Genome-scale screening of drug-target associations relevant to Ki using a chemogenomics approach.

ABSTRACT: The identification of interactions between drugs and target proteins plays a key role in genomic drug discovery. In the present study, the quantitative binding affinities of drug-target pairs are differentiated as a measurement to define whether a drug interacts with a protein or not, and then a chemogenomics framework using an unbiased set of general integrated features and random forest (RF) is employed to construct a predictive model which can accurately classify drug-target pairs. The predictability of the model is further investigated and validated by several independent validation sets. The built model is used to predict drug-target associations, some of which were confirmed by comparing experimental data from public biological resources. A drug-target interaction network with high c

SUBMITTER: Cao DS 

PROVIDER: S-EPMC3618265 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature