Identifying the potential anti-lung cancer targets of Baicalein using a network pharmacology approach

作者
Xiaoping Chen,Kehan Chen,Xingxing Ma,Bo Chen,Peng Liang,Qianxi Chen
出处
期刊:Scientific Reports [Nature Portfolio]
卷期号:16 (1): 5527-5527 被引量:2
标识
DOI:10.1038/s41598-026-35351-6
摘要

Background Lung cancer remains the deadliest malignancy globally. Although therapies, including immune checkpoint inhibitors and targeted therapy, have gradually prolonged overall survival, resistance and relapse still plague clinical management. Baicalein, a naturally derived compound exhibiting potent antitumor and anti-inflammatory properties, is widely regarded as a promising candidate for the development of anticancer therapeutic agents. Nevertheless, its mechanism of action in lung cancer remains unclear. Objective This study aims to elucidate the multi-target pharmacological mechanism by which Baicalein acts in lung cancer treatment, utilizing network pharmacology, immune infiltration analysis, molecular docking, and molecular dynamics simulation. Methods Using the TCMSP, Swiss Target Prediction, and Pharm Mapper databases, we identified the relevant targets of Baicalein. Meanwhile, lung cancer-associated targets were retrieved from the GeneCards database. The targets were obtained by taking the intersection of these two sets. A protein-protein interaction (PPI) network was then constructed using Cytoscape. Furthermore, the influence of these core targets to the tumor immune microenvironment was investigated via immune infiltration analysis. Finally, we employed molecular docking to evaluate the binding affinity between Baicalein and targets, followed by molecular dynamics simulations to confirm the stability of these interactions. Results A total of 92 potential targets of Baicalein for lung cancer were identified. Five core targets, including TP53, AKT1, MAPK3, BCL2, and EGFR, were determined based on the connectivity characteristics of the PPI network. These core targets were significantly enriched in the PI3K-AKT signaling pathway. Molecular dynamics simulations displayed that the binding free energy of the AKT1-baicalein complex was - 199.8 kJ/mol. Energy decomposition analysis suggested that complex stabilization is primarily driven by shape complementarity and hydrophobic effects, rather than conventional hydrogen bonding or salt bridges. Conclusion This study reveals that the antitumor activity of Baicalein is mediated through its multi-target action on core components of the PI3K-AKT pathway, thereby offering novel insights for exploring its therapeutic targets.
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
秀丽的忆南完成签到,获得积分10
刚刚
从容的鱼发布了新的文献求助10
1秒前
gu完成签到,获得积分20
1秒前
1秒前
1秒前
tianzhen完成签到,获得积分10
3秒前
3秒前
科研通AI6.4的应助被冷静怜珊采纳,获得10
4秒前
百里健柏完成签到,获得积分10
4秒前
zhouqin完成签到 ,获得积分10
4秒前
5秒前
5秒前
李李李发布了新的文献求助10
6秒前
6秒前
shisui完成签到,获得积分10
6秒前
打我呀发布了新的文献求助10
6秒前
7秒前
8秒前
8秒前
bq完成签到,获得积分10
8秒前
霡霂完成签到,获得积分20
9秒前
ding的应助被lilibibi采纳,获得10
10秒前
12秒前
12秒前
QQ发布了新的文献求助10
12秒前
霡霂发布了新的文献求助10
12秒前
isonomia发布了新的文献求助200
17秒前
温温的应助被刘铠瑜采纳,获得10
17秒前
酷波er的应助被自然丹寒采纳,获得10
18秒前
杨杨杨完成签到 ,获得积分10
18秒前
lilin完成签到,获得积分10
19秒前
秀丽笑容发布了新的文献求助10
19秒前
19秒前
dunphy完成签到 ,获得积分10
20秒前
20秒前
22秒前
lilin发布了新的文献求助30
22秒前
斯文败类的应助被wei采纳,获得10
22秒前
weirdo发布了新的文献求助10
22秒前
Cherry完成签到 ,获得积分10
23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
Spec 401: Standards for Jet Fuel Facility and Equipment Commissioning and Flushing at Airports, 2026.1 (Original Issue) 1000
Spec 103: Standard for Jet Fuel Quality Control at Airports, Revision 2026.1 1000
5th World Conference on Detergents: Reinventing the Industry : Opportunities and Challenges 500
Erzählte Gnade 500
Butadiene hydroxytelechelic oligomers PBHT 500
Illustrated Atlas of Aesthetic Botulinum Toxin Therapy 388
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8104468
求助须知:如何正确求助?哪些是违规求助? 9513814
关于积分的说明 21489133
捐赠科研通 7680767
什么是DOI,文献DOI怎么找? 3409416
关于科研通互助平台的介绍 2537199
邀请新用户注册赠送积分活动 2449312