In Silico Assessment of Atrial Fibrillation-Selectivity of Ikur Inhibitors: Role of Variability in Disease-Associated Remodeling

Abstract

The ultra-rapid delayed-rectifier current (IKur), carried by the atrial predominant (vs. ventricle) alpha subunit KV1.5, has been studied as a promising target to treat atrial fibrillation (AF). However, while numerous KV1.5-selective compounds have been screened in vitro and in animal models of AF, evidence of antiarrhythmic efficacy in human clinical trials is lacking, perhaps because preclinical assessment of candidate drugs overly relies on steady state drug concentration response curves rather than accounting for channel conformational state specificity and kinetics of drug binding. Here, we simulated a Markov-type model of IKur gating and drug-channel interaction within our comprehensive atrial cell model to reveal the ideal binding properties of IKur inhibitors that maximize AF-selectivity in normal sinus rhythm (nSR) and chronic AF (cAF). Specifically, we identified drugs exhibiting anti-AF properties at fast-pacing rates (prolongation of effective refractory period, ERP), while having little effect during normal heart rhythm (limited prolongation of action potential duration, APD). We also found that despite being downregulated in our simulations (by 50%), IKur contributes more prominently to APD and ERP in cAF than in nSR, and block of IKur in cAF has less cardiotoxic effects and increased efficacy. Finally, we studied how inter-subject variability and/or variable degrees of ionic remodeling modulate the response to IKur anti-AF therapy, by revealing the efficacy and toxicity of IKur inhibitors in populations of nSR and cAF atrial myocyte models, where ion channel conductances are randomly varied in each cell. Our in silico strategy can be combined with in vitro and in vivo assays to identify the complex net impact of IKur inhibitors in different AF-remodeling conditions, and to facilitate the ongoing search for novel agents against AF during the pre-clinical drug development process.