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Revealing kinetics and state-dependent binding properties of IKur-targeting drugs that maximize atrial fibrillation selectivity.

Nicholas EllinwoodDobromir DobrevStefano MorottiEleonora Grandi
Published in: Chaos (Woodbury, N.Y.) (2018)
The KV1.5 potassium channel, which underlies the ultra-rapid delayed-rectifier current (IKur) and is predominantly expressed in atria vs. ventricles, has emerged as a promising target to treat atrial fibrillation (AF). However, while numerous KV1.5-selective compounds have been screened, characterized, and tested in various animal models of AF, evidence of antiarrhythmic efficacy in humans is still lacking. Moreover, current guidelines for pre-clinical assessment of candidate drugs heavily rely on steady-state concentration-response curves or IC50 values, which can overlook adverse cardiotoxic effects. We sought to investigate the effects of kinetics and state-dependent binding of IKur-targeting drugs on atrial electrophysiology in silico and reveal the ideal properties of IKur blockers that maximize anti-AF efficacy and minimize pro-arrhythmic risk. To this aim, we developed a new Markov model of IKur that describes KV1.5 gating based on experimental voltage-clamp data in atrial myocytes from patient right-atrial samples in normal sinus rhythm. We extended the IKur formulation to account for state-specificity and kinetics of KV1.5-drug interactions and incorporated it into our human atrial cell model. We simulated 1- and 3-Hz pacing protocols in drug-free conditions and with a [drug] equal to the IC50 value. The effects of binding and unbinding kinetics were determined by examining permutations of the forward (kon) and reverse (koff) binding rates to the closed, open, and inactivated states of the KV1.5 channel. We identified a subset of ideal drugs exhibiting anti-AF electrophysiological parameter changes at fast pacing rates (effective refractory period prolongation), while having little effect on normal sinus rhythm (limited action potential prolongation). Our results highlight that accurately accounting for channel interactions with drugs, including kinetics and state-dependent binding, is critical for developing safer and more effective pharmacological anti-AF options.
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