基于分子对接和分子动力学探索阿司匹林治疗川崎病的机制
Exploring the Mechanism of Aspirin in the Treatment of Kawasaki Disease Based on Molecular Docking and Molecular Dynamics.
作者信息
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
机构信息
Clinical Medicine, Chengdu Medical College, Chengdu, China.
Center for Experimental Technology of Preclinical Medicine, Chengdu Medical College, Chengdu, China.
出版信息
Evid Based Complement Alternat Med. 2022 Aug 12;2022:9828518. doi: 10.1155/2022/9828518. eCollection 2022.
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.
目的
本研究旨在探讨阿司匹林治疗川崎病的作用机制。
方法
借助Drugbank和PharmMapper数据库预测阿司匹林的靶点，在GeneCards和Disgenet数据库中挖掘川崎病的靶基因，在Venny数据库中处理交集靶点，并在GEO数据库中观察基因表达差异。利用Drugbank和PharmMapper数据库预测阿司匹林的靶点，在GeneCards和Disgenet数据库中探索川崎病的靶基因，并使用Venny进行交集处理。我们在GEO数据库中观察基因表达差异。建立疾病-核心基因靶点-药物网络并使用分子对接进行验证。进行分子动力学模拟验证，以使活性成分与靶点稳定结合。使用超级计算机平台测量和分析结合自由能、氢键数量、蛋白质靶点在残基水平的稳定性、回转半径和溶剂可及表面积。
结果
阿司匹林有294个基因靶点，川崎病有416个基因靶点，获得42个交集靶点，通过蛋白质-蛋白质相互作用筛选出13个核心靶点；在基因本体（GO）分析中，我们了解到川崎病的生物学过程涉及趋化因子生物合成和炎症反应的正调控；通路富集涉及磷脂酰肌醇-3激酶-蛋白激酶B（PI3K-AKT）信号通路、肿瘤坏死因子信号通路等。分子对接后，数据显示组织蛋白酶G（CTSG）、弹性蛋白酶（ELANE）和成纤维细胞生长因子1（FGF1）与阿司匹林的结合度最佳。使用分子动力学证明和分析活性成分与蛋白质靶点的结合稳定性，阿司匹林/弹性蛋白酶组合具有最强的结合能。
结论
在川崎病的治疗中，阿司匹林可能通过组织蛋白酶G、弹性蛋白酶和成纤维细胞生长因子1调节炎症反应和血管重塑。
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