Elucidating the Synergistic Effect of Multiple Chinese Herbal Prescriptions in the Treatment of Post-stroke Neurological Damage

传统医学 汤剂 小桶 药理学 药方 中医药 缺血性中风 梓醇 黄芩苷 槲皮素 医学 化学 立体化学 生物化学 基因本体论 内科学 替代医学 基因 高效液相色谱法 基因表达 病理 糖苷 缺血 抗氧化剂 色谱法
作者
Anqi Xu,Zhuohua Wen,Shixing Su,Yupeng Chen,Wenchao Liu,Shenquan Guo,Xifeng Li,Xin Zhang,Ran Li,Ningbo Xu,Kexin Wang,Wenxing Li,Daogang Guan,Chuanzhi Duan
出处
期刊:Frontiers in Pharmacology [Frontiers Media]
卷期号:13: 784242-784242 被引量:16
标识
DOI:10.3389/fphar.2022.784242
摘要

Background: Traditional Chinese medicine (TCM) has been widely used in the treatment of human diseases. However, the synergistic effects of multiple TCM prescriptions in the treatment of stroke have not been thoroughly studied. Objective of the study: This study aimed to reveal the mechanisms underlying the synergistic effects of these TCM prescriptions in stroke treatment and identify the active compounds. Methods: Herbs and compounds in the Di-Tan Decoction (DTD), Xue-Fu Zhu-Yu Decoction (XFZYD), and Xiao-Xu-Ming Decoction (XXMD) were acquired from the TCMSP database. SEA, HitPick, and TargetNet web servers were used for target prediction. The compound-target (C-T) networks of three prescriptions were constructed and then filtered using the collaborative filtering algorithm. We combined KEGG enrichment analysis, molecular docking, and network analysis approaches to identify active compounds, followed by verification of these compounds with an oxygen-glucose deprivation and reoxygenation (OGD/R) model. Results: The filtered DTD network contained 39 compounds and 534 targets, the filtered XFZYD network contained 40 compounds and 508 targets, and the filtered XXMD network contained 55 compounds and 599 targets. The filtered C-T networks retained approximately 80% of the biological functions of the original networks. Based on the enriched pathways, molecular docking, and network analysis results, we constructed a complex network containing 3 prescriptions, 14 botanical drugs, 26 compounds, 13 targets, and 5 pathways. By calculating the synergy score, we identified the top 5 candidate compounds. The experimental results showed that quercetin, baicalin, and ginsenoside Rg1 independently and synergistically increased cell viability. Conclusion: By integrating pharmacological and chemoinformatic approaches, our study provides a new method for identifying the effective synergistic compounds of TCM prescriptions. The filtered compounds and their synergistic effects on stroke require further research.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
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
1秒前
滑蛋猪排饭完成签到,获得积分10
1秒前
may发布了新的文献求助10
2秒前
way完成签到,获得积分10
3秒前
3秒前
3秒前
机智的亦竹完成签到,获得积分10
3秒前
冷静的友易完成签到,获得积分20
3秒前
洁净思枫完成签到,获得积分10
3秒前
3秒前
6秒前
6秒前
CodeCraft应助Jasmine采纳,获得10
6秒前
茉莉发布了新的文献求助10
7秒前
悦耳代双完成签到 ,获得积分10
7秒前
研友_VZG7GZ应助caigou采纳,获得10
8秒前
11111111发布了新的文献求助10
8秒前
ma发布了新的文献求助10
8秒前
宠溺Ovo完成签到 ,获得积分10
8秒前
香蕉觅云应助苹果万恶采纳,获得10
8秒前
卷卷卷儿发布了新的文献求助10
8秒前
眼睛大的太阳关注了科研通微信公众号
8秒前
彩色面包完成签到,获得积分10
8秒前
pyl发布了新的文献求助10
9秒前
完美世界应助may采纳,获得10
9秒前
77应助如意竺采纳,获得10
10秒前
HSTrigger发布了新的文献求助10
10秒前
香蕉觅云应助123采纳,获得10
11秒前
冷酷的醉柳完成签到 ,获得积分10
11秒前
斯文败类应助云书采纳,获得10
12秒前
12秒前
机智铃铛完成签到,获得积分10
12秒前
馒头完成签到 ,获得积分10
13秒前
liuziyu完成签到,获得积分10
13秒前
气凝前沿完成签到,获得积分10
13秒前
14秒前
李爱国应助11111111采纳,获得10
15秒前
毛毛发布了新的文献求助10
16秒前
16秒前
17秒前
高分求助中
Malcolm Fraser : a biography 700
Signals, Systems, and Signal Processing 610
天津市智库成果选编 600
Climate change and sports: Statistics report on climate change and sports 500
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
Organic Reactions Volume 118 400
A Foreign Missionary on the Long March: The Unpublished Memoirs of Arnolis Hayman of the China Inland Mission 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6462013
求助须知:如何正确求助?哪些是违规求助? 8270224
关于积分的说明 17630054
捐赠科研通 5533008
什么是DOI,文献DOI怎么找? 2906656
邀请新用户注册赠送积分活动 1883425
关于科研通互助平台的介绍 1729646