Abstract

This study aimed to identify potential novel drug candidates and targets for Parkinson’s disease. First, 970 genes that have been reported to be related to PD were collected from five databases, and functional enrichment analysis of these genes was conducted to investigate their potential mechanisms. Then, we collected drugs and related targets from DrugBank, narrowed the list by proximity scores and Inverted Gene Set Enrichment analysis of drug targets, and identified potential drug candidates for PD treatment. Finally, we compared the expression distribution of the candidate drug-target genes between the PD group and the control group in the public dataset with the largest sample size (GSE99039) in Gene Expression Omnibus. Ten drugs with an FDR < 0.1 and their corresponding targets were identified. Some target genes of the ten drugs significantly overlapped with PD-related genes or already known therapeutic targets for PD. Nine differentially expressed drug-target genes with p < 0.05 were screened. This work will facilitate further research into the possible efficacy of new drugs for PD and will provide valuable clues for drug design.

Details

Title
Integrated network analysis identifying potential novel drug candidates and targets for Parkinson's disease
Author
Quan Pusheng 1 ; Wang, Kai 2 ; Shi, Yan 1 ; Wen Shirong 1 ; Chengqun, Wei 3 ; Zhang, Xinyu 1 ; Cao Jingwei 1 ; Yao Lifen 1 

 The First Affiliated Hospital, Harbin Medical University, Department of Neurology, Harbin, China (GRID:grid.412596.d) (ISNI:0000 0004 1797 9737) 
 The Fourth Affiliated Hospital, Harbin Medical University, Center of TOF-PET/CT/MR, Harbin, China (GRID:grid.411491.8) 
 Heilongjiang Provincial Hospital, Department of General Practice, Harbin, China (GRID:grid.413985.2) (ISNI:0000 0004 1757 7172) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2544321166
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.