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

Electrophysiological and sick sinus syndrome effects of Remdesivir challenge in guinea-pig hearts

Remdesivir (RDV) is the first drug approved by the FDA for clinical treatment of hospitalized patients infected with COVID-19 because it has been shown to have good antiviral activity against a variety of viruses, including Arenaviridae and Coronaviridae viral families. However, it has been reported that its clinical treatment leads to the symptoms of sick sinus syndrome such as sinus bradycardia, conduction block, and sinus arrest, but the electrophysiological mechanism of its specific cardiac adverse events is still unclear. We report complementary, experimental, studies of its electrophysiological effects. In wireless cardiac telemetry experiments in vivo and electrocardiographic studies in ex vivo cardiac preparations, RDV significantly caused sinus bradycardia, sinus atrial block, and prolongation of the QT interval in guinea pigs. Dose-dependent effects of RDV on the electrical activities of sinoatrial node (SA node) preparations of guinea pigs were characterised by multielectrode, optical RH237 voltage mapping. These revealed reversibly reduced sinoatrial conduction time (SACT), increased AP durations (APDs), and decreased the pacemaking rate of the SA node. Patch-clamp experiments showed that RDV significantly inhibited the If current of HCN4 channels, resulting in a significant decrease in the spontaneous firing rate of SA node cells, which may underlie the development of sick sinus node syndrome. In addition, RDV significantly inhibits IKr currents in hERG channels, leading to prolongation of the QT interval and playing a role in bradycardia. Therefore, these findings provide insights into the understanding the bradycardia effect of RDV, which may be used as basic theoretical guidance for the intervention of its adverse events, and prompt safety investigations of RDV's cardiac safety in the future.

Electrophysiological Profile of Different Antiviral Therapies in a Rabbit Whole-Heart Model

Antiviral therapies for treatment of COVID-19 may be associated with significant proarrhythmic potential. In the present study, the potential cardiotoxic side effects of these therapies were evaluated using a Langendorff model of the isolated rabbit heart. 51 hearts of female rabbits were retrogradely perfused, employing a Langendorff-setup. Eight catheters were placed endo- and epicardially to perform an electrophysiology study, thus obtaining cycle length-dependent action potential duration at 90% of repolarization (APD90), QT intervals and dispersion of repolarization. After generating baseline data, the hearts were assigned to four groups: In group 1 (HXC), hearts were treated with 1 µM hydroxychloroquine. Thereafter, 3 µM hydroxychloroquine were infused additionally. Group 2 (HXC + AZI) was perfused with 3 µM hydroxychloroquine followed by 150 µM azithromycin. In group 3 (LOP) the hearts were perfused with 3 µM lopinavir followed by 5 µM and 10 µM lopinavir. Group 4 (REM) was perfused with 1 µM remdesivir followed by 5 µM and 10 µM remdesivir. Hydroxychloroquine- and azithromycin-based therapies have a significant proarrhythmic potential mediated by action potential prolongation and an increase in dispersion. Lopinavir and remdesivir showed overall significantly less pronounced changes in electrophysiology. In accordance with the reported bradycardic events under remdesivir, it significantly reduced the rate of the ventricular escape rhythm.

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.

Chronic Administration of COVID-19 Drugs Fluvoxamine and Lopinavir Shortens Action Potential Duration by Inhibiting the Human Ether-à-go-go-Related Gene and Cav1.2

Background: Old drugs for new indications in the novel coronavirus disease of 2019 (COVID-19) pandemic have raised concerns regarding cardiotoxicity, especially the development of drug-induced QT prolongation. The acute blocking of the cardiac hERG potassium channel is conventionally thought to be the primary mechanism of QT prolongation induced by COVID-19 drugs fluvoxamine (FLV) and lopinavir (LPV). The chronic impact of these medications on the hERG expression has yet to be determined. Methods: To investigate the effect of long-term incubation of FLV and LPV on the hERG channel, we used electrophysiological assays and molecular experiments, such as Western blot, RT-qPCR, and immunofluorescence, in HEK-293 cells stably expressing hERG and human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Results: Compared to the acute effects, chronic incubation for FLV and LPV generated much lower half-maximal inhibitory concentration (IC50) values, along with a left-shifted activation curve and retarded channel activation. Inconsistent with the reduction in current, we unexpectedly found that the chronic effects of drugs promoted the maturation of hERG proteins, accompanied by the high expression of Hsp70 and low expression of Hsp90. Targeting Hsp70 using siRNA was able to reverse the effects of these drugs on hERG proteins. In addition, FLV and LPV resulted in a significant reduction of APD90 and triggered the early after-depolarizations (EADs), as well as inhibited the protein level of the L-type voltage-operated calcium channel (L-VOCC) in hiPSC-CMs. Conclusion: Chronic incubation with FLV and LPV produced more severe channel-blocking effects and contributed to altered channel gating and shortened action potential duration by inhibiting hERG and Cav1.2.

Structure-Based Prediction of hERG-Related Cardiotoxicity: A Benchmark Study

Drug-induced blockade of the human ether-à-go-go-related gene (hERG) channel is today considered the main cause of cardiotoxicity in postmarketing surveillance. Hence, several ligand-based approaches were developed in the last years and are currently employed in the early stages of a drug discovery process for in silico cardiac safety assessment of drug candidates. Herein, we present the first structure-based classifiers able to discern hERG binders from nonbinders. LASSO regularized support vector machines were applied to integrate docking scores and protein–ligand interaction fingerprints. A total of 396 models were trained and validated based on: (i) high-quality experimental bioactivity information returned by 8337 curated compounds extracted from ChEMBL (version 25) and (ii) structural predictor data. Molecular docking simulations were performed using GLIDE and GOLD software programs and four different hERG structural models, namely, the recently published structures obtained by cryoelectron microscopy (PDB codes: 5VA1 and 7CN1) and two published homology models selected for comparison. Interestingly, some classifiers return performances comparable to ligand-based models in terms of area under the ROC curve (AUC_MAX = 0.86 ± 0.01) and negative predictive values (NPV_MAX = 0.81 ± 0.01), thus putting forward the herein proposed computational workflow as a valuable tool for predicting hERG-related cardiotoxicity without the limitations of ligand-based models, typically affected by low interpretability and a limited applicability domain. From a methodological point of view, our study represents the first example of a successful integration of docking scores and protein–ligand interaction fingerprints (IFs) through a support vector machine (SVM) LASSO regularized strategy. Finally, the study highlights the importance of using hERG structural models accounting for ligand-induced fit effects and allowed us to select the best-performing protein conformation (made available in the Supporting Information, SI) to be employed for a reliable structure-based prediction of hERG-related cardiotoxicity.