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The Temperature Dependence of Kinetics Associated with Drug Block of hERG Channels Is Compound-Specific and an Important Factor for Proarrhythmic Risk Prediction
Author(s) -
Monique J. Windley,
William Lee,
Jamie I. Vandenberg,
Adam P. Hill
Publication year - 2018
Publication title -
molecular pharmacology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.469
H-Index - 198
eISSN - 1521-0111
pISSN - 0026-895X
DOI - 10.1124/mol.117.111534
Subject(s) - herg , proarrhythmia , in silico , kinetics , chemistry , repolarization , drug , pharmacology , computational biology , biophysics , potassium channel , biology , medicine , electrophysiology , biochemistry , physics , quantum mechanics , gene
Current mandated preclinical tests for drug-induced proarrhythmia are very sensitive, but not sufficiently specific. This has led to concern that there is a high attrition rate of potentially safe drugs that could have been beneficial to patients. The comprehensive in vitro proarrhythmia initiative has proposed new metrics based around in silico risk predictions, which are informed, among other things, by measures of human ether-à-go-go-related gene channel (hERG) block kinetics. However, high-throughput patch-clamp systems set to collect these data largely operate at ambient temperature, whereas the simulations for risk prediction are carried out at physiologic temperature. The aims of this study were to: 1) determine to what degree kinetics of drug block of hERG are temperature-dependent, 2) assess the impact of any temperature dependence of drug binding kinetics on repolarization in silico, and 3) identify whether a common set of Q 10 scalars can be used to extrapolate kinetic data gathered at ambient to physiologic temperatures for use in in silico proarrhythmic risk prediction. We show that, for a range of drugs, kinetics of block are temperature-dependent and, furthermore, that the degree of temperature dependence is different for each drug. As a result, no common set of Q 10 scalars could describe the observed range of temperature dependencies. These results suggest that if accurate physiologic temperature models of the kinetics of drug binding are important for in silico risk prediction, the in vitro data should be acquired at physiologic temperature.

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