畜牧兽医学报 ›› 2022, Vol. 53 ›› Issue (11): 4097-4109.doi: 10.11843/j.issn.0366-6964.2022.11.035

• 临床兽医 • 上一篇    下一篇

基于网络药理学探讨黄芩素对猪丁型冠状病毒感染的潜在作用机制

刘贺娟1, 史晨曦2, 王静1, 王美乐1, 王栋涵2, 魏战勇2, 尹素改1*   

  1. 1. 河南中医药大学医学院, 郑州 450046;
    2. 河南农业大学动物医学院, 郑州 450046
  • 收稿日期:2021-11-10 出版日期:2022-11-23 发布日期:2022-11-25
  • 通讯作者: 尹素改,主要从事中医药抗感染性疾病研究,E-mail:yinsugai@163.com
  • 作者简介:刘贺娟(1994-),女,河南驻马店人,主要从事中医药抗感染性疾病研究,E-mail:lhjsrxh@163.com
  • 基金资助:
    河南省杰出青年基金(202300410192);国家自然科学基金(31972678);河南省科技公关项目(202102310504)

Exploration on the Potential Mechanism of Baicalein on Porcine Deltacoronavirus Infection Based on Network Pharmacology

LIU Hejuan1, SHI Chenxi2, WANG Jing1, WANG Meile1, WANG Donghan2, WEI Zhanyong2, YIN Sugai1*   

  1. 1. School of Medicine, Henan University of Chinese Medicine, Zhengzhou 450046, China;
    2. College of Veterinary Medicine, Henan Agricultural University, Zhengzhou 450046, China
  • Received:2021-11-10 Online:2022-11-23 Published:2022-11-25

摘要: 本研究旨在探讨黄芩素抗猪丁型冠状病毒(porcine deltacoronavirus,PDCoV)感染的作用机制。通过Pharmmapper、Pubchem、STITCH、TCMSP和Swiss Targer Prediction数据库获得黄芩素的作用靶点。根据前期蛋白组学结果获得PDCoV感染的相关靶点,获取黄芩素与PDCoV感染的共同靶点,并利用STRING数据库和Cytoscape 3.8.2软件构建“药物-疾病-靶点”网络和靶蛋白相互作用网络,利用CytoNCA插件进行网络拓扑分析和核心网络构建,使用Metascape数据库对核心网络基因进行GO和KEGG分析。通过细胞试验对富集得到的信号通路下游基因表达水平进行检测。通过筛选,共获得黄芩素的潜在靶基因268个,黄芩素-PDCoV的共同靶点75个,GO富集结果表明黄芩素主要参与细胞周期、细胞膜筏形成、线粒体膜形成、纺锤体形成和MAPK信号级联传导过程;KEGG富集筛选得到277条信号通路(P<0.01),主要涉及PI3K-Akt信号通路、Ras信号通路和MAPK信号通路等。细胞试验结果表明,与正常细胞对照组相对,病毒感染后PI3K、AKTNF-κB mRNA表达显著升高;与病毒感染组相比,黄芩素处理组PI3KAKTNF-κB mRNA的表达显著降低(P<0.05)。黄芩素对PDCoV感染的作用具有多靶点、多通路的特点,可能是通过作用于AKT1、HSP90AA1、SRCEGFRCASP3、MAPKSTAT3等核心基因调控PI3K-Akt、Ras和MAPK信号通路、细胞凋亡、病毒感染等通路发挥作用,可以作为抗PDCoV感染的潜在治疗药物进一步研究。

关键词: 网络药理学, 黄芩素, 猪丁型冠状病毒, 抗病毒作用机制

Abstract: This study aimed to explore the protective mechanism of baicalein against porcine deltacoronavirus (PDCoV) infection. The targets of baicalein were obtained through Pharmamapper, Pubchem, STITCH, TCMSP and Swiss Targer Prediction databases, and the targets of PDCoV infection were obtained according to the proteomics data from our previous study. The targets of baicalein-PDCoV interaction were obtained and analyzed by STRING database and Cytoscape 3.8.2 software to construct a network diagram of "baicalein-PDCoV-targets". The CytoNCA was used to analyze network topology and core network construction. Metascape database was used for GO and KEGG analysis of core network genes. The expression levels of genes in the predicted signaling pathways were detected in vitro. A total of 268 potential targets of baicalein were screened out. There were 75 potential targets of baicalein-PDCoV infection. GO enrichment results showed that baicalein was mainly involved in the formations of membrane raft, spindle and mitochondrial membrane, cell cycle and MAPK signaling pathways. A total of 277 signaling pathways (P<0.01) were screened out by KEGG enrichment. The PI3K-Akt, Ras and MAPK signaling pathways were the main pathways that involved in the protective effects of baicalein against PDCoV infection. The results showed that compared with the cellular control groups, the mRNA expressions of PI3K, AKT and NF-κB significantly increased in the PDCoV infection group. Compared with the PDCoV group, treatment of baicalein significantly decreased the mRNA expressions of PI3K, AKT and NF-κB (P<0.05). The effect of baicalein on PDCoV infection has the characteristics of multi-targets and multi-pathways, through the intervention of AKT1, HSP90AA1, SRC, EGFR, CASP3, MAPK, STAT3 and other core genes in regulating PI3K-Akt signaling pathway, Ras signaling pathway and MAPK signaling pathway, apoptosis, and virus infection. These results suggested that baicalein could be a potential therapeutic drug against PDCoV infection for further study.

Key words: network pharmacology, baicalein, porcine deltacoronavirus, mechanism of anti-virus

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