药物数据库
肺癌
医学
癌症
交互网络
传统医学
药品
活性成分
药理学
内科学
肿瘤科
计算生物学
化学
生物
生物化学
基因
作者
Sixian Liang,Yin Li,Xiangguo Zhang,Yugan Guo,Suming Pan
出处
期刊:Anti-cancer Agents in Medicinal Chemistry
[Bentham Science]
日期:2021-02-12
卷期号:21 (15): 2012-2022
被引量:5
标识
DOI:10.2174/1871520621666210126090632
摘要
Compound Kushen Injection (CKI) is used clinically for relieving cancer pain and treating various solid tumors, particularly lung cancer. However, the underlying mechanisms of CKI in lung cancer remain to be further elucidated.This study aimed to obtain evidence regarding the potential efficacy of the active compounds and therapeutic targets of CKI at a molecular level by using Network Pharmacology (NP), which is an emerging technique for dealing with complex systems, such as those of herbal medicine.The chemical and predicted target information of CKI was obtained from databases and computational prediction, respectively; lung-cancer drugs and their corresponding targets were retrieved from Drugbank and Drugcentral. The online tool, STRING, was used to gather target-pathway interactions for establishing a target-(pathway)-target network to identify the target group that was most relevant to cancer. Based on this module, a protein-protein interaction network was established for identifying the potential therapeutic targets and the potential active ingredients.CKI might affect lung cancer drug targets or their neighbor nodes to trigger anti-cancer effects. The compounds that were predicted to bind to the potential therapeutic targets were recommended as potential active ingredients of CKI, which included naringenin from Baituling, and kurarinone and isoxanthohumol from Kushen.This NP-based study might provide insights into understanding CKI from the perspective of modern science with reference to approved Western medicine for lung cancer. Moreover, network-based methods could also be further used with distinct advantages in dealing with complex information and systems of medicine.
科研通智能强力驱动
Strongly Powered by AbleSci AI