已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Network pharmacology analysis combined with experimental validation to explore the therapeutic mechanism of Schisandra Chinensis Mixture on diabetic nephropathy

系统药理学 计算生物学 五味子 药理学 微阵列分析技术 生物 分子药理学 机制(生物学) 药品 生物信息学 医学 中医药 基因 受体 遗传学 基因表达 认识论 哲学 病理 替代医学
作者
Yu Ma,Yuanyuan Deng,Na Li,Ao Dong,Hongdian Li,Shu Chen,Sai Zhang,Mianzhi Zhang
出处
期刊:Journal of Ethnopharmacology [Elsevier BV]
卷期号:302 (Pt A): 115768-115768 被引量:24
标识
DOI:10.1016/j.jep.2022.115768
摘要

ETHNOPHARMACOLOGICAL RELEVANCE: Diabetic nephropathy (DN) is one of the most common and serious microvascular complications of Diabetes mellitus (DM). The inflammatory response plays a critical role in DN. Schisandra Chinensis Mixture (SM) has shown promising clinical efficacy in the treatment of DN while the pharmacological mechanisms are still unclear. AIM OF THE STUDY: In this study, a network pharmacology approach and bioinformatic analysis were adopted to predict the pharmacological mechanisms of SM in DN therapy. Based on the predicted results, molecular docking and in vivo experiments were used for verification. MATERIALS AND METHODS: In this study, the candidate bioactive ingredients of SM were obtained via Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and supplementing according to the literature. SM putative targets and the verified targets were acquired from TCMSP and SiwssTartgetPrediction Database. DN-related target genes were collected from GeneCards, OMIM, DisGeNET databases, and microarray data analysis. Biological function and pathway analysis were performed to further explore the pharmacological mechanisms of SM in DN therapy. The protein-protein interaction (PPI) network was established to screen the hub gene. The Receiver Operating Characteristic (ROC) analysis and the molecular docking simulations were performed to validate the potential target-drug interactions. The fingerprint spectrum of multi-components of the SM was characterized by UPLC-MS/MS. The signaling pathways associated with inflammation and hub genes were partially validated in SD rats. RESULTS: A total of 36 bioactive ingredients were contained, and 666 component-related targets were screened from SM, of which 50 intersected with DN targets and were considered potential therapeutic targets. GO analyses revealed that the 50 intersection targets were mainly enriched in the inflammatory response, positive regulation of angiogenesis, and positive regulation of phosphatidylinositol 3-kinase(PI3K) signaling. KEGG analyses indicated that the PI3K-Akt signaling pathway was considered as the most important pathway for SM antagonism to the occurrence and development of DN, with the highest target count enrichment. PPI network results showed that the top 15 protein targets in degree value, VEGFA, JAK2, CSF1R, NOS3, CCR2, CCR5, TLR7, FYN, BTK, LCK, PLAT, NOS2, TEK, MMP1 and MCL1, were identified as hub genes. The results of ROC analysis showed that VEGFA and NOS3 were valuable in the diagnosis of DN. The molecular docking confirmed that the core bioactive ingredients had well-binding affinity for VEGFA and NOS3. The in vivo experiments confirmed that SM significantly inhibited the over-release of inflammatory cytokines such as interleukin (IL)-6 and tumor necrosis factor receptor (TNF)-α in DN rats, while regulating the PI3K-AKT and VEGFA-NOS3 signaling pathways. CONCLUSION: This study revealed the multi-component, multi-target and multi-pathway characteristics of SM therapeutic DN. SM inhibited the inflammatory response and improved renal pathological damage in DN rats, which was related to the regulation of the PI3K-Akt and VEGFA-NOS3 signaling pathways.
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
很酷的妞子完成签到 ,获得积分10
1秒前
2秒前
霍夫斯泰德完成签到,获得积分20
2秒前
syangZ发布了新的文献求助10
2秒前
张欢馨应助科研通管家采纳,获得10
5秒前
华仔应助科研通管家采纳,获得10
5秒前
Owen应助科研通管家采纳,获得10
5秒前
ddd应助科研通管家采纳,获得50
5秒前
Criminology34应助科研通管家采纳,获得10
5秒前
爆米花应助科研通管家采纳,获得10
6秒前
Criminology34应助科研通管家采纳,获得10
6秒前
Criminology34应助科研通管家采纳,获得10
6秒前
隐形曼青应助科研通管家采纳,获得10
6秒前
思源应助科研通管家采纳,获得10
6秒前
robsten完成签到,获得积分10
6秒前
Akim应助科研通管家采纳,获得10
7秒前
无花果应助科研通管家采纳,获得10
7秒前
Criminology34应助科研通管家采纳,获得10
7秒前
彭于晏应助科研通管家采纳,获得30
7秒前
张欢馨应助科研通管家采纳,获得10
7秒前
9秒前
i97完成签到 ,获得积分10
9秒前
Nancy完成签到 ,获得积分10
11秒前
奋斗雨灵完成签到,获得积分10
12秒前
13秒前
方既白发布了新的文献求助10
13秒前
刘永睿发布了新的文献求助10
15秒前
15秒前
聪明的豌豆完成签到,获得积分10
15秒前
16秒前
16秒前
罗二狗完成签到 ,获得积分10
17秒前
勤劳的乐安完成签到,获得积分10
19秒前
19秒前
21秒前
稳重大地发布了新的文献求助10
21秒前
黄浦江发布了新的文献求助10
21秒前
23秒前
24秒前
lhw应助Doc.Lee采纳,获得20
24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
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
Management and the Arts 310
Teaching Social and Emotional Learning in Physical Education 300
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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7632848
求助须知:如何正确求助?哪些是违规求助? 9207250
关于积分的说明 19746882
捐赠科研通 7202025
什么是DOI,文献DOI怎么找? 3274886
关于科研通互助平台的介绍 2436792
邀请新用户注册赠送积分活动 2271669