In silico assessment of drug safety in human heart applied to late sodium current blockers

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.

Computer Modeling of the Heart for ECG Interpretation—A Review

Computer modeling of the electrophysiology of the heart has undergone significant progress. A healthy heart can be modeled starting from the ion channels via the spread of a depolarization wave on a realistic geometry of the human heart up to the potentials on the body surface and the ECG. Research is advancing regarding modeling diseases of the heart. This article reviews progress in calculating and analyzing the corresponding electrocardiogram (ECG) from simulated depolarization and repolarization waves. First, we describe modeling of the P-wave, the QRS complex and the T-wave of a healthy heart. Then, both the modeling and the corresponding ECGs of several important diseases and arrhythmias are delineated: ischemia and infarction, ectopic beats and extrasystoles, ventricular tachycardia, bundle branch blocks, atrial tachycardia, flutter and fibrillation, genetic diseases and channelopathies, imbalance of electrolytes and drug-induced changes. Finally, we outline the potential impact of computer modeling on ECG interpretation. Computer modeling can contribute to a better comprehension of the relation between features in the ECG and the underlying cardiac condition and disease. It can pave the way for a quantitative analysis of the ECG and can support the cardiologist in identifying events or non-invasively localizing diseased areas. Finally, it can deliver very large databases of reliably labeled ECGs as training data for machine learning.

A predictive in vitro risk assessment platform for pro-arrhythmic toxicity using human 3D cardiac microtissues

Cardiotoxicity of pharmaceutical drugs, industrial chemicals, and environmental toxicants can be severe, even life threatening, which necessitates a thorough evaluation of the human response to chemical compounds. Predicting risks for arrhythmia and sudden cardiac death accurately is critical for defining safety profiles. Currently available approaches have limitations including a focus on single select ion channels, the use of non-human species in vitro and in vivo, and limited direct physiological translation. We have advanced the robustness and reproducibility of in vitro platforms for assessing pro-arrhythmic cardiotoxicity using human induced pluripotent stem cell-derived cardiomyocytes and human cardiac fibroblasts in 3-dimensional microtissues. Using automated algorithms and statistical analyses of eight comprehensive evaluation metrics of cardiac action potentials, we demonstrate that tissue-engineered human cardiac microtissues respond appropriately to physiological stimuli and effectively differentiate between high-risk and low-risk compounds exhibiting blockade of the hERG channel (E4031 and ranolazine, respectively). Further, we show that the environmental endocrine disrupting chemical bisphenol-A (BPA) causes acute and sensitive disruption of human action potentials in the nanomolar range. Thus, this novel human 3D in vitro pro-arrhythmic risk assessment platform addresses critical needs in cardiotoxicity testing for both environmental and pharmaceutical compounds and can be leveraged to establish safe human exposure levels.

Computational prediction of drug response in short QT syndrome type 1 based on measurements of compound effect in stem cell-derived cardiomyocytes

Short QT (SQT) syndrome is a genetic cardiac disorder characterized by an abbreviated QT interval of the patient's electrocardiogram. The syndrome is associated with increased risk of arrhythmia and sudden cardiac death and can arise from a number of ion channel mutations. Cardiomyocytes derived from induced pluripotent stem cells generated from SQT patients (SQT hiPSC-CMs) provide promising platforms for testing pharmacological treatments directly in human cardiac cells exhibiting mutations specific for the syndrome. However, a difficulty is posed by the relative immaturity of hiPSC-CMs, with the possibility that drug effects observed in SQT hiPSC-CMs could be very different from the corresponding drug effect in vivo. In this paper, we apply a multistep computational procedure for translating measured drug effects from these cells to human QT response. This process first detects drug effects on individual ion channels based on measurements of SQT hiPSC-CMs and then uses these results to estimate the drug effects on ventricular action potentials and QT intervals of adult SQT patients. We find that the procedure is able to identify IC50 values in line with measured values for the four drugs quinidine, ivabradine, ajmaline and mexiletine. In addition, the predicted effect of quinidine on the adult QT interval is in good agreement with measured effects of quinidine for adult patients. Consequently, the computational procedure appears to be a useful tool for helping predicting adult drug responses from pure in vitro measurements of patient derived cell lines.

Late sodium current and calcium homeostasis in arrhythmogenesis

The cardiac late sodium current (I_Na,late) is the small sustained component of the sodium current active during the plateau phase of the action potential. Several studies demonstrated that augmentation of the current can lead to cardiac arrhythmias; therefore, I_Na,late is considered as a promising antiarrhythmic target. Fundamentally, enlarged I_Na,late increases Na⁺ influx into the cell, which, in turn, is converted to elevated intracellular Ca²⁺ concentration through the Na⁺/Ca²⁺ exchanger. The excessive Ca²⁺ load is known to be proarrhythmic. This review describes the behavior of the voltage-gated Na⁺ channels generating I_Na,late in health and disease and aims to discuss the physiology and pathophysiology of Na⁺ and Ca²⁺ homeostasis in context with the enhanced I_Na,late demonstrating also the currently accessible antiarrhythmic choices.

In Silico Classifiers for the Assessment of Drug Proarrhythmicity

Drug-induced torsade de pointes (TdP) is a life-threatening ventricular arrhythmia responsible for the withdrawal of many drugs from the market. Although currently used TdP risk-assessment methods are effective, they are expensive and prone to produce false positives. In recent years, in silico cardiac simulations have proven to be a valuable tool for the prediction of drug effects. The objective of this work is to evaluate different biomarkers of drug-induced proarrhythmic risk and to develop an in silico risk classifier. Cellular simulations were performed using a modified version of the O'Hara et al. ventricular action potential model and existing pharmacological data (IC₅₀ and effective free therapeutic plasma concentration, EFTPC) for 109 drugs of known torsadogenic risk (51 positive). For each compound, four biomarkers were tested: T_x (drug concentration leading to a 10% prolongation of the action potential over the EFTPC), T_qNet (net charge carried by ionic currents when exposed to 10 times the EFTPC with respect to the net charge in control), T_triang (triangulation for a drug concentration of 10 times the EFTPC over triangulation in control), and T_EAD (drug concentration originating early afterdepolarizations over EFTPC). Receiver operating characteristic (ROC) curves were built for each biomarker to evaluate their individual predictive quality. At the optimal cutoff point, accuracies for T_x, T_qNet, T_triang, and T_EAD were 89.9, 91.7, 90.8, and 78.9% respectively. The resulting accuracy of the hERG IC₅₀ test (current biomarker) was 78.9%. When combining T_x, T_qNet and T_triang into a classifier based on decision trees, the prediction improves, achieving an accuracy of 94.5%. The sensitivity analysis revealed that most of the effects on the action potential are mainly due to changes in I_Kr, I_CaL, I_NaL and I_Ks. In fact, considering that drugs affect only these four currents, TdP risk classification can be as accurate as when considering effects on the seven main currents proposed by the CiPA initiative. Finally, we built a ready-to-use tool (based on more than 450 000 simulations), which can be used to quickly assess the proarrhythmic risk of a compound. In conclusion, our in silico tool can be useful for the preclinical assessment of TdP-risk and to reduce costs related with new drug development. The TdP risk-assessment tool and the software used in this work are available at https://riunet.upv.es/handle/10251/136919.

Global Sensitivity Analysis of Ventricular Myocyte Model-Derived Metrics for Proarrhythmic Risk Assessment

Multiscale computational models of the heart are being extensively investigated for improved assessment of drug-induced torsades de pointes (TdP) risk, a fatal side effect of many drugs. Model-derived metrics such as action potential duration and net charge carried by ionic currents (qNet) have been proposed as potential candidates for TdP risk stratification after being tested on small datasets. Unlike purely statistical approaches, model-derived metrics are thought to provide mechanism-based classification. In particular, qNet has been recently proposed as a surrogate metric for early afterdepolarizations (EADs), which are known to be cellular triggers of TdP. Analysis of critical model components and of the ion channels that have major impact on model-derived metrics can lead to improvements in the confidence of the prediction. In this paper, we analyze large populations of virtual drugs to systematically examine the influence of different ion channels on model-derived metrics that have been proposed for proarrhythmic risk assessment. We demonstrate via global sensitivity analysis (GSA) that model-derived metrics are most sensitive to different sets of input parameters. Similarly, important differences in sensitivity to specific channel blocks are highlighted when classifying drugs into different risk categories by either qNet or a metric directly based on simulated EADs. In particular, the higher sensitivity of qNet to the block of the late sodium channel might explain why its classification accuracy is better than that of the EAD-based metric, as shown for a small set of known drugs. Our results highlight the need for a better mechanistic interpretation of promising metrics like qNet based on a formal analysis of models. GSA should, therefore, constitute an essential component of the in silico workflow for proarrhythmic risk assessment, as an improved understanding of the structure of model-derived metrics could increase confidence in model-predicted risk.

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.

In Silico QT and APD Prolongation Assay for Early Screening of Drug-Induced Proarrhythmic Risk

Drug-induced proarrhythmicity is a major concern for regulators and pharmaceutical companies. For novel drug candidates, the standard assessment involves the evaluation of the potassium hERG channels block and the in vivo prolongation of the QT interval. However, this method is known to be too restrictive and to stop the development of potentially valuable therapeutic drugs. The aim of this work is to create an in silico tool for early detection of drug-induced proarrhythmic risk. The system is based on simulations of how different compounds affect the action potential duration (APD) of isolated endocardial, midmyocardial, and epicardial cells as well as the QT prolongation in a virtual tissue. Multiple channel-drug interactions and state-of-the-art human ventricular action potential models ( O'Hara , T. , PLos Comput. Biol. 2011 , 7 , e1002061 ) were used in our simulations. Specifically, 206.766 cellular and 7072 tissue simulations were performed by blocking the slow and the fast components of the delayed rectifier current ( I_Ks and I_Kr, respectively) and the L-type calcium current ( I_CaL) at different levels. The performance of our system was validated by classifying the proarrhythmic risk of 84 compounds, 40 of which present torsadogenic properties. On the basis of these results, we propose the use of a new index (Tx) for discriminating torsadogenic compounds, defined as the ratio of the drug concentrations producing 10% prolongation of the cellular endocardial, midmyocardial, and epicardial APDs and the QT interval, over the maximum effective free therapeutic plasma concentration (EFTPC). Our results show that the Tx index outperforms standard methods for early identification of torsadogenic compounds. Indeed, for the analyzed compounds, the Tx tests accuracy was in the range of 87-88% compared with a 73% accuracy of the hERG IC₅₀ based test.

Pro-arrhythmic effects of low plasma [K+] in human ventricle: An illustrated review

Potassium levels in the plasma, [K⁺]_o, are regulated precisely under physiological conditions. However, increases (from approx. 4.5 to 8.0mM) can occur as a consequence of, e.g., endurance exercise, ischemic insult or kidney failure. This hyperkalemic modulation of ventricular electrophysiology has been studied extensively. Hypokalemia is also common. It can occur in response to diuretic therapy, following renal dialysis, or during recovery from endurance exercise. In the human ventricle, clinical hypokalemia (e.g., [K⁺]_o levels of approx. 3.0mM) can cause marked changes in both the resting potential and the action potential waveform, and these may promote arrhythmias. Here, we provide essential background information concerning the main K⁺-sensitive ion channel mechanisms that act in concert to produce prominent short-term ventricular electrophysiological changes, and illustrate these by implementing recent mathematical models of the human ventricular action potential. Even small changes (~1mM) in [K⁺]_o result in significant alterations in two different K⁺ currents, I_K1 and HERG. These changes can markedly alter in resting membrane potential and/or action potential waveform in human ventricle. Specifically, a reduction in net outward transmembrane K⁺ currents (repolarization reserve) and an increased substrate input resistance contribute to electrophysiological instability during the plateau of the action potential and may promote pro-arrhythmic early after-depolarizations (EADs). Translational settings where these insights apply include: optimal diuretic therapy, and the interpretation of data from Phase II and III trials for anti-arrhythmic drug candidates.

Novel Two-Step Classifier for Torsades de Pointes Risk Stratification from Direct Features

While pre-clinical Torsades de Pointes (TdP) risk classifiers had initially been based on drug-induced block of hERG potassium channels, it is now well established that improved risk prediction can be achieved by considering block of non-hERG ion channels. The current multi-channel TdP classifiers can be categorized into two classes. First, the classifiers that take as input the values of drug-induced block of ion channels (direct features). Second, the classifiers that are built on features extracted from output of the drug-induced multi-channel blockage simulations in the in-silico models (derived features). The classifiers built on derived features have thus far not consistently provided increased prediction accuracies, and hence casts doubt on the value of such approaches given the cost of including biophysical detail. Here, we propose a new two-step method for TdP risk classification, referred to as Multi-Channel Blockage at Early After Depolarization (MCB@EAD). In the first step, we classified the compound that produced insufficient hERG block as non-torsadogenic. In the second step, the role of non-hERG channels to modulate TdP risk are considered by constructing classifiers based on direct or derived features at critical hERG block concentrations that generates EADs in the computational cardiac cell models. MCB@EAD provides comparable or superior TdP risk classification of the drugs from the direct features in tests against published methods. TdP risk for the drugs highly correlated to the propensity to generate EADs in the model. However, the derived features of the biophysical models did not improve the predictive capability for TdP risk assessment.

Improving the In Silico Assessment of Proarrhythmia Risk by Combining hERG (Human Ether-à-go-go-Related Gene) Channel-Drug Binding Kinetics and Multichannel Pharmacology

BACKGROUND

The current proarrhythmia safety testing paradigm, although highly efficient in preventing new torsadogenic drugs from entering the market, has important limitations that can restrict the development and use of valuable new therapeutics. The CiPA (Comprehensive in vitro Proarrhythmia Assay) proposes to overcome these limitations by evaluating drug effects on multiple cardiac ion channels in vitro and using these data in a predictive in silico model of the adult human ventricular myocyte. A set of drugs with known clinical torsade de pointes risk was selected to develop and calibrate the in silico model.

METHODS AND RESULTS

Manual patch-clamp data assessing drug effects on expressed cardiac ion channels were integrated into the O'Hara-Rudy myocyte model modified to include dynamic drug-hERG channel (human Ether-à-go-go-Related Gene) interactions. Together with multichannel pharmacology data, this model predicts that compounds with high torsadogenic risk are more likely to be trapped within the hERG channel and show stronger reverse use dependency of action potential prolongation. Furthermore, drug-induced changes in the amount of electronic charge carried by the late sodium and L-type calcium currents was evaluated as a potential metric for assigning torsadogenic risk.

CONCLUSIONS

Modeling dynamic drug-hERG channel interactions and multi-ion channel pharmacology improves the prediction of torsadogenic risk. With further development, these methods have the potential to improve the regulatory assessment of drug safety models under the CiPA paradigm.

Changes in Intracellular Na+ following Enhancement of Late Na+ Current in Virtual Human Ventricular Myocytes

The slowly inactivating or late Na+ current, INa-L, can contribute to the initiation of both atrial and ventricular rhythm disturbances in the human heart. However, the cellular and molecular mechanisms that underlie these pro-arrhythmic influences are not fully understood. At present, the major working hypothesis is that the Na+ influx corresponding to INa-L significantly increases intracellular Na+, [Na+]i; and the resulting reduction in the electrochemical driving force for Na+ reduces and (may reverse) Na+/Ca2+ exchange. These changes increase intracellular Ca2+, [Ca2+]i; which may further enhance INa-L due to calmodulin-dependent phosphorylation of the Na+ channels. This paper is based on mathematical simulations using the O'Hara et al (2011) model of baseline or healthy human ventricular action potential waveforms(s) and its [Ca2+]i homeostasis mechanisms. Somewhat surprisingly, our results reveal only very small changes (≤ 1.5 mM) in [Na+]i even when INa-L is increased 5-fold and steady-state stimulation rate is approximately 2 times the normal human heart rate (i.e. 2 Hz). Previous work done using well-established models of the rabbit and human ventricular action potential in heart failure settings also reported little or no change in [Na+]i when INa-L was increased. Based on our simulations, the major short-term effect of markedly augmenting INa-L is a significant prolongation of the action potential and an associated increase in the likelihood of reactivation of the L-type Ca2+ current, ICa-L. Furthermore, this action potential prolongation does not contribute to [Na+]i increase.

Current-Voltage Relationship for Late Na(+) Current in Adult Rat Ventricular Myocytes

It is now well established that the slowly inactivating component of the Na(+) current (INa-L) in the mammalian heart is a significant regulator of the action potential waveform. This insight has led to detailed studies of the role of INa-L in a number of important and challenging pathophysiological settings. These include genetically based ventricular arrhythmias (LQT 1, 2, and 3), ventricular arrhythmias arising from progressive cardiomyopathies (including diabetic), and proarrhythmic abnormalities that develop during local or global ventricular ischemia. Inhibition of INa-L may also be a useful strategy for management of atrial flutter and fibrillation. Many important biophysical parameters that characterize INa-L have been identified; and INa-L as an antiarrhythmia drug target has been studied extensively. However, relatively little information is available regarding (1) the ion transfer or current-voltage relationship for INa-L or (2) the time course of its reactivation at membrane potentials similar to the resting or diastolic membrane potential in mammalian ventricle. This chapter is based on our preliminary findings concerning these two very important physiological/biophysical descriptors for INa-L. Our results were obtained using whole-cell voltage clamp methods applied to enzymatically isolated rat ventricular myocytes. A chemical agent, BDF 9148, which was once considered to be a drug candidate in the Na(+)-dependent inotropic agent category has been used to markedly enhance INa-L current. BDF acts in a potent, selective, and reversible fashion. These BDF 9148 effects are compared and contrasted with the prototypical activator of INa-L, a sea anemone toxin, ATX II.

How computer simulations of the human heart can improve anti-arrhythmia therapy

Over the last decade, the state-of-the-art in cardiac computational modelling has progressed rapidly. The electrophysiological function of the heart can now be simulated with a high degree of detail and accuracy, opening the doors for simulation-guided approaches to anti-arrhythmic drug development and patient-specific therapeutic interventions. In this review, we outline the basic methodology for cardiac modelling, which has been developed and validated over decades of research. In addition, we present several recent examples of how computational models of the human heart have been used to address current clinical problems in cardiac electrophysiology. We will explore the use of simulations to improve anti-arrhythmic pacing and defibrillation interventions; to predict optimal sites for clinical ablation procedures; and to aid in the understanding and selection of arrhythmia risk markers. Together, these studies illustrate how the tremendous advances in cardiac modelling are poised to revolutionize medical treatment and prevention of arrhythmia.

Deranged sodium to sudden death

In February 2014, a group of scientists convened as part of the University of California Davis Cardiovascular Symposium to bring together experimental and mathematical modelling perspectives and discuss points of consensus and controversy on the topic of sodium in the heart. This paper summarizes the topics of presentation and discussion from the symposium, with a focus on the role of aberrant sodium channels and abnormal sodium homeostasis in cardiac arrhythmias and pharmacotherapy from the subcellular scale to the whole heart. Two following papers focus on Na(+) channel structure, function and regulation, and Na(+)/Ca(2+) exchange and Na(+)/K(+) ATPase. The UC Davis Cardiovascular Symposium is a biannual event that aims to bring together leading experts in subfields of cardiovascular biomedicine to focus on topics of importance to the field. The focus on Na(+) in the 2014 symposium stemmed from the multitude of recent studies that point to the importance of maintaining Na(+) homeostasis in the heart, as disruption of homeostatic processes are increasingly identified in cardiac disease states. Understanding how disruption in cardiac Na(+)-based processes leads to derangement in multiple cardiac components at the level of the cell and to then connect these perturbations to emergent behaviour in the heart to cause disease is a critical area of research. The ubiquity of disruption of Na(+) channels and Na(+) homeostasis in cardiac disorders of excitability and mechanics emphasizes the importance of a fundamental understanding of the associated mechanisms and disease processes to ultimately reveal new targets for human therapy.

Computational Models for Predictive Cardiac Ion Channel Pharmacology

A wealth of experimental data exists describing the elementary building blocks of complex physiological systems. However, it is increasingly apparent in the biomedical sciences that mechanisms of biological function cannot be observed or readily predicted via study of constituent elements alone. This is especially clear in the longstanding failures in prediction of effects of drug treatment for heart rhythm disturbances. These failures stem in part from classical assumptions that have been made in cardiac antiarrhythmic drug development - that a drug operates by one mechanism via one target receptor that arises from one gene.

Ranolazine inhibition of hERG potassium channels: drug-pore interactions and reduced potency against inactivation mutants

The antianginal drug ranolazine, which combines inhibitory actions on rapid and sustained sodium currents with inhibition of the hERG/I_Kr potassium channel, shows promise as an antiarrhythmic agent. This study investigated the structural basis of hERG block by ranolazine, with lidocaine used as a low potency, structurally similar comparator. Recordings of hERG current (I_hERG) were made from cell lines expressing wild-type (WT) or mutant hERG channels. Docking simulations were performed using homology models built on MthK and KvAP templates. In conventional voltage clamp, ranolazine inhibited I_hERG with an IC₅₀ of 8.03 μM; peak I_hERG during ventricular action potential clamp was inhibited ~ 62% at 10 μM. The IC₅₀ values for ranolazine inhibition of the S620T inactivation deficient and N588K attenuated inactivation mutants were respectively ~ 73-fold and ~ 15-fold that for WT I_hERG. Mutations near the bottom of the selectivity filter (V625A, S624A, T623A) exhibited IC₅₀s between ~ 8 and 19-fold that for WT I_hERG, whilst the Y652A and F656A S6 mutations had IC₅₀s ~ 22-fold and 53-fold WT controls. Low potency lidocaine was comparatively insensitive to both pore helix and S6 mutations, but was sensitive to direction of K⁺ flux and particularly to loss of inactivation, with an IC₅₀ for S620T-hERG ~ 49-fold that for WT I_hERG. Docking simulations indicated that the larger size of ranolazine gives it potential for a greater range of interactions with hERG pore side chains compared to lidocaine, in particular enabling interaction of its two aromatic groups with side chains of both Y652 and F656. The N588K mutation is responsible for the SQT1 variant of short QT syndrome and our data suggest that ranolazine is unlikely to be effective against I_Kr/hERG in SQT1 patients.

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hERG K⁺ channels regulate cardiac action potential repolarization.

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The molecular basis of hERG block by ranolazine and structurally related lidocaine was studied.

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S6 Y652A and F656A mutations affected greatly ranolazine but not lidocaine binding.

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T623 and S624 residues may directly interact with ranolazine but not lidocaine.

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N588K and S620T attenuated inactivation mutants had reduced sensitivity to both drugs.

Comprehensive analyses of ventricular myocyte models identify targets exhibiting favorable rate dependence

Reverse rate dependence is a problematic property of antiarrhythmic drugs that prolong the cardiac action potential (AP). The prolongation caused by reverse rate dependent agents is greater at slow heart rates, resulting in both reduced arrhythmia suppression at fast rates and increased arrhythmia risk at slow rates. The opposite property, forward rate dependence, would theoretically overcome these parallel problems, yet forward rate dependent (FRD) antiarrhythmics remain elusive. Moreover, there is evidence that reverse rate dependence is an intrinsic property of perturbations to the AP. We have addressed the possibility of forward rate dependence by performing a comprehensive analysis of 13 ventricular myocyte models. By simulating populations of myocytes with varying properties and analyzing population results statistically, we simultaneously predicted the rate-dependent effects of changes in multiple model parameters. An average of 40 parameters were tested in each model, and effects on AP duration were assessed at slow (0.2 Hz) and fast (2 Hz) rates. The analysis identified a variety of FRD ionic current perturbations and generated specific predictions regarding their mechanisms. For instance, an increase in L-type calcium current is FRD when this is accompanied by indirect, rate-dependent changes in slow delayed rectifier potassium current. A comparison of predictions across models identified inward rectifier potassium current and the sodium-potassium pump as the two targets most likely to produce FRD AP prolongation. Finally, a statistical analysis of results from the 13 models demonstrated that models displaying minimal rate-dependent changes in AP shape have little capacity for FRD perturbations, whereas models with large shape changes have considerable FRD potential. This can explain differences between species and between ventricular cell types. Overall, this study provides new insights, both specific and general, into the determinants of AP duration rate dependence, and illustrates a strategy for the design of potentially beneficial antiarrhythmic drugs.

Several drugs intended to treat cardiac arrhythmias have failed because of unfavorable rate-dependent properties. That is, the drugs fail to alter electrical activity at fast heart rates, where this would be beneficial, but they do affect electrical activity at slow rates, where this is unwanted. In targeted studies, several agents have been shown to exhibit these unfavorable properties, suggesting that these rate-dependent responses may be intrinsic to ventricular muscle. To determine whether drugs with desirable rate-dependent properties could be rationally designed, we performed comprehensive and systematic analyses of several heart cell models. These analyses calculated the rate-dependent properties of changes in any model parameter, thereby generating simultaneously a large number of model predictions. The analyses showed that targets with favorable rate-dependent properties could indeed be identified, and further simulations uncovered the mechanisms underlying these behaviors. Moreover, a quantitative comparison of results obtained in different models provided new insight in why a given drug applied to different species, or to different tissue types, might produce different rate-dependent behaviors. Overall this study shows how a comprehensive and systematic approach to heart cell models can both identify novel targets and produce more general insight into rate-dependent alterations to cardiac electrical activity.

Carbon monoxide effects on human ventricle action potential assessed by mathematical simulations

Carbon monoxide (CO) that is produced in a number of different mammalian tissues is now known to have significant effects on the cardiovascular system. These include: (i) vasodilation, (ii) changes in heart rate and strength of contractions, and (iii) modulation of autonomic nervous system input to both the primary pacemaker and the working myocardium. Excessive CO in the environment is toxic and can initiate or mediate life threatening cardiac rhythm disturbances. Recent reports link these ventricular arrhythmias to an increase in the slowly inactivating, or “late” component of the Na⁺ current in the mammalian heart. The main goal of this paper is to explore the basis of this pro-arrhythmic capability of CO by incorporating changes in CO-induced ion channel activity with intracellular signaling pathways in the mammalian heart. To do this, a quite well-documented mathematical model of the action potential and intracellular calcium transient in the human ventricular myocyte has been employed. In silico iterations based on this model provide a useful first step in illustrating the cellular electrophysiological consequences of CO that have been reported from mammalian heart experiments. Specifically, when the Grandi et al. model of the human ventricular action potential is utilized, and after the Na⁺ and Ca²⁺ currents in a single myocyte are modified based on the experimental literature, early after-depolarization (EAD) rhythm disturbances appear, and important elements of the underlying causes of these EADs are revealed/illustrated. Our modified mathematical model of the human ventricular action potential also provides a convenient digital platform for designing future experimental work and relating these changes in cellular cardiac electrophysiology to emerging clinical and epidemiological data on CO toxicity.