Key result
In silico drug-IKr binding kinetics strongly dictate reverse use-dependence and vulnerable proarrhythmic windows.
Why the study?
In silico human models are increasingly used to predict proarrhythmic risk, but the impact of drug-hERG channel interaction dynamics on biomarkers beyond action potential duration at normal heart rates is not fully understood.
Incorporating drug-hERG channel interaction dynamics into in silico models improves the prediction of proarrhythmic risk for new compounds.
In silico models with drug-hERG dynamics may improve proarrhythmic biomarker assessment; leaves open whether they should alter clinical risk stratification.
BACKGROUND AND OBJECTIVE: In silico human models are being used more and more to predict the potential proarrhythmic risk of compounds. It has been shown that incorporation of the dynamics of drug-hERG channel interactions can have an important impact on the action potential duration (APD) at normal heart rates. Our aim is to investigate the relevance of drug dynamics on other important biomarkers of proarrhythmic risk. METHODS: blockers at the concentration leading to a 25 % prolongation of the APD. RESULTS: blockers are in line with those obtained with the virtual drugs. CONCLUSIONS: blockers. Moreover, adoption of in silico models mimicking these characteristics would contribute to the improvement of the prediction of the proarrhythmic risk of new compounds.
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Gomis-Tena et al. (2024) studied Proarrhythmic risk. Drug-IKr binding mechanisms (blockers) was evaluated on Biomarkers of proarrhythmic risk (action potential duration and vulnerable window). In silico modeling of drug-IKr binding mechanisms reveals a crucial role in reverse use-dependence of action potential duration and a marked influence on the vulnerable window for proarrhythmic risk.
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