细胞周期蛋白依赖激酶1
基因
对接(动物)
计算生物学
微阵列
微阵列分析技术
生物信息学
宫颈癌
生物
癌症
遗传学
基因表达
医学
细胞周期
护理部
作者
Harsha Vaghasia,Shiralee Sakaria,Jignesh Prajapati,Meenu Saraf,Rakesh Rawal
标识
DOI:10.1016/j.compbiomed.2022.105994
摘要
Cervical cancer (CC) is the world's fourth most prevalent cancer among women. The mortality rate of cervical cancer increases each year due to a lack of early diagnosis. Our study aims to find potential genes linked to cervical cancer and validate the findings using docking analysis. The microarray datasets (GSE6791, GSE7803, GSE9750, GSE39001, GSE52903, GSE63514, and GSE75132) were downloaded from the GEO (Gene Expression Omnibus) database. A total of 1160 Differentially Expressed Genes (DEGs) were discovered using the R statistical language, including 825 up-regulated and 335 down-regulated genes. STRING, which predicts the potential interaction between genes at the protein level, was used to build the PPI network of these DEGs. Moreover, hub gene expression analysis was carried out by CytoHubba plugin Cytoscape. CDK1 was considered for subsequent molecular docking because of its frequent appearance throughout the analysis. CDK1 was docked with the 399 phytochemicals of Indian kitchen spices. The top three compounds namely, Vicenin 2, 2-O,3-O,4-O,6-O-Tetragalloyl-d-glucopyranose and Pentagalloylglucose, were chosen based on their docking scores and their interactions with the key amino acids present in the ATP binding pocket, like the positive control Dinaciclib. In conclusion, the findings of this study may lead to new insights on CC diagnosis, aetiology, and treatment options. In the future, it may be possible to develop particular diagnostics and therapies for CC by identifying hub genes and studying overexpressed proteins as therapeutic targets.
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