The hERG potassium channel and hERG screening for drug-induced torsades de pointes

Elevating performance and interpretability of in silico classifiers for drug proarrhythmia risk evaluations using multi-biomarker approach with ranking algorithm

BACKGROUND AND OBJECTIVE

Using electrophysiological simulations and machine learning to predict drug proarrhythmia risk has gained popularity due to its effectiveness. The leading in silico drug assessment system mainly uses a single biomarker (qNet) to predict proarrhythmia risk, offering good performance and straightforward interpretation. Other advanced classifiers incorporating additional physiological biomarkers provide better predictive capabilities but are less intuitive. Thus, a method that accommodates multiple biomarkers while maintaining interpretability is needed.

METHODS

We enhance the current best ordinal logistic regression (OLR) model by adding more physiological biomarkers to overcome its limitations. We also introduce a general torsade metric score (TMS) for multi-biomarker approaches to facilitate easier interpretation. Additionally, a novel ranking algorithm based on a simple multi-criteria decision analysis method is employed to evaluate various classifiers against standard proarrhythmia risk criteria efficiently.

RESULTS

Our proposed method demonstrates that using multiple well-known biomarkers yields better performance than using qNet alone. Some accepted multi-biomarker OLR models do not incorporate qNet yet outperform those that do. Moreover, some ill-performing biomarkers when utilized individually can show improved performance in combination with other biomarkers.

CONCLUSION

The proposed approach offers an effective way of utilizing multiple biomarkers, including well-known ones, providing practical alternatives for proarrhythmia risk assessment. The interpretability of the accepted models is straightforward, thanks to the TMS thresholds for multi-biomarker OLR models that allow direct evaluation of the classification prediction of individual drugs.

Optimizing experimental designs for model selection of ion channel drug-binding mechanisms

The rapid delayed rectifier current carried by the human Ether-à-go-go-Related Gene (hERG) channel is susceptible to drug-induced reduction, which can lead to an increased risk of cardiac arrhythmia. Establishing the mechanism by which a specific drug compound binds to hERG can help reduce uncertainty when quantifying pro-arrhythmic risk. In this study, we introduce a methodology for optimizing experimental voltage protocols to produce data that enable different proposed models for the drug-binding mechanism to be distinguished. We demonstrate the performance of this methodology via a synthetic data study. If the underlying model of hERG current is known exactly, then the optimized protocols generated show noticeable improvements in our ability to select the true model when compared with a simple protocol used in previous studies. However, if the model is not known exactly, and we assume a discrepancy between the data-generating hERG model and the hERG model used in fitting the models, then the optimized protocols become less effective in determining the 'true' binding dynamics. While the introduced methodology shows promise, we must be careful to ensure that, if applied to a real data study, we have a well-calibrated model of hERG current gating.This article is part of the theme issue 'Uncertainty quantification for healthcare and biological systems (Part 1)'.

Identifying multi-target drugs for prostate cancer using machine learning-assisted transcriptomic analysis

Prostate cancer is a leading cause of cancer death in men, and the development of effective treatments is of great importance. This study explored to identify the candidate drugs for prostate cancer by transcriptomic data and CMap database analysis. After integrating the results of omics analysis, bisoprolol is confirmed as a promising drug. Moreover, cell experiment reveals its potential inhibitory effect on the proliferation of prostate cancer cells. Importantly, machine learning methods are employed to predict the targets of bisoprolol, and the dual-target ADRB3 and hERG are explored by dynamic simulation. The findings of this study demonstrate the potential of bisoprolol as a multi-target drug for prostate cancer treatment and the feasibility of using beta-adrenergic receptor inhibitors in prostate cancer treatment. In addition, the proposed research approach is promising for discovering potential drugs for cancer treatment by leveraging the concept of drug side effects leading to anticancer effects. Further research is necessary to investigate the pharmacological action, potential toxicity, and underlying mechanisms of bisoprolol in treating prostate cancer with ADRB3.Communicated by Ramaswamy H. Sarma.

Low Proarrhythmic Risk of Imetelstat, a Novel Oligonucleotide Telomerase Inhibitor: A Translational Analysis

Evaluation of the proarrhythmic potential of imetelstat, a novel oligonucleotide telomerase inhibitor, in nonclinical and clinical studies is presented. In vitro, imetelstat sodium ≤ 750 μg/mL and negative (vehicle) and positive (cisapride) controls were evaluated for hERG channel current inhibition. In vivo, cynomolgus monkeys received a single vehicle control or imetelstat sodium (5 mg/kg [2-h infusion], 10 mg/kg [6-h infusion], or 15 mg/kg [6- or 24-h infusion]); cardiovascular parameters were collected before and after drug administration. A ventricular repolarization substudy of the IMerge phase III study evaluated patients with lower-risk myelodysplastic syndromes administered imetelstat 7.1 mg/kg active dose every 4 weeks; intensive electrocardiograms and pharmacokinetic samples were collected for concentration-QTc and by-time point analyses after a single dose. In vitro, imetelstat did not inhibit the hERG channel (IC50 > 750 μg/mL). In monkeys, imetelstat demonstrated no treatment-related changes in cardiac parameters, including QTc using Fridericia correction (QTcF). In the IMerge QTc substudy, 45 patients received imetelstat (n = 29) or placebo (n = 16). The concentration-QTc relationship was described by a linear mixed-effects model; at the geometric mean maximum plasma concentration (Cmax) for imetelstat 7.1 mg/kg of 89.5 μg/mL, the predicted effect on placebo-corrected change from baseline QTcF was 2.36 ms (90% confidence interval, -3.04 to 7.76), supporting no evidence of QTcF prolongation. By-time point analysis demonstrated no clinically significant effect of imetelstat on QTc. Nonclinical studies demonstrated no proarrhythmic risk at > 140× (in vitro) and > 2.6× (in vivo) imetelstat 7.1 mg/kg Cmax. Clinical evaluations showed no significant effects on QTcF or other electrocardiogram parameters at 7.1 mg/kg. Collectively, this integrated risk assessment supports the low proarrhythmic potential of imetelstat.

hERGBoost: A gradient boosting model for quantitative IC50 prediction of hERG channel blockers

The human ether-a-go-go-related gene (hERG) potassium channel is pivotal in drug discovery due to its susceptibility to blockage by drug candidate molecules, which can cause severe cardiotoxic effects. Consequently, identifying and excluding potential hERG channel blockers at the earliest stages of drug development is crucial. Most traditional machine learning models predict a molecule's cardiotoxicity or non-cardiotoxicity typically at 10 μM, which doesn't account for compounds with low IC50 values that are non-toxic at therapeutic levels due to their high effectiveness at lower concentrations. To address the need for more precise, quantitative predictions, we developed hERGBoost, a cutting-edge machine learning model employing a gradient-boosting algorithm. This model demonstrates superior accuracy in predicting the IC50 of drug candidates. Trained on a specially curated dataset for this study, hERGBoost not only exhibited excellent performance in external validation, achieving an R2 score of 0.394 and a low root mean square error of 0.616 but also significantly outstripped previous models in both qualitative and quantitative assessments. Representing a notable leap forward in the prediction of hERG channel blockers, the hERGBoost model and its datasets are freely available to the drug discovery community on our web server at. http://ssbio.cau.ac.kr/software/hergboost This resource promises to be invaluable in advancing safer pharmaceutical development.

Mechanistic Relevance of Ventricular Arrhythmias in Heart Failure with Preserved Ejection Fraction

Heart failure with preserved ejection fraction (HFpEF) is increasing at an alarming rate worldwide, with limited effective therapeutic interventions in patients. Sudden cardiac death (SCD) and ventricular arrhythmias present substantial risks for the prognosis of these patients. Obesity is a risk factor for HFpEF and life-threatening arrhythmias. Obesity and its associated metabolic dysregulation, leading to metabolic syndrome, are an epidemic that poses a significant public health problem. More than one-third of the world population is overweight or obese, leading to an enhanced risk of incidence and mortality due to cardiovascular disease (CVD). Obesity predisposes patients to atrial fibrillation and ventricular and supraventricular arrhythmias-conditions that are caused by dysfunction in the electrical activity of the heart. To date, current therapeutic options for the cardiomyopathy of obesity are limited, suggesting that there is considerable room for the development of therapeutic interventions with novel mechanisms of action that will help normalize sinus rhythms in obese patients. Emerging candidates for modulation by obesity are cardiac ion channels and Ca-handling proteins. However, the underlying molecular mechanisms of the impact of obesity on these channels and Ca-handling proteins remain incompletely understood. Obesity is marked by the accumulation of adipose tissue, which is associated with a variety of adverse adaptations, including dyslipidemia (or abnormal systemic levels of free fatty acids), increased secretion of proinflammatory cytokines, fibrosis, hyperglycemia, and insulin resistance, which cause electrical remodeling and, thus, predispose patients to arrhythmias. Furthermore, adipose tissue is also associated with the accumulation of subcutaneous and visceral fat, which is marked by distinct signaling mechanisms. Thus, there may also be functional differences in the effects of the regional distribution of fat deposits on ion channel/Ca-handling protein expression. Evaluating alterations in their functional expression in obesity will lead to progress in the knowledge of the mechanisms responsible for obesity-related arrhythmias. These advances are likely to reveal new targets for pharmacological modulation. Understanding how obesity and related mechanisms lead to cardiac electrical remodeling is likely to have a significant medical and economic impact. Nevertheless, substantial knowledge gaps remain regarding HFpEF treatment, requiring further investigations to identify potential therapeutic targets. The objective of this study is to review cardiac ion channel/Ca-handling protein remodeling in the predisposition to metabolic HFpEF and arrhythmias. This review further highlights interleukin-6 (IL-6) as a potential target, cardiac bridging integrator 1 (cBIN1) as a promising gene therapy agent, and leukotriene B4 (LTB4) as an underappreciated pathway in future HFpEF management.

Small Molecule with Big Impact: Metarrestin Targets the Perinucleolar Compartment in Cancer Metastasis

Metarrestin (ML246) is a first-in-class pyrrole-pyrimidine-derived small molecule that selectively targets the perinucleolar compartment (PNC). PNC is a distinct subnuclear structure predominantly found in solid tumor cells. The occurrence of PNC demonstrates a positive correlation with malignancy, serving as an indicator of tumor aggressiveness, progression, and metastasis. Various promising preclinical results have led to the clinical translation of metarrestin into a first-in-human trial. This review aims to summarize (i) the current understanding of the structure and function of PNC and its role in cancer progression and metastasis, (ii) key findings from studies examining the effect of metarrestin on various cancers across the translational spectrum, including in vitro, in vivo, and human clinical trial studies, and (iii) the pharmaceutical relevance of metarrestin as a promising anticancer candidate. Furthermore, our molecular docking and MD simulation studies show that metarrestin binds to eEF1A1 and eEF1A2 with a strong and stable affinity and inhibits eEF1A2 more efficiently compared to eEF1A1. The promising results from preclinical studies suggest that metarrestin has the potential to revolutionize the treatment of cancer, heralding a paradigm shift in its therapeutic management.

Cardiotoxicity evaluation of two-drug fixed-dose combination therapy under CiPA: a computational study

The Comprehensive In Vitro Proarrhythmia Assay (CiPA) evaluates drug-induced torsade de pointes (TdP) risk, with qNet commonly used to classify drugs into low-, intermediate-, and high-risk categories. While most studies focus on single-drug effects, 2-drug fixed-dose combination (FDC) therapy is widely used for cardiovascular disease management. We aimed to develop the CiPA-based methodology to predict adverse effects of FDC therapy. A human ventricular cell model was stimulated under the effects of various drug combinations from twelve well-characterized compounds suggested by CiPA at 1 to 4 maximum plasma concentration, and the qNetavg biomarker as a function of the ratio of two drugs was used to evaluate the TdP risk of combined compounds. Results showed that high-risk and intermediate-risk drug combinations often yielded lower qNetavg than individual drugs, suggesting increased TdP risk. Conversely, combinations involving low-risk drugs tended to reduce TdP risk by raising qNetavg above individual drug levels. Also, we found that the interplay of some major ionic channels caused variations on qNetavg. These findings highlight the importance of evaluating FDC cardiotoxicity to predict risks that may not appear in single-drug analysis.

Stereoselective block of the hERG potassium channel by the Class Ia antiarrhythmic drug disopyramide

Potassium channels encoded by human Ether-à-go-go-Related Gene (hERG) are inhibited by diverse cardiac and non-cardiac drugs. Disopyramide is a chiral Class Ia antiarrhythmic that inhibits hERG at clinical concentrations. This study evaluated effects of disopyramide enantiomers on hERG current (IhERG) from hERG expressing HEK 293 cells at 37 °C. S(+) and R(-) disopyramide inhibited wild-type (WT) IhERG with IC50 values of 3.9 µM and 12.9 µM respectively. The attenuated-inactivation mutant N588K had little effect on the action of S(+) disopyramide but the IC50 for the R(-) enantiomer was ~ 15-fold that for S(+) disopyramide. The enhanced inactivation mutant N588E only slightly increased the potency of R(-) disopyramide. S6 mutation Y652A reduced S(+) disopyramide potency more than that of R(-) disopyramide (respective IC50 values ~ 49-fold and 11-fold their WT controls). The F656A mutation also exerted a stronger effect on S(+) than R(-) disopyramide, albeit with less IC50 elevation. A WT-Y652A tandem dimer exhibited a sensitivity to the enantiomers that was intermediate between that of WT and Y652A, suggesting Y652 groups on adjacent subunits contribute to the binding. Moving the Y (normally at site 652) one residue in the N- terminal (up) direction in N588K hERG markedly increased the blocking potency of R(-) disopyramide. Molecular dynamics simulations using a hERG pore model produced different binding modes for S(+) and R(-) disopyramide consistent with the experimental observations. In conclusion, S(+) disopyramide interacts more strongly with S6 aromatic binding residues on hERG than does R(-) disopyramide, whilst optimal binding of the latter is more reliant on intact inactivation.

Investigating the cardiotoxicity of N-n-butyl haloperidol iodide: Inhibition mechanisms on hERG channels

The human Ether-à-go-go-Related Gene (hERG) encodes a protein responsible for forming the alpha subunit of the IKr channel, which plays a crucial role in cardiac repolarization. The proper functioning of hERG channels is paramount in maintaining a normal cardiac rhythm. Inhibition of these channels can result in the prolongation of the QT interval and potentially life-threatening arrhythmias. Cardiotoxicity is a primary concern in the field of drug development. N-n-Butyl haloperidol iodide (F2), a derivative of haloperidol, has been investigated for its therapeutic potential. However, the impact of this compound on cardiac toxicity, specifically on hERG channels, remains uncertain. This study employs computational and experimental methodologies to examine the inhibitory mechanisms of F2 on hERG channels. Molecular docking and molecular dynamics simulations commonly used techniques in computational biology to predict protein-ligand complexes' binding interactions and stability. In the context of the F2-hERG complex, these methods can provide valuable insights into the potential binding modes and strength of interaction between F2 and the hERG protein. On the other hand, electrophysiological assays are experimental techniques used to characterize the extent and nature of hERG channel inhibition caused by various compounds. By measuring the electrical activity of the hERG channel in response to different stimuli, these assays can provide important information about the functional effects of ligand binding to the channel. The study's key findings indicate that F2 interacts with the hERG channel by forming hydrogen bonding, π-cation interactions, and hydrophobic forces. This interaction leads to the inhibition of hERG currents in a concentration-dependent manner, with an IC50 of 3.75 μM. The results presented in this study demonstrate the potential cardiotoxicity of F2 and underscore the significance of considering hERG channel interactions during its clinical development. This study aims to provide comprehensive insights into the interaction between F2 and hERG, which will may guid us in the safe use of F2 and in the development of new derivatives with high efficiency while low toxicity.

STAT4 Mediates IL-6 Trans-Signaling Arrhythmias in High Fat Diet Guinea Pig Heart

Obesity is a major risk factor for the development of life-threatening malignant ventricular tachyarrhythmias (VT) and sudden cardiac death (SCD). Risks may be highest for patients with high levels of the proinflammatory cytokine interleukin (IL)-6. We used our guinea pig model of high-fat diet (HFD)-induced arrhythmias that exhibit a heightened proinflammatory-like pathology, which is also observed in human obesity arrhythmias, as well as immunofluorescence and confocal microscopy approaches to evaluate the pathological IL-6 trans-signaling function and explore the underlying mechanisms. Using blind-stick and electrocardiogram (ECG) techniques, we tested the hypothesis that heightened IL-6 trans-signaling would exhibit increased ventricular arrhythmia/SCD incidence and underlying arrhythmia substrates. Remarkably, compared to low-fat diet (LFD)-fed controls, HFD promoted phosphorylation of the IL-6 signal transducer and activator of transcription 4 (STAT4), leading to its activation and enhanced nuclear translocation of pSTAT4/STAT4 compared to LFD controls and pSTAT3/STAT3 nuclear expression. Overactivation of IL-6 trans-signaling in guinea pigs prolonged the QT interval, which resulted in greater susceptibility to arrhythmias/SCD with isoproterenol challenge, as also observed with the downstream Janus kinase (JAK) 2 activator. These findings may have potentially profound implications for more effective arrhythmia therapy in the vulnerable obese patient population.

Short-term azithromycin use is associated with QTc interval prolongation in children with cystic fibrosis

BACKGROUND

Azithromycin is used for children with cystic fibrosis (CF) for its immunomodulatory and anti-inflammatory action. This study investigated the short-term alterations in QTc interval associated with azithromycin prophylaxis in pediatric patients with CF.

METHODS

This study included 121 patients with mild CF, of whom 76 received azithromycin (patient group) and 45 did not receive azithromycin (control group). The patient and control groups were categorized according to age as under 12 years of age and over 12 years of age. The first presentation measured all the patient and control groups at basic QTc time intervals. The QTc intervals of all patients were then remeasured systemically at 1, 3, and 6 months. Age categories and QTc intervals that were calculated at each month in the patient and control groups were compared statistically.

RESULTS

A statistically significant difference was detected in the patient group between the initial QTc interval time and the electrocardiogram (ECG) findings in the first and third months after prophylaxis treatment (p < 0.001; p = 0.01). However, no statistically significant difference was detected in the sixth month (p > 0.05) in all groups. Almost all of the children's QTc intervals were within normal range and within the safety zone (under 0.44 s). No statistically significant difference was detected in the control group between the initial ECG and the QTc intervals measured at 1, 3, and 6 months.

CONCLUSION

Short-term use of azithromycin prophylaxis in pediatric patients with mild CF slightly increased the QTc interval in the first and third months of follow-up. Nevertheless, all QTc interval changes fell within the safety zone. Notably, 1 month of follow-up treatment should be performed to check for any alteration in the QTc interval. If increased QTc interval duration is not detected in the first month, azithromycin prophylaxis can be safely prescribed.

Non-invasive hERG channel screening based on electrical impedance tomography and extracellular voltage activation (EIT-EVA)

hERG channel screening has been achieved based on electrical impedance tomography and extracellular voltage activation (EIT-EVA) to improve the non-invasive aspect of drug discovery. EIT-EVA screens hERG channels by considering the change in extracellular ion concentration which modifies the extracellular resistance in cell suspension. The rate of ion passing in cell suspension is calculated from the extracellular resistance Rex, which is obtained from the EIT measurement at a frequency of 500 kHz. In the experiment, non-invasive screening is applied by a novel integrated EIT-EVA printed circuit board (PCB) sensor to human embryonic kidney (HEK) 293 cells transfected with the human ether-a-go-go-related gene (hERG) ion channel, while the E-4031 antiarrhythmic drug is used for hERG channel inhibition. The extracellular resistance Rex of the HEK 293 cells suspension is measured by EIT as the hERG channels are activated by EVA over time. The Rex is reconstructed into extracellular conductivity distribution change Δσ to reflect the extracellular K+ ion concentration change Δc resulting from the activated hERG channel. Δc is increased rapidly during the hERG channel non-inhibition state while Δc is increased slower with increasing drug concentration cd. In order to evaluate the EIT-EVA system, the inhibitory ratio index (IR) was calculated based on the rate of Δc over time. Half-maximal inhibitory concentration (IC50) of 2.7 nM is obtained from the cd and IR dose-response relationship. The IR from EIT-EVA is compared with the results from the patch-clamp method, which gives R2 of 0.85. In conclusion, EIT-EVA is successfully applied to non-invasive hERG channel screening.

Optimization of a cardiomyocyte model illuminates role of increased INa,L in repolarization reserve

Cardiac ion currents may compensate for each other when one is compromised by a congenital or drug-induced defect. Such redundancy contributes to a robust repolarization reserve that can prevent the development of lethal arrhythmias. Most efforts made to describe this phenomenon have quantified contributions by individual ion currents. However, it is important to understand the interplay between all major ion-channel conductances, as repolarization reserve is dependent on the balance between all ion currents in a cardiomyocyte. Here, a genetic algorithm was designed to derive profiles of nine ion-channel conductances that optimize repolarization reserve in a mathematical cardiomyocyte model. Repolarization reserve was quantified using a previously defined metric, repolarization reserve current, i.e., the minimum constant current to prevent normal action potential repolarization in a cell. The optimization improved repolarization reserve current up to 84% compared to baseline in a human adult ventricular myocyte model and increased resistance to arrhythmogenic insult. The optimized conductance profiles were not only characterized by increased repolarizing current conductances but also uncovered a previously unreported behavior by the late sodium current. Simulations demonstrated that upregulated late sodium increased action potential duration, without compromising repolarization reserve current. The finding was generalized to multiple models. Ultimately, this computational approach, in which multiple currents were studied simultaneously, illuminated mechanistic insights into how the metric's magnitude could be increased and allowed for the unexpected role of late sodium to be elucidated.NEW & NOTEWORTHY Genetic algorithms are typically used to fit models or extract desired parameters from data. Here, we use the tool to produce a ventricular cardiomyocyte model with increased repolarization reserve. Since arrhythmia mitigation is dependent on multiple cardiac ion-channel conductances, study using a comprehensive, unbiased, and systems-level approach is important. The use of this optimization strategy allowed us to find robust profiles that illuminated unexpected mechanistic determinants of key ion-channel conductances in repolarization reserve.

Recording ten-fold larger IKr conductances with automated patch clamping using equimolar Cs+ solutions

Background: The rapid delayed rectifier potassium current (IKr) is important for cardiac repolarization and is most often involved in drug-induced arrhythmias. However, accurately measuring this current can be challenging in human-induced pluripotent stem cell (hiPSC)-derived cardiomyocytes because of its small current density. Interestingly, the ion channel conducting IKr, hERG channel, is not only permeable to K+ ions but also to Cs+ ions when present in equimolar concentrations inside and outside of the cell. Methods: In this study, IhERG was measured from Chinese hamster ovary (CHO)-hERG cells and hiPSC-CM using either Cs+ or K+ as the charge carrier. Equimolar Cs+ has been used in the literature in manual patch-clamp experiments, and here, we apply this approach using automated patch-clamp systems. Four different (pre)clinical drugs were tested to compare their effects on Cs+- and K+-based currents. Results: Using equimolar Cs+ solutions gave rise to approximately ten-fold larger hERG conductances. Comparison of Cs+- and K+-mediated currents upon application of dofetilide, desipramine, moxifloxacin, or LUF7244 revealed many similarities in inhibition or activation properties of the drugs studied. Using equimolar Cs+ solutions gave rise to approximately ten-fold larger hERG conductances. In hiPSC-CM, the Cs+-based conductance is larger compared to the known K+-based conductance, and the Cs+ hERG conductance can be inhibited similarly to the K+-based conductance. Conclusion: Using equimolar Cs+ instead of K+ for IhERG measurements in an automated patch-clamp system gives rise to a new method by which, for example, quick scans can be performed on effects of drugs on hERG currents. This application is specifically relevant when such experiments are performed using cells which express small IKr current densities in combination with small membrane capacitances.

Optimization of Pharmacokinetic and In Vitro Safety Profile of a Series of Pyridine Diamide Indirect AMPK Activators

A set of focused analogues have been generated around a lead indirect adenosine monophosphate-activated kinase (AMPK) activator to improve the rat clearance of the molecule. Analogues were focused on inhibiting amide hydrolysis by the strategic placement of substituents that increased the steric environment about the secondary amide bond between 4-aminopiperidine and pyridine-5-carboxylic acid. It was found that placing substituents at position 3 of the piperidine ring and position 4 of the pyridine could all improve clearance without significantly impacting on-target potency. Notably, trans-3-fluoropiperidine 32 reduced rat clearance from above liver blood flow to 19 mL/min/kg and improved the hERG profile by attenuating the basicity of the piperidine moiety. Oral dosing of 32 activated AMPK in mouse liver and after 2 weeks of dosing improved glucose handling in a db/db mouse model of Type II diabetes as well as lowering fasted glucose and insulin levels.

Tricyclic hydrocarbon fluorene attenuates ventricular ionic currents and pressure development in the navaga cod

The release of polycyclic aromatic hydrocarbons (PAHs) into the environment due to oil and diesel fuel spills is a serious threat to Arctic fish populations. PAHs produce multiple toxic effects in fish, but disturbance of electrical and contractile activity of the heart seems to be the most negative effect. Our study focused on the effects of fluorene, a tricyclic PAH resembling the well-investigated tricyclic phenanthrene, on major ionic currents and action potential (AP) waveform in isolated ventricular myocytes and on contractile activity in isolated whole hearts of polar navaga cod (Eleginus nawaga). Among the studied currents, the repolarizing rapid delayed rectifier K+ current IKr demonstrated the highest sensitivity to fluorene with IC50 of 0.54 μM. The depolarizing inward currents, INa and ICaL, were inhibited with 10 μM fluorene by 20.2 ± 2.8 % and 27.9 ± 8.4 %, respectively, thereby being much less sensitive to fluorene than IKr. Inward rectifier IK1 current was insensitive to fluorene (up to 10 μM). While 3 μM fluorene prolonged APs, 10 μM also slowed the AP upstroke. Resting membrane potential was not affected by any tested concentrations. In isolated heart experiments 10 μM fluorene caused modest depression of ventricular contractile activity. Thus, we have demonstrated that fluorene, a tricyclic PAH present in high quantities in crude oil, strongly impacts electrical activity with only slight effects on contractile activity in the heart of the polar fish, the navaga cod.

hERG agonists pose challenges to web-based machine learning methods for prediction of drug-hERG channel interaction

Pharmacological blockade of the IKr channel (hERG) by diverse drugs in clinical use is associated with the Long QT Syndrome that can lead to life threatening arrhythmia. Various computational tools including machine learning models (MLM) for the prediction of hERG inhibition have been developed to facilitate the throughput screening of drugs in development and optimise thus the prediction of hERG liabilities. The use of MLM relies on large libraries of training compounds for the quantitative structure-activity relationship (QSAR) modelling of hERG inhibition. The focus on inhibition omits potential effects of hERG channel agonist molecules and their associated QT shortening risk. It is instructive, therefore, to consider how known hERG agonists are handled by MLM. Here, two highly developed online computational tools for the prediction of hERG liability, Pred-hERG and HergSPred were probed for their ability to detect hERG activator drug molecules as hERG interactors. In total, 73 hERG blockers were tested with both computational tools giving overall good predictions for hERG blockers with reported IC50s below Pred-hERG and HergSPred cut-off threshold for hERG inhibition. However, for compounds with reported IC50s above this threshold such as disopyramide or sotalol discrepancies were observed. HergSPred identified all 20 hERG agonists selected as interacting with the hERG channel. Further studies are warranted to improve online MLM prediction of hERG related cardiotoxicity, by explicitly taking into account channel agonism as well as inhibition.

Prolonged Exposure to Remdesivir Inhibits the Human Ether-A-Go-Go-Related Gene Potassium Current

ABSTRACT

Remdesivir, approved for the treatment of COVID-19, has been associated with heart-rate corrected QT interval (QTc) prolongation and torsade de pointes in case reports. However, data are conflicting regarding the ability of remdesivir to inhibit the human ether-a-go-go-related gene (hERG) -related current. The objective of this study was to investigate the effects remdesivir and its primary metabolite, GS-441524, on hERG-related currents. Human embryonic kidney 293 cells stably expressing hERG were treated with various concentrations of remdesivir and GS-441524. The effects of acute and prolonged exposure on hERG-related current were assessed using whole-cell configuration of voltage-clamp protocols. Acute exposure to remdesivir and GS-441524 had no effect on hERG currents and the half-activation voltage (V 1/2 ). Prolonged treatment with 100 nM and 1 µM remdesivir significantly reduced peak tail currents and hERG current density. The propensity for remdesivir to prolong QTc intervals and induce torsade de pointes in predisposed patients warrants further investigation.

The Strength of hERG Inhibition by Erythromycin at Different Temperatures Might Be Due to Its Interacting Features with the Channels

Erythromycin is one of the few compounds that remarkably increase ether-a-go-go-related gene (hERG) inhibition from room temperature (RT) to physiological temperature (PT). Understanding how erythromycin inhibits the hERG could help us to decide which compounds are needed for further studies. The whole-cell patch clamp technique was used to investigate the effects of erythromycin on hERG channels at different temperatures. While erythromycin caused a concentration-dependent inhibition of cardiac hERG channels, it also shifted the steady-state activation and steady-state inactivation of the channel to the left and significantly accelerated the onset of inactivation at both temperatures, although temperature itself caused a profound change in the dynamics of hERG channels. Our data also suggest that the binding pattern to S6 of the channels changes at PT. In contrast, cisapride, a well-known hERG blocker whose inhibition is not affected by temperature, does not change its critical binding sites after the temperature is raised to PT. Our data suggest that erythromycin is unique and that the shift in hERG inhibition may not apply to other compounds.

Automated Patch-Clamp and Induced Pluripotent Stem Cell-Derived Cardiomyocytes: A Synergistic Approach in the Study of Brugada Syndrome

The development of high-throughput automated patch-clamp technology is a recent breakthrough in the field of Brugada syndrome research. Brugada syndrome is a heart disorder marked by abnormal electrocardiographic readings and an elevated risk of sudden cardiac death due to arrhythmias. Various experimental models, developed either in animals, cell lines, human tissue or computational simulation, play a crucial role in advancing our understanding of this condition, and developing effective treatments. In the perspective of the pathophysiological role of ion channels and their pharmacology, automated patch-clamp involves a robotic system that enables the simultaneous recording of electrical activity from multiple single cells at once, greatly improving the speed and efficiency of data collection. By combining this approach with the use of patient-derived cardiomyocytes, researchers are gaining a more comprehensive view of the underlying mechanisms of heart disease. This has led to the development of more effective treatments for those affected by cardiovascular conditions.

In silico assessment on TdP risks of drug combinations under CiPA paradigm

Researchers have recently proposed the Comprehensive In-vitro Proarrhythmia Assay (CiPA) to analyze medicines' TdP risks. Using the TdP metric known as qNet, numerous single-drug effects have been studied to classify the medications as low, intermediate, and high-risk. Furthermore, multiple medication therapies are recognized as a potential method for curing patients, mainly when limited drugs are available. This work expands the TdP risk assessment of drugs by introducing a CiPA-based in silico analysis of the TdP risk of combined drugs. The cardiac cell model was simulated using the population of models approach incorporating drug-drug interactions (DDIs) models on several ion channels for various drug pairs. Action potential duration (APD90), qNet, and calcium duration (CaD90) were computed and analyzed as biomarker features. The drug combination maps were also used to illustrate combined medicines' TdP risk. We found that the combined drugs alter cell responses in terms of biomarkers such as APD90, qNet, and CaD90 in a highly nonlinear manner. The results also revealed that combinations of high-risk with low-risk and intermediate-risk with low-risk drugs could result in compounds with varying TdP risks depending on the drug concentrations.

Modeling Heart Diseases on a Chip: Advantages and Future Opportunities

Heart disease is a significant burden on global health care systems and is a leading cause of death each year. To improve our understanding of heart disease, high quality disease models are needed. These will facilitate the discovery and development of new treatments for heart disease. Traditionally, researchers have relied on 2D monolayer systems or animal models of heart disease to elucidate pathophysiology and drug responses. Heart-on-a-chip (HOC) technology is an emerging field where cardiomyocytes among other cell types in the heart can be used to generate functional, beating cardiac microtissues that recapitulate many features of the human heart. HOC models are showing great promise as disease modeling platforms and are poised to serve as important tools in the drug development pipeline. By leveraging advances in human pluripotent stem cell-derived cardiomyocyte biology and microfabrication technology, diseased HOCs are highly tuneable and can be generated via different approaches such as: using cells with defined genetic backgrounds (patient-derived cells), adding small molecules, modifying the cells' environment, altering cell ratio/composition of microtissues, among others. HOCs have been used to faithfully model aspects of arrhythmia, fibrosis, infection, cardiomyopathies, and ischemia, to name a few. In this review, we highlight recent advances in disease modeling using HOC systems, describing instances where these models outperformed other models in terms of reproducing disease phenotypes and/or led to drug development.

Automatic modeling of dynamic drug-hERG channel interactions using three voltage protocols and machine learning techniques: A simulation study

BACKGROUND

Assessment of drug cardiac safety is critical in the development of new compounds and is commonly addressed by evaluating the half-maximal blocking concentration of the potassium human ether-à-go-go related gene (hERG) channels. However, recent works have evidenced that the modelling of drug-binding dynamics to hERG can help to improve early cardiac safety assessment. Our goal is to develop a methodology to automatically generate Markovian models of the drug-hERG channel interactions.

METHODS

The training and the test sets consisted of 20800 and 5200 virtual drugs, respectively, distributed into 104 groups with different affinities and kinetics to the conformational states of the channel. In our system, drugs may bind to any state (individually or simultaneously), with different degrees of preference for a conformational state and the change of the conformational state of the drug bound channels may be restricted or allowed. To model such a wide range of possibilities, 12 Markovian chains are considered. Our approach uses the response of the drugs to our three previously developed voltage clamp protocols, which enhance the differences in the probabilities of occupying a certain conformational state of the channel (open, closed and inactivated). The computing tool is comprised of a classifier and a parameter optimizer and uses linear interpolation, support vector machines and a simplex method for function minimization.

RESULTS

We propose a novel methodology that automatically generates dynamic drug models using Markov model formulations and that elucidates the states where the drug binds and unbinds and the preferential binding state using data obtained from simple voltage clamp protocols that captures the preferential state-dependent binding properties, the relative affinities, trapping and non-trapping dynamics and the onset of I_Kr block. Overall, the tool correctly predicted the class of 92.04% of the drugs and the model provided by the tool accurately fitted the response of the target compound, the mean accuracy being 97.53%. Moreover, generation of the dynamic model of an I_Kr blocker from its response to our voltage clamp protocols usually takes less than an hour on a common desktop computer.

CONCLUSION

Our methodology could be very useful to model and simulate dynamic drug-hERG channel interactions. It would contribute to the improvement of the preclinical assessment of the proarrhythmic risk of drugs that inhibit I_Kr and the efficacy of antiarrhythmic I_Kr blockers.

An in silico-in vitro pipeline for drug cardiotoxicity screening identifies ionic pro-arrhythmia mechanisms

BACKGROUND AND PURPOSE

Before advancing to clinical trials, new drugs are screened for their pro-arrhythmic potential using a method that is overly conservative and provides limited mechanistic insight. The shortcomings of this approach can lead to the mis-classification of beneficial drugs as pro-arrhythmic.

EXPERIMENTAL APPROACH

An in silico-in vitro pipeline was developed to circumvent these shortcomings. A computational human induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) model was used as part of a genetic algorithm to design experiments, specifically electrophysiological voltage clamp (VC) protocols, to identify which of several cardiac ion channels were blocked during in vitro drug studies. Such VC data, along with dynamically clamped action potentials (AP), were acquired from iPSC-CMs before and after treatment with a control solution or a low- (verapamil), intermediate- (cisapride or quinine) or high-risk (quinidine) drug.

KEY RESULTS

Significant AP prolongation (a pro-arrhythmia marker) was seen in response to quinidine and quinine. The VC protocol identified block of IKr (a source of arrhythmias) by all strong IKr blockers, including cisapride, quinidine and quinine. The protocol also detected block of ICaL by verapamil and Ito by quinidine. Further demonstrating the power of the approach, the VC data uncovered a previously unidentified If block by quinine, which was confirmed with experiments using a HEK-293 expression system and automated patch-clamp.

CONCLUSION AND IMPLICATIONS

We developed an in silico-in vitro pipeline that simultaneously identifies pro-arrhythmia risk and mechanism of ion channel-blocking drugs. The approach offers a new tool for evaluating cardiotoxicity during preclinical drug screening.

Structural modeling of the hERG potassium channel and associated drug interactions

The voltage-gated potassium channel, KV11.1, encoded by the human Ether-à-go-go-Related Gene (hERG), is expressed in cardiac myocytes, where it is crucial for the membrane repolarization of the action potential. Gating of the hERG channel is characterized by rapid, voltage-dependent, C-type inactivation, which blocks ion conduction and is suggested to involve constriction of the selectivity filter. Mutations S620T and S641A/T within the selectivity filter region of hERG have been shown to alter the voltage dependence of channel inactivation. Because hERG channel blockade is implicated in drug-induced arrhythmias associated with both the open and inactivated states, we used Rosetta to simulate the effects of hERG S620T and S641A/T mutations to elucidate conformational changes associated with hERG channel inactivation and differences in drug binding between the two states. Rosetta modeling of the S641A fast-inactivating mutation revealed a lateral shift of the F627 side chain in the selectivity filter into the central channel axis along the ion conduction pathway and the formation of four lateral fenestrations in the pore. Rosetta modeling of the non-inactivating mutations S620T and S641T suggested a potential molecular mechanism preventing F627 side chain from shifting into the ion conduction pathway during the proposed inactivation process. Furthermore, we used Rosetta docking to explore the binding mechanism of highly selective and potent hERG blockers - dofetilide, terfenadine, and E4031. Our structural modeling correlates well with much, but not all, existing experimental evidence involving interactions of hERG blockers with key residues in hERG pore and reveals potential molecular mechanisms of ligand interactions with hERG in an inactivated state.

Pharmacological activation of the hERG K+ channel for the management of the long QT syndrome: A review

In the human heart, the rapid delayed rectifier K+ current (I Kr) contributes significantly to ventricular action potential (AP) repolarization and to set the duration of the QT interval of the surface electrocardiogram (ECG). The pore-forming (α) subunit of the I Kr channel is encoded by KCNH2 or human ether-à-go-go-related gene 1 (hERG1). Impairment of hERG function through either gene mutation (congenital) or pharmacological blockade by diverse drugs in clinical use (acquired) can cause a prolongation of the AP duration (APD) reflected onto the surface ECG as a prolonged QT interval or Long QT Syndrome (LQTS). LQTS can increase the risk of triggered activity of ventricular cardiomyocytes and associated life-threatening arrhythmia. Current treatments all focus on reducing the incidence of arrhythmia or terminating it after its onset but there is to date no prophylactic treatment for the pharmacological management of LQTS. A new class of hERG modulators (agonists) have been suggested through direct interaction with the hERG channel to shorten the action potential duration (APD) and/or increase the postrepolarisation refractoriness period (PRRP) of ventricular cardiomyocytes protecting thereby against triggered activity and associated arrhythmia. Although promising drug candidates, there remain major obstacles to their clinical development. The aim of this review is to summarize the latest advances as well as the limitations of this proposed pharmacotherapy.

The utility of hERG channel inhibition data in the derivation of occupational exposure limits

Inhibition of the human ether-à-go-go (hERG) channel may lead to QT prolongation and fatal arrhythmia. While pharmaceutical drug candidates that exhibit potent hERG channel inhibition often fail early in development, many drugs with both cardiac and non-cardiac indications proceed to market. In this study, the relationship between in vitro hERG channel inhibition and published occupational exposure limit (OEL) was evaluated. A total of 23 cardiac drugs and 44 drugs with non-cardiac indications with published hERG channel IC₅₀ and published OELs were identified. There was an apparent relationship between hERG IC₅₀ potency and the OEL for cardiac and non-cardiac drugs. Twenty cardiac and non-cardiac drugs were identified that had a potent hERG IC₅₀ (≤25 μM) and a contrastingly large OEL value (≥100 μg/m³). OELs or hazard banding corresponding to ≤100 μg/m³ should be sufficiently protective of effects following occupational exposure to the majority of APIs with hERG IC₅₀ values ≤ 100 μM. It is important to consider hERG IC₅₀ values and possible cardiac effects when deriving OEL values for drugs, regardless of indication. These considerations may be particularly important early in the drug development process for establishing exposure control bands for drugs that do not yet have full clinical safety data.

Corticotropin releasing hormone receptor 2 antagonist, RQ-00490721, for the prevention of pressure overload-induced cardiac dysfunction

BACKGROUND

G protein-coupled receptors (GPCRs) regulate the pathological and physiological functions of the heart. GPCR antagonists are widely used in the treatment of chronic heart failure. Despite therapeutic advances in the treatments for cardiovascular diseases, heart failure is a major clinical health problem, with significant mortality and morbidity. Corticotropin releasing hormone receptor 2 (CRHR2) is highly expressed in cardiomyocytes, and cardiomyocyte-specific deletion of the genes encoding CRHR2 suppresses pressure overload-induced cardiac dysfunction. This suggests that the negative modulation of CRHR2 may prevent the progression of heart failure. However, there are no systemic drugs against CRHR2.

FINDINGS

We developed a novel, oral, small molecule antagonist of CRHR2, RQ-00490721, to investigate the inhibition of CRHR2 as a potential therapeutic approach for the treatment of heart failure. In vitro, RQ-00490721 decreased CRHR2 agonist-induced 3', 5'-cyclic adenosine monophosphate (cAMP) production. In vivo, RQ-00490721 showed sufficient oral absorption and better distribution to peripheral organs than to the central nervous system. Oral administration of RQ-00490721 inhibited the CRHR2 agonist-induced phosphorylation of cAMP-response element binding protein (CREB) in the heart, which regulates a transcription activator involved in heart failure. RQ-00490721 administration was not found to affect basal heart function in mice but protected them from pressure overload-induced cardiac dysfunction.

INTERPRETATION

Our results suggest that RQ-00490721 is a promising agent for use in the treatment of chronic heart failure.

Inhibition of the hERG potassium channel by phenanthrene: a polycyclic aromatic hydrocarbon pollutant

The lipophilic polycyclic aromatic hydrocarbon (PAH) phenanthrene is relatively abundant in polluted air and water and can access and accumulate in human tissue. Phenanthrene has been reported to interact with cardiac ion channels in several fish species. This study was undertaken to investigate the ability of phenanthrene to interact with hERG (human Ether-à-go-go-Related Gene) encoded Kv11.1 K+ channels, which play a central role in human ventricular repolarization. Pharmacological inhibition of hERG can be proarrhythmic. Whole-cell patch clamp recordings of hERG current (IhERG) were made from HEK293 cells expressing wild-type (WT) and mutant hERG channels. WT IhERG1a was inhibited by phenanthrene with an IC50 of 17.6 ± 1.7 µM, whilst IhERG1a/1b exhibited an IC50 of 1.8 ± 0.3 µM. WT IhERG block showed marked voltage and time dependence, indicative of dependence of inhibition on channel gating. The inhibitory effect of phenanthrene was markedly impaired by the attenuated inactivation N588K mutation. Remarkably, mutations of S6 domain aromatic amino acids (Y652, F656) in the canonical drug binding site did not impair the inhibitory action of phenanthrene; the Y652A mutation augmented IhERG block. In contrast, the F557L (S5) and M651A (S6) mutations impaired the ability of phenanthrene to inhibit IhERG, as did the S624A mutation below the selectivity filter region. Computational docking using a cryo-EM derived hERG structure supported the mutagenesis data. Thus, phenanthrene acts as an inhibitor of the hERG K+ channel by directly interacting with the channel, binding to a distinct site in the channel pore domain.

Proteome-Informed Machine Learning Studies of Cocaine Addiction

No anti-cocaine addiction drugs have been approved by the Food and Drug Administration despite decades of effort. The main challenge is the intricate molecular mechanisms of cocaine addiction, involving synergistic interactions among proteins upstream and downstream of the dopamine transporter. However, it is difficult to study so many proteins with traditional experiments, highlighting the need for innovative strategies in the field. We propose a proteome-informed machine learning (ML) platform for discovering nearly optimal anti-cocaine addiction lead compounds. We analyze proteomic protein-protein interaction networks for cocaine dependence to identify 141 involved drug targets and build 32 ML models for cross-target analysis of more than 60,000 drug candidates or experimental drugs for side effects and repurposing potentials. We further predict their ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties. Our platform reveals that essentially all of the existing drug candidates fail in our cross-target and ADMET screenings but identifies several nearly optimal leads for further optimization.

TSSF-hERG: A machine-learning-based hERG potassium channel-specific scoring function for chemical cardiotoxicity prediction

The human ether-à-go-go-related gene (hERG) encodes the Kv11.1 voltage-gated potassium ion (K⁺) channel that conducts the rapidly activating delayed rectifier current (I_Kr) in cardiomyocytes to regulate the repolarization process. Some drugs, as blockers of hERG potassium channels, cannot be marketed due to prolonged QT intervals, as well known as cardiotoxicity. Predetermining the binding affinity values between drugs and hERG through in silico methods can greatly reduce the time and cost required for experimental verification. In this study, we collected 9,215 compounds with AutoDock Vina's docking structures as training set, and collected compounds from four references as test sets. A series of models for predicting the binding affinities of hERG blockers were built based on five machine learning algorithms and combinations of interaction features and ligand features. The model built by support vector regression (SVR) using the combination of all features achieved the best performance on both tenfold cross-validation and external verification, which was selected and named as TSSF-hERG (target-specific scoring function for hERG). TSSF-hERG is more accurate than the classic scoring function of AutoDock Vina and the machine-learning-based generic scoring function RF-Score, with a Pearson's correlation coefficient (Rp) of 0.765, a Spearman's rank correlation coefficient (Rs) of 0.757, a root-mean-square error (RMSE) of 0.585 in a tenfold cross-validation study. All results demonstrated that TSSF-hERG would be useful for improving the power of binding affinity prediction between hERG and compounds, which can be further used for prediction or virtual screening of the hERG-related cardiotoxicity of drug candidates.

Ginsenoside Rg3 Alleviates Antithyroid Cancer Drug Vandetanib-Induced QT Interval Prolongation

Inhibition of human ether-a-go-go-related gene (hERG) potassium channel is responsible for acquired long QT syndromes, which leads to life-threatening cardiac arrhythmia. A multikinase inhibitor, vandetanib, prolongs the progression-free survival time in advanced medullary thyroid cancer. However, vandetanib has been reported to induce significant QT interval prolongation, which limits its clinical application. Some studies have showed that ginsenoside Rg3 decelerated hERG K(+) channel tail current deactivation. Therefore, in this study, we aim to confirm whether ginsenoside Rg3 targeting hERG K(+) channel could be used to reverse the vandetanib-induced QT interval prolongation. Electrocardiogram (ECG) and monophasic action potential (MAP) were recorded using electrophysiology signal sampling and analysis system in Langendorff-perfused rabbit hearts. The current clamp mode of the patch-clamp technique was used to record transmembrane action potential. The whole-cell patch-clamp technique was used to record the hERG K+ current. In Langendorff-perfused hearts, vandetanib prolonged the QT interval in a concentration-dependent manner with an IC50 of 1.96 μmol/L. In human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs), vandetanib significantly prolonged the action potential duration at 50%, 70%, and 90% repolarization (APD50, APD70, and APD90). In stable transfected human hERG gene HEK293 cells, vandetanib caused concentrate-dependent inhibition in the step and tail currents of hERG. As expected, ginsenoside Rg3 relieved vandetanib-induced QT interval prolongation in Langendorff-perfused heart and reversed vandetanib-induced APD prolongation in hiPSC-CMs. Furthermore, ginsenoside Rg3 alleviated vandetanib-induced hERG current inhibition and accelerated the process of the channel activation. Ginsenoside Rg3 may be a promising cardioprotective agent against vandetanib-induced QT interval prolongation through targeting hERG channel. These novel findings highlight the therapeutic potential of ginsenoside to prevent vandetanib-induced cardiac arrhythmia.

Ventricular voltage-gated ion channels: Detection, characteristics, mechanisms, and drug safety evaluation

Cardiac voltage-gated ion channels (VGICs) play critical roles in mediating cardiac electrophysiological signals, such as action potentials, to maintain normal heart excitability and contraction. Inherited or acquired alterations in the structure, expression, or function of VGICs, as well as VGIC-related side effects of pharmaceutical drug delivery can result in abnormal cellular electrophysiological processes that induce life-threatening cardiac arrhythmias or even sudden cardiac death. Hence, to reduce possible heart-related risks, VGICs must be acknowledged as important targets in drug discovery and safety studies related to cardiac disease. In this review, we first summarize the development and application of electrophysiological techniques that are employed in cardiac VGIC studies alone or in combination with other techniques such as cryoelectron microscopy, optical imaging and optogenetics. Subsequently, we describe the characteristics, structure, mechanisms, and functions of various well-studied VGICs in ventricular myocytes and analyze their roles in and contributions to both physiological cardiac excitability and inherited cardiac diseases. Finally, we address the implications of the structure and function of ventricular VGICs for drug safety evaluation. In summary, multidisciplinary studies on VGICs help researchers discover potential targets of VGICs and novel VGICs in heart, enrich their knowledge of the properties and functions, determine the operation mechanisms of pathological VGICs, and introduce groundbreaking trends in drug therapy strategies, and drug safety evaluation.

Toward Reducing hERG Affinities for DAT Inhibitors with a Combined Machine Learning and Molecular Modeling Approach

Psychostimulant drugs, such as cocaine, inhibit dopamine reuptake via blockading the dopamine transporter (DAT), which is the primary mechanism underpinning their abuse. Atypical DAT inhibitors are dissimilar to cocaine and can block cocaine- or methamphetamine-induced behaviors, supporting their development as part of a treatment regimen for psychostimulant use disorders. When developing these atypical DAT inhibitors as medications, it is necessary to avoid off-target binding that can produce unwanted side effects or toxicities. In particular, the blockade of a potassium channel, human ether-a-go-go (hERG), can lead to potentially lethal ventricular tachycardia. In this study, we established a counter screening platform for DAT and against hERG binding by combining machine learning-based quantitative structure-activity relationship (QSAR) modeling, experimental validation, and molecular modeling and simulations. Our results show that the available data are adequate to establish robust QSAR models, as validated by chemical synthesis and pharmacological evaluation of a validation set of DAT inhibitors. Furthermore, the QSAR models based on subsets of the data according to experimental approaches used have predictive power as well, which opens the door to target specific functional states of a protein. Complementarily, our molecular modeling and simulations identified the structural elements responsible for a pair of DAT inhibitors having opposite binding affinity trends at DAT and hERG, which can be leveraged for rational optimization of lead atypical DAT inhibitors with desired pharmacological properties.

Prediction of potential drug interactions between repurposed COVID-19 and antitubercular drugs: an integrational approach of drug information software and computational techniques data

Introduction:

Tuberculosis is a major respiratory disease globally with a higher prevalence in Asian and African countries than rest of the world. With a larger population of tuberculosis patients anticipated to be co-infected with COVID-19 infection, an ongoing pandemic, identifying, preventing and managing drug–drug interactions is inevitable for maximizing patient benefits for the current repurposed COVID-19 and antitubercular drugs.

Methods:

We assessed the potential drug–drug interactions between repurposed COVID-19 drugs and antitubercular drugs using the drug interaction checker of IBM Micromedex®. Extensive computational studies were performed at a molecular level to validate and understand the drug–drug interactions found from the Micromedex drug interaction checker database at a molecular level. The integrated knowledge derived from Micromedex and computational data was collated and curated for predicting potential drug–drug interactions between repurposed COVID-19 and antitubercular drugs.

Results:

A total of 91 potential drug–drug interactions along with their severity and level of documentation were identified from Micromedex between repurposed COVID-19 drugs and antitubercular drugs. We identified 47 pharmacodynamic, 42 pharmacokinetic and 2 unknown DDIs. The majority of our molecular modelling results were in line with drug–drug interaction data obtained from the drug information software. QT prolongation was identified as the most common type of pharmacodynamic drug–drug interaction, whereas drug–drug interactions associated with cytochrome P450 3A4 (CYP3A4) and P-glycoprotein (P-gp) inhibition and induction were identified as the frequent pharmacokinetic drug–drug interactions. The results suggest antitubercular drugs, particularly rifampin and second-line agents, warrant high alert and monitoring while prescribing with the repurposed COVID-19 drugs.

Conclusion:

Predicting these potential drug–drug interactions, particularly related to CYP3A4, P-gp and the human Ether-à-go-go-Related Gene proteins, could be used in clinical settings for screening and management of drug–drug interactions for delivering safer chemotherapeutic tuberculosis and COVID-19 care. The current study provides an initial propulsion for further well-designed pharmacokinetic-pharmacodynamic-based drug–drug interaction studies.

Plain Language Summary

In silico investigation of pro-arrhythmic effects of azithromycin on the human ventricle

The macrolide antibiotic azithromycin (AZM) is widely used for respiratory infections and has been suggested to be a possible treatment for the Coronavirus Disease of 2019 (COVID-19). However, AZM-associated QT interval prolongation and arrhythmias have been reported. Integrated mechanistic information on AZM actions on human ventricular excitation and conduction is lacking. Therefore, this study was undertaken to investigate the actions of AZM on ventricular cell and tissue electrical activity. The O'Hara- Virag-Varro-Rudy dynamic (ORd) model of human ventricular cells was modified to incorporate experimental data on the concentration-dependent actions of AZM on multiple ion channels, including INa, ICaL, IKr, IKs, IK1 and INaL in both acute and chronic exposure conditions. In the single cell model, AZM prolonged the action potential duration (APD) in a concentration-dependent manner, which was predominantly attributable to IKr reduction in the acute condition and potentiated INaL in the chronic condition. High concentrations of AZM also increased action potential (AP) triangulation (determined as an increased difference between APD30 and APD90) which is a marker of arrhythmia risk. In the chronic condition, the potentiated INaL caused a modest intracellular Na + concentration accumulation at fast pacing rates. At the 1D tissue level, the AZM-prolonged APD at the cellular level was reflected by an increased QT interval in the simulated pseudo-ECG, consistent with clinical observations. Additionally, AZM reduced the conduction velocity (CV) of APs in the acute condition due to a reduced INa, and it augmented the transmural APD dispersion of the ventricular tissue, which is also pro-arrhythmic. Such actions were markedly augmented when the effects of chronic exposure of AZM were also considered, or with additional IKr block, as may occur with concurrent use of other medications. This study provides insights into the ionic mechanisms by which high concentrations of AZM may modulate ventricular electrophysiology and susceptibility to arrhythmia.

In silico Exploration of Interactions Between Potential COVID-19 Antiviral Treatments and the Pore of the hERG Potassium Channel-A Drug Antitarget

Background: In the absence of SARS-CoV-2 specific antiviral treatments, various repurposed pharmaceutical approaches are under investigation for the treatment of COVID-19. Antiviral drugs considered for this condition include atazanavir, remdesivir, lopinavir-ritonavir, and favipiravir. Whilst the combination of lopinavir and ritonavir has been previously linked to prolongation of the QTc interval on the ECG and risk of torsades de pointes arrhythmia, less is known in this regard about atazanavir, remdesivir, and favipiravir. Unwanted abnormalities of drug-induced QTc prolongation by diverse drugs are commonly mediated by a single cardiac anti-target, the hERG potassium channel. This computational modeling study was undertaken in order to explore the ability of these five drugs to interact with known determinants of drug binding to the hERG channel pore. Methods: Atazanavir, remdesivir, ritonavir, lopinavir and favipiravir were docked to in silico models of the pore domain of hERG, derived from cryo-EM structures of hERG and the closely related EAG channel. Results: Atazanavir was readily accommodated in the open hERG channel pore in proximity to the S6 Y652 and F656 residues, consistent with published experimental data implicating these aromatic residues in atazanavir binding to the channel. Lopinavir, ritonavir, and remdesivir were also accommodated in the open channel, making contacts in a model-dependent fashion with S6 aromatic residues and with residues at the base of the selectivity filter/pore helix. The ability of remdesivir (at 30 μM) to inhibit the channel was confirmed using patch-clamp recording. None of these four drugs could be accommodated in the closed channel structure. Favipiravir, a much smaller molecule, was able to fit within the closed channel and could adopt multiple binding poses in the open channel, but with few simultaneous interactions with key binding residues. Only favipiravir and remdesivir showed the potential to interact with lateral pockets below the selectivity filter of the channel. Conclusions: All the antiviral drugs studied here can, in principle, interact with components of the hERG potassium channel canonical binding site, but are likely to differ in their ability to access lateral binding pockets. Favipiravir's small size and relatively paucity of simultaneous interactions may confer reduced hERG liability compared to the other drugs. Experimental structure-function studies are now warranted to validate these observations.

Rutaecarpine targets hERG channels and participates in regulating electrophysiological properties leading to ventricular arrhythmia

Drug-mediated or medical condition-mediated disruption of hERG function accounts for the main cause of acquired long-QT syndrome (acLQTs), which predisposes affected individuals to ventricular arrhythmias (VA) and sudden death. Many Chinese herbal medicines, especially alkaloids, have risks of arrhythmia in clinical application. The characterized mechanisms behind this adverse effect are frequently associated with inhibition of cardiac hERG channels. The present study aimed to assess the potent effect of Rutaecarpine (Rut) on hERG channels. hERG-HEK293 cell was applied for evaluating the effect of Rut on hERG channels and the underlying mechanism. hERG current (I_hERG ) was measured by patch-clamp technique. Protein levels were analysed by Western blot, and the phosphorylation of Sp1 was determined by immunoprecipitation. Optical mapping and programmed electrical stimulation were used to evaluate cardiac electrophysiological activities, such as APD, QT/QTc, occurrence of arrhythmia, phase singularities (PSs), and dominant frequency (DF). Our results demonstrated that Rut reduced the I_hERG by binding to F656 and Y652 amino acid residues of hERG channel instantaneously, subsequently accelerating the channel inactivation, and being trapped in the channel. The level of hERG channels was reduced by incubating with Rut for 24 hours, and Sp1 in nucleus was inhibited simultaneously. Mechanismly, Rut reduced threonine (Thr)/ tyrosine (Tyr) phosphorylation of Sp1 through PI3K/Akt pathway to regulate hERG channels expression. Cell-based model unables to fully reveal the pathological process of arrhythmia. In vivo study, we found that Rut prolonged QT/QTc intervals and increased induction rate of ventricular fibrillation (VF) in guinea pig heart after being dosed Rut for 2 weeks. The critical reasons led to increased incidence of arrhythmias eventually were prolonged APD₉₀ and APD₅₀ and the increase of DF, numbers of PSs, incidence of early after-depolarizations (EADs). Collectively, the results of this study suggest that Rut could reduce the I_hERG by binding to hERG channels through F656 and Y652 instantaneously. While, the PI3K/Akt/Sp1 axis may play an essential role in the regulation of hERG channels, from the perspective of the long-term effects of Rut (incubating for 24 hours). Importantly, the changes of electrophysiological properties by Rut were the main cause of VA.

Cardiac hERG K+ Channel as Safety and Pharmacological Target

The human ether-á-go-go related gene (hERG, KCNH2) encodes the pore-forming subunit of the potassium channel responsible for a fast component of the cardiac delayed rectifier potassium current (I_Kr). Outward I_Kr is an important determinant of cardiac action potential (AP) repolarization and effectively controls the duration of the QT interval in humans. Dysfunction of hERG channel can cause severe ventricular arrhythmias and thus modulators of the channel, including hERG inhibitors and activators, continue to attract intense pharmacological interest. Certain inhibitors of hERG channel prolong the action potential duration (APD) and effective refractory period (ERP) to suppress premature ventricular contraction and are used as class III antiarrhythmic agents. However, a reduction of the hERG/I_Kr current has been recognized as a predominant mechanism responsible for the drug-induced delayed repolarization known as acquired long QT syndromes (LQTS), which is linked to an increased risk for "torsades de pointes" (TdP) ventricular arrhythmias and sudden cardiac death. Many drugs of different classes and structures have been identified to carry TdP risk. Hence, assessing hERG/I_Kr blockade of new drug candidates is mandatory in the drug development process according to the regulatory agencies. In contrast, several hERG channel activators have been shown to enhance I_Kr and shorten the APD and thus might have potential antiarrhythmic effects against pathological LQTS. However, these activators may also be proarrhythmic due to excessive shortening of APD and the ERP.

The influence of calculated physicochemical properties of compounds on their ADMET profiles

We analyzed the influence of calculated physicochemical properties of more than 20,000 compounds on their P-gp and BCRP mediated efflux, microsomal stability, hERG inhibition, and plasma protein binding. Our goal was to provide guidance for designing compounds with desired pharmacokinetic profiles. Our analysis showed that compounds with ClogP less than 3 and molecular weight less than 400 will have high microsomal stability and low plasma protein binding. Compounds with logD less than 2.2 and/or basic pKa larger than 5.3 are likely to be BCRP substrates and compounds with basic pKa less than 5.2 and/or acidic pKa less than 13.4 are less likely to inhibit hERG. Based on these results, compounds with MW < 400, ClogP < 3, basic pKa < 5.2 and acidic pKa < 13.4 are likely to have good bioavailability and low hERG inhibition.

Phenanthrene impacts zebrafish cardiomyocyte excitability by inhibiting IKr and shortening action potential duration

Air pollution is an environmental hazard that is associated with cardiovascular dysfunction. Phenanthrene is a three-ringed polyaromatic hydrocarbon that is a significant component of air pollution and crude oil and has been shown to cause cardiac dysfunction in marine fishes. We investigated the cardiotoxic effects of phenanthrene in zebrafish (Danio rerio), an animal model relevant to human cardiac electrophysiology, using whole-cell patch-clamp of ventricular cardiomyocytes. First, we show that phenanthrene significantly shortened action potential duration without altering resting membrane potential or upstroke velocity (dV/dt). L-type Ca2+ current was significantly decreased by phenanthrene, consistent with the decrease in action potential duration. Phenanthrene blocked the hERG orthologue (zfERG) native current, IKr, and accelerated IKr deactivation kinetics in a dose-dependent manner. Furthermore, we show that phenanthrene significantly inhibits the protective IKr current envelope, elicited by a paired ventricular AP-like command waveform protocol. Phenanthrene had no effect on other IK. These findings demonstrate that exposure to phenanthrene shortens action potential duration, which may reduce refractoriness and increase susceptibility to certain arrhythmia triggers, such as premature ventricular contractions. These data also reveal a previously unrecognized mechanism of polyaromatic hydrocarbon cardiotoxicity on zfERG by accelerating deactivation and decreasing IKr protective current.

Assessing hERG1 Blockade from Bayesian Machine-Learning-Optimized Site Identification by Ligand Competitive Saturation Simulations

Drug-induced cardiotoxicity is a potentially lethal and yet one of the most common side effects with the drugs in clinical use. Most of the drug-induced cardiotoxicity is associated with an off-target pharmacological blockade of K+ currents carried out by the cardiac Human-Ether-a-go-go-Related (hERG1) potassium channel. There is a compulsory preclinical stage safety assessment for the hERG1 blockade for all classes of drugs, which adds substantially to the cost of drug development. The availability of a high-resolution cryogenic electron microscopy (cryo-EM) structure for the channel in its open/depolarized state solved in 2017 enabled the application of molecular modeling for rapid assessment of drug blockade by molecular docking and simulation techniques. More importantly, if successful, in silico methods may allow a path to lead-compound salvaging by mapping out key block determinants. Here, we report the blind application of the site identification by the ligand competitive saturation (SILCS) protocol to map out druggable/regulatory hotspots in the hERG1 channel available for blockers and activators. The SILCS simulations use small solutes representative of common functional groups to sample the chemical space for the entire protein and its environment using all-atom simulations. The resulting chemical maps, FragMaps, explicitly account for receptor flexibility, protein-fragment interactions, and fragment desolvation penalty allowing for rapid ranking of potential ligands as blockers or nonblockers of hERG1. To illustrate the power of the approach, SILCS was applied to a test set of 55 blockers with diverse chemical scaffolds and pIC50 values measured under uniform conditions. The original SILCS model was based on the all-atom modeling of the hERG1 channel in an explicit lipid bilayer and was further augmented with a Bayesian-optimization/machine-learning (BML) stage employing an independent literature-derived training set of 163 molecules. BML approach was used to determine weighting factors for the FragMaps contributions to the scoring function. pIC50 predictions from the combined SILCS/BML approach to the 55 blockers showed a Pearson correlation (PC) coefficient of >0.535 relative to the experimental data. SILCS/BML model was shown to yield substantially improved performance as compared to commonly used rigid and flexible molecular docking methods for a well-established cohort of hERG1 blockers, where no correlation with experimental data was recorded. SILCS/BML results also suggest that a proper weighting of protonation states of common blockers present at physiological pH is essential for accurate predictions of blocker potency. The precalculated and optimized SILCS FragMaps can now be used for the rapid screening of small molecules for their cardiotoxic potential as well as for exploring alternative binding pockets in the hERG1 channel with applications to the rational design of activators.

Functional evaluation of gene mutations in Long QT Syndrome: strength of evidence from in vitro assays for deciphering variants of uncertain significance

Background

Genetic screening is now commonplace for patients suspected of having inherited cardiac conditions. Variants of uncertain significance (VUS) in disease-associated genes pose problems for the diagnostician and reliable methods for evaluating VUS function are required. Although function is difficult to interrogate for some genes, heritable channelopathies have established mechanisms that should be amenable to well-validated evaluation techniques.

The cellular electrophysiology techniques of ‘voltage-’ and ‘patch-’ clamp have a long history of successful use and have been central to identifying both the roles of genes involved in different forms of congenital Long QT Syndrome (LQTS) and the mechanisms by which mutations lead to aberrant ion channel function underlying clinical phenotypes. This is particularly evident for KCNQ1, KCNH2 and SCN5A, mutations in which underlie > 90% of genotyped LQTS cases (the LQT1-LQT3 subtypes). Recent studies utilizing high throughput (HT) planar patch-clamp recording have shown it to discriminate effectively between rare benign and pathological variants, studied through heterologous expression of recombinant channels. In combination with biochemical methods for evaluating channel trafficking and supported by biophysical modelling, patch clamp also provides detailed mechanistic insight into the functional consequences of identified mutations. Whilst potentially powerful, patient-specific stem-cell derived cardiomyocytes and genetically modified animal models are currently not well-suited to high throughput VUS study.

Conclusion

The widely adopted 2015 American College of Medical Genetics (ACMG) and Association for Molecular Pathology (AMP) guidelines for the interpretation of sequence variants include the PS3 criterion for consideration of evidence from well-established in vitro or in vivo assays. The wealth of information on underlying mechanisms of LQT1-LQT3 and recent HT patch clamp data support consideration of patch clamp data together (for LQT1 and LQT2) with information from biochemical trafficking assays as meeting the PS3 criterion of well established assays, able to provide ‘strong’ evidence for functional pathogenicity of identified VUS.

Norquetiapine blocks the human cardiac sodium channel Nav1.5 in a state-dependent manner

Quetiapine, an atypical antipsychotic drug, is used for the treatment of schizophrenia and acute mania. Although a previous report showed that quetiapine blocked hERG potassium current, quetiapine has been considered relatively safe in terms of cardiovascular side effects. In the present study, we used the whole-cell patch-clamp technique to investigate the effect that quetiapine and its major metabolite norquetiapine can exert on human cardiac sodium channels (hNa_v1.5). The half-maximal inhibitory concentrations of quetiapine and norquetiapine at a holding potential of -90 mV near the resting potential of cardiomyocytes were 30 and 6 μM, respectively. Norquetiapine as well as quetiapine was preferentially bound in the inactivated state of the hNa_v1.5 channel. Norquetiapine slowed the recovery from inactivation of hNa_v1.5 and consequently induced strong use-dependent inhibition. Our results indicate that norquetiapine blocks hNa_v1.5 current in concentration-, state- and use-dependent manners, suggesting that the blockade of hNa_v1.5 current by norquetiapine may shorten the cardiac action potential duration and reduce the risk of QT interval prolongation induced by the inhibition of hERG potassium currents.

Electrophysiological characterization of the modified hERGT potassium channel used to obtain the first cryo-EM hERG structure

The voltage-gated hERG (human-Ether-à-go-go Related Gene) K+ channel plays a fundamental role in cardiac action potential repolarization. Loss-of-function mutations or pharmacological inhibition of hERG leads to long QT syndrome, whilst gain-of-function mutations lead to short QT syndrome. A recent open channel cryo-EM structure of hERG represents a significant advance in the ability to interrogate hERG channel structure-function. In order to suppress protein aggregation, a truncated channel construct of hERG (hERGT ) was used to obtain this structure. In hERGT cytoplasmic domain residues 141 to 350 and 871 to 1,005 were removed from the full-length channel protein. There are limited data on the electrophysiological properties of hERGT channels. Therefore, this study was undertaken to determine how hERGT influences channel function at physiological temperature. Whole-cell measurements of hERG current (IhERG ) were made at 37°C from HEK 293 cells expressing wild-type (WT) or hERGT channels. With a standard +20 mV activating command protocol, neither end-pulse nor tail IhERG density significantly differed between WT and hERGT . However, the IhERG deactivation rate was significantly slower for hERGT . Half-maximal activation voltage (V0.5 ) was positively shifted for hERGT by ~+8 mV (p < .05 versus WT), without significant change to the activation relation slope factor. Neither the voltage dependence of inactivation, nor time course of development of inactivation significantly differed between WT and hERGT , but recovery of IhERG from inactivation was accelerated for hERGT (p < .05 versus WT). Steady-state "window" current was positively shifted for hERGT with a modest increase in the window current peak. Under action potential (AP) voltage clamp, hERGT IhERG showed modestly increased current throughout the AP plateau phase with a significant increase in current integral during the AP. The observed consequences for hERGT IhERG of deletion of the two cytoplasmic regions may reflect changes to electrostatic interactions influencing the voltage sensor domain.

A greedy classifier optimization strategy to assess ion channel blocking activity and pro-arrhythmia in hiPSC-cardiomyocytes

Novel studies conducting cardiac safety assessment using human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are promising but might be limited by their specificity and predictivity. It is often challenging to correctly classify ion channel blockers or to sufficiently predict the risk for Torsade de Pointes (TdP). In this study, we developed a method combining in vitro and in silico experiments to improve machine learning approaches in delivering fast and reliable prediction of drug-induced ion-channel blockade and proarrhythmic behaviour. The algorithm is based on the construction of a dictionary and a greedy optimization, leading to the definition of optimal classifiers. Finally, we present a numerical tool that can accurately predict compound-induced pro-arrhythmic risk and involvement of sodium, calcium and potassium channels, based on hiPSC-CM field potential data.

QT interval prolongation and Torsades de Pointes with donepezil, rivastigmine and galantamine

Background

Acetylcholinesterase inhibitors (AChEis) including donepezil, galantamine and rivastigmine are used to treat Alzheimer's disease (AD). This study aimed to evaluate evidence from the case report literature for an association between these agents and risk of QT interval prolongation and Torsades de Pointes (TdP) arrhythmia.

Methods

Published literature was mined with predetermined MeSH terms for each of donepezil, galantamine and rivastigmine, to identify cases of QT interval prolongation and TdP. Case reports were analysed using causality scales and a QT interval nomogram.

Results

A total of 13 case reports were found (10 for donepezil, 2 for galantamine and 1 for rivastigmine) with rate corrected QT interval (QT_c) prolongation. Five cases with donepezil exhibited TdP. TdP was not reported in the cases with galantamine and rivastigmine. The use of a QT heart rate nomogram highlighted risk with donepezil compared with the other two drugs and the application of the Naranjo causality scale suggested probable or possible causation for all donepezil cases. All patients had at least two other risk factors for TdP, including modifiable risk factors such as electrolyte disturbances, bradycardia, co-administration of QT prolonging drugs. A number of recent cases involved recent changes in medication.

Conclusion

Our evaluation of the case report literature suggests that there is evidence for a causal association between donepezil and QT_c/TdP risk. Attention to risk factors for QT_c prolongation/TdP should be exercised when prescribing donepezil and modifiable risk factors corrected. Owing to the low number of cases with galantamine and rivastigmine, further work is needed to establish whether these drugs may be more suitable than donepezil for patients with other risk factors for TdP.