Development of a pharmaceutical database as an aid to the nonclinical detection of drug-induced cardiac toxicity

The Health and Environmental Sciences Institute (HESI) Cardiac Safety Committee designed and created a publicly accessible database with an initial set of 128 pharmacologically defined pharmaceutical agents, many with known cardiotoxic properties. The database includes specific information about each compound that could be useful in evaluating hypotheses around mechanisms of drug-induced cardiac toxicity or for development of novel cardiovascular safety assays. Data on each of the compounds was obtained from published literature and online sources (e.g., DrugBank.ca and International Union of Basic and Clinical Pharmacology (IUPHAR) / British Pharmacological Society (BPS) Guide to PHARMACOLOGY) and was curated by 10 subject matter experts. The database includes information such as compound name, pharmacological mode of action, characterized cardiac mode of action, type of cardiac toxicity, known clinical cardiac toxicity profile, animal models used to evaluate the cardiotoxicity profile, routes of administration, and toxicokinetic parameters (i.e., Cmax). Data from both nonclinical and clinical studies are included for each compound. The user-friendly web interface allows for multiple approaches to search the database and is also intended to provide a means for the submission of new data/compounds from relevant users. This will ensure that the database is constantly updated and remains current. Such a data repository will not only aid the HESI working groups in defining drugs for use in any future studies, but safety scientists can also use the database as a vehicle of support for broader cardiovascular safety studies or exploring mechanisms of toxicity associated with certain pharmacological modes of action.

Assessing drug safety by identifying the axis of arrhythmia in cardiomyocyte electrophysiology

Many classes of drugs can induce fatal cardiac arrhythmias by disrupting the electrophysiology of cardiomyocytes. Safety guidelines thus require all new drugs to be assessed for pro-arrhythmic risk prior to conducting human trials. The standard safety protocols primarily focus on drug blockade of the delayed-rectifier potassium current (IKr). Yet the risk is better assessed using four key ion currents (IKr, ICaL, INaL, IKs). We simulated 100,000 phenotypically diverse cardiomyocytes to identify the underlying relationship between the blockade of those currents and the emergence of ectopic beats in the action potential. We call that relationship the axis of arrhythmia. It serves as a yardstick for quantifying the arrhythmogenic risk of any drug from its profile of multi-channel block alone. We tested it on 109 drugs and found that it predicted the clinical risk labels with an accuracy of 88.1-90.8%. Pharmacologists can use our method to assess the safety of novel drugs without resorting to animal testing or unwieldy computer simulations.

Empirical Quantification of Predictive Uncertainty Due to Model Discrepancy by Training with an Ensemble of Experimental Designs: An Application to Ion Channel Kinetics

When using mathematical models to make quantitative predictions for clinical or industrial use, it is important that predictions come with a reliable estimate of their accuracy (uncertainty quantification). Because models of complex biological systems are always large simplifications, model discrepancy arises-models fail to perfectly recapitulate the true data generating process. This presents a particular challenge for making accurate predictions, and especially for accurately quantifying uncertainty in these predictions. Experimentalists and modellers must choose which experimental procedures (protocols) are used to produce data used to train models. We propose to characterise uncertainty owing to model discrepancy with an ensemble of parameter sets, each of which results from training to data from a different protocol. The variability in predictions from this ensemble provides an empirical estimate of predictive uncertainty owing to model discrepancy, even for unseen protocols. We use the example of electrophysiology experiments that investigate the properties of hERG potassium channels. Here, 'information-rich' protocols allow mathematical models to be trained using numerous short experiments performed on the same cell. In this case, we simulate data with one model and fit it with a different (discrepant) one. For any individual experimental protocol, parameter estimates vary little under repeated samples from the assumed additive independent Gaussian noise model. Yet parameter sets arising from the same model applied to different experiments conflict-highlighting model discrepancy. Our methods will help select more suitable ion channel models for future studies, and will be widely applicable to a range of biological modelling problems.

Development of new adeno-associated virus capsid variants for targeted gene delivery to human cardiomyocytes

Recombinant adeno-associated viruses (rAAVs) have emerged as one of the most promising gene therapy vectors that have been successfully used in pre-clinical models of heart disease. However, this has not translated well to humans due to species differences in rAAV transduction efficiency. As a result, the search for human cardiotropic capsids is a major contemporary challenge. We used a capsid-shuffled rAAV library to perform directed evolution in human iPSC-derived cardiomyocytes (hiPSC-CMs). Five candidates emerged, with four presenting high sequence identity to AAV6, while a fifth divergent variant was related to AAV3b. Functional analysis of the variants was performed in vitro using hiPSC-CMs, cardiac organoids, human cardiac slices, non-human primate and porcine cardiac slices, as well as mouse heart and liver in vivo. We showed that cell entry was not the best predictor of transgene expression efficiency. The novel variant rAAV.KK04 was the best-performing vector in human-based screening platforms, exceeding the benchmark rAAV6. None of the novel capsids demonstrate a significant transduction of liver in vivo. The range of experimental models used revealed the value of testing for tropism differences under the conditions of human specificity, bona fide, myocardium and cell type of interest.

Development of a robust induced pluripotent stem cell atrial cardiomyocyte differentiation protocol to model atrial arrhythmia

BACKGROUND

Atrial fibrillation is the most common arrhythmia syndrome and causes significant morbidity and mortality. Current therapeutics, however, have limited efficacy. Notably, many therapeutics shown to be efficacious in animal models have not proved effective in humans. Thus, there is a need for a drug screening platform based on human tissue. The aim of this study was to develop a robust protocol for generating atrial cardiomyocytes from human-induced pluripotent stem cells.

METHODS

A novel protocol for atrial differentiation, with optimized timing of retinoic acid during mesoderm formation, was compared to two previously published methods. Each differentiation method was assessed for successful formation of a contractile syncytium, electrical properties assayed by optical action potential recordings and multi-electrode array electrophysiology, and response to the G-protein-gated potassium channel activator, carbamylcholine. Atrial myocyte monolayers, derived using the new differentiation protocol, were further assessed for cardiomyocyte purity, gene expression, and the ability to form arrhythmic rotors in response to burst pacing.

RESULTS

Application of retinoic acid at day 1 of mesoderm formation resulted in a robust differentiation of atrial myocytes with contractile syncytium forming in 16/18 differentiations across two cell lines. Atrial-like myocytes produced have shortened action potentials and field potentials, when compared to standard application of retinoic acid at the cardiac mesoderm stage. Day 1 retinoic acid produced atrial cardiomyocytes are also carbamylcholine sensitive, indicative of active I_kach currents, which was distinct from ventricular myocytes and standard retinoic addition in matched differentiations. A current protocol utilizing reduced Activin A and BMP4 can produce atrial cardiomyocytes with equivalent functionality but with reduced robustness of differentiation; only 8/17 differentiations produced a contractile syncytium. The day 1 retinoic acid protocol was successfully applied to 6 iPSC lines (3 male and 3 female) without additional optimization or modification. Atrial myocytes produced could also generate syncytia with rapid conduction velocities, > 40 cm s^-1, and form rotor style arrhythmia in response to burst pacing.

CONCLUSIONS

This method combines an enhanced atrial-like phenotype with robustness of differentiation, which will facilitate further research in human atrial arrhythmia and myopathies, while being economically viable for larger anti-arrhythmic drug screens.

Action Potential Morphology Accurately Predicts Proarrhythmic Risk for Drugs With Potential to Prolong Cardiac Repolarization

BACKGROUND

Drug-induced or acquired long QT syndrome occurs as a result of the unintended disruption of cardiac repolarization due to drugs that block cardiac ion channels. These side effects have been responsible for the withdrawal of a range of drugs from market and are a common reason for termination of the development of new drugs in the preclinical stage. Existing approaches to risk prediction are expensive and overly sensitive meaning that recently there have been renewed efforts, largely driven by the comprehensive proarrhythmic assay initiative, to develop more accurate methods for allocation of proarrhythmic risk.

METHODS

In this study, we aimed to quantify changes in the morphology of the repolarization phase of the cardiac action potential as an indicator of proarrhythmia, supposing that these shape changes might precede the emergence of ectopic depolarizations that trigger arrhythmia. To do this, we describe a new method of quantifying action potential morphology by measuring the radius of curvature of the repolarization phase both in simulated action potentials, as well as in action potentials measured from induced pluripotent stem cell-derived cardiomyocytes. Features derived from the curvature signal were used as inputs for logistic regressions to predict proarrhythmic risk.

RESULTS

Optimal risk classifiers based on morphology were able to correctly classify risk to drugs in the comprehensive proarrhythmic assay initiative panels with very high accuracy (0.9375) and outperformed conventional metrics based on action potential duration at 90% repolarization, triangulation, and charge movement (qNet).

CONCLUSIONS

Analysis of action potential morphology in response to proarrhythmic drugs improves prediction of torsadogenic risk. Furthermore, morphology metrics can be measured directly from the action potential, potentially eliminating the burden of undertaking complex screens of potency and drug-binding kinetics against multiple cardiac ion channels. As such, this method has the potential to improve and streamline regulatory assessment of proarrhythmia in preclinical drug development.

A calibrated functional patch-clamp assay to enhance clinical variant interpretation in KCNH2-related long QT syndrome

Modern sequencing technologies have revolutionized our detection of gene variants. However, in most genes, including KCNH2, the majority of missense variants are currently classified as variants of uncertain significance (VUSs). The aim of this study was to investigate the utility of an automated patch-clamp assay for aiding clinical variant classification in KCNH2. The assay was designed according to recommendations proposed by the Clinical Genome Sequence Variant Interpretation Working Group. Thirty-one variants (17 pathogenic/likely pathogenic, 14 benign/likely benign) were classified internally as variant controls. They were heterozygously expressed in Flp-In HEK293 cells for assessing the effects of variants on current density and channel gating in order to determine the sensitivity and specificity of the assay. All 17 pathogenic variant controls had reduced current density, and 13 of 14 benign variant controls had normal current density, which enabled determination of normal and abnormal ranges for applying evidence of moderate or supporting strength for VUS reclassification. Inclusion of functional assay evidence enabled us to reclassify 6 out of 44 KCNH2 VUSs as likely pathogenic. The high-throughput patch-clamp assay can provide moderate-strength evidence for clinical interpretation of clinical KCNH2 variants and demonstrates the value of developing automated patch-clamp assays for functional characterization of ion channel gene variants.

A massively parallel assay accurately discriminates between functionally normal and abnormal variants in a hotspot domain of KCNH2

Many genes, including KCNH2, contain "hotspot" domains associated with a high density of variants associated with disease. This has led to the suggestion that variant location can be used as evidence supporting classification of clinical variants. However, it is not known what proportion of all potential variants in hotspot domains cause loss of function. Here, we have used a massively parallel trafficking assay to characterize all single-nucleotide variants in exon 2 of KCNH2, a known hotspot for variants that cause long QT syndrome type 2 and an increased risk of sudden cardiac death. Forty-two percent of KCNH2 exon 2 variants caused at least 50% reduction in protein trafficking, and 65% of these trafficking-defective variants exerted a dominant-negative effect when co-expressed with a WT KCNH2 allele as assessed using a calibrated patch-clamp electrophysiology assay. The massively parallel trafficking assay was more accurate (AUC of 0.94) than bioinformatic prediction tools (REVEL and CardioBoost, AUC of 0.81) in discriminating between functionally normal and abnormal variants. Interestingly, over half of variants in exon 2 were found to be functionally normal, suggesting a nuanced interpretation of variants in this "hotspot" domain is necessary. Our massively parallel trafficking assay can provide this information prospectively.

A nonlinear and time-dependent leak current in the presence of calcium fluoride patch-clamp seal enhancer

Automated patch-clamp platforms are widely used and vital tools in both academia and industry to enable high-throughput studies such as drug screening. A leak current to ground occurs whenever the seal between a pipette and cell (or internal solution and cell in high-throughput machines) is not perfectly insulated from the bath (extracellular) solution. Over 1 GΩ seal resistance between pipette and bath solutions is commonly used as a quality standard for manual patch work. With automated platforms it can be difficult to obtain such a high seal resistance between the intra- and extra-cellular solutions. One suggested method to alleviate this problem is using an F ⁻ containing internal solution together with a Ca ²⁺ containing external solution — so that a CaF ₂ crystal forms when the two solutions meet which ‘plugs the holes’ to enhance the seal resistance. However, we observed an unexpected nonlinear-in-voltage and time-dependent current using these solutions on an automated patch-clamp platform. We performed manual patch-clamp experiments with the automated patch-clamp solutions, but no biological cell, and observed the same nonlinear time-dependent leak current. The current could be completely removed by washing out F ⁻ ions to leave a conventional leak current that was linear and not time-dependent. We therefore conclude fluoride ions interacting with the CaF ₂ crystal are the origin of the nonlinear time-dependent leak current. The consequences of such a nonlinear and time-dependent leak current polluting measurements should be considered carefully if it cannot be isolated and subtracted.

Pathophysiological metabolic changes associated with disease modify the proarrhythmic risk profile of drugs with potential to prolong repolarisation

BACKGROUND AND PURPOSE

Hydroxychloroquine, chloroquine and azithromycin are three drugs that were proposed to treat COVID-19. While concern already existed around their proarrhythmic potential there is little data regarding how altered physiological states encountered in patients such as febrile state, electrolyte imbalances or acidosis might change their risk profiles.

EXPERIMENTAL APPROACH

Potency of hERG block was measured using high-throughput electrophysiology in the presence of variable environmental factors. These potencies informed simulations to predict population risk profiles. Effects on cardiac repolarisation were verified in human induced pluripotent stem cell-derived cardiomyocytes from multiple individuals.

KEY RESULTS

Chloroquine and hydroxychloroquine blocked hERG with IC₅₀ of 1.47±0.07 μM and 3.78±0.17 μM respectively, indicating proarrhythmic risk at concentrations effective against SARS-CoV-2 in vitro. Hypokalaemia and hypermagnesemia increased potency of chloroquine and hydroxychloroquine, indicating increased proarrhythmic risk. Acidosis significantly reduced potency of all drugs, whereas increased temperature decreased potency of chloroquine and hydroxychloroquine against hERG but increased potency for azithromycin. In silico simulations demonstrated that proarrhythmic risk was increased by female sex, hypokalaemia and heart failure, and identified specific genetic backgrounds associated with emergence of arrhythmia.

CONCLUSION AND IMPLICATIONS

Our study demonstrates how proarrhythmic risk can be exacerbated by metabolic changes and pre-existing disease. More broadly, the study acts as a blueprint for how high-throughput in vitro screening, combined with in silico simulations can help guide both preclinical screening and clinical management of patients in relation to drugs with potential to prolong repolarisation.

Heterozygous KCNH2 variant phenotyping using Flp-In HEK293 and high-throughput automated patch clamp electrophysiology

KCNH2 is one of the 59 medically actionable genes recommended by the American College of Medical Genetics for reporting of incidental findings from clinical genomic sequencing. However, half of the reported KCNH2 variants in the ClinVar database are classified as variants of uncertain significance. In the absence of strong clinical phenotypes, there is a need for functional phenotyping to help decipher the significance of variants identified incidentally. Here, we report detailed methods for assessing the molecular phenotype of any KCNH2 missense variant. The key components of the assay include quick and cost-effective generation of a bi-cistronic vector to co-express Wild-type (WT) and any KCNH2 variant allele, generation of stable Flp-In HEK293 cell lines and high-throughput automated patch clamp electrophysiology analysis of channel function. Stable cell lines take 3–4 weeks to produce and can be generated in bulk, which will then allow up to 30 variants to be phenotyped per week after 48 h of channel expression. This high-throughput functional genomics assay will enable a much more rapid assessment of the extent of loss of function of any KCNH2 variant.

Conserved Role of the Large Conductance Calcium-Activated Potassium Channel, KCa1.1, in Sinus Node Function and Arrhythmia Risk

BACKGROUND

KCNMA1 encodes the α-subunit of the large-conductance Ca²⁺-activated K⁺ channel, K_Ca1.1, and lies within a linkage interval for atrial fibrillation (AF). Insights into the cardiac functions of K_Ca1.1 are limited, and KCNMA1 has not been investigated as an AF candidate gene.

METHODS

The KCNMA1 gene was sequenced in 118 patients with familial AF. The role of K_Ca1.1 in normal cardiac structure and function was evaluated in humans, mice, zebrafish, and fly. A novel KCNMA1 variant was functionally characterized.

RESULTS

A complex KCNMA1 variant was identified in 1 kindred with AF. To evaluate potential disease mechanisms, we first evaluated the distribution of K_Ca1.1 in normal hearts using immunostaining and immunogold electron microscopy. K_Ca1.1 was seen throughout the atria and ventricles in humans and mice, with strong expression in the sinus node. In an ex vivo murine sinoatrial node preparation, addition of the K_Ca1.1 antagonist, paxilline, blunted the increase in beating rate induced by adrenergic receptor stimulation. Knockdown of the K_Ca1.1 ortholog, kcnma1b, in zebrafish embryos resulted in sinus bradycardia with dilatation and reduced contraction of the atrium and ventricle. Genetic inactivation of the Drosophila K_Ca1.1 ortholog, slo, systemically or in adult stages, also slowed the heartbeat and produced fibrillatory cardiac contractions. Electrophysiological characterization of slo-deficient flies revealed bursts of action potentials, reflecting increased events of fibrillatory arrhythmias. Flies with cardiac-specific overexpression of the human KCNMA1 mutant also showed increased heart period and bursts of action potentials, similar to the K_Ca1.1 loss-of-function models.

CONCLUSIONS

Our data point to a highly conserved role of K_Ca1.1 in sinus node function in humans, mice, zebrafish, and fly and suggest that K_Ca1.1 loss of function may predispose to AF.

Arrhythmogenic effects of ultra-long and bistable cardiac action potentials

Contemporary accounts of the initiation of cardiac arrhythmias typically rely on after-depolarizations as the trigger for reentrant activity. The after-depolarizations are usually triggered by calcium entry or spontaneous release within the cells of the myocardium or the conduction system. Here we propose an alternative mechanism whereby arrhythmias are triggered autonomously by cardiac cells that fail to repolarize after a normal heartbeat. We investigated the proposal by representing the heart as an excitable medium of FitzHugh-Nagumo cells where a proportion of cells were capable of remaining depolarized indefinitely. As such, those cells exhibit bistable membrane dynamics. We found that heterogeneous media can tolerate a surprisingly large number of bistable cells and still support normal rhythmic activity. Yet there is a critical limit beyond which the medium is persistently arrhythmogenic. Numerical analysis revealed that the critical threshold for arrhythmogenesis depends on both the strength of the coupling between cells and the extent to which the abnormal cells resist repolarization. Moreover, arrhythmogenesis was found to emerge preferentially at tissue boundaries where cells naturally have fewer neighbors to influence their behavior. These findings may explain why atrial fibrillation typically originates from tissue boundaries such as the cuff of the pulmonary vein.

Cardiac fibrillation is a medical condition where normal heart function is compromised as electrical activity becomes disordered. How fibrillation arises spontaneously is not fully understood. It is generally thought to be triggered by premature depolarization of the cardiac action potential in one or more cells. Those premature beats, known as after-depolarizations, subsequently initiate a self-sustaining rotor in the otherwise normal heart tissue. In this study, we propose an alternative mechanism whereby arrhythmias are initiated by cardiac cells that fail to repolarize of their own accord but still operate normally when embedded in functional heart tissue. We find that such cells can act as focal ectopic sources under appropriate conditions of inter-cellular coupling. Moreover, those cells are more prone to initiating arrhythmia when they are located on natural tissue boundaries. This may explain why atrial fibrillation typically originates from the site where the pulmonary vein attaches to the wall of the heart.

Pharmacological activation of IKr in models of long QT Type 2 risks overcorrection of repolarization

AIMS

Current treatment for congenital long QT syndrome Type 2 (cLQTS2), an electrical disorder that increases the risk of life-threatening cardiac arrhythmias, is aimed at reducing the incidence of arrhythmia triggers (beta-blockers) or terminating the arrhythmia after onset (implantable cardioverter-defibrillator). An alternative strategy is to target the underlying disease mechanism, which is reduced rapid delayed rectifier current (IKr) passed by Kv11.1 channels. Small molecule activators of Kv11.1 have been identified but the extent to which these can restore normal cardiac signalling in cLQTS2 backgrounds remains unclear. Here, we examined the ability of ICA-105574, an activator of Kv11.1 that impairs transition to the inactivated state, to restore function to heterozygous Kv11.1 channels containing either inactivation enhanced (T618S, N633S) or expression deficient (A422T) mutations.

METHODS AND RESULTS

ICA-105574 effectively restored Kv11.1 current from heterozygous inactivation enhanced or expression defective mutant channels in heterologous expression systems. In a human-induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) model of cLQTS2 containing the expression defective Kv11.1 mutant A422T, cardiac repolarization, estimated from the duration of calcium transients in isolated cells and the rate corrected field potential duration (FPDc) in culture monolayers of cells, was significantly prolonged. The Kv11.1 activator ICA-105574 was able to reverse the prolonged repolarization in a concentration-dependent manner. However, at higher doses, ICA-105574 produced a shortening of the FPDc compared to controls. In vitro and in silico analysis suggests that this overcorrection occurs as a result of a temporal redistribution of the peak IKr to much earlier in the plateau phase of the action potential, which results in early repolarization.

CONCLUSION

Kv11.1 activators, which target the primary disease mechanism, provide a possible treatment option for cLQTS2, with the caveat that there may be a risk of overcorrection that could itself be pro-arrhythmic.

Co-expression of calcium and hERG potassium channels reduces the incidence of proarrhythmic events

AIMS

Cardiac electrical activity is extraordinarily robust. However, when it goes wrong it can have fatal consequences. Electrical activity in the heart is controlled by the carefully orchestrated activity of more than a dozen different ion conductances. While there is considerable variability in cardiac ion channel expression levels between individuals, studies in rodents have indicated that there are modules of ion channels whose expression co-vary. The aim of this study was to investigate whether meta-analytic co-expression analysis of large-scale gene expression datasets could identify modules of co-expressed cardiac ion channel genes in human hearts that are of functional importance.

METHODS AND RESULTS

Meta-analysis of 3653 public human RNA-seq datasets identified a strong correlation between expression of CACNA1C (L-type calcium current, ICaL) and KCNH2 (rapid delayed rectifier K+ current, IKr), which was also observed in human adult heart tissue samples. In silico modelling suggested that co-expression of CACNA1C and KCNH2 would limit the variability in action potential duration seen with variations in expression of ion channel genes and reduce susceptibility to early afterdepolarizations, a surrogate marker for proarrhythmia. We also found that levels of KCNH2 and CACNA1C expression are correlated in human-induced pluripotent stem cell-derived cardiac myocytes and the levels of CACNA1C and KCNH2 expression were inversely correlated with the magnitude of changes in repolarization duration following inhibition of IKr.

CONCLUSION

Meta-analytic approaches of multiple independent human gene expression datasets can be used to identify gene modules that are important for regulating heart function. Specifically, we have verified that there is co-expression of CACNA1C and KCNH2 ion channel genes in human heart tissue, and in silico analyses suggest that CACNA1C-KCNH2 co-expression increases the robustness of cardiac electrical activity.

A nonlinear and time-dependent leak current in the presence of calcium fluoride patch-clamp seal enhancer

Automated patch-clamp platforms are widely used and vital tools in both academia and industry to enable high-throughput studies such as drug screening. A leak current to ground occurs whenever the seal between a pipette and cell (or internal solution and cell in high-throughput machines) is not perfectly insulated from the bath (extracellular) solution. Over 1 GΩ seal resistance between pipette and bath solutions is commonly used as a quality standard for manual patch work. With automated platforms it can be difficult to obtain such a high seal resistance between the intra- and extra-cellular solutions. One suggested method to alleviate this problem is using an F− containing internal solution together with a Ca2+ containing external solution — so that a CaF2 crystal forms when the two solutions meet which ‘plugs the holes’ to enhance the seal resistance. However, we observed an unexpected nonlinear-in-voltage and time-dependent current using these solutions on an automated patch-clamp platform. We performed manual patch-clamp experiments with the automated patch-clamp solutions, but no biological cell, and observed the same nonlinear time-dependent leak current. The current could be completely removed by washing out F− ions to leave a conventional leak current that was linear and not time-dependent. We therefore conclude fluoride ions interacting with the CaF2 crystal are the origin of the nonlinear time-dependent leak current. The consequences of such a nonlinear and time-dependent leak current polluting measurements should be considered carefully if it cannot be isolated and subtracted.

Protocol-Dependent Differences in IC50 Values Measured in Human Ether-Á-Go-Go-Related Gene Assays Occur in a Predictable Way and Can Be Used to Quantify State Preference of Drug Binding

Current guidelines around preclinical screening for drug-induced arrhythmias require the measurement of the potency of block of voltage-gated potassium channel subtype 11.1 (K_v11.1) as a surrogate for risk. A shortcoming of this approach is that the measured IC₅₀ of K_v11.1 block varies widely depending on the voltage protocol used in electrophysiological assays. In this study, we aimed to investigate the factors that contribute to these differences and to identify whether it is possible to make predictions about protocol-dependent block that might facilitate the comparison of potencies measured using different assays. Our data demonstrate that state preferential binding, together with drug-binding kinetics and trapping, is an important determinant of the protocol dependence of K_v11.1 block. We show for the first time that differences in IC₅₀ measured between protocols occurs in a predictable way, such that machine-learning algorithms trained using a selection of simple voltage protocols can indeed predict protocol-dependent potency. Furthermore, we also show that the preference of a drug for binding to the open versus the inactivated state of K_v11.1 can also be inferred from differences in IC₅₀ values measured between protocols. Our work therefore identifies how state preferential drug binding is a major determinant of the protocol dependence of IC₅₀ values measured in preclinical K_v11.1 assays. It also provides a novel method for quantifying the state dependence of K_v11.1 drug binding that will facilitate the development of more complete models of drug binding to K_v11.1 and improve our understanding of proarrhythmic risk associated with compounds that block K_v11.1.

Experimentally Validated Pharmacoinformatics Approach to Predict hERG Inhibition Potential of New Chemical Entities

The hERG (human ether-a-go-go-related gene) encoded potassium ion (K⁺) channel plays a major role in cardiac repolarization. Drug-induced blockade of hERG has been a major cause of potentially lethal ventricular tachycardia termed Torsades de Pointes (TdPs). Therefore, we presented a pharmacoinformatics strategy using combined ligand and structure based models for the prediction of hERG inhibition potential (IC₅₀) of new chemical entities (NCEs) during early stages of drug design and development. Integrated GRid-INdependent Descriptor (GRIND) models, and lipophilic efficiency (LipE), ligand efficiency (LE) guided template selection for the structure based pharmacophore models have been used for virtual screening and subsequent hERG activity (pIC₅₀) prediction of identified hits. Finally selected two hits were experimentally evaluated for hERG inhibition potential (pIC₅₀) using whole cell patch clamp assay. Overall, our results demonstrate a difference of less than ±1.6 log unit between experimentally determined and predicted hERG inhibition potential (IC₅₀) of the selected hits. This revealed predictive ability and robustness of our models and could help in correctly rank the potency order (lower μM to higher nM range) against hERG.

Sinusoidal voltage protocols for rapid characterisation of ion channel kinetics

Key points

Ion current kinetics are commonly represented by current–voltage relationships, time constant–voltage relationships and subsequently mathematical models fitted to these. These experiments take substantial time, which means they are rarely performed in the same cell.

Rather than traditional square‐wave voltage clamps, we fitted a model to the current evoked by a novel sum‐of‐sinusoids voltage clamp that was only 8 s long.

Short protocols that can be performed multiple times within a single cell will offer many new opportunities to measure how ion current kinetics are affected by changing conditions.

The new model predicts the current under traditional square‐wave protocols well, with better predictions of underlying currents than literature models. The current under a novel physiologically relevant series of action potential clamps is predicted extremely well.

The short sinusoidal protocols allow a model to be fully fitted to individual cells, allowing us to examine cell–cell variability in current kinetics for the first time.

Abstract

Understanding the roles of ion currents is crucial to predict the action of pharmaceuticals and mutations in different scenarios, and thereby to guide clinical interventions in the heart, brain and other electrophysiological systems. Our ability to predict how ion currents contribute to cellular electrophysiology is in turn critically dependent on our characterisation of ion channel kinetics – the voltage‐dependent rates of transition between open, closed and inactivated channel states. We present a new method for rapidly exploring and characterising ion channel kinetics, applying it to the hERG potassium channel as an example, with the aim of generating a quantitatively predictive representation of the ion current. We fitted a mathematical model to currents evoked by a novel 8 second sinusoidal voltage clamp in CHO cells overexpressing hERG1a. The model was then used to predict over 5 minutes of recordings in the same cell in response to further protocols: a series of traditional square step voltage clamps, and also a novel voltage clamp comprising a collection of physiologically relevant action potentials. We demonstrate that we can make predictive cell‐specific models that outperform the use of averaged data from a number of different cells, and thereby examine which changes in gating are responsible for cell–cell variability in current kinetics. Our technique allows rapid collection of consistent and high quality data, from single cells, and produces more predictive mathematical ion channel models than traditional approaches.

Ion current kinetics are commonly represented by current–voltage relationships, time constant–voltage relationships and subsequently mathematical models fitted to these. These experiments take substantial time, which means they are rarely performed in the same cell.

Rather than traditional square‐wave voltage clamps, we fitted a model to the current evoked by a novel sum‐of‐sinusoids voltage clamp that was only 8 s long.

Short protocols that can be performed multiple times within a single cell will offer many new opportunities to measure how ion current kinetics are affected by changing conditions.

The new model predicts the current under traditional square‐wave protocols well, with better predictions of underlying currents than literature models. The current under a novel physiologically relevant series of action potential clamps is predicted extremely well.

The short sinusoidal protocols allow a model to be fully fitted to individual cells, allowing us to examine cell–cell variability in current kinetics for the first time.

Subtyping cognitive profiles in Autism Spectrum Disorder using a Functional Random Forest algorithm

DSM-5 Autism Spectrum Disorder (ASD) comprises a set of neurodevelopmental disorders characterized by deficits in social communication and interaction and repetitive behaviors or restricted interests, and may both affect and be affected by multiple cognitive mechanisms. This study attempts to identify and characterize cognitive subtypes within the ASD population using our Functional Random Forest (FRF) machine learning classification model. This model trained a traditional random forest model on measures from seven tasks that reflect multiple levels of information processing. 47 ASD diagnosed and 58 typically developing (TD) children between the ages of 9 and 13 participated in this study. Our RF model was 72.7% accurate, with 80.7% specificity and 63.1% sensitivity. Using the random forest model, the FRF then measures the proximity of each subject to every other subject, generating a distance matrix between participants. This matrix is then used in a community detection algorithm to identify subgroups within the ASD and TD groups, and revealed 3 ASD and 4 TD putative subgroups with unique behavioral profiles. We then examined differences in functional brain systems between diagnostic groups and putative subgroups using resting-state functional connectivity magnetic resonance imaging (rsfcMRI). Chi-square tests revealed a significantly greater number of between group differences (p < .05) within the cingulo-opercular, visual, and default systems as well as differences in inter-system connections in the somato-motor, dorsal attention, and subcortical systems. Many of these differences were primarily driven by specific subgroups suggesting that our method could potentially parse the variation in brain mechanisms affected by ASD.

Structural Dynamics of the MscL C-terminal Domain

The large conductance mechanosensitive channel (MscL), acts as an osmoprotective emergency valve in bacteria by opening a large, water-filled pore in response to changes in membrane tension. In its closed configuration, the last 36 residues at the C-terminus form a bundle of five α-helices co-linear with the five-fold axis of symmetry. Here, we examined the structural dynamics of the C-terminus of EcMscL using site-directed spin labelling electron paramagnetic resonance (SDSL EPR) spectroscopy. These experiments were complemented with computational modelling including molecular dynamics (MD) simulations and finite element (FE) modelling. Our results show that under physiological conditions, the C-terminus is indeed an α-helical bundle, located near the five-fold symmetry axis of the molecule. Both experiments and computational modelling demonstrate that only the top part of the C-terminal domain (from the residue A110 to E118) dissociates during the channel gating, while the rest of the C-terminus stays assembled. This result is consistent with the view that the C-terminus functions as a molecular sieve and stabilizer of the oligomeric MscL structure as previously suggested.

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?

Endocardial TRPC-6 Channels Act as Atrial Mechanosensors and Load-Dependent Modulators of Endocardial/Myocardial Cross-Talk

Mechanoelectrical feedback may increase arrhythmia susceptibility, but the molecular mechanisms are incompletely understood. This study showed that mechanical stretch altered the localization, protein levels, and function of the cation-selective transient receptor potential channel (TRPC)-6 in atrial endocardial cells in humans, pigs, and mice. In endocardial/myocardial cross-talk studies, addition of media from porcine atrial endocardium (AE) cells altered the calcium (Ca²⁺) transient characteristics of human-induced pluripotent stem cell-derived cardiomyocytes. These changes did not occur with media from stretched AE cells. Our data suggested that endocardial TRPC-6-dependent paracrine signaling may modulate myocardial Ca²⁺ homeostasis under basal conditions and protect against stretch-induced atrial arrhythmias.

Recent advances in understanding and prevention of sudden cardiac death

There have been tremendous advances in the diagnosis and treatment of heart disease over the last 50 years. Nevertheless, it remains the number one cause of death. About half of heart-related deaths occur suddenly, and in about half of these cases the person was unaware that they had underlying heart disease. Genetic heart disease accounts for only approximately 2% of sudden cardiac deaths, but as it typically occurs in younger people it has been a particular focus of activity in our quest to not only understand the underlying mechanisms of cardiac arrhythmogenesis but also develop better strategies for earlier detection and prevention. In this brief review, we will highlight trends in the recent literature focused on sudden cardiac death in genetic heart diseases and how these studies are contributing to a broader understanding of sudden death in the community.

Measuring kinetics and potency of hERG block for CiPA

INTRODUCTION

The Comprehensive in vitro Proarrhythmic Assay (CiPA) aims to update current cardiac safety testing to better evaluate arrhythmic risk. A central theme of CiPA is the use of in silico approaches to risk prediction incorporating models of drug binding to hERG. To parameterize these models, accurate in vitro measurement of potency and kinetics of block is required. The Ion Channel Working Group was tasked with: i) selecting a protocol that could measure kinetics of block and was easily implementable on automated platforms for future rollout in industry and ii) acquiring a reference dataset using the standardized protocol.

METHODS

Data were acquired using a 'step depolarisation' protocol using manual patch-clamp at ambient temperature.

RESULTS

Potency, kinetics and trapping characteristics of hERG block for the CiPA training panel of twelve drugs were measured. Timecourse of block and trapping characteristics could be reliably measured if the time constant for onset of block was between ~500ms and ~15s. Seven drugs, however had time courses of block faster than this cut-off.

DISCUSSION

Here we describe the implementation of the standardized protocol for measurement of kinetics and potency of hERG block for CiPA. The results highlight the challenges in identifying a single protocol to measure hERG block over a range of kinetics. The dataset from this study is being used by the In Silico Working Group to develop models of drug binding for risk prediction and is freely available as a 'gold standard' ambient temperature dataset to evaluate variability across high throughput platforms.

Nanomechanical properties of MscL α helices: A steered molecular dynamics study

Gating of mechanosensitive (MS) channels is driven by a hierarchical cascade of movements and deformations of transmembrane helices in response to bilayer tension. Determining the intrinsic mechanical properties of the individual transmembrane helices is therefore central to understanding the intricacies of the gating mechanism of MS channels. We used a constant-force steered molecular dynamics (SMD) approach to perform unidirectional pulling tests on all the helices of MscL in M. tuberculosis and E. coli homologs. Using this method, we could overcome the issues encountered with the commonly used constant-velocity SMD simulations, such as low mechanical stability of the helix during stretching and high dependency of the elastic properties on the pulling rate. We estimated Young's moduli of the α-helices of MscL to vary between 0.2 and 12.5 GPa with TM2 helix being the stiffest. We also studied the effect of water on the properties of the pore-lining TM1 helix. In the absence of water, this helix exhibited a much stiffer response. By monitoring the number of hydrogen bonds, it appears that water acts like a 'lubricant' (softener) during TM1 helix elongation. These data shed light on another physical aspect underlying hydrophobic gating of MS channels, in particular MscL.

T-wave morphology can distinguish healthy controls from LQTS patients

Long QT syndrome (LQTS) is an inherited disorder associated with prolongation of the QT/QTc interval on the surface electrocardiogram (ECG) and a markedly increased risk of sudden cardiac death due to cardiac arrhythmias. Up to 25% of genotype-positive LQTS patients have QT/QTc intervals in the normal range. These patients are, however, still at increased risk of life-threatening events compared to their genotype-negative siblings. Previous studies have shown that analysis of T-wave morphology may enhance discrimination between control and LQTS patients. In this study we tested the hypothesis that automated analysis of T-wave morphology from Holter ECG recordings could distinguish between control and LQTS patients with QTc values in the range 400-450 ms. Holter ECGs were obtained from the Telemetric and Holter ECG Warehouse (THEW) database. Frequency binned averaged ECG waveforms were obtained and extracted T-waves were fitted with a combination of 3 sigmoid functions (upslope, downslope and switch) or two 9th order polynomial functions (upslope and downslope). Neural network classifiers, based on parameters obtained from the sigmoid or polynomial fits to the 1 Hz and 1.3 Hz ECG waveforms, were able to achieve up to 92% discrimination between control and LQTS patients and 88% discrimination between LQTS1 and LQTS2 patients. When we analysed a subgroup of subjects with normal QT intervals (400-450 ms, 67 controls and 61 LQTS), T-wave morphology based parameters enabled 90% discrimination between control and LQTS patients, compared to only 71% when the groups were classified based on QTc alone. In summary, our Holter ECG analysis algorithms demonstrate the feasibility of using automated analysis of T-wave morphology to distinguish LQTS patients, even those with normal QTc, from healthy controls.

Computational cardiology and risk stratification for sudden cardiac death: one of the grand challenges for cardiology in the 21st century

Risk stratification in the context of sudden cardiac death has been acknowledged as one of the major challenges facing cardiology for the past four decades. In recent years, the advent of high performance computing has facilitated organ-level simulation of the heart, meaning we can now examine the causes, mechanisms and impact of cardiac dysfunction in silico. As a result, computational cardiology, largely driven by the Physiome project, now stands at the threshold of clinical utility in regards to risk stratification and treatment of patients at risk of sudden cardiac death. In this white paper, we outline a roadmap of what needs to be done to make this translational step, using the relatively well-developed case of acquired or drug-induced long QT syndrome as an exemplar case.

Rescue of protein expression defects may not be enough to abolish the pro-arrhythmic phenotype of long QT type 2 mutations

KEY POINTS

Most missense long QT syndrome type 2 (LQTS2) mutations result in Kv11.1 channels that show reduced levels of membrane expression. Pharmacological chaperones that rescue mutant channel expression could have therapeutic potential to reduce the risk of LQTS2-associated arrhythmias and sudden cardiac death, but only if the mutant Kv11.1 channels function normally (i.e. like WT channels) after membrane expression is restored. Fewer than half of mutant channels exhibit relatively normal function after rescue by low temperature. The remaining rescued missense mutant Kv11.1 channels have perturbed gating and/or ion selectivity characteristics. Co-expression of WT subunits with gating defective missense mutations ameliorates but does not eliminate the functional abnormalities observed for most mutant channels. For patients with mutations that affect gating in addition to expression, it may be necessary to use a combination therapy to restore both normal function and normal expression of the channel protein.

ABSTRACT

In the heart, Kv11.1 channels pass the rapid delayed rectifier current (IKr ) which plays critical roles in repolarization of the cardiac action potential and in the suppression of arrhythmias caused by premature stimuli. Over 500 inherited mutations in Kv11.1 are known to cause long QT syndrome type 2 (LQTS2), a cardiac electrical disorder associated with an increased risk of life threatening arrhythmias. Most missense mutations in Kv11.1 reduce the amount of channel protein expressed at the membrane and, as a consequence, there has been considerable interest in developing pharmacological agents to rescue the expression of these channels. However, pharmacological chaperones will only have clinical utility if the mutant Kv11.1 channels function normally after membrane expression is restored. The aim of this study was to characterize the gating phenotype for a subset of LQTS2 mutations to assess what proportion of mutations may be suitable for rescue. As an initial screen we used reduced temperature to rescue expression defects of mutant channels expressed in Xenopus laevis oocytes. Over half (∼56%) of Kv11.1 mutants exhibited functional gating defects that either dramatically reduced the amount of current contributing to cardiac action potential repolarization and/or reduced the amount of protective current elicited in response to premature depolarizations. Our data demonstrate that if pharmacological rescue of protein expression defects is going to have clinical utility in the treatment of LQTS2 then it will be important to assess the gating phenotype of LQTS2 mutations before attempting rescue.

Temperature Effects on Kinetics of KV11.1 Drug Block Have Important Consequences for In Silico Proarrhythmic Risk Prediction

Drug block of voltage-gated potassium channel subtype 11.1 human ether-a-go-go related gene (Kv11.1) (hERG) channels, encoded by the KCNH2 gene, is associated with reduced repolarization of the cardiac action potential and is the predominant cause of acquired long QT syndrome that can lead to fatal cardiac arrhythmias. Current safety guidelines require that potency of KV11.1 block is assessed in the preclinical phase of drug development. However, not all drugs that block KV11.1 are proarrhythmic, meaning that screening on the basis of equilibrium measures of block can result in high attrition of potentially low-risk drugs. The basis of the next generation of drug-screening approaches is set to be in silico risk prediction, informed by in vitro mechanistic descriptions of drug binding, including measures of the kinetics of block. A critical issue in this regard is characterizing the temperature dependence of drug binding. Specifically, it is important to address whether kinetics relevant to physiologic temperatures can be inferred or extrapolated from in vitro data gathered at room temperature in high-throughout systems. Here we present the first complete study of the temperature-dependent kinetics of block and unblock of a proarrhythmic drug, cisapride, to KV11.1. Our data highlight a complexity to binding that manifests at higher temperatures and can be explained by accumulation of an intermediate, non-blocking encounter-complex. These results suggest that for cisapride, physiologically relevant kinetic parameters cannot be simply extrapolated from those measured at lower temperatures; rather, data gathered at physiologic temperatures should be used to constrain in silico models that may be used for proarrhythmic risk prediction.

Heritability of ECG Biomarkers in the Netherlands Twin Registry Measured from Holter ECGs

Introduction: The resting ECG is the most commonly used tool to assess cardiac electrophysiology. Previous studies have estimated heritability of ECG parameters based on these snapshots of the cardiac electrical activity. In this study we set out to determine whether analysis of heart rate specific data from Holter ECGs allows more complete assessment of the heritability of ECG parameters.

Methods and Results: Holter ECGs were recorded from 221 twin pairs and analyzed using a multi-parameter beat binning approach. Heart rate dependent estimates of heritability for QRS duration, QT interval, T_peak–T_end and T_height were calculated using structural equation modeling. QRS duration is largely determined by environmental factors whereas repolarization is primarily genetically determined. Heritability estimates of both QT interval and T_height were significantly higher when measured from Holter compared to resting ECGs and the heritability estimate of each was heart rate dependent. Analysis of the genetic contribution to correlation between repolarization parameters demonstrated that covariance of individual ECG parameters at different heart rates overlap but at each specific heart rate there was relatively little overlap in the genetic determinants of the different repolarization parameters.

Conclusions: Here we present the first study of heritability of repolarization parameters measured from Holter ECGs. Our data demonstrate that higher heritability can be estimated from the Holter than the resting ECG and reveals rate dependence in the genetic—environmental determinants of the ECG that has not previously been tractable. Future applications include deeper dissection of the ECG of participants with inherited cardiac electrical disease.

Getting to the heart of hERG K(+) channel gating

Potassium ion channels encoded by the human ether-a-go-go related gene (hERG) form the ion-conducting subunit of the rapid delayed rectifier potassium current (IKr ). Although hERG channels exhibit a widespread tissue distribution they play a particularly important role in the heart. There has been considerable interest in hERG K(+) channels for three main reasons. First, they have very unusual gating kinetics, most notably rapid and voltage-dependent inactivation coupled to slow deactivation, which has led to the suggestion that they may play a specific role in the suppression of arrhythmias. Second, mutations in hERG are the cause of 30-40% of cases of congenital long QT syndrome (LQTS), the commonest inherited primary arrhythmia syndrome. Third, hERG is the molecular target for the vast majority of drugs that cause drug-induced LQTS, the commonest cause of drug-induced arrhythmias and cardiac death. Drug-induced LQTS has now been reported for a large range of both cardiac and non-cardiac drugs, in which this side effect is entirely undesired. In recent years there have been comprehensive reviews published on hERG K(+) channels (Vandenberg et al. 2012) and we will not re-cover this ground. Rather, we focus on more recent work on the structural basis and dynamics of hERG gating with an emphasis on how the latest developments may facilitate translational research in the area of stratifying risk of arrhythmias.

In silico assessment of kinetics and state dependent binding properties of drugs causing acquired LQTS

The Kv11.1 or hERG potassium channel is responsible for one of the major repolarising currents (IKr) in cardiac myocytes. Drug binding to hERG can result in reduction in IKr, action potential prolongation, acquired long QT syndrome and fatal cardiac arrhythmias. The current guidelines for pre-clinical assessment of drugs in development is based on the measurement of the drug concentration that causes 50% current block, i.e., IC50. However, drugs with the same apparent IC50 may have very different kinetics of binding and unbinding, as well as different affinities for the open and inactivated states of Kv11.1. Therefore, IC50 measurements may not reflect the true risk of drug induced arrhythmias. Here we have used an in silico approach to test the hypothesis that drug binding kinetics and differences in state-dependent affinity will influence the extent of cardiac action potential prolongation independent of apparent IC50 values. We found, in general that drugs with faster overall kinetics and drugs with higher affinity for the open state relative to the inactivated state cause more action potential prolongation. These characteristics of drug-hERG interaction are likely to be more arrhythmogenic but cannot be predicted by IC50 measurement alone. Our results suggest that the pre-clinical assessment of Kv11.1-drug interactions should include descriptions of the kinetics and state dependence of drug binding. Further, incorporation of this information into sophisticated in silico models should be able to better predict arrhythmia risk and therefore more accurately assess safety of new drugs in development.

Profiles of perfectionism, parental climate, and burnout among competitive junior athletes

Recent research suggests that groups of athletes which differ in terms of perfectionism and perceptions of achievement climate can be identified. Moreover, these groups also differ in terms of burnout symptoms. The purpose of the current study was to extend this research by examining whether discernible groups can be identified based on scores of perfectionism and perceptions of parent-initiated climate and, then, whether these groups differ in terms of burnout. Two-hundred and thirty-seven Swedish junior athletes (124 males and 113 females aged 16-19) from a variety of sports completed measures of athlete burnout, multidimensional perfectionism, and parent-initiated motivational climate. Latent profile analysis identified four groups: non-perfectionistic athletes in a task-involving climate, moderately perfectionistic athletes in a task-involving climate, highly perfectionistic athletes in a task-involving climate, and highly perfectionistic athletes in a mixed climate. The latter two groups reported higher levels of burnout in comparison to other groups. The findings suggest that junior athletes high in perfectionism may be at comparatively greater risk to burnout and that this may especially be the case when they perceive their parents to emphasize concerns about failure and winning without trying one's best.

PhosphOrtholog: a web-based tool for cross-species mapping of orthologous protein post-translational modifications

Background

Most biological processes are influenced by protein post-translational modifications (PTMs). Identifying novel PTM sites in different organisms, including humans and model organisms, has expedited our understanding of key signal transduction mechanisms. However, with increasing availability of deep, quantitative datasets in diverse species, there is a growing need for tools to facilitate cross-species comparison of PTM data. This is particularly important because functionally important modification sites are more likely to be evolutionarily conserved; yet cross-species comparison of PTMs is difficult since they often lie in structurally disordered protein domains. Current tools that address this can only map known PTMs between species based on known orthologous phosphosites, and do not enable the cross-species mapping of newly identified modification sites. Here, we addressed this by developing a web-based software tool, PhosphOrtholog (www.phosphortholog.com) that accurately maps protein modification sites between different species. This facilitates the comparison of datasets derived from multiple species, and should be a valuable tool for the proteomics community.

Results

Here we describe PhosphOrtholog, a web-based application for mapping known and novel orthologous PTM sites from experimental data obtained from different species. PhosphOrtholog is the only generic and automated tool that enables cross-species comparison of large-scale PTM datasets without relying on existing PTM databases. This is achieved through pairwise sequence alignment of orthologous protein residues. To demonstrate its utility we apply it to two sets of human and rat muscle phosphoproteomes generated following insulin and exercise stimulation, respectively, and one publicly available mouse phosphoproteome following cellular stress revealing high mapping and coverage efficiency. Although coverage statistics are dataset dependent, PhosphOrtholog increased the number of cross-species mapped sites in all our example data sets by more than double when compared to those recovered using existing resources such as PhosphoSitePlus.

Conclusions

PhosphOrtholog is the first tool that enables mapping of thousands of novel and known protein phosphorylation sites across species, accessible through an easy-to-use web interface. Identification of conserved PTMs across species from large-scale experimental data increases our knowledgebase of functional PTM sites. Moreover, PhosphOrtholog is generic being applicable to other PTM datasets such as acetylation, ubiquitination and methylation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1820-x) contains supplementary material, which is available to authorized users.

Multiscale cardiac modelling reveals the origins of notched T waves in long QT syndrome type 2

The heart rhythm disorder long QT syndrome (LQTS) can result in sudden death in the young or remain asymptomatic into adulthood. The features of the surface electrocardiogram (ECG), a measure of the electrical activity of the heart, can be equally variable in LQTS patients, posing well-described diagnostic dilemmas. Here we report a correlation between QT interval prolongation and T-wave notching in LQTS2 patients and use a novel computational framework to investigate how individual ionic currents, as well as cellular and tissue level factors, contribute to notched T waves. Furthermore, we show that variable expressivity of ECG features observed in LQTS2 patients can be explained by as little as 20% variation in the levels of ionic conductances that contribute to repolarization reserve. This has significant implications for interpretation of whole-genome sequencing data and underlies the importance of interpreting the entire molecular signature of disease in any given individual.

Multiple interactions between cytoplasmic domains regulate slow deactivation of Kv11.1 channels

The intracellular domains of many ion channels are important for fine-tuning their gating kinetics. In Kv11.1 channels, the slow kinetics of channel deactivation, which are critical for their function in the heart, are largely regulated by the N-terminal N-Cap and Per-Arnt-Sim (PAS) domains, as well as the C-terminal cyclic nucleotide-binding homology (cNBH) domain. Here, we use mutant cycle analysis to probe for functional interactions between the N-Cap/PAS domains and the cNBH domain. We identified a specific and stable charge-charge interaction between Arg(56) of the PAS domain and Asp(803) of the cNBH domain, as well an additional interaction between the cNBH domain and the N-Cap, both of which are critical for maintaining slow deactivation kinetics. Furthermore, we found that positively charged arginine residues within the disordered region of the N-Cap interact with negatively charged residues of the C-linker domain. Although this interaction is likely more transient than the PAS-cNBD interaction, it is strong enough to stabilize the open conformation of the channel and thus slow deactivation. These findings provide novel insights into the slow deactivation mechanism of Kv11.1 channels.

The Romano-Ward syndrome--1964-2014: 50 years of progress

This year marks the 50th anniversary of publication in the then Journal of the Irish Medical Association of the seminal work by Irish paediatrician Professor Conor Ward entitled 'A new familial Cardiac Syndrome in Children'. The condition soon became known by the eponym Romano-Ward Syndrome and is now recognised as the congenital Long QT Syndrome. Here we review the major developments in the field over the past fifty years, with special mention of the important contributions made by Irish researches.