Protein-protein interaction network analysis for the identification of novel multi-target inhibitors and target miRNAs against Alzheimer’s disease

鉴定(生物学) 小RNA 疾病 计算生物学 蛋白质-蛋白质相互作用 生物 医学 遗传学 基因 病理 植物
作者
Vinay Kumar,Kunal Roy
出处
期刊:Advances in protein chemistry and structural biology
标识
DOI:10.1016/bs.apcsb.2023.11.005
摘要

This study presents a strategy for extracting significant gene complexes and then provides prospective therapeutics for AD. In this research, a total of 7905 reports published from 1981 to 2022 were retrieved. Following a review of all those articles, only the genetic association studies on AD were considered. Finally, there is a list of 453 Alzheimer-related genes in our dataset for network analysis. To this end, an experimentally derived protein-protein interaction (PPI) network from the String database was utilized to extract four meaningful gene complexes functionally interconnected using Cytoscape v3.9.1 software. The acquired gene complexes were subjected to an enrichment analysis using the ClueGO v2.5.9 tool to emphasize the most significant biological processes and pathways. Afterward, extracted gene complexes were used to extract the drugs related to AD from DGI v3.0 database and introduce some new drugs which may be helpful for this disease. Finally, a comprehensive network that included every gene connected to each gene complex group as well as the drug targets for each gene has been shown. Moreover, molecular docking studies have been performed with the selected compounds to identify the interaction pattern with the respective targets. Finally, we proposed a list of 62 compounds as multi-targeted directed drug-like compounds with a degree value between 2 and 5 and 30 compounds as target-specific drug-like compounds, which have not been proclaimed as AD-related drugs in prior scientific and medical investigations. Then, new drugs were suggested that can be experimentally examined for future work. In addition to this, four bipartite networks representing each group’s genes and target miRNAs were established to introduce target miRNAs by using the miRWalk v3 server.
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
刚刚
1秒前
xiaoan应助Ll采纳,获得10
1秒前
充电宝应助轻松的雪枫采纳,获得10
1秒前
冷酷莫茗发布了新的文献求助10
1秒前
2秒前
btbu2015应助kk采纳,获得50
2秒前
2秒前
2秒前
3秒前
开心栾完成签到,获得积分10
3秒前
小王博士发布了新的文献求助10
3秒前
脑洞疼应助标致的方盒采纳,获得10
3秒前
he发布了新的文献求助20
3秒前
共享精神应助杨66采纳,获得10
3秒前
4秒前
是ok耶完成签到,获得积分10
4秒前
4秒前
poorzz发布了新的文献求助20
5秒前
千百度发布了新的文献求助10
5秒前
cxecho发布了新的文献求助10
6秒前
hululu发布了新的文献求助10
6秒前
yyxhahaha完成签到,获得积分10
7秒前
7秒前
麦迪应助Dai采纳,获得30
7秒前
乐乐应助马绍清采纳,获得10
8秒前
9秒前
开心栾发布了新的文献求助150
10秒前
10秒前
11秒前
11秒前
11秒前
刻苦耳机关注了科研通微信公众号
11秒前
情怀应助捱小秋采纳,获得10
12秒前
思源应助青尘枫叶采纳,获得10
12秒前
大1完成签到,获得积分10
12秒前
司空茵茵发布了新的文献求助10
13秒前
无理完成签到 ,获得积分10
14秒前
小王博士完成签到,获得积分10
14秒前
MING完成签到,获得积分20
14秒前
高分求助中
Handbook of Fuel Cells, 6 Volume Set 1666
求助这个网站里的问题集 1000
Floxuridine; Third Edition 1000
Tracking and Data Fusion: A Handbook of Algorithms 1000
Sustainable Land Management: Strategies to Cope with the Marginalisation of Agriculture 800
消化器内視鏡関連の偶発症に関する第7回全国調査報告2019〜2021年までの3年間 500
One Man Talking: Selected Essays of Shao Xunmei, 1929–1939 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 内科学 物理 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 冶金 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 2862358
求助须知:如何正确求助?哪些是违规求助? 2468242
关于积分的说明 6693068
捐赠科研通 2159043
什么是DOI,文献DOI怎么找? 1146996
版权声明 585178
科研通“疑难数据库(出版商)”最低求助积分说明 563543