A transcriptome based approach to predict candidate drug targets and drugs for Parkinson's disease using an in vitro 6-OHDA model

转录组 帕金森病 药品 候选药物 计算生物学 体外 生物 药理学 疾病 基因 基因表达 医学 内科学 遗传学
作者
Esra Nur Yi̇ği̇t,Ekin Sönmez,İsa Yüksel,Işıl Aksan Kurnaz,Tunahan Çakır
出处
期刊:Molecular omics [The Royal Society of Chemistry]
卷期号:19 (3): 218-228 被引量:4
标识
DOI:10.1039/d2mo00267a
摘要

The most common treatment strategies for Parkinson's disease (PD) aim to slow down the neurodegeneration process or control the symptoms. In this study, using an in vitro PD model we carried out a transcriptome-based drug target prediction strategy. We identified novel drug target candidates by mapping genes upregulated in 6-OHDA-treated cells on a human protein-protein interaction network. Among the predicted targets, we show that AKR1C3 and CEBPB are promising in validating our bioinformatics approach since their known ligands, rutin and quercetin, respectively, act as neuroprotective drugs that effectively decrease cell death, and restore the expression profiles of key genes upregulated in 6-OHDA-treated cells. We also show that these two genes upregulated in our in vitro PD model are downregulated to basal levels upon drug administration. As a further validation of our methodology, we further confirm that the potential target genes identified with our bioinformatics approach are also upregulated in post-mortem transcriptome samples of PD patients from the literature. Therefore, we propose that this methodology predicts novel drug targets AKR1C3 and CEBPB, which are relevant to future clinical applications as potential drug repurposing targets for PD. Our systems-based computational approach to predict candidate drug targets can be employed in identifying novel drug targets in other diseases without a priori assumption.
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
xxx发布了新的文献求助10
刚刚
刚刚
刘宇发布了新的文献求助10
刚刚
21完成签到,获得积分10
刚刚
Allen完成签到,获得积分10
刚刚
1秒前
月月发布了新的文献求助10
1秒前
1秒前
1秒前
2秒前
可爱的函函应助爆螺钉采纳,获得10
2秒前
zsmj23发布了新的文献求助10
2秒前
2秒前
3秒前
3秒前
ZHAOYN完成签到,获得积分10
3秒前
ggggg发布了新的文献求助10
4秒前
4秒前
小马甲应助LP采纳,获得10
4秒前
北林发布了新的文献求助30
4秒前
tzjz_zrz发布了新的文献求助10
5秒前
Acetonitrile应助zyh采纳,获得10
5秒前
宁霸发布了新的文献求助10
5秒前
葛怀锐发布了新的文献求助10
6秒前
凉宫sos发布了新的文献求助10
6秒前
6秒前
锅包肉发布了新的文献求助10
7秒前
8秒前
8秒前
波波完成签到,获得积分10
9秒前
海的呼唤发布了新的文献求助10
9秒前
情怀应助嘟嘟嘟采纳,获得10
9秒前
Sledge完成签到,获得积分10
10秒前
不见高山完成签到,获得积分10
10秒前
酷波er应助Keily采纳,获得10
11秒前
无花果应助小九不太乖采纳,获得10
11秒前
科研通AI2S应助慈祥的翠桃采纳,获得10
11秒前
11秒前
英姑应助粥粥采纳,获得10
11秒前
11秒前
高分求助中
The late Devonian Standard Conodont Zonation 2000
The Lali Section: An Excellent Reference Section for Upper - Devonian in South China 1500
Nickel superalloy market size, share, growth, trends, and forecast 2023-2030 1000
Smart but Scattered: The Revolutionary Executive Skills Approach to Helping Kids Reach Their Potential (第二版) 1000
Mantiden: Faszinierende Lauerjäger Faszinierende Lauerjäger 800
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 800
A new species of Coccus (Homoptera: Coccoidea) from Malawi 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 3245398
求助须知:如何正确求助?哪些是违规求助? 2889057
关于积分的说明 8256709
捐赠科研通 2557392
什么是DOI,文献DOI怎么找? 1386090
科研通“疑难数据库(出版商)”最低求助积分说明 650285
邀请新用户注册赠送积分活动 626541