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基于网络药理学的黄芪对乙酰氨基酚诱导肝损伤影响的预测及药理验证

Network Pharmacology-Based Prediction and Pharmacological Validation of Effects of Astragali Radix on Acetaminophen-Induced Liver Injury.

作者信息

Peng Yuan, Zhu Gerui, Ma Yuanyuan, Huang Kai, Chen Gaofeng, Liu Chenghai, Tao Yanyan

机构信息

Institute of Liver Diseases, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.

Shanghai Key Laboratory of Traditional Chinese Clinical Medicine, Shanghai, China.

出版信息

Front Med (Lausanne). 2022 Jul 4;9:697644. doi: 10.3389/fmed.2022.697644. eCollection 2022.

Abstract

Astragali Radix (AR) has been widely used in traditional Chinese medicine prescriptions for acute and chronic liver injury. However, little is known about the effects of AR on acetaminophen (APAP)-induced liver injury (ALI). In the current study, a network pharmacology-based approach was applied to characterize the action mechanism of AR on ALI. All compounds of AR were obtained from the corresponding databases, and active compounds were selected according to its oral bioavailability and drug-likeness index. The potential genes of AR were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) and PubChem, whereas the potential genes related to ALI were obtained from Online databases (GeneCards and Online Mendelian Inheritance in Man) and Gene Expression Omnibus profiles. The enriched processes, pathways, and target genes of the diseases were analyzed by referring to the Search Tool for the Retrieval of Interacting Genes/Proteins database. A network constructed through Cytoscape software was used to identify the target proteins that connected the compounds in AR with the differential genes of ALI. Subsequently, the potential underlying action mechanisms of AR on ALI predicted by the network pharmacology analyses were experimentally validated in APAP-induced liver injury in mice and HL7702 cells incubated with APAP. The compound-target network included 181 targets, whereas the potential genes related to ALI were 4,621. A total of 49 AR-ALI crossover proteins, corresponding to 49 genes, were filtered into a protein-protein interaction network complex and designated as the potential targets of AR on ALI. Among the genes, the three highest-scoring genes, , , and were highly associated with apoptosis in ALI. Then and experiments confirmed that AR exhibited its prominent therapeutic effects on ALI mainly via regulating hepatocyte apoptosis related to inhibiting the expressions of (c-Myc), (JNK1), and (IL-8). In conclusion, our study suggested that the combination of network pharmacology prediction with experimental validation might offer a useful tool to characterize the molecular mechanism of AR on ALI.

摘要

黄芪在治疗急慢性肝损伤的中药方剂中已被广泛应用。然而,关于黄芪对乙酰氨基酚(APAP)诱导的肝损伤(ALI)的影响却知之甚少。在本研究中,采用基于网络药理学的方法来表征黄芪对ALI的作用机制。黄芪的所有化合物均从相应数据库中获取,并根据其口服生物利用度和类药指数选择活性化合物。黄芪的潜在基因从中药系统药理学数据库和分析平台(TCMSP)、中药分子机制生物信息学分析工具(BATMAN-TCM)以及PubChem中获取,而与ALI相关的潜在基因则从在线数据库(GeneCards和人类孟德尔遗传在线)以及基因表达综合谱中获取。通过参考检索相互作用基因/蛋白质数据库的搜索工具来分析疾病的富集过程、途径和靶基因。利用Cytoscape软件构建的网络来识别将黄芪中的化合物与ALI的差异基因联系起来的靶蛋白。随后,在APAP诱导的小鼠肝损伤以及与APAP孵育的HL7702细胞中,对网络药理学分析预测的黄芪对ALI的潜在作用机制进行了实验验证。化合物-靶标网络包含181个靶标,而与ALI相关的潜在基因有4621个。总共49个黄芪-ALI交叉蛋白,对应49个基因,被筛选到一个蛋白质-蛋白质相互作用网络复合体中,并被指定为黄芪对ALI的潜在靶标。在这些基因中,得分最高的三个基因,即 、 和 与ALI中的细胞凋亡高度相关。然后 实验和 实验证实,黄芪对ALI具有显著的治疗作用,主要是通过调节肝细胞凋亡,这与抑制 (c-Myc)、 (JNK1)和 (IL-8)的表达有关。总之,我们的研究表明,网络药理学预测与实验验证相结合可能为表征黄芪对ALI的分子机制提供一个有用的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/afbb/9289209/c8fc729a58a6/fmed-09-697644-g001.jpg

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