Predicting inhibitory and activatory drug targets by chemically and genetically perturbed transcriptome signatures.

ABSTRACT: Genome-wide identification of all target proteins of drug candidate compounds is a challenging issue in drug discovery. Moreover, emerging phenotypic effects, including therapeutic and adverse effects, are heavily dependent on the inhibition or activation of target proteins. Here we propose a novel computational method for predicting inhibitory and activatory targets of drug candidate compounds. Specifically, we integrated chemically-induced and genetically-perturbed gene expression profiles in human cell lines, which avoided dependence on chemical structures of compounds or proteins. Predictive models for individual target proteins were simultaneously constructed by the joint learning algorithm based on transcriptomic changes in global patterns of gene expression profiles following chemic

SUBMITTER: Sawada R 

PROVIDER: S-EPMC5760621 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature