Chemogenomic Profiling on a Genome - Wide Scale Using Revers - Engineered Gene Networks  

Oleh:

Collins, James J. ; Bernardo, Diego di ; Thompson, Michael J. ; Gardner, Timothy S. ; Chobot, Sarah E. ; Eastwood, Erin L. ; Wojtovich, Andrew P. ; Elliott, Sean J. ; Schaus, Scott Edward

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Nature Biotechnology: The Science and Business of Biotechnology vol. 23 no. 3 (Mar. 2005), page 377-384.
Topik: networks; chemogenomic; genome wide scale; gene networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: NN9.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

A major challenge in drug discovery is to distinguish the molecular targets of a biocative compoud 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 archieved 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.

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