Evaluating current status of network pharmacology for herbal medicine focusing on identifying mechanisms and therapeutic effects

医学 药理学 传统医学
作者
Won-Yung Lee,Kwang‐Il Park,Seon-Been Bak,Seung‐Ho Lee,Su-Jin Bae,Min‐Jin Kim,Sun‐Dong Park,Choon Ok Kim,Ji-Hwan Kim,Young Woo Kim,Chang-Eop Kim
出处
期刊:Journal of Advanced Research [Elsevier BV]
卷期号:76: 799-815 被引量:22
标识
DOI:10.1016/j.jare.2024.12.040
摘要

INTRODUCTION: Network pharmacology has gained significant traction as a tool for identifying the mechanisms and therapeutic effects of herbal medicines. However, despite the usefulness of these approaches, their diversity underscores the critical need for a systematic evaluation to ensure consistency and reliability. OBJECTIVES: We aimed to evaluate the network pharmacological analyses, focusing on identifying the mechanisms and therapeutic effects of herbal medicines. METHODS: We employed a comprehensive approach involving systematic data retrieval, network construction, and analysis. Herbal compounds and their targets were meticulously extracted from five distinct network pharmacology databases to ensure extensive coverage and high data reliability. Advanced network-based methods were used to identify key herbal targets and predict therapeutic effects, thereby enriching the depth and breadth of the analysis. Experimental validation was performed on prostate cancer models to substantiate the computational predictions. RESULTS: The results of the recapitulating task for known herbal ingredient targets revealed distinct patterns in performance and coverage based on network construction and aggregation methods. We performed the same analysis to identify herbal targets and found that network centrality, path counts, and downweighted path counts had their own pros and cons. By comparing network-based methods, we found that considering the impact on the multiscale interactome yielded the highest accuracy in discriminating known therapeutic effects. Using optimal conditions, we successfully identified new indications for herbal medicines and validated these findings through follow-up in vitro and in vivo experiments. CONCLUSION: This study presents the first comprehensive and critical evaluation of the current network pharmacology analyses in the field of herbal medicine and provides valuable guidance for continued advances in the elucidation of the mechanisms and therapeutic effects.
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
rzn完成签到 ,获得积分10
刚刚
默幻弦完成签到,获得积分10
1秒前
ligaft发布了新的文献求助10
1秒前
2秒前
鱼子酱发布了新的文献求助10
2秒前
2秒前
3秒前
zxy关注了科研通微信公众号
3秒前
所所应助深海采纳,获得10
4秒前
今后应助Smiling采纳,获得30
4秒前
十二应助自信的牛排采纳,获得10
4秒前
luckbaby发布了新的文献求助10
4秒前
才高八斗发布了新的文献求助10
5秒前
6秒前
Aroojshams发布了新的文献求助10
6秒前
vivid完成签到,获得积分10
7秒前
7秒前
李健应助111采纳,获得10
7秒前
Dallas发布了新的文献求助10
8秒前
逍遥发布了新的文献求助30
9秒前
10秒前
英姑应助医药小康采纳,获得10
10秒前
10秒前
12秒前
13秒前
整齐续完成签到,获得积分10
14秒前
wi发布了新的文献求助10
16秒前
16秒前
16秒前
YHQ发布了新的文献求助10
16秒前
17秒前
苏苏不是我完成签到,获得积分10
17秒前
18秒前
江河发布了新的文献求助10
18秒前
18秒前
称心小天鹅完成签到,获得积分10
19秒前
xiaochuan发布了新的文献求助30
19秒前
luckbaby完成签到,获得积分10
19秒前
王鑫完成签到,获得积分10
19秒前
joker完成签到,获得积分10
19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
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Rosenblum, Global Change Biology 500
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
DIPPR Project 801 - Full Version 380
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 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7768165
求助须知:如何正确求助?哪些是违规求助? 9311532
关于积分的说明 20324156
捐赠科研通 7353204
什么是DOI,文献DOI怎么找? 3315619
关于科研通互助平台的介绍 2464810
邀请新用户注册赠送积分活动 2330307