Mechanisms underlying the therapeutic effects of cinobufagin in treating melanoma based on network pharmacology, single-cell RNA sequencing data, molecular docking, and molecular dynamics simulation

黑色素瘤 小桶 生物 药物数据库 癌症研究 计算生物学 基因 基因表达 药理学 遗传学 药品 转录组
作者
Yang Jian-sheng,Christine Cheng,Zhuolin Wu
出处
期刊:Frontiers in Pharmacology [Frontiers Media SA]
卷期号:14
标识
DOI:10.3389/fphar.2023.1315965
摘要

Malignant melanoma is one of the most aggressive of cancers; if not treated early, it can metastasize rapidly. Therefore, drug therapy plays an important role in the treatment of melanoma. Cinobufagin, an active ingredient derived from Venenum bufonis, can inhibit the growth and development of melanoma. However, the mechanism underlying its therapeutic effects is unclear. The purpose of this study was to predict the potential targets of cinobufagin in melanoma. We gathered known and predicted targets for cinobufagin from four online databases. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were then performed. Gene expression data were downloaded from the GSE46517 dataset, and differential gene expression analysis and weighted gene correlation network analysis were performed to identify melanoma-related genes. Using input melanoma-related genes and drug targets in the STRING online database and applying molecular complex detection (MCODE) analysis, we identified key targets that may be the potential targets of cinobufagin in melanoma. Moreover, we assessed the distribution of the pharmacological targets of cinobufagin in melanoma key clusters using single-cell data from the GSE215120 dataset obtained from the Gene Expression Omnibus database. The crucial targets of cinobufagin in melanoma were identified from the intersection of key clusters with melanoma-related genes and drug targets. Receiver operating characteristic curve (ROC) analysis, survival analysis, molecular docking, and molecular dynamics simulation were performed to gain further insights. Our findings suggest that cinobufagin may affect melanoma by arresting the cell cycle by inhibiting three protein tyrosine/serine kinases (EGFR, ERBB2, and CDK2). However, our conclusions are not supported by relevant experimental data and require further study.
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
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
子凡完成签到,获得积分10
刚刚
1秒前
小木发布了新的文献求助10
1秒前
1秒前
1秒前
吃不饱星球球长应助123采纳,获得20
1秒前
光亮笑柳发布了新的文献求助10
2秒前
开心夏云应助asiera采纳,获得10
2秒前
无语的鱼完成签到,获得积分10
3秒前
宓不评发布了新的文献求助10
3秒前
赘婿应助赵哥采纳,获得10
4秒前
4秒前
所所应助JxJ采纳,获得10
5秒前
吐司大王发布了新的文献求助10
5秒前
nan发布了新的文献求助10
6秒前
阿yueyue完成签到 ,获得积分10
6秒前
sq完成签到 ,获得积分10
8秒前
8秒前
8秒前
8秒前
8秒前
雪123发布了新的文献求助10
9秒前
9秒前
more应助浅浅采纳,获得10
10秒前
小小发布了新的文献求助10
11秒前
11秒前
stronger发布了新的文献求助10
12秒前
fan发布了新的文献求助10
13秒前
Onyx完成签到,获得积分20
13秒前
TO完成签到,获得积分10
13秒前
Alwaite完成签到 ,获得积分10
14秒前
14秒前
大模型应助不晚采纳,获得10
14秒前
孤独梦曼发布了新的文献求助10
15秒前
大宇完成签到,获得积分10
15秒前
章鱼大丸子完成签到,获得积分10
16秒前
小顾完成签到,获得积分20
16秒前
YESKY发布了新的文献求助10
16秒前
完美世界应助Kevin采纳,获得10
17秒前
adrenline完成签到,获得积分10
18秒前
高分求助中
Evolution 10000
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
Mantiden: Faszinierende Lauerjäger Faszinierende Lauerjäger 600
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
A new species of Velataspis (Hemiptera Coccoidea Diaspididae) from tea in Assam 500
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3156528
求助须知:如何正确求助?哪些是违规求助? 2807966
关于积分的说明 7875565
捐赠科研通 2466256
什么是DOI,文献DOI怎么找? 1312779
科研通“疑难数据库(出版商)”最低求助积分说明 630273
版权声明 601919