Small current, big potential: bridging mechanistic insight of the SK channel with translational promise

Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia, with a lifetime risk of approximately 1 in 4 for adults aged 40 years and above. Despite advances in clinical management, AF remains a major public health concern. Its burden extends beyond symptoms; it quadruples the risk of heart failure and increases the likelihood of stroke fivefold – strokes that are often more severe and fatal than those unrelated to AF. In the United States alone, AF-associated healthcare costs exceed $26 billion annually, and the cost is projected to grow as the population ages (Ko et al., 2025). Regarding current treatments, anti-coagulation is largely palliative; anti-arrhythmic drugs (AADs) often have limited efficacy and carry proarrhythmic risks; while catheter ablation is invasive and frequently followed by recurrences. Additionally, none of these approaches reverses the underlying electrical and structural remodelling that maintain AF. Therefore, there is a growing need for therapies that target the disease at the mechanistic level while minimizing side effects. Small-conductance Ca2+-activated K+ (SK or KCa2) channels have emerged as promising targets for atrial-specific therapies. Their exclusive activation by intracellular Ca2+ links the beat-to-beat Ca2+ dynamics to membrane excitability in cardiomyocytes; and their preferential expression in atria over ventricles makes them attractive for minimizing off-target effects (Xu et al., 2003). The SK2 (KCa2.2) isoform, encoded by the KCNN2 gene, is the predominant subtype in cardiomyocytes and has been studied as an anti-AF target. The clinical potential of SK channels is supported by emerging evidence from preclinical studies in large animals and clinical trials with SK channel blockers, such as AP30663 (NCT04571385) (Saljic et al., 2024). However, compared to other cardiac ion channels, SK channels remain understudied in terms of gating, trafficking and arrhythmogenic potential. These knowledge gaps greatly limit safe therapeutic exploitation. Recent computational studies have provided much-needed mechanistic insights into the critical roles of SK channels in AF. Notably, a comprehensive study by Heijman et al. published in the current issue of the Journal of Physiology incorporated Ca2+-dependent SK channel trafficking into a computational atrial cardiomyocyte model, revealing that rapid atrial pacing, as seen in AF, enhances SK trafficking and current density. The rate-dependent upregulation of SK channel activity can lead to action potential shortening, which promotes the formation of re-entry in the vulnerable substrates. Importantly, their 2-D tissue model shows that SK channel inhibition can significantly reduce the duration and occurrence of re-entry. However, blockade can also cause triggered activities such as delayed afterdepolarizations. These findings highlight the complex and diametrical effects and reinforce the importance of understanding mechanistic underpinnings of the anti-arrhythmic and proarrhythmic outcomes of SK channel modulation. The study also suggests that rate-dependent SK channel regulation is not only pathophysiologically relevant but also therapeutically targetable, albeit its application in arrhythmia modulation should be done with caution (Stefan Meier et al., 2025). New mechanistic insights into SK channel regulation have come from molecular-level investigations. A recent study revealed a previously uncharacterized regulatory axis of SK channel gating involving both calmodulin and phosphatidylinositol 4,5-bisphosphate (PIP2) in cardiomyocytes. The PIP2-dependent regulation may be particularly relevant under pathological conditions like AF, in which phosphoinositide metabolism and membrane lipid composition are often altered due to inflammation or oxidative stress. Such changes could dynamically shift SK channel function and drug sensitivity. Additionally, the recently revealed cryogenic electron microscopic SK2 channel structure has uncovered a unique ‘canopy’ architecture in the outer vestibule, not found in intermediate- or large-conductance Ca2+-activated K+ channels. The high-resolution structure of the SK2 channel provides unprecedented opportunities for structure-based drug design of isoform-specific modulators (Nam et al., 2025). The structural information, combined with computational modelling and functional studies, affords a roadmap for developing next-generation SK channel modulators with improved selectivity and safety profiles. To advance the use of SK channels as drug targets in treating AF, additional aspects of their function and regulation must be investigated. At the transcriptional level, SK channel expression can be modulated by a host of factors such as transcription factors, oxidative signalling and inflammatory cytokines – all of which are commonly altered in AF. At the protein level, SK channels are known to undergo post-translational modifications such as phosphorylation and ubiquitination, which may differentially alter their trafficking and gating kinetics between normal and AF conditions. Interactions with L-type Ca2+ channels and the ubiquitous Ca2+-sensing protein, calmodulin, as well as Ca2+-handling proteins like ryanodine receptors, could further regulate SK channel function and arrhythmogenic potentials. Moreover, different SK channel isoforms (SK1, SK2 and SK3) can form heterotetramers, and the subunit composition may influence channel behaviours, pharmacological responses and tissue-specific effects. Finally, AF is often accompanied by comorbid conditions such as diabetes, hypertension and obesity, in which SK channels could potentially be regulated by systemic metabolic or inflammatory pathways. In summary, SK channels represent a promising but complex therapeutic target. Unlocking their potential demands both mechanistic precision and translational foresight. In this pursuit, artificial intelligence (AI) offers a transformative opportunity. AI-driven modelling can accelerate the identification of patient-specific electrophysiological responses, prediction of SK channel interaction dynamics and optimization of SK-targeting drug discovery. Deep learning approaches are beginning to assist in the prediction of off-target effects and isoform-specific modulation. Therapeutics will be tailored not only to specific channel isoforms, but also to dynamic disease remodelling and individual patient profiles. With continued interdisciplinary efforts, SK channels may transition from an intriguing target to a foundation for the next generation of personalized AF therapies. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. The authors have no conflicts of interest to declare. Y.Z.: Conception or design of the work; Drafting the work or revising it critically for important intellectual content; Final approval of the version to be published; Agreement to be accountable for all aspects of the work M.Z.: Conception or design of the work; Drafting the work or revising it critically for important intellectual content; Final approval of the version to be published; Agreement to be accountable for all aspects of the work N.C.: Conception or design of the work; Drafting the work or revising it critically for important intellectual content; Final approval of the version to be published; Agreement to be accountable for all aspects of the work. This work was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health (NIH) R01 HL170520, R01 HL152055 and R01 HL085844 (N.C.), Heart Rhythm Society Postdoctoral Research Fellowship (Y.Z.), and National Institute of Neurological Disorders and Stroke (NIH) R15 NS130420 and R33 NS101182 (M.Z).