Key result
Enhanced QSAR models combining in vitro parameters and physico-chemical descriptors demonstrated reasonably high predictive power for cardiac ion current inhibition in 10-fold cross-validation.
Enhanced QSAR models combining in vitro parameters and physico-chemical descriptors provide reliable predictions of drug-induced cardiac ion channel block, aiding in preclinical cardiac safety testing.
The currently changing cardiac safety testing paradigm suggests, among other things, a shift towards using in silico models of cellular electrophysiology and assessment of a concomitant block of multiple ion channels. In this study, a set of four enhanced QSAR models have been developed: for the rapid delayed rectifying potassium current (IKr), slow delayed rectifying potassium current (IKs), peak sodium current (INa) and late calcium current (ICaL), predicting ion currents changes for the specific in vitro experiment from the 2D structure of the compounds. The models are a combination of both in vitro study parameters and physico-chemical descriptors, which is a novel approach in drug-ion channels interactions modeling. Their predictive power assessed in the enhanced, more demanding than standard procedure, 10-fold cross validation was reasonably high. Rough comparison with published pure in silico hERG interaction models shows that the quality of the model predictions does not differ from other models available in the public domain, however, it takes its advantage in accounting for inter-experimental settings variability. Developed models are implemented in the Cardiac Safety Simulator, a commercially available platform enabling the in vitro-in vivo extrapolation of the drugs proarrhythmic effect and ECG simulation. A more comprehensive assessment of the effects of the compounds on ion channels allows for making more informed decisions regarding the risk - and thus avoidance - of exclusion of potentially safe and effective drugs.
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Wiśniowska et al. (2015) studied Drug-induced proarrhythmia. Enhanced QSAR models for cardiac ion currents (IKr, IKs, INa, ICaL) vs. Published pure in silico hERG interaction models was evaluated on Predictive power for ion currents changes. Enhanced QSAR models combining in vitro parameters and physico-chemical descriptors demonstrated reasonably high predictive power for cardiac ion current inhibition in 10-fold cross-validation.
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