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Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics
PURPOSE: The research aims to investigate the mechanism of action of aspirin in the treatment of Kawasaki disease. METHODS: We predicted the targets of aspirin with the help of the Drugbank and PharmMapper databases, the target genes of Kawasaki disease were mined in the GeneCards and Disgenet datab...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9391120/ https://www.ncbi.nlm.nih.gov/pubmed/35990842 http://dx.doi.org/10.1155/2022/9828518 |
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author | Xiong, Li Cao, Junfeng Qiu, Yixin Fu, Yinyin Chen, Siyi He, Mengjia Chen, Shengyan Xie, Wei Yang, Xingyu Wang, Chaochao Wu, Mei Xu, Hengxiang Chen, Yijun Zhang, Xiao |
author_facet | Xiong, Li Cao, Junfeng Qiu, Yixin Fu, Yinyin Chen, Siyi He, Mengjia Chen, Shengyan Xie, Wei Yang, Xingyu Wang, Chaochao Wu, Mei Xu, Hengxiang Chen, Yijun Zhang, Xiao |
author_sort | Xiong, Li |
collection | PubMed |
description | PURPOSE: The research aims to investigate the mechanism of action of aspirin in the treatment of Kawasaki disease. METHODS: We predicted the targets of aspirin with the help of the Drugbank and PharmMapper databases, the target genes of Kawasaki disease were mined in the GeneCards and Disgenet databases, the intersection targets were processed in the Venny database, and the gene expression differences were observed in the GEO database. The Drugbank and PharmMapper databases were used to predict the target of aspirin, and the target genes of Kawasaki disease were explored in the GeneCards and Disgenet databases, and the Venny was used for intersection processing. We observed the gene expression differences in the GEO database. The disease-core gene target-drug network was established and molecular docking was used for verification. Molecular dynamics simulation verification was carried out to combine the active ingredient and the target with a stable combination. The supercomputer platform was used to measure and analyze the binding free energy, the number of hydrogen bonds, the stability of the protein target at the residue level, the radius of gyration, and the solvent accessible surface area. RESULTS: Aspirin had 294 gene targets, Kawasaki disease had 416 gene targets, 42 intersecting targets were obtained, we screened 13 core targets by PPI; In the GO analysis, we learned that the biological process of Kawasaki disease involved the positive regulation of chemokine biosynthesis and inflammatory response; pathway enrichment involved PI3K-AKT signaling pathway, tumor necrosis factor signaling pathway, etc. After molecular docking, the data showed that CTSG, ELANE, and FGF1 had the best binding degree to aspirin. Molecular dynamics was used to prove and analyze the binding stability of active ingredients and protein targets, and Aspirin/ELANE combination has the strongest binding energy. CONCLUSION: In the treatment of Kawasaki disease, aspirin may regulate inflammatory response and vascular remodeling through CTSG, ELANE, and FGF1. |
format | Online Article Text |
id | pubmed-9391120 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-93911202022-08-20 Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics Xiong, Li Cao, Junfeng Qiu, Yixin Fu, Yinyin Chen, Siyi He, Mengjia Chen, Shengyan Xie, Wei Yang, Xingyu Wang, Chaochao Wu, Mei Xu, Hengxiang Chen, Yijun Zhang, Xiao Evid Based Complement Alternat Med Research Article PURPOSE: The research aims to investigate the mechanism of action of aspirin in the treatment of Kawasaki disease. METHODS: We predicted the targets of aspirin with the help of the Drugbank and PharmMapper databases, the target genes of Kawasaki disease were mined in the GeneCards and Disgenet databases, the intersection targets were processed in the Venny database, and the gene expression differences were observed in the GEO database. The Drugbank and PharmMapper databases were used to predict the target of aspirin, and the target genes of Kawasaki disease were explored in the GeneCards and Disgenet databases, and the Venny was used for intersection processing. We observed the gene expression differences in the GEO database. The disease-core gene target-drug network was established and molecular docking was used for verification. Molecular dynamics simulation verification was carried out to combine the active ingredient and the target with a stable combination. The supercomputer platform was used to measure and analyze the binding free energy, the number of hydrogen bonds, the stability of the protein target at the residue level, the radius of gyration, and the solvent accessible surface area. RESULTS: Aspirin had 294 gene targets, Kawasaki disease had 416 gene targets, 42 intersecting targets were obtained, we screened 13 core targets by PPI; In the GO analysis, we learned that the biological process of Kawasaki disease involved the positive regulation of chemokine biosynthesis and inflammatory response; pathway enrichment involved PI3K-AKT signaling pathway, tumor necrosis factor signaling pathway, etc. After molecular docking, the data showed that CTSG, ELANE, and FGF1 had the best binding degree to aspirin. Molecular dynamics was used to prove and analyze the binding stability of active ingredients and protein targets, and Aspirin/ELANE combination has the strongest binding energy. CONCLUSION: In the treatment of Kawasaki disease, aspirin may regulate inflammatory response and vascular remodeling through CTSG, ELANE, and FGF1. Hindawi 2022-08-12 /pmc/articles/PMC9391120/ /pubmed/35990842 http://dx.doi.org/10.1155/2022/9828518 Text en Copyright © 2022 Li Xiong et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Xiong, Li Cao, Junfeng Qiu, Yixin Fu, Yinyin Chen, Siyi He, Mengjia Chen, Shengyan Xie, Wei Yang, Xingyu Wang, Chaochao Wu, Mei Xu, Hengxiang Chen, Yijun Zhang, Xiao Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics |
title | Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics |
title_full | Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics |
title_fullStr | Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics |
title_full_unstemmed | Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics |
title_short | Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics |
title_sort | exploring the mechanism of aspirin in the treatment of kawasaki disease based on molecular docking and molecular dynamics |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9391120/ https://www.ncbi.nlm.nih.gov/pubmed/35990842 http://dx.doi.org/10.1155/2022/9828518 |
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