Predicting drug-target interactions using drug-drug interactions.

ABSTRACT: Computational methods for predicting drug-target interactions have become important in drug research because they can help to reduce the time, cost, and failure rates for developing new drugs. Recently, with the accumulation of drug-related data sets related to drug side effects and pharmacological data, it has became possible to predict potential drug-target interactions. In this study, we focus on drug-drug interactions (DDI), their adverse effects ([Formula: see text]) and pharmacological information ([Formula: see text]), and investigate the relationship among chemical structures, side effects, and DDIs from several data sources. In this study, [Formula: see text] data from the STITCH database, [Formula: see text] from drugs.com, and drug-target pairs from ChEMBL and SIDER were first c

SUBMITTER: Kim S 

PROVIDER: S-EPMC3836969 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature