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

Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation

The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

Dual effects of the small-conductance Ca2+-activated K+ current on human atrial electrophysiology and Ca2+-driven arrhythmogenesis: an in silico study

By sensing changes in intracellular Ca2+, small-conductance Ca2+-activated K+ (SK) channels dynamically regulate the dynamics of the cardiac action potential (AP) on a beat-to-beat basis. Given their predominance in atria versus ventricles, SK channels are considered a promising atrial-selective pharmacological target against atrial fibrillation (AF), the most common cardiac arrhythmia. However, the precise contribution of SK current (ISK) to atrial arrhythmogenesis is poorly understood, and may potentially involve different mechanisms that depend on species, heart rates, and degree of AF-induced atrial remodeling. Both reduced and enhanced ISK have been linked to AF. Similarly, both SK channel up- and downregulation have been reported in chronic AF (cAF) versus normal sinus rhythm (nSR) patient samples. Here, we use our multiscale modeling framework to obtain mechanistic insights into the contribution of ISK in human atrial cardiomyocyte electrophysiology. We simulate several protocols to quantify how ISK modulation affects the regulation of AP duration (APD), Ca2+ transient, refractoriness, and occurrence of alternans and delayed afterdepolarizations (DADs). Our simulations show that ISK activation shortens the APD and atrial effective refractory period, limits Ca2+ cycling, and slightly increases the propensity for alternans in both nSR and cAF conditions. We also show that increasing ISK counteracts DAD development by enhancing the repolarization force that opposes the Ca2+-dependent depolarization. Taken together, our results suggest that increasing ISK in human atrial cardiomyocytes could promote reentry while protecting against triggered activity. Depending on the leading arrhythmogenic mechanism, ISK inhibition may thus be a beneficial or detrimental anti-AF strategy.NEW & NOTEWORTHY Using our established framework for human atrial myocyte simulations, we investigated the role of the small-conductance Ca2+-activated K+ current (ISK) in the regulation of cell function and the development of Ca2+-driven arrhythmias. We found that ISK inhibition, a promising atrial-selective pharmacological strategy against atrial fibrillation, counteracts the reentry-promoting abbreviation of atrial refractoriness, but renders human atrial myocytes more vulnerable to delayed afterdepolarizations, thus potentially increasing the propensity for ectopic (triggered) activity.

Populations of in silico myocytes and tissues reveal synergy of multiatrial-predominant K+ -current block in atrial fibrillation

BACKGROUND AND PURPOSE

Pharmacotherapy of atrial fibrillation (AF), the most common cardiac arrhythmia, remains unsatisfactory due to low efficacy and safety concerns. New therapeutic strategies target atrial-predominant ion-channels and involve multichannel block (poly)therapy. As AF is characterized by rapid and irregular atrial activations, compounds displaying potent antiarrhythmic effects at fast and minimal effects at slow rates are desirable. We present a novel systems pharmacology framework to quantitatively evaluate synergistic anti-AF effects of combined block of multiple atrial-predominant K⁺ currents (ultra-rapid delayed rectifier K⁺ current, I_Kur , small conductance Ca²⁺ -activated K⁺ current, I_KCa , K_2P 3.1 2-pore-domain K⁺ current, I_K2P ) in AF.

EXPERIMENTAL APPROACH

We constructed experimentally calibrated populations of virtual atrial myocyte models in normal sinus rhythm and AF-remodelled conditions using two distinct, well-established atrial models. Sensitivity analyses on our atrial populations was used to investigate the rate dependence of action potential duration (APD) changes due to blocking I_Kur , I_K2P or I_KCa and interactions caused by blocking of these currents in modulating APD. Block was simulated in both single myocytes and one-dimensional tissue strands to confirm insights from the sensitivity analyses and examine anti-arrhythmic effects of multi-atrial-predominant K⁺ current block in single cells and coupled tissue.

KEY RESULTS

In both virtual atrial myocytes and tissues, multiple atrial-predominant K⁺ -current block promoted favourable positive rate-dependent APD prolongation and displayed positive rate-dependent synergy, that is, increasing synergistic antiarrhythmic effects at fast pacing versus slow rates.

CONCLUSION AND IMPLICATIONS

Simultaneous block of multiple atrial-predominant K⁺ currents may be a valuable antiarrhythmic pharmacotherapeutic strategy for AF.

When Does the IC50 Accurately Assess the Blocking Potency of a Drug?

Preclinical assessment of drug-induced proarrhythmicity is typically evaluated by the potency of the drug to block the potassium human ether-à-go-go-related gene (hERG) channels, which is currently quantified by the IC₅₀. However, channel block depends on the experimental conditions. Our aim is to improve the evaluation of the blocking potency of drugs by designing experimental stimulation protocols to measure the IC₅₀ that will help to decide whether the IC₅₀ is representative enough. We used the state-of-the-art mathematical models of the cardiac electrophysiological activity to design three stimulation protocols that enhance the differences in the probabilities to occupy a certain conformational state of the channel and, therefore, the potential differences in the blocking effects of a compound. We simulated an extensive set of 144 in silico I_Kr blockers with different kinetics and affinities to conformational states of the channel and we also experimentally validated our key predictions. Our results show that the IC₅₀ protocol dependency relied on the tested compounds. Some of them showed no differences or small differences on the IC₅₀ value, which suggests that the IC₅₀ could be a good indicator of the blocking potency in these cases. However, others provided highly protocol dependent IC₅₀ values, which could differ by even 2 orders of magnitude. Moreover, the protocols yielding the maximum IC₅₀ and minimum IC₅₀ depended on the drug, which complicates the definition of a "standard" protocol to minimize the influence of the stimulation protocol on the IC₅₀ measurement in safety pharmacology. As a conclusion, we propose the adoption of our three-protocol IC₅₀ assay to estimate the potency to block hERG in vitro. If the IC₅₀ values obtained for a compound are similar, then the IC₅₀ could be used as an indicator of its blocking potency, otherwise kinetics and state-dependent binding properties should be accounted.

Understanding AF Mechanisms Through Computational Modelling and Simulations

AF is a progressive disease of the atria, involving complex mechanisms related to its initiation, maintenance and progression. Computational modelling provides a framework for integration of experimental and clinical findings, and has emerged as an essential part of mechanistic research in AF. The authors summarise recent advancements in development of multi-scale AF models and focus on the mechanistic links between alternations in atrial structure and electrophysiology with AF. Key AF mechanisms that have been explored using atrial modelling are pulmonary vein ectopy; atrial fibrosis and fibrosis distribution; atrial wall thickness heterogeneity; atrial adipose tissue infiltration; development of repolarisation alternans; cardiac ion channel mutations; and atrial stretch with mechano-electrical feedback. They review modelling approaches that capture variability at the cohort level and provide cohort-specific mechanistic insights. The authors conclude with a summary of future perspectives, as envisioned for the contributions of atrial modelling in the mechanistic understanding of AF.

Understanding the Beat-to-Beat Variations of P-Waves Morphologies in AF Patients During Sinus Rhythm: A Scoping Review of the Atrial Simulation Studies

The remarkable advances in high-performance computing and the resulting increase of the computational power have the potential to leverage computational cardiology toward improving our understanding of the pathophysiological mechanisms of arrhythmias, such as Atrial Fibrillation (AF). In AF, a complex interaction between various triggers and the atrial substrate is considered to be the leading cause of AF initiation and perpetuation. In electrocardiography (ECG), P-wave is supposed to reflect atrial depolarization. It has been found that even during sinus rhythm (SR), multiple P-wave morphologies are present in AF patients with a history of AF, suggesting a higher dispersion of the conduction route in this population. In this scoping review, we focused on the mechanisms which modify the electrical substrate of the atria in AF patients, while investigating the existence of computational models that simulate the propagation of the electrical signal through different routes. The adopted review methodology is based on a structured analytical framework which includes the extraction of the keywords based on an initial limited bibliographic search, the extensive literature search and finally the identification of relevant articles based on the reference list of the studies. The leading mechanisms identified were classified according to their scale, spanning from mechanisms in the cell, tissue or organ level, and the produced outputs. The computational modeling approaches for each of the factors that influence the initiation and the perpetuation of AF are presented here to provide a clear overview of the existing literature. Several levels of categorization were adopted while the studies which aim to translate their findings to ECG phenotyping are highlighted. The results denote the availability of multiple models, which are appropriate under specific conditions. However, the consideration of complex scenarios taking into account multiple spatiotemporal scales, personalization of electrophysiological and anatomical models and the reproducibility in terms of ECG phenotyping has only partially been tackled so far.

Closed and open state dependent block of potassium channels cause opposing effects on excitability - a computational approach

Block of voltage-gated potassium (Kv) channels has been demonstrated to affect neuronal activity described as increasing excitability. The effect has been associated with a closed-state dependent block. However, the block of Kv channels in e.g. local anesthetic and antiarrhythmics, is open state-dependent. Since the reduced excitability in this case mainly is due to sodium channel block, the role of the Kv channel block is concealed. The present investigation aims to analyse the specific role of state-dependent Kv channel block for excitability. Using a computational approach, with introduced blocked states in the Kv channel of the Frankenhaeuser-Huxley axon membrane model, we calculated the effects on threshold, firing and presynaptic Ca influx. The Ca influx was obtained from an N-type Cav channel model linked to the Frankenhaeuser-Huxley membrane. The results suggested that a selective block of open Kv channels decreased the rate of repetitive firing and the consequent Ca influx, thus challenging the traditional view. In contrast, presence of a closed-state block, increased the firing rate and the Ca influx. These findings propose that Kv channel block may either increase or decrease cellular excitability, thus highlighting the importance of further investigating the role of state-specific blocking mechanisms.

Computational modeling: What does it tell us about atrial fibrillation therapy?

Atrial fibrillation (AF) is a complex cardiac arrhythmia with diverse etiology that negatively affects morbidity and mortality of millions of patients. Technological and experimental advances have provided a wealth of information on the pathogenesis of AF, highlighting a multitude of mechanisms involved in arrhythmia initiation and maintenance, and disease progression. However, it remains challenging to identify the predominant mechanisms for specific subgroups of AF patients, which, together with an incomplete understanding of the pleiotropic effects of antiarrhythmic therapies, likely contributes to the suboptimal efficacy of current antiarrhythmic approaches. Computer modeling of cardiac electrophysiology has advanced in parallel to experimental research and provides an integrative framework to attempt to overcome some of these challenges. Multi-scale cardiac modeling and simulation integrate structural and functional data from experimental and clinical work with knowledge of atrial electrophysiological mechanisms and dynamics, thereby improving our understanding of AF mechanisms and therapy. In this review, we describe recent advances in our quantitative understanding of AF through mathematical models. We discuss computational modeling of AF mechanisms and therapy using detailed, mechanistic cell/tissue-level models, including approaches to incorporate variability in patient populations. We also highlight efforts using whole-atria models to improve catheter ablation therapies. Finally, we describe recent efforts and suggest future extensions to model clinical concepts of AF using patient-level models.

Computational Modeling of Electrophysiology and Pharmacotherapy of Atrial Fibrillation: Recent Advances and Future Challenges

The pathophysiology of atrial fibrillation (AF) is broad, with components related to the unique and diverse cellular electrophysiology of atrial myocytes, structural complexity, and heterogeneity of atrial tissue, and pronounced disease-associated remodeling of both cells and tissue. A major challenge for rational design of AF therapy, particularly pharmacotherapy, is integrating these multiscale characteristics to identify approaches that are both efficacious and independent of ventricular contraindications. Computational modeling has long been touted as a basis for achieving such integration in a rapid, economical, and scalable manner. However, computational pipelines for AF-specific drug screening are in their infancy, and while the field is progressing quite rapidly, major challenges remain before computational approaches can fill the role of workhorse in rational design of AF pharmacotherapies. In this review, we briefly detail the unique aspects of AF pathophysiology that determine requirements for compounds targeting AF rhythm control, with emphasis on delimiting mechanisms that promote AF triggers from those providing substrate or supporting reentry. We then describe modeling approaches that have been used to assess the outcomes of drugs acting on established AF targets, as well as on novel promising targets including the ultra-rapidly activating delayed rectifier potassium current, the acetylcholine-activated potassium current and the small conductance calcium-activated potassium channel. Finally, we describe how heterogeneity and variability are being incorporated into AF-specific models, and how these approaches are yielding novel insights into the basic physiology of disease, as well as aiding identification of the important molecular players in the complex AF etiology.

A Heart for Diversity: Simulating Variability in Cardiac Arrhythmia Research

In cardiac electrophysiology, there exist many sources of inter- and intra-personal variability. These include variability in conditions and environment, and genotypic and molecular diversity, including differences in expression and behavior of ion channels and transporters, which lead to phenotypic diversity (e.g., variable integrated responses at the cell, tissue, and organ levels). These variabilities play an important role in progression of heart disease and arrhythmia syndromes and outcomes of therapeutic interventions. Yet, the traditional in silico framework for investigating cardiac arrhythmias is built upon a parameter/property-averaging approach that typically overlooks the physiological diversity. Inspired by work done in genetics and neuroscience, new modeling frameworks of cardiac electrophysiology have been recently developed that take advantage of modern computational capabilities and approaches, and account for the variance in the biological data they are intended to illuminate. In this review, we outline the recent advances in statistical and computational techniques that take into account physiological variability, and move beyond the traditional cardiac model-building scheme that involves averaging over samples from many individuals in the construction of a highly tuned composite model. We discuss how these advanced methods have harnessed the power of big (simulated) data to study the mechanisms of cardiac arrhythmias, with a special emphasis on atrial fibrillation, and improve the assessment of proarrhythmic risk and drug response. The challenges of using in silico approaches with variability are also addressed and future directions are proposed.

Synergistic Anti-arrhythmic Effects in Human Atria with Combined Use of Sodium Blockers and Acacetin

Atrial fibrillation (AF) is the most common cardiac arrhythmia. Developing effective and safe anti-AF drugs remains an unmet challenge. Simultaneous block of both atrial-specific ultra-rapid delayed rectifier potassium (K⁺) current (I_Kur) and the Na⁺ current (I_Na) has been hypothesized to be anti-AF, without inducing significant QT prolongation and ventricular side effects. However, the antiarrhythmic advantage of simultaneously blocking these two channels vs. individual block in the setting of AF-induced electrical remodeling remains to be documented. Furthermore, many I_Kur blockers such as acacetin and AVE0118, partially inhibit other K⁺ currents in the atria. Whether this multi-K⁺-block produces greater anti-AF effects compared with selective I_Kur-block has not been fully understood. The aim of this study was to use computer models to (i) assess the impact of multi-K⁺-block as exhibited by many I_Kur blokers, and (ii) evaluate the antiarrhythmic effect of blocking I_Kur and I_Na, either alone or in combination, on atrial and ventricular electrical excitation and recovery in the setting of AF-induced electrical-remodeling. Contemporary mathematical models of human atrial and ventricular cells were modified to incorporate dose-dependent actions of acacetin (a multichannel blocker primarily inhibiting I_Kur while less potently blocking I_to, I_Kr, and I_Ks). Rate- and atrial-selective inhibition of I_Na was also incorporated into the models. These single myocyte models were then incorporated into multicellular two-dimensional (2D) and three-dimensional (3D) anatomical models of the human atria. As expected, application of I_Kur blocker produced pronounced action potential duration (APD) prolongation in atrial myocytes. Furthermore, combined multiple K⁺-channel block that mimicked the effects of acacetin exhibited synergistic APD prolongations. Synergistically anti-AF effects following inhibition of I_Na and combined I_Kur/K⁺-channels were also observed. The attainable maximal AF-selectivity of I_Na inhibition was greatly augmented by blocking I_Kur or multiple K⁺-currents in the atrial myocytes. This enhanced anti-arrhythmic effects of combined block of Na⁺- and K⁺-channels were also seen in 2D and 3D simulations; specially, there was an enhanced efficacy in terminating re-entrant excitation waves, exerting improved antiarrhythmic effects in the human atria as compared to a single-channel block. However, in the human ventricular myocytes and tissue, cellular repolarization and computed QT intervals were modestly affected in the presence of actions of acacetin and I_Na blockers (either alone or in combination). In conclusion, this study demonstrates synergistic antiarrhythmic benefits of combined block of I_Kur and I_Na, as well as those of I_Na and combined multi K⁺-current block of acacetin, without significant alterations of ventricular repolarization and QT intervals. This approach may be a valuable strategy for the treatment of AF.

In Vitro and In Silico Risk Assessment in Acquired Long QT Syndrome: The Devil Is in the Details

Acquired long QT syndrome, mostly as a result of drug block of the Kv11. 1 potassium channel in the heart, is characterized by delayed cardiac myocyte repolarization, prolongation of the T interval on the ECG, syncope and sudden cardiac death due to the polymorphic ventricular arrhythmia Torsade de Pointes (TdP). In recent years, efforts are underway through the Comprehensive in vitro proarrhythmic assay (CiPA) initiative, to develop better tests for this drug induced arrhythmia based in part on in silico simulations of pharmacological disruption of repolarization. However, drug binding to Kv11.1 is more complex than a simple binary molecular reaction, meaning simple steady state measures of potency are poor surrogates for risk. As a result, there is a plethora of mechanistic detail describing the drug/Kv11.1 interaction—such as drug binding kinetics, state preference, temperature dependence and trapping—that needs to be considered when developing in silico models for risk prediction. In addition to this, other factors, such as multichannel pharmacological profile and the nature of the ventricular cell models used in simulations also need to be considered in the search for the optimum in silico approach. Here we consider how much of mechanistic detail needs to be included for in silico models to accurately predict risk and further, how much of this detail can be retrieved from protocols that are practical to implement in high throughout screens as part of next generation of preclinical in silico drug screening approaches?

In Silico Assessment of Efficacy and Safety of IKur Inhibitors in Chronic Atrial Fibrillation: Role of Kinetics and State-Dependence of Drug Binding

Current pharmacological therapy against atrial fibrillation (AF), the most common cardiac arrhythmia, is limited by moderate efficacy and adverse side effects including ventricular proarrhythmia and organ toxicity. One way to circumvent the former is to target ion channels that are predominantly expressed in atria vs. ventricles, such as K_V1.5, carrying the ultra-rapid delayed-rectifier K⁺ current (I_Kur). Recently, we used an in silico strategy to define optimal K_V1.5-targeting drug characteristics, including kinetics and state-dependent binding, that maximize AF-selectivity in human atrial cardiomyocytes in normal sinus rhythm (nSR). However, because of evidence for I_Kur being strongly diminished in long-standing persistent (chronic) AF (cAF), the therapeutic potential of drugs targeting I_Kur may be limited in cAF patients. Here, we sought to simulate the efficacy (and safety) of I_Kur inhibitors in cAF conditions. To this end, we utilized sensitivity analysis of our human atrial cardiomyocyte model to assess the importance of I_Kur for atrial cardiomyocyte electrophysiological properties, simulated hundreds of theoretical drugs to reveal those exhibiting anti-AF selectivity, and compared the results obtained in cAF with those in nSR. We found that despite being downregulated, I_Kur contributes more prominently to action potential (AP) and effective refractory period (ERP) duration in cAF vs. nSR, with ideal drugs improving atrial electrophysiology (e.g., ERP prolongation) more in cAF than in nSR. Notably, the trajectory of the AP during cAF is such that more I_Kur is available during the more depolarized plateau potential. Furthermore, I_Kur block in cAF has less cardiotoxic effects (e.g., AP duration not exceeding nSR values) and can increase Ca²⁺ transient amplitude thereby enhancing atrial contractility. We propose that in silico strategies such as that presented here should be combined with in vitro and in vivo assays to validate model predictions and facilitate the ongoing search for novel agents against AF.