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Discovery of the neuroprotective effects of alvespimycin by computational prioritization of potential anti‐parkinson agents
Author(s) -
Gao Li,
Zhao Gang,
Fang JianSong,
Yuan TianYi,
Liu AiLin,
Du GuanHua
Publication year - 2014
Publication title -
the febs journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 204
eISSN - 1742-4658
pISSN - 1742-464X
DOI - 10.1111/febs.12672
Subject(s) - toxicogenomics , drug repositioning , neuroprotection , gene , drug discovery , computational biology , rotenone , parkinson's disease , gene expression , drug development , biology , bioinformatics , disease , mitochondrion , drug , pharmacology , genetics , medicine , pathology
Based on public gene expression data, we propose a computational approach to optimize gene expression signatures for the use with Connectivity Map ( CM ap) to reposition drugs or discover lead compounds for Parkinson's disease. This approach integrates genetic information from the Gene Expression Omnibus ( GEO ) database, the Parkinson's disease gene expression database (Park DB ), the Online Mendelian Inheritance in Man ( OMIM ) database and the Comparative Toxicogenomics Database ( CTD ), with the aim of identifying a set of interesting genes for use in computational drug screening via CM ap. The results showed that CM ap, using the top 20 differentially expressed genes identified by our approach as a gene expression signature, outperformed the same method using all differentially expressed genes ( n = 535) as a signature. Utilizing this approach, the candidate compound alvespimycin (17‐ DMAG ) was selected for experimental evaluation in a model of rotenone‐induced toxicity in human SH ‐ SY 5Y neuroblastoma cells and isolated rat brain mitochondria. The results showed that 17‐ DMAG significantly attenuated rotenone‐induced toxicity, as reflected by the increase of cell viability, the reduction of intracellular reactive oxygen species generation and a reduction in mitochondrial respiratory dysfunction. In conclusion, this computational method provides an effective systematic approach for drug repositioning or lead compound discovery for Parkinson's disease, and the discovery of the neuroprotective effects of 17‐ DMAG supports the practicability of this method.