A Molecularly Detailed NaV1.5 Model Reveals a New Class I Antiarrhythmic Target

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Antiarrhythmic therapies remain suboptimal due to our inability to predict how drug interactions with ion channels will affect the ability of the tissue to initiate and sustain an arrhythmia.

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We built a computational framework that allows for in silico design of precision-targeted therapeutic agents that simultaneously assesses antiarrhythmic markers of success and failure at multiple spatial and time scales. Using this framework, a novel in silico mexiletine “booster” was designed that may dramatically improve the efficacy of mexiletine in suppression of arrhythmia triggers.

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These results provide a roadmap for the design of novel molecular-based therapy to treat myriad arrhythmia syndromes, including ventricular tachycardia, heart failure arrhythmias, and inherited arrhythmia syndromes.

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In summary, computational modeling approaches to drug discovery represent a novel tool to design and test precision-targeted therapeutic agents. By exploiting nontraditional ion channel drug targets, an entirely new dimension can be added to the wide parameter space of traditional antiarrhythmic drugs to develop more precision-targeted and potent Class I therapeutic agents.

Antiarrhythmic treatment strategies remain suboptimal due to our inability to predict how drug interactions with ion channels will affect the ability of the tissues to initiate and sustain an arrhythmia. We built a multiscale molecular model of the Na⁺ channel domain III (domain III voltage-sensing domain) to highlight the molecular underpinnings responsible for mexiletine drug efficacy. This model predicts that a hyperpolarizing shift in the domain III voltage-sensing domain is critical for drug efficacy and may be leveraged to design more potent Class I molecules. The model was therefore used to design, in silico, a theoretical mexiletine booster that can dramatically rescue a mutant resistant to the potent antiarrhythmic effects of mexiletine. Our framework provides a strategy for in silico design of precision-targeted therapeutic agents that simultaneously assesses antiarrhythmic markers of success and failure at multiple spatial and time scales. This approach provides a roadmap for the design of novel molecular-based therapy to treat myriad arrhythmia syndromes, including ventricular tachycardia, heart failure arrhythmias, and inherited arrhythmia syndromes.