The mechanisms of Qizhu Tangshen formula in the treatment of diabetic kidney disease: Network pharmacology, machine learning, molecular docking and experimental assessment

小桶 系统药理学 对接(动物) 药理学 计算生物学 PI3K/AKT/mTOR通路 信号转导 血管生成 化学 医学 生物信息学 生物 癌症研究 基因 基因表达 生物化学 基因本体论 内科学 药品 护理部
作者
Juqin Peng,Kuo Yang,Haoyu Tian,Yadong Lin,Min Hou,Yunxiao Gao,Xuezhong Zhou,Z Gao,Junguo Ren
出处
期刊:Phytomedicine [Elsevier BV]
卷期号:108: 154525-154525 被引量:23
标识
DOI:10.1016/j.phymed.2022.154525
摘要

Qizhu Tangshen Formula (QZTS) has been shown therapeutic effects on diabetic kidney disease (DKD). However, to date, the pharmacological mechanisms remain vague.To explore the underlying mechanisms of QZTS in treating DKD using network pharmacology, machine learning, molecular docking and experimental assessment.First, we found that QZTS improved glycolipid metabolism disorder, decreased proteinuria and alleviated kidney tissue injury in DKD model KKAy mice. Then, by integrating multiple databases, a total of 96 targets of 74 active compounds in QZTS and 759 DKD-related genes were acquired. Next, we identified 13 hub targets of QZTS in DKD by three rank algorithms, including functional similarity, topological similarity and shortest path. Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses demonstrated that the pathways mainly centered on the processes of glycolipid metabolism disorder, inflammation and angiogenesis. Among them, VEGF signaling pathway was significantly enriched. Molecular docking showed that key active compounds of QZTS all had relatively good binding affinity with predicted hub targets. Finally, animal experiments found that QZTS significantly inhibited the secretion of plasma VEGF and downregulated the protein and mRNA expression levels of AKT, p38MAPK and VEGFR2.Our results indicated that QZTS treated DKD via multiple targets and pathways and the VEGF signaling pathway may be highly involved in this process.
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
DevilJiang完成签到 ,获得积分10
刚刚
Quick完成签到,获得积分10
刚刚
刚刚
1秒前
1秒前
科研通AI6.2应助LLYYWW采纳,获得10
1秒前
gujiamin完成签到,获得积分10
2秒前
2秒前
hh发布了新的文献求助10
2秒前
曲奇饼发布了新的文献求助50
2秒前
华仔应助ZZL采纳,获得10
2秒前
3秒前
友好的小狗应助aliu采纳,获得10
3秒前
molihuakai应助jinyu采纳,获得10
3秒前
3秒前
寒冷凌雪发布了新的文献求助10
3秒前
tian完成签到,获得积分10
4秒前
风中的双完成签到 ,获得积分10
4秒前
llb发布了新的文献求助10
5秒前
5秒前
5秒前
科研通AI2S应助是danoo采纳,获得10
6秒前
十六完成签到,获得积分20
6秒前
6秒前
小章发布了新的文献求助10
7秒前
7秒前
liyudan发布了新的文献求助10
8秒前
8秒前
8秒前
小呼发布了新的文献求助10
9秒前
SciGPT应助随心采纳,获得300
9秒前
zzzzzp完成签到,获得积分10
9秒前
幸福台灯发布了新的文献求助10
9秒前
10秒前
大米发布了新的文献求助10
11秒前
hh完成签到,获得积分10
11秒前
11秒前
ucas大菠萝完成签到,获得积分10
11秒前
二黑发布了新的文献求助10
11秒前
11秒前
高分求助中
Adhesion Science: Principles & Practice 1234
Signals, Systems, and Signal Processing 610
Solution-State NMR of Lignocellulosic Biomass 400
Introduction to Cosmetic Formulation and Technology, 2nd Edition 400
Petrology and Plate Tectonics,2025 400
Burger's Medicinal Chemistry and Drug Discovery 400
A Step-by-Step Guide to Qualitative Data Coding 2nd Edition 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 6696808
求助须知:如何正确求助?哪些是违规求助? 8439188
关于积分的说明 18029519
捐赠科研通 5928698
什么是DOI,文献DOI怎么找? 2987139
邀请新用户注册赠送积分活动 1963153
关于科研通互助平台的介绍 1904460