Mechanism of astragaloside A against lung adenocarcinoma based on network pharmacology combined with molecular dynamics simulation technique

机制(生物学) 腺癌 计算机科学 动力学(音乐) 计算生物学 药理学 生物信息学 医学 生物 内科学 癌症 心理学 教育学 哲学 认识论
作者
Jian Ding,Qian Xue,Weizhen Guo,Gang Cheng,Lu Zhang,Tian‐Yun Huang,Di Wu,Jincheng Tong,Cheng Yang,Yu‐Tang Gao,Zegeng Li
出处
期刊:Scientific Reports [Nature Portfolio]
卷期号:15 (1)
标识
DOI:10.1038/s41598-025-94793-6
摘要

This study explores the mechanisms of Astragaloside A (AS-A), a significant active ingredient in Astragalus, This traditional Chinese medicine is both a medication and a food, combating lung adenocarcinoma using network pharmacology, molecular docking, molecular dynamics, and experimental validation. A protein-protein interaction (PPI) network was developed, identifying 10 key targets, including STAT3 and AKT1. GO and KEGG enrichment analyses indicated that these targets primarily participated in biological processes and pathways, including oxidative stress and the PI3K-Akt signalling pathway. Molecular docking and dynamic simulation evaluated AS-A's binding mode and stability with key targets. In molecular docking, 14 key targets of the HIF-1 signalling pathway had different binding energies with AS-A, such as the binding energy of PIK3R1 being -9.3. Kinetic simulations indicated the stability of the protein-ligand complex, as evidenced by RMSD values ranging from 0.2 to 0.4 nm. RMSF analysis showed that the protein residue flexibility characteristics were stable, the Rg values were stable, the number of hydrogen bonds was 10-20, and the solvent-accessible surface area was stable. Cell experiments showed that AS-A could regulate the expression of key signalling molecules such as STAT3 and AKT in lung adenocarcinoma models. This study provides insights into the mechanism of AS-A in treating lung adenocarcinoma. It proposes a new direction for anticancer research in traditional Chinese medicines, especially medications and foods.

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
FashionBoy应助科研通管家采纳,获得10
刚刚
在水一方应助科研通管家采纳,获得10
刚刚
打打应助科研通管家采纳,获得10
刚刚
Ava应助科研通管家采纳,获得10
刚刚
Nexus应助科研通管家采纳,获得10
刚刚
清秀冰凡发布了新的文献求助10
1秒前
漂亮藏鸟完成签到,获得积分20
1秒前
华仔应助科研通管家采纳,获得10
1秒前
清爽子默完成签到,获得积分10
1秒前
星辰大海应助科研通管家采纳,获得150
1秒前
星辰大海应助科研通管家采纳,获得10
1秒前
彭于晏应助雪山飞狐采纳,获得10
1秒前
1秒前
Owen应助科研通管家采纳,获得10
1秒前
传奇3应助科研通管家采纳,获得10
1秒前
FashionBoy应助科研通管家采纳,获得10
1秒前
1秒前
Moonlight应助科研通管家采纳,获得10
1秒前
脑洞疼应助科研通管家采纳,获得10
1秒前
传奇3应助科研通管家采纳,获得10
1秒前
1秒前
1秒前
2秒前
Hello应助科研通管家采纳,获得10
2秒前
2秒前
2秒前
JamesPei应助科研通管家采纳,获得10
2秒前
在水一方应助科研通管家采纳,获得30
2秒前
Avalonx应助科研通管家采纳,获得20
2秒前
Sea_U应助科研通管家采纳,获得10
2秒前
英姑应助科研通管家采纳,获得10
2秒前
Owen应助科研通管家采纳,获得10
2秒前
2秒前
ding应助科研通管家采纳,获得10
2秒前
搜集达人应助科研通管家采纳,获得10
2秒前
NexusExplorer应助科研通管家采纳,获得10
2秒前
JamesPei应助科研通管家采纳,获得30
2秒前
蓝天应助科研通管家采纳,获得10
2秒前
3秒前
3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
Adhesion Science: Principles & Practice 800
The Graphene Handbook (2019 Edition) 700
Signals, Systems, and Signal Processing 610
IEST-RP-CC018: Cleanroom Cleaning and Sanitization: Operating and Monitoring Procedures 600
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 600
Fundamentals of Modern Mathematics: A Practical Review (Dover Books on Mathematics) 500
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 6533166
求助须知:如何正确求助?哪些是违规求助? 8326250
关于积分的说明 17832837
捐赠科研通 5634468
什么是DOI,文献DOI怎么找? 2933747
邀请新用户注册赠送积分活动 1910109
关于科研通互助平台的介绍 1768920