Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks.
Nat Biotechnol
; 23(3): 377-83, 2005 Mar.
Article
em En
| MEDLINE
| ID: mdl-15765094
ABSTRACT
A major challenge in drug discovery is to distinguish the molecular targets of a bioactive compound from the hundreds to thousands of additional gene products that respond indirectly to changes in the activity of the targets. Here, we present an integrated computational-experimental approach for computing the likelihood that gene products and associated pathways are targets of a compound. This is achieved by filtering the mRNA expression profile of compound-exposed cells using a reverse-engineered model of the cell's gene regulatory network. We apply the method to a set of 515 whole-genome yeast expression profiles resulting from a variety of treatments (compounds, knockouts and induced expression), and correctly enrich for the known targets and associated pathways in the majority of compounds examined. We demonstrate our approach with PTSB, a growth inhibitory compound with a previously unknown mode of action, by predicting and validating thioredoxin and thioredoxin reductase as its target.
Buscar no Google
Base de dados:
MEDLINE
Assunto principal:
Saccharomyces cerevisiae
/
Algoritmos
/
Desenho de Fármacos
/
Engenharia de Proteínas
/
Transdução de Sinais
/
Regulação da Expressão Gênica
/
Perfilação da Expressão Gênica
/
Proteínas de Saccharomyces cerevisiae
Tipo de estudo:
Evaluation_studies
/
Prognostic_studies
Idioma:
En
Ano de publicação:
2005
Tipo de documento:
Article