Its Implication in Drug Prediction against Fluorosis |
title_sort | in silico analysis of ferroptosis-related genes and its implication in drug prediction against fluorosis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9961266/ https://www.ncbi.nlm.nih.gov/pubmed/36835629 http://dx.doi.org/10.3390/ijms24044221 |
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