Making Sense of Large-Scale Kinase Inhibitor Bioactivity Data Sets: A Comparative and Integrative Analysis

We
carried out a systematic evaluation of target selectivity profiles
across three recent large-scale biochemical assays of kinase inhibitors
and further compared these standardized bioactivity assays with data
reported in the widely used databases ChEMBL and STITCH. Our comparative
evaluation revealed relative benefits and potential limitations among
the bioactivity types, as well as pinpointed biases in the database
curation processes. Ignoring such issues in data heterogeneity and
representation may lead to biased modeling of drugs’ polypharmacological
effects as well as to unrealistic evaluation of computational strategies
for the prediction of drug–target interaction networks. Toward
making use of the complementary information captured by the various
bioactivity types, including IC50, Ki, and Kd, we also introduce a
model-based integration approach, termed KIBA, and demonstrate here
how it can be used to classify kinase inhibitor targets and to pinpoint
potential errors in database-reported drug–target interactions.
An integrated drug–target bioactivity matrix across 52 498
chemical compounds and 467 kinase targets, including a total of 246 088
KIBA scores, has been made freely available.