Combining transcriptomic analysis and network pharmacology to explore the mechanism by which Shaofu Zhuyu decoction improves diabetes mellitus erectile dysfunction

勃起功能障碍 医学 药理学 链脲佐菌素 糖尿病 纤维化 内科学 内分泌学
作者
Yinhui Mao,Juntao Sun,Zhuo Wang,Yang Liu,Jilei Sun,Zhitao Wei,Mingxing Wang,Yong Yang
出处
期刊:Phytomedicine [Elsevier BV]
卷期号:119: 155006-155006 被引量:21
标识
DOI:10.1016/j.phymed.2023.155006
摘要

Erectile dysfunction is common among the complications of diabetes mellitus. Shaofu Zhuyu decoction (SFZYD) is commonly used to treat diabetic mellitus erectile dysfunction (DMED). However, its main active components and specific mechanism are still unknown.To confirm the activity of SFZYD in improving DMED, explore the main active components of SFZYD, and clarify the underlying mechanism.A diabetic rat model was induced with streptozotocin (STZ). After intragastric administration, erectile function was assessed by the maximum intracavernous pressure (ICPmax)/mean arterial pressure (MAP). Corpus cavernosum fibrosis was evaluated by Masson staining, and ELISA methods were used to determine the serum levels of IL-6, TNF-α, IL-10, IL-4 and IL-1β to evaluate inflammation. Then, the main active components of SFZYD were identified by UPLC‒MS/MS. Finally, the target and biological mechanism of SFZYD in improving DMED were predicted by combined network pharmacology and transcriptomics, which was also validated by molecular docking and cellular thermal shift assay (CETSA) experiments.SFZYD significantly improved erectile dysfunction and inhibited inflammatory responses and local tissue fibrosis in diabetic rats. A total of 1846 active components were identified by UPLC‒MS/MS, and isorhamnetin was the main active component. The transcriptomic results were used to identify differentially expressed genes among the control, DM and SFZYD groups, and 1264 differentially expressed genes were obtained from the intersection. The network pharmacology results showed that SFZYD acts on core targets such as AKT1, ALB, HSP90AA1 and ESR1 through core components such as isorhamnetin, quercetin and chrysophanic acid. Further combined analysis revealed that multiple targets, such as CYP1B1, DPP4, NOS2 and LCN2, as well as the regulation of the PI3K-AKT signaling pathway, may be important mechanisms by which SFZYD improves DMED. Molecular docking verification showed that isorhamnetin, the key component of SFZYD, has good binding ability with several core targets, and its binding ability with CYP1B1 was the strongest. The CETSA results showed that isorhamnetin binds to CYP1B1 in CCECs.SFZYD improves DMED, inhibits the inflammatory response and alleviates local tissue fibrosis. The combined application of transcriptomic, network pharmacology, molecular docking and CETSA approaches was helpful for revealing the mechanism by which SFZYD improves DMED, which may be related to the regulation of CYP1B1 and the PI3K-Akt signaling pathway.
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
小小牛马应助starry采纳,获得10
1秒前
啊呀完成签到,获得积分10
2秒前
Herman发布了新的文献求助10
2秒前
3秒前
Copyright应助小韩童学采纳,获得10
4秒前
lee007发布了新的文献求助10
6秒前
heavenzzz发布了新的文献求助20
6秒前
doou发布了新的文献求助10
8秒前
Casper1完成签到,获得积分10
11秒前
11秒前
arniu2008应助鹌鹑大王采纳,获得20
12秒前
科研通AI6.3应助海棠采纳,获得10
12秒前
丘比特应助不回采纳,获得10
16秒前
陈中航发布了新的文献求助50
17秒前
17秒前
深情安青应助六百六十六采纳,获得10
18秒前
迅速的智宸完成签到,获得积分10
19秒前
大模型应助zyc采纳,获得10
19秒前
wujiasheng完成签到,获得积分10
20秒前
21秒前
12138完成签到,获得积分10
23秒前
大气夏瑶发布了新的文献求助10
23秒前
23秒前
24秒前
25秒前
cc完成签到,获得积分10
26秒前
27秒前
chuanyongcui完成签到,获得积分10
27秒前
余杭村王小虎完成签到,获得积分10
28秒前
上官若男应助lt1014采纳,获得10
28秒前
不回发布了新的文献求助10
29秒前
29秒前
30秒前
幸运活勒发布了新的文献求助10
30秒前
30秒前
大气夏瑶完成签到,获得积分10
32秒前
满意问晴发布了新的文献求助10
32秒前
顾矜应助刘恋采纳,获得10
33秒前
不回完成签到,获得积分10
36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
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Resiliency Scale for Adolescents--Chinese Version 600
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
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 7319810
求助须知:如何正确求助?哪些是违规求助? 8935503
关于积分的说明 18942493
捐赠科研通 6978363
什么是DOI,文献DOI怎么找? 3214413
关于科研通互助平台的介绍 2382293
邀请新用户注册赠送积分活动 2193474