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尿石素A作为治疗脊髓损伤的潜在药物:一项使用网络药理学方法的机制研究。

Urolithin A as a Potential Drug for the Treatment of Spinal Cord Injuries: A Mechanistic Study Using Network Pharmacology Approaches.

作者信息

Mao Chao, Luan HaoPeng, Gao ShuTao, Sheng WeiBin

机构信息

Department of Spine Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang 830054, China.

出版信息

Evid Based Complement Alternat Med. 2022 Apr 22;2022:9090113. doi: 10.1155/2022/9090113. eCollection 2022.

Abstract

OBJECTIVE

This research was focused to examine the potential targets, action network, and mechanism of urolithin A (UA) in spinal cord injury (SCI) management exploiting the network pharmacology (NP).

METHODS

We used the SwissTargetPrediction, PharmMapper, and TargetNet databases to obtain UA action targets. We searched the OMIM, GeneCards, CTD, and DrugBank databases to screen selected target genes for SCI treatment. The intersection of target genes between the UA and SCI databases was obtained by constructing Venn diagrams, which led to the identification of common druggable targets for the disease. The relationship network of the targets was built with Cytoscape 3.7.2, and the protein interaction network was analyzed with the STRING platform. The protein-protein interaction (PPI) network can be built on the STRING database. Gene Ontology (GO) function and KEGG pathway analyses of target intersections were completed with the DAVID 6.8 database. We constructed preliminary network targets for actions underlying UA-SCI interactions. Using the AutoDock software, we examined the molecular docking interactions between UA and its target proteins and further verified the mechanism of the action of UA.

RESULTS

We obtained 318 UA drug targets and 1492 SCI disease targets. We identified a total of 118 common UA-SCI targets. Based on the PPI analysis, we identified MAPK1, SRC, AKT1, HRAS, MAPK8, HSP90AA1, MAPK14, JAK2, ESR1, and NF-B1 as possible therapeutic targets. Enrichment analysis revealed that the PI3K-AKT, VEGF, and TNF signaling pathways could be critical for the NP analysis. Molecular docking indicated that UA had a strong affinity for docked proteins (binding energy range: -6.3 to -9.3 kcal mol).

CONCLUSIONS

We employed an NP approach to validate and predict the underlying mechanisms associated with UA therapy for SCI. An additional purpose of this study was to provide a theoretical basis for further experimental studies on UA's potential in SCI treatment.

摘要

目的

本研究旨在利用网络药理学(NP)研究尿石素A(UA)在脊髓损伤(SCI)治疗中的潜在靶点、作用网络和机制。

方法

我们使用SwissTargetPrediction、PharmMapper和TargetNet数据库获取UA作用靶点。我们搜索了OMIM、GeneCards、CTD和DrugBank数据库,以筛选用于SCI治疗的选定靶基因。通过构建维恩图获得UA和SCI数据库之间的靶基因交集,从而确定该疾病的常见可药物靶点。使用Cytoscape 3.7.2构建靶点关系网络,并使用STRING平台分析蛋白质相互作用网络。蛋白质-蛋白质相互作用(PPI)网络可基于STRING数据库构建。使用DAVID 6.8数据库完成靶标交集的基因本体(GO)功能和KEGG通路分析。我们构建了UA-SCI相互作用潜在作用的初步网络靶点。使用AutoDock软件,我们研究了UA与其靶蛋白之间的分子对接相互作用,并进一步验证了UA的作用机制。

结果

我们获得了318个UA药物靶点和1492个SCI疾病靶点。我们总共鉴定出118个常见的UA-SCI靶点。基于PPI分析,我们确定丝裂原活化蛋白激酶1(MAPK1)、原癌基因酪氨酸蛋白激酶(SRC)、蛋白激酶B1(AKT1)、哈维鼠肉瘤病毒癌基因同源物(HRAS)、丝裂原活化蛋白激酶8(MAPK8)、热休克蛋白90α家族成员1(HSP90AA1)、丝裂原活化蛋白激酶14(MAPK14)、 Janus激酶2(JAK2)、雌激素受体1(ESR1)和核因子κB1(NF-κB1)为可能的治疗靶点。富集分析表明,PI3K-AKT、血管内皮生长因子(VEGF)和肿瘤坏死因子(TNF)信号通路可能对NP分析至关重要。分子对接表明,UA与对接蛋白具有很强的亲和力(结合能范围:-6.3至-9.3 kcal/mol)。

结论

我们采用NP方法验证和预测了与UA治疗SCI相关的潜在机制。本研究的另一个目的是为进一步研究UA在SCI治疗中的潜力提供理论基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3dd9/9054438/8417dd676121/ECAM2022-9090113.001.jpg

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