Network pharmacological study of Banxia-Chenpi in the treatment of cough variant asthma in children with phlegm evil accumulation lung syndrome

活性成分 药理学 医学 中医药 替代医学 病理
作者
B. Xin,Tianyi Liu,Yue Wu,Qingyang Hu,Xue Dong,Huanhuan Wang,Zhong Li
标识
DOI:10.1016/j.ipha.2023.04.004
摘要

To explore the molecular mechanism of Banxia -Chenpi in the treatment of cough variant asthma with phlegm evil accumulation lung syndrome based on network pharmacology and molecular docking technology. TCMSP database was used to screen the active ingredients and targets of Banxia-Chenpi. GeneCards, OMIM and PharmGKB databases were used to obtain the targets of cough variant asthma. Cytoscape 3.9.1 software was used to construct the "couplet medicines-active ingredients-targets" network and screen key ingredients according to the degree value. The protein–protein interaction data were obtained from the STRING database and core targets were screened by Cytoscape plugin cytoNCA. The core targets conduct GO and KEGG pathway enrichment analyses in the David database. Molecular docking technology was used to verify the binding energy between key ingredients and core targets. There were 16 active ingredients and potential 118 targets in Banxia-Chenpi,2429 cough variant asthma targets, and 72 intersection targets. The key ingredients of the Banxia-Chenpi in treating cough variant asthma were nobiletin, baicalein, naringenin, stigmasterol, beta-sitosterol and coniferin. The core targets of the Banxia-Chenpi for CVA treatment were FOS, MMP9, AKT1, CASP3, TP53, JUN and VEGFA. The molecular docking results indicated key ingredients and core targets of the Banxia-Chenpi in CVA treatment had a good binding affinity. Active ingredients maybe act on MMP9, AKT1, VEGFR and FOS to reduce eosinophils and neutrophils accumulation, dissolve phlegm, alleviate airway inflammation, and reduce airway resistance and hyperresponsiveness for treating CVA. This study provides a reference for clinical medication and subsequent research.

科研通智能强力驱动
Strongly Powered by AbleSci AI

祝大家在新的一年里科研腾飞
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
3秒前
ding应助素简采纳,获得10
4秒前
4秒前
小梦完成签到,获得积分10
4秒前
科研通AI6.1应助huang采纳,获得20
7秒前
刘刘发布了新的文献求助20
8秒前
Cindy发布了新的文献求助10
9秒前
可爱寄松发布了新的文献求助10
9秒前
11秒前
可爱寄松完成签到,获得积分10
14秒前
多年以后完成签到 ,获得积分10
15秒前
16秒前
CrazyLion完成签到,获得积分10
19秒前
务实的靖应助蒙眼过河采纳,获得10
21秒前
阔达宛凝完成签到,获得积分10
21秒前
21秒前
Jason2002完成签到 ,获得积分10
25秒前
26秒前
铮铮铁骨发布了新的文献求助100
31秒前
研友_VZG7GZ应助yunshui采纳,获得10
32秒前
寻道图强应助fxtx1234采纳,获得100
37秒前
刘刘完成签到,获得积分10
38秒前
甜蜜的大象完成签到 ,获得积分10
38秒前
39秒前
39秒前
40秒前
40秒前
40秒前
40秒前
40秒前
40秒前
40秒前
40秒前
40秒前
40秒前
嘿小黑应助科研通管家采纳,获得30
40秒前
charint应助科研通管家采纳,获得20
40秒前
斯文败类应助科研通管家采纳,获得10
40秒前
40秒前
华仔应助科研通管家采纳,获得10
40秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Operational Bulk Evaporation Duct Model for MORIAH Version 1.2 1200
Signals, Systems, and Signal Processing 880
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 800
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 600
Discrete-Time Signals and Systems 510
Clinical Efficacy of the Hydrogel Patch Containing Loxoprofen Sodium (LX-A) on Osteoarthritis of the Knee-A Randomized, Open Label Clinical Study with Ketoprofen Patch-(Phase III Therapeutic Confirmatory Study) 410
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5843748
求助须知:如何正确求助?哪些是违规求助? 6183992
关于积分的说明 15612471
捐赠科研通 4960611
什么是DOI,文献DOI怎么找? 2674413
邀请新用户注册赠送积分活动 1619312
关于科研通互助平台的介绍 1574491