亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Potential anti-liver cancer targets and mechanisms of kaempferitrin based on network pharmacology, molecular docking and experimental verification

药物数据库 计算生物学 小桶 肝癌 对接(动物) 生物信息学 生物 交互网络 癌症 癌症研究 基因 药理学 生物化学 转录组 基因表达 医学 遗传学 护理部 药品
作者
Siyu Zhou,Huidong Zhang,Jiao Li,Wei Li,Min Su,Yao Ren,Fengya Ge,Hong Zhang,Hongli Shang
出处
期刊:Computers in Biology and Medicine [Elsevier]
卷期号:178: 108693-108693 被引量:19
标识
DOI:10.1016/j.compbiomed.2024.108693
摘要

Kaempferitrin is an active component in Chenopodium ambrosioides, showing medicinal functions against liver cancer. This study aimed to identify the potential targets and pathways of kaempferitrin against liver cancer using network pharmacology and molecular docking, and verify the essential hub targets and pathway in mice model of SMMC-7721 cells xenografted tumors and SMMC-7721 cells. Kaempferitrin therapeutical targets were obtained by searching SwissTargetPrediction, PharmMapper, STITCH, DrugBank, and TTD databases. Liver cancer specific genes were obtained by searching GeneCards, DrugBank, TTD, OMIM, and DisGeNET databases. PPI network of "kaempferitrin-targets-liver cancer" was constructed to screen the hub targets. GO, KEGG pathway and MCODE clustering analyses were performed to identify possible enrichment of genes with specific biological subjects. Molecular docking and molecular dynamics simulation were employed to determine the docking pose, potential and stability of kaempferitrin with hub targets. The potential anti-liver cancer mechanisms of kaempferitrin, as predicted by network pharmacology analyses, were verified by in vitro and in vivo experiments. 228 kaempferitrin targets and 2186 liver cancer specific targets were identified, of which 50 targets were overlapped. 8 hub targets were identified through network topology analysis, and only SIRT1 and TP53 had a potent binding activity with kaempferitrin as indicated by molecular docking and molecular dynamics simulation. MCODE clustering analysis revealed the most significant functional module of PPI network including SIRT1 and TP53 was mainly related to cell apoptosis. GO and KEGG enrichment analyses suggested that kaempferitrin exerted therapeutic effects on liver cancer possibly by promoting apoptosis via p21/Bcl-2/Caspase 3 signaling pathway, which were confirmed by in vivo and in vitro experiments, such as HE staining of tumor tissues, CCK-8, qRT-PCR and western blot. This study provided not only insight into how kaempferitrin could act against liver cancer by identifying hub targets and their associated signaling pathways, but also experimental evidence for the clinical use of kaempferitrin in liver cancer treatment.
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
2秒前
SSY发布了新的文献求助10
8秒前
dwz完成签到,获得积分10
13秒前
16秒前
20秒前
Marciu33完成签到,获得积分10
20秒前
Theta完成签到,获得积分10
22秒前
dwz发布了新的文献求助10
23秒前
kcl发布了新的文献求助10
27秒前
fu完成签到,获得积分10
28秒前
35秒前
wmd完成签到,获得积分20
48秒前
东城区吴彦祖完成签到,获得积分10
51秒前
ys完成签到 ,获得积分10
51秒前
姬双完成签到,获得积分20
52秒前
许大脚完成签到 ,获得积分10
54秒前
正直的不平完成签到,获得积分10
56秒前
姬双发布了新的文献求助10
1分钟前
NiceSunnyDay完成签到 ,获得积分10
1分钟前
komorebi完成签到 ,获得积分10
1分钟前
jintian完成签到 ,获得积分10
1分钟前
所所应助SSY采纳,获得10
1分钟前
1分钟前
未来可期发布了新的文献求助30
1分钟前
2分钟前
寒冷念文完成签到,获得积分10
2分钟前
讨厌下雨天完成签到 ,获得积分10
2分钟前
完美世界应助跳跃采纳,获得10
2分钟前
量子星尘发布了新的文献求助30
2分钟前
寒冷念文发布了新的文献求助10
2分钟前
就吃一小口完成签到 ,获得积分10
2分钟前
2分钟前
跳跃发布了新的文献求助10
2分钟前
2分钟前
2分钟前
万能图书馆应助是Tt呀采纳,获得10
2分钟前
2分钟前
3分钟前
dwz发布了新的文献求助10
3分钟前
慕青应助kcl采纳,获得10
3分钟前
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
Introduction to strong mixing conditions volume 1-3 5000
Clinical Microbiology Procedures Handbook, Multi-Volume, 5th Edition 2000
The Cambridge History of China: Volume 4, Sui and T'ang China, 589–906 AD, Part Two 1000
The Composition and Relative Chronology of Dynasties 16 and 17 in Egypt 1000
Real World Research, 5th Edition 800
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5723624
求助须知:如何正确求助?哪些是违规求助? 5279622
关于积分的说明 15298934
捐赠科研通 4872008
什么是DOI,文献DOI怎么找? 2616456
邀请新用户注册赠送积分活动 1566278
关于科研通互助平台的介绍 1523161