Network-based relating pharmacological and genomic spaces for drug target identification.

ABSTRACT:

Background

Identifying drug targets is a critical step in pharmacology. Drug phenotypic and chemical indexes are two important indicators in this field. However, in previous studies, the indexes were always isolated and the candidate proteins were often limited to a small subset of the human genome.

Methodology/principal findings

Based on the correlations observed in pharmacological and genomic spaces, we develop a computational framework, drugCIPHER, to infer drug-target interactions in a genome-wide scale. Three linear regression models are proposed, which respectively relate drug therapeutic similarity, chemical similarity and their combination to the relevance of the targets on the basis of a protein-protein interaction network. Typically, the model integrating both drug

SUBMITTER: Zhao S 

PROVIDER: S-EPMC2909904 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature