New potential binding determinant for hERG channel inhibitors

Molecular Structure, Antioxidant Potential, and Pharmacokinetic Properties of Plant Flavonoid Blumeatin and Investigating Its Inhibition Mechanism on Xanthine Oxidase for Hyperuricemia by Molecular Modeling

Hyperuricemia, which usually results in metabolic syndrome symptoms, is increasing rapidly all over the world and becoming a global public health issue. Xanthine oxidase (XO) is regarded as a key drug target for the treatment of this disease. Therefore, finding natural, nontoxic, and highly active XO inhibitors is quite important. To get insights into inhibitory potential toward XO and determine antioxidant action mechanism depending on the molecular structure, plant flavonoid blumeatin was investigated for the first time by Fourier transform infrared (FTIR) spectroscopy, density functional theory (DFT), ADME/Tox (absorption, distribution, metabolism, excretion, and toxicity) analysis, and molecular docking study. Theoretical findings indicated that blumeatin has high radical scavenging activity due to its noncoplanarity and over twisted torsion angle (-94.64°) with respect to its flavanone skeleton could explain that there might be a correlation between antioxidant activity and planarity of blumeatin. Based on the ADME/Tox analysis, it is determined that blumeatin has a high absorption profile in the human intestine (81.93%), and this plant flavonoid is not carcinogenic or mutagenic. A molecular docking study showed that Thr1010, Val1011, Phe914, and Ala1078 are the main amino acid residues participating in XO's interaction with blumeatin via hydrogen bonds.

Harnessing AlphaFold to reveal state secrets: Prediction of hERG closed and inactivated states

To design safe, selective, and effective new therapies, there must be a deep understanding of the structure and function of the drug target. One of the most difficult problems to solve has been resolution of discrete conformational states of transmembrane ion channel proteins. An example is KV11.1 (hERG), comprising the primary cardiac repolarizing current, IKr. hERG is a notorious drug anti-target against which all promising drugs are screened to determine potential for arrhythmia. Drug interactions with the hERG inactivated state are linked to elevated arrhythmia risk, and drugs may become trapped during channel closure. However, the structural details of multiple conformational states have remained elusive. Here, we guided AlphaFold2 to predict plausible hERG inactivated and closed conformations, obtaining results consistent with myriad available experimental data. Drug docking simulations demonstrated hERG state-specific drug interactions aligning well with experimental results, revealing that most drugs bind more effectively in the inactivated state and are trapped in the closed state. Molecular dynamics simulations demonstrated ion conduction that aligned with earlier studies. Finally, we identified key molecular determinants of state transitions by analyzing interaction networks across closed, open, and inactivated states in agreement with earlier mutagenesis studies. Here, we demonstrate a readily generalizable application of AlphaFold2 as a novel method to predict discrete protein conformations and novel linkages from structure to function.

Structural modeling of hERG channel-drug interactions using Rosetta

The human ether-a-go-go-related gene (hERG) not only encodes a potassium-selective voltage-gated ion channel essential for normal electrical activity in the heart but is also a major drug anti-target. Genetic hERG mutations and blockage of the channel pore by drugs can cause long QT syndrome, which predisposes individuals to potentially deadly arrhythmias. However, not all hERG-blocking drugs are proarrhythmic, and their differential affinities to discrete channel conformational states have been suggested to contribute to arrhythmogenicity. We used Rosetta electron density refinement and homology modeling to build structural models of open-state hERG channel wild-type and mutant variants (Y652A, F656A, and Y652A/F656 A) and a closed-state wild-type channel based on cryo-electron microscopy structures of hERG and EAG1 channels. These models were used as protein targets for molecular docking of charged and neutral forms of amiodarone, nifekalant, dofetilide, d/l-sotalol, flecainide, and moxifloxacin. We selected these drugs based on their different arrhythmogenic potentials and abilities to facilitate hERG current. Our docking studies and clustering provided atomistic structural insights into state-dependent drug-channel interactions that play a key role in differentiating safe and harmful hERG blockers and can explain hERG channel facilitation through drug interactions with its open-state hydrophobic pockets.

In silico prediction of hERG blockers using machine learning and deep learning approaches

The human ether-à-go-go-related gene (hERG) is associated with drug cardiotoxicity. If the hERG channel is blocked, it will lead to prolonged QT interval and cause sudden death in severe cases. Therefore, it is important to evaluate the hERG-blocking property of compounds in early drug discovery. In this study, a dataset containing 4556 compounds with IC50 values determined by patch clamp techniques on mammalian lineage cells was collected, and hERG blockers and non-blockers were distinguished according to three single thresholds and two binary thresholds. Four machine learning (ML) algorithms combining four molecular fingerprints and molecular descriptors as well as graph convolutional neural networks (GCNs) were used to construct a series of binary classification models. The results showed that the best models varied for different thresholds. The ML models implemented by support vector machine and random forest performed well based on Morgan fingerprints and molecular descriptors, with AUCs ranging from 0.884 to 0.950. GCN showed superior prediction performance with AUCs above 0.952, which might be related to its direct extraction of molecular features from the original input. Meanwhile, the classification of binary threshold was better than that of single threshold, which could provide us with a more accurate prediction of hERG blockers. At last, the applicability domain for the model was defined, and seven structural alerts that might generate hERG blockage were identified by information gain and substructure frequency analysis. Our work would be beneficial for identifying hERG blockers in chemicals.

Inhibition of the hERG Potassium Channel by a Methanesulphonate-Free E-4031 Analogue

hERG (human Ether-à-go-go Related Gene)-encoded potassium channels underlie the cardiac rapid delayed rectifier (IKr) potassium current, which is a major target for antiarrhythmic agents and diverse non-cardiac drugs linked to the drug-induced form of long QT syndrome. E-4031 is a high potency hERG channel inhibitor from the methanesulphonanilide drug family. This study utilized a methanesulphonate-lacking E-4031 analogue, "E-4031-17", to evaluate the role of the methanesulphonamide group in E-4031 inhibition of hERG. Whole-cell patch-clamp measurements of the hERG current (IhERG) were made at physiological temperature from HEK 293 cells expressing wild-type (WT) and mutant hERG constructs. For E-4031, WT IhERG was inhibited by a half-maximal inhibitory concentration (IC50) of 15.8 nM, whilst the comparable value for E-4031-17 was 40.3 nM. Both compounds exhibited voltage- and time-dependent inhibition, but they differed in their response to successive applications of a long (10 s) depolarisation protocol, consistent with greater dissociation of E-4031-17 than the parent compound between applied commands. Voltage-dependent inactivation was left-ward voltage shifted for E-4031 but not for E-4031-17; however, inhibition by both compounds was strongly reduced by attenuated-inactivation mutations. Mutations of S6 and S5 aromatic residues (F656V, Y652A, F557L) greatly attenuated actions of both drugs. The S624A mutation also reduced IhERG inhibition by both molecules. Overall, these results demonstrate that the lack of a methanesulphonate in E-4031-17 is not an impediment to high potency inhibition of IhERG.

Calculations of the binding free energies of the Comprehensive in vitro Proarrhythmia Assay (CiPA) reference drugs to cardiac ion channels

The evaluation of the inhibitory activities of drugs on multiple cardiac ion channels is required for the accurate assessment of proarrhythmic risks. Moreover, the in silico prediction of such inhibitory activities of drugs on cardiac channels can improve the efficiency of the drug-development process. Here, we performed molecular docking simulations to predict the complex structures of 25 reference drugs that were proposed by the Comprehensive in vitro Proarrhythmia Assay consortium using two cardiac ion channels, the human ether-a-go-go-related gene (hERG) potassium channel and human NaV1.5 (hNaV1.5) sodium channel, with experimentally available structures. The absolute binding free energy (ΔGbind) values of the predicted structures were calculated by a molecular dynamics-based method and compared with the experimental half-maximal inhibitory concentration (IC50) data. Furthermore, the regression analysis between the calculated values and negative of the common logarithm of the experimental IC50 values (pIC50) revealed that the calculated values of four and ten drugs deviated significantly from the regression lines of the hERG and hNaV1.5 channels, respectively. We reconsidered the docking poses and protonation states of the drugs based on the experimental data and recalculated their ΔGbind values. Finally, the calculated ΔGbind values of 24 and 19 drugs correlated with their experimental pIC50 values (coefficients of determination=0.791 and 0.613 for the hERG and hNaV1.5 channels, respectively). Thus, the regression analysis between the calculated ΔGbind and experimental IC50 data ensured the realization of an increased number of reliable complex structures.

Ensemble of structure and ligand-based classification models for hERG liability profiling

Drug-induced cardiotoxicity represents one of the most critical safety concerns in the early stages of drug development. The blockade of the human ether-à-go-go-related potassium channel (hERG) is the most frequent cause of cardiotoxicity, as it is associated to long QT syndrome which can lead to fatal arrhythmias. Therefore, assessing hERG liability of new drugs candidates is crucial to avoid undesired cardiotoxic effects. In this scenario, computational approaches have emerged as useful tools for the development of predictive models able to identify potential hERG blockers. In the last years, several efforts have been addressed to generate ligand-based (LB) models due to the lack of experimental structural information about hERG channel. However, these methods rely on the structural features of the molecules used to generate the model and often fail in correctly predicting new chemical scaffolds. Recently, the 3D structure of hERG channel has been experimentally solved enabling the use of structure-based (SB) strategies which may overcome the limitations of the LB approaches. In this study, we compared the performances achieved by both LB and SB classifiers for hERG-related cardiotoxicity developed by using Random Forest algorithm and employing a training set containing 12789 hERG binders. The SB models were trained on a set of scoring functions computed by docking and rescoring calculations, while the LB classifiers were built on a set of physicochemical descriptors and fingerprints. Furthermore, models combining the LB and SB features were developed as well. All the generated models were internally validated by ten-fold cross-validation on the TS and further verified on an external test set. The former revealed that the best performance was achieved by the LB model, while the model combining the LB and the SB attributes displayed the best results when applied on the external test set highlighting the usefulness of the integration of LB and SB features in correctly predicting unseen molecules. Overall, our predictive models showed satisfactory performances providing new useful tools to filter out potential cardiotoxic drug candidates in the early phase of drug discovery.

The voltage-sensing domain of a hERG1 mutant is a cation-selective channel

A cationic leak current known as an "omega current" may arise from mutations of the first charged residue in the S4 of the voltage sensor domains of sodium and potassium voltage-gated channels. The voltage-sensing domains (VSDs) in these mutated channels act as pores allowing nonspecific passage of cations, such as Li+, K+, Cs+, and guanidinium. Interestingly, no omega currents have been previously detected in the nonswapped voltage-gated potassium channels such as the human-ether-a-go-go-related (hERG1), hyperpolarization-activated cyclic nucleotide-gated, and ether-a-go-go channels. In this work, we discovered a novel omega current by mutating the first charged residue of the S4 of the hERG1, K525 to serine. To characterize this omega current, we used various probes, including the hERG1 pore domain blocker, dofetilide, to show that the omega current does not require cation flux via the canonical pore domain. In addition, the omega flux does not cross the conventional selectivity filter. We also show that the mutated channel (K525S hERG1) conducts guanidinium. These data are indicative of the formation of an omega current channel within the VSD. Using molecular dynamics simulations with replica-exchange umbrella sampling simulations of the wild-type hERG1 and the K525S hERG1, we explored the molecular underpinnings governing the cation flow in the VSD of the mutant. We also show that the wild-type hERG1 may form water crevices supported by the biophysical surface accessibility data. Overall, our multidisciplinary study demonstrates that the VSD of hERG1 may act as a cation-selective channel wherein a mutation of the first charged residue in the S4 generates an omega current. Our simulation uncovers the atomistic underpinning of this mechanism.

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.

The hEag1 K+ Channel Inhibitor Astemizole Stimulates Ca2+ Deposition in SaOS-2 and MG-63 Osteosarcoma Cultures

The hEag1 (Kv10.1) K⁺ channel is normally found in the brain, but it is ectopically expressed in tumor cells, including osteosarcoma. Based on the pivotal role of ion channels in osteogenesis, we tested whether pharmacological modulation of hEag1 may affect osteogenic differentiation of osteosarcoma cell lines. Using molecular biology (RT-PCR), electrophysiology (patch-clamp) and pharmacology (astemizole sensitivity, IC₅₀ = 0.135 μM) we demonstrated that SaOS-2 osteosarcoma cells also express hEag1 channels. SaOS-2 cells also express to KCa1.1 K⁺ channels as shown by mRNA expression and paxilline sensitivity of the current. The inhibition of hEag1 (2 μM astemizole) or KCa1.1 (1 mM TEA) alone did not induce Ca²⁺ deposition in SaOS-2 cultures, however, these inhibitors, at identical concentrations, increased Ca²⁺ deposition evoked by the classical or pathological (inorganic phosphate, Pi) induction pathway without causing cytotoxicity, as reported by three completer assays (LDH release, MTT assay and SRB protein assay). We observed a similar effect of astemizole on Ca²⁺ deposition in MG-63 osteosarcoma cultures as well. We propose that the increase in the osteogenic stimuli-induced mineral matrix formation of osteosarcoma cell lines by inhibiting hEag1 may be a useful tool to drive terminal differentiation of osteosarcoma.

hERG Blockade Prediction by Combining Site Identification by Ligand Competitive Saturation and Physicochemical Properties

Human ether-a-go-go-related gene (hERG) potassium channel is well-known contributor to drug-induced cardiotoxicity and therefore an extremely important target when performing safety assessments of drug candidates. Ligand-based approaches in connection with quantitative structure active relationships (QSAR) analyses have been developed to predict hERG toxicity. Availability of the recent published cryogenic electron microscopy (cryo-EM) structure for the hERG channel opened the prospect for using structure-based simulation and docking approaches for hERG drug liability predictions. In recent time, the idea of combining structure- and ligand-based approaches for modeling hERG drug liability has gained momentum offering improvements in predictability when compared to ligand-based QSAR practices alone. The present article demonstrates uniting the structure-based SILCS (site-identification by ligand competitive saturation) approach in conjunction with physicochemical properties to develop predictive models for hERG blockade. This combination leads to improved model predictability based on Pearson's R and percent correct (represents rank-ordering of ligands) metric for different validation sets of hERG blockers involving diverse chemical scaffold and wide range of pIC50 values. The inclusion of the SILCS structure-based approach allows determination of the hERG region to which compounds bind and the contribution of different chemical moieties in the compounds to blockade, thereby facilitating the rational ligand design to minimize hERG liability.

Diminishing hERG inhibitory activity of aminopiperidine-naphthyridine linked NBTI antibacterials by structural and physicochemical optimizations

Novel bacterial topoisomerase inhibitors (NBTIs) are an important new class of antibacterials targeting bacterial type II topoisomerases (DNA gyrase and topoisomerase IV). Notwithstanding their potent antibacterial activity, they suffer from a detrimental class-related hERG blockage. In this study, we designed and synthesized an optimized library of NBTIs comprising different linker moieties that exhibit reduced hERG inhibition and retain inhibitory potencies on DNA gyrase and topoisomerase IV of Staphylococcus aureus and Escherichia coli, respectively, as well as potent antibacterial activities. Substitution of the linker's tertiary amine with polar groups outcome in diminished hERG inhibition. Compound 17 expresses nanomolar enzyme inhibitory potency and antibacterial activity against both Gram-positive and Gram-negative bacteria as well as reduced hERG inhibition relative to our previously published NBTI analogs. Here, we point to some important NBTI's structural features that influence their hERG inhibitory activity.

Hypoglycaemic activity of Oleanonic acid, a 3-oxotriterpenoid isolated from Aidia Genipiflora (DC.) Dandy, involves inhibition of carbohydrate metabolic enzymes and promotion of glucose uptake

The present study evaluated the antidiabetic activities of the 70% ethanol stem bark extract of Aidia genipiflora (AGB) and one of its constituents, oleanonic acid in streptozotocin (40 mg/kg)-induced diabetic rats. In vitro assays of glucose uptake and inhibition of carbohydrate metabolizing enzymes were then used to investigate their mechanism(s) of hypoglycaemic action. In silico evaluation of the pharmacokinetic and toxicity properties of the compound was also carried out. Administration of AGB (100-400 mg/kg) and oleanonic acid (15 - 60 mg/kg) resulted in significant reductions (p < 0.001) in the blood glucose and considerable decrease (p < 0.05) in the elevated lipid parameters of the diabetic animals. AGB activity at 200 and 400 mg/kg; and oleanonic acid at 60 mg/kg were comparable to glibenclamide (5 mg/kg). The extract and its isolate strongly inhibited α-glucosidase and α-amylase activity with IC₅₀ values of (10.48 ± 1.39 µg/mL and 14.51 ± 1.26 µg/mL) and (36.52 ± 1.95 µM and 105.84 ± 1.08 µM) respectively. The glucose uptake assays showed that AGB and oleanonic acid exerted both insulin-dependent and independent promotional effect of glucose transport into the periphery by upregulating the expression of PI3K and PPARγ transcripts with a concomitant increase in GLUT-4 transcripts. Although oleanonic acid was predicted to be teratogenic, it was found to be generally non-lethal with favourable pharmacokinetics properties making it suitable for further studies. The study has shown that the stem bark of A. genipiflora is a source of new hypoglycaemic agents and that oleanonic acid possesses hypoglycaemic and anti-hyperlipidaemic activities.

In silico approaches in organ toxicity hazard assessment: Current status and future needs for predicting heart, kidney and lung toxicities

The kidneys, heart and lungs are vital organ systems evaluated as part of acute or chronic toxicity assessments. New methodologies are being developed to predict these adverse effects based on in vitro and in silico approaches. This paper reviews the current state of the art in predicting these organ toxicities. It outlines the biological basis, processes and endpoints for kidney toxicity, pulmonary toxicity, respiratory irritation and sensitization as well as functional and structural cardiac toxicities. The review also covers current experimental approaches, including off-target panels from secondary pharmacology batteries. Current in silico approaches for prediction of these effects and mechanisms are described as well as obstacles to the use of in silico methods. Ultimately, a commonly accepted protocol for performing such assessment would be a valuable resource to expand the use of such approaches across different regulatory and industrial applications. However, a number of factors impede their widespread deployment including a lack of a comprehensive mechanistic understanding, limited in vitro testing approaches and limited in vivo databases suitable for modeling, a limited understanding of how to incorporate absorption, distribution, metabolism, and excretion (ADME) considerations into the overall process, a lack of in silico models designed to predict a safe dose and an accepted framework for organizing the key characteristics of these organ toxicants.

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.

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.

Molecular Dynamics-Derived Pharmacophore Model Explaining the Nonselective Aspect of KV10.1 Pore Blockers

The K_V10.1 voltage-gated potassium channel is highly expressed in 70% of tumors, and thus represents a promising target for anticancer drug discovery. However, only a few ligands are known to inhibit K_V10.1, and almost all also inhibit the very similar cardiac hERG channel, which can lead to undesirable side-effects. In the absence of the structure of the K_V10.1–inhibitor complex, there remains the need for new strategies to identify selective K_V10.1 inhibitors and to understand the binding modes of the known K_V10.1 inhibitors. To investigate these binding modes in the central cavity of K_V10.1, a unique approach was used that allows derivation and analysis of ligand–protein interactions from molecular dynamics trajectories through pharmacophore modeling. The final molecular dynamics-derived structure-based pharmacophore model for the simulated K_V10.1–ligand complexes describes the necessary pharmacophore features for K_V10.1 inhibition and is highly similar to the previously reported ligand-based hERG pharmacophore model used to explain the nonselectivity of K_V10.1 pore blockers. Moreover, analysis of the molecular dynamics trajectories revealed disruption of the π–π network of aromatic residues F359, Y464, and F468 of K_V10.1, which has been reported to be important for binding of various ligands for both K_V10.1 and hERG channels. These data indicate that targeting the K_V10.1 channel pore is also likely to result in undesired hERG inhibition, and other potential binding sites should be explored to develop true K_V10.1-selective inhibitors as new anticancer agents.

Genetic and Molecular Aspects of Drug-Induced QT Interval Prolongation

Long QT syndromes can be either acquired or congenital. Drugs are one of the many etiologies that may induce acquired long QT syndrome. In fact, many drugs frequently used in the clinical setting are a known risk factor for a prolonged QT interval, thus increasing the chances of developing torsade de pointes. The molecular mechanisms involved in the prolongation of the QT interval are common to most medications. However, there is considerable inter-individual variability in drug response, thus making the application of personalized medicine a relevant aspect in long QT syndrome, in order to evaluate the risk of every individual from a pharmacogenetic standpoint.

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.

Flavonoids and hERG channels: Friends or foes?

The cardiac action potential is regulated by several ion channels. Drugs capable to block these channels, in particular the human ether-à-go-go-related gene (hERG) channel, also known as K_V11.1 channel, may lead to a potentially lethal ventricular tachyarrhythmia called "Torsades de Pointes". Thus, evaluation of the hERG channel off-target activity of novel chemical entities is nowadays required to safeguard patients as well as to avoid attrition in drug development. Flavonoids, a large class of natural compounds abundantly present in food, beverages, herbal medicines, and dietary food supplements, generally escape this assessment, though consumed in consistent amounts. Continuously growing evidence indicates that these compounds may interact with the hERG channel and block it. The present review, by examining numerous studies, summarizes the state-of-the-art in this field, describing the most significant examples of direct and indirect inhibition of the hERG channel current operated by flavonoids. A description of the molecular interactions between a few of these natural molecules and the Rattus norvegicus channel protein, achieved by an in silico approach, is also presented.

Molecular dynamics of hERG channel: insights into understanding the binding of small molecules for detuning cardiotoxicity

Evaluation of cardiotoxicity potential of new chemical entities (NCEs) has lately become one of the stringent filters in the drug discovery and development process. Cardiotoxicity is caused mainly by the inhibition of human ether-a-go-go related gene (hERG) channel protein. Inhibition of the hERG channel leads to a life-threatening condition known as cardiac arrhythmia. Knowledge of the structural behaviour of the hERG would aid greatly in the design of new drug molecules that do not interact with the protein and add to the safety index. In this study, a computational model for the active-state of hERG was developed. This model was equilibrated by performing the molecular dynamics simulations for 100 ns followed by clustering and selection of a representative structure based on the largest populated cluster. To study the changes in the protein structure on inhibition, three inhibitory ligands, namely, dofetilide, cisapride and terfenadine were docked, followed by molecular dynamics simulations of 200 ns for the apo and each ligand-bound structure. It was observed that docking and simulation studies of the hERG model exhibited noticeable conformational changes in the protein upon ligand-binding. A significant change in the kink of the S6-transmembrane helix was observed. Inter-chain distances between the crucial residues Y652 and F656 (present below the ion-selectivity filter), their side-chain orientation and hydrogen bonding indicated a probable collapse of the pore. These changes may infer the initiation in transition of hERG from an open to an inactive state. Hence, these findings would help in designing compounds devoid of hERG inhibition with reduced cardiotoxicity.Communicated by Ramaswamy H. Sarma.

Cryo-EM Structure of K+-Bound hERG Channel Complexed with the Blocker Astemizole

The hERG channel is a voltage-gated potassium channel involved in cardiac repolarization. Off-target hERG inhibition by drugs has become a critical issue in the pharmaceutical industry. The three-dimensional structure of the hERG channel was recently reported at 3.8-Å resolution using cryogenic electron microscopy (cryo-EM). However, the drug inhibition mechanism remains unclear because of the scarce structural information regarding the drug- and potassium-bound hERG channels. In this study, we obtained the cryo-EM density map of potassium-bound hERG channel complexed with astemizole, a well-known hERG inhibitor that increases risk of potentially fatal arrhythmia, at 3.5-Å resolution. The structure suggested that astemizole inhibits potassium conduction by binding directly below the selectivity filter. Furthermore, we propose a possible binding model of astemizole to the hERG channel and provide insights into the unusual sensitivity of hERG to several drugs.

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 (I_hERG) were made from HEK293 cells expressing wild-type (WT) and mutant hERG channels. WT I_hERG1a was inhibited by phenanthrene with an IC₅₀ of 17.6 ± 1.7 µM, whilst I_hERG1a/1b exhibited an IC₅₀ of 1.8 ± 0.3 µM. WT I_hERG 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 I_hERG block. In contrast, the F557L (S5) and M651A (S6) mutations impaired the ability of phenanthrene to inhibit I_hERG, 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.

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.

Off-label use of chloroquine, hydroxychloroquine, azithromycin and lopinavir/ritonavir in COVID-19 risks prolonging the QT interval by targeting the hERG channel

Coronavirus disease-2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses an enormous challenge to the medical system, especially the lack of safe and effective COVID-19 treatment methods, forcing people to look for drugs that may have therapeutic effects as soon as possible. Some old drugs have shown clinical benefits after a few small clinical trials that attracted great attention. Clinically, however, many drugs, including those currently used in COVID-19, such as chloroquine, hydroxychloroquine, azithromycin, and lopinavir/ritonavir, may cause cardiotoxicity by acting on cardiac potassium channels, especially hERG channel through their off-target effects. The blocking of the hERG channel prolongs QT intervals on electrocardiograms; thus, it might induce severe ventricular arrhythmias and even sudden cardiac death. Therefore, while focusing on the efficacy of COVID-19 drugs, the fact that they block hERG channels to cause arrhythmias cannot be ignored. To develop safer and more effective drugs, it is necessary to understand the interactions between drugs and the hERG channel and the molecular mechanism behind this high affinity. In this review, we focus on the biochemical and molecular mechanistic aspects of drug-related blockade of the hERG channel to provide insights into QT prolongation caused by off-label use of related drugs in COVID-19, and hope to weigh the risks and benefits when using these drugs.

In-silico studies on Myo inositol-1-phosphate synthase of Leishmania donovani in search of anti-leishmaniasis

Myo-inositol is one of the vital nutritional requirements for the Leishmania parasites' survival and virulence in the mammalian host. . Myo-inositol-1-phosphate synthase (MIPS) is responsible for the synthesis of myo-inositol in Leishmania, which plays a vital role in Leishmania's virulence to mammalian hosts. Earlier studies suggest MIP synthase as a potential drug target against which valproate was used as a drug. So, MIP synthase can be used as a target for anti-leishmanial drugs, and its inhibition may help in preventing leishmaniasis. The present study aims to identify valproate's potent analogs as drugs against MIP synthase of L. donovani (Ld-MIPS) with minimum side effects and toxicity to host.In this study, the three-dimensional structure of Ld-MIPS was built, followed by active site prediction. Ligand-based virtual screening was done using hybrid similarity recognition methods. The best 123 valproate analogs were filtered based on their quantitative structure activity relationship (QSAR) properties and were docked against Ld-MIPS using FlexX, PyRx and iGEMDOCK software. The topmost five ligands were selected for molecular dynamics simulation and pharmacokinetic analysis based on the docking score. Simulation studies up to 30 ns revealed that all five lead molecules bound with Ld-MIPS throughout MD simulation and there was no variation in their backbone. All the chosen inhibitors exhibited good pharmacokinetics/ADMET predictions with an excellent absorption profile, metabolism, oral bioavailability, solubility, excretion, and minimal toxicity, suggesting that these inhibitors may further be developed as anti-leishmaniasis drugs to prevent the spread of leishmaniasis.Communicated by Ramaswamy H. Sarma.

Synthesis, Molecular Docking, Druglikeness Analysis, and ADMET Prediction of the Chlorinated Ethanoanthracene Derivatives as Possible Antidepressant Agents

Ethanoanthracene cycloadducts (5–7) anti, (5–7) syn, and (5–7) dec have been synthesized from the Diels–Alder (DA) reaction of diene 1,8-dichloroanthracene 2, with the dienophiles; acrylonitrile 3, 1-cynavinyl acetate 4, and phenyl vinyl sulfone 5, individually. The steric effect of dienophile substituents were more favorable toward the anti-isomer formation as deduced from 1H-NMR spectrum. The cheminformatics prediction for (5–7) anti and (5–7) syn was investigated. The in silico anticipated anti-depression activity of the (5–7) anti and (5–7) syn compounds were investigated and compared to maprotiline 9 as reference anti-depressant drug. The study showed that steric interactions play a crucial role in the binding affinity of these compounds to the representative models; 4xnx, 2QJU, and 3GWU. The pharmacokinetic and drug-like properties of (5–7) anti and (5–7) syn exhibited that these compounds could be represented as potential candidates for further development into antidepressant-like agents.

Flavanols and triterpenoids from Myrianthus arboreus ameliorate hyperglycaemia in streptozotocin-induced diabetic rats possibly via glucose uptake enhancement and α-amylase inhibition

Myrianthus arboreus is use traditionally as an antidiabetic agent in Ghana. We reported the in vivo antidiabetic activity of its 70 % ethanol stem bark extract (MAB) which we found to be strongly concentrated in its EtOAc fraction using glucose uptake and enzyme inhibitory assays. The present study sought to investigate the in vivo hypoglycaemic and anti-hyperlipidaemic activity of this ethyl acetate fraction of MAB (MAB-EtOAc, 50 and 100 mg/kg) in streptozotocin (STZ)-induced diabetic rats for 21 days, isolate and evaluate the bioactive constituents responsible for the antidiabetic activity. In silico pharmacokinetic and toxicity properties of the most active compound was also determined. MAB-EtOAc significantly (p < 0.001) reduced the blood glucose levels while normalizing considerably the altered serum lipid parameters of the diabetic rats which was comparable to glibenclamide (5 mg/kg). Chemical investigation of MAB-EtOAc led to the isolation of seven known compounds including three flavanols which are reported for the first time in the plant: epicatechin (1), epigallocatechin (2), dulcisflavan (3), euscaphic acid (4), tormentic acid (5), sitosterol-3-O-β-d-glucopyranoside (6) and arjunolic acid (7). The compounds markedly inhibited the action of α-amylase and, except for 4 and 6, which stimulated considerably glucose uptake in C2C12 cells. Compounds 2, 3, 5, 6 and 7 which were further evaluated in STZ-induced diabetic rats demonstrated hypoglycaemic and anti-hyperlipidaemic activities which, however, were not comparable with MAB-EtOAc. Compound 3, the most active compound was predicted to be non-toxic, non-mutagenic, has reasonable oral bioavailability and a decent substrate for further drug development. The findings of this study show that the isolated compounds may contribute to the antidiabetic activity of M. arboreus and could serve as marker compounds for the quality control of herbal medicines that would be made from the plant.

A structure-based computational workflow to predict liability and binding modes of small molecules to hERG

Off-target interactions of drugs with the human ether-à-go-go related gene 1 (hERG1) channel have been associated with severe cardiotoxic conditions leading to the withdrawal of many drugs from the market over the last decades. Consequently, predicting drug-induced hERG-liability is now a prerequisite in any drug discovery campaign. Understanding the atomic level interactions of drug with the channel is essential to guide the efficient development of safe drugs. Here we utilize the recent cryo-EM structure of the hERG channel and describe an integrated computational workflow to characterize different drug-hERG interactions. The workflow employs various structure-based approaches and provides qualitative and quantitative insights into drug binding to hERG. Our protocol accurately differentiated the strong blockers from weak and revealed three potential anchoring sites in hERG. Drugs engaging in all these sites tend to have high affinity towards hERG. Our results were cross-validated using a fluorescence polarization kit binding assay and with electrophysiology measurements on the wild-type (WT-hERG) and on the two hERG mutants (Y652A-hERG and F656A-hERG), using the patch clamp technique on HEK293 cells. Finally, our analyses show that drugs binding to hERG disrupt and hijack certain native—structural networks in the channel, thereby, gaining more affinity towards hERG.

Allosteric Coupling Between Drug Binding and the Aromatic Cassette in the Pore Domain of the hERG1 Channel: Implications for a State-Dependent Blockade

Human-ether-a-go-go-related channel (hERG1) is the pore-forming domain of the delayed rectifier K⁺ channel in the heart which underlies the I_Kr current. The channel has been extensively studied due to its propensity to bind chemically diverse group of drugs. The subsequent hERG1 block can lead to a prolongation of the QT interval potentially leading to an abnormal cardiac electrical activity. The recently solved cryo-EM structure featured a striking non-swapped topology of the Voltage-Sensor Domain (VSD) which is packed against the pore-domain as well as a small and hydrophobic intra-cavity space. The small size and hydrophobicity of the cavity was unexpected and challenges the already-established hypothesis of drugs binding to the wide cavity. Recently, we showed that an amphipathic drug, ivabradine, may favorably bind the channel from the lipid-facing surface and we discovered a mutant (M651T) on the lipid facing domain between the VSD and the PD which inhibited the blocking capacity of the drug. Using multi-microseconds Molecular Dynamics (MD) simulations of wild-type and M651T mutant hERG1, we suggested the block of the channel through the lipid mediated pathway, the opening of which is facilitated by the flexible phenylalanine ring (F656). In this study, we characterize the dynamic interaction of the methionine-aromatic cassette in the S5-S6 helices by combining data from electrophysiological experiments with MD simulations and molecular docking to elucidate the complex allosteric coupling between drug binding to lipid-facing and intra-cavity sites and aromatic cassette dynamics. We investigated two well-established hERG1 blockers (ivabradine and dofetilide) for M651 sensitivity through electrophysiology and mutagenesis techniques. Our electrophysiology data reveal insensitivity of dofetilide to the mutations at site M651 on the lipid facing side of the channel, mirroring our results obtained from docking experiments. Moreover, we show that the dofetilide-induced block of hERG1 occurs through the intracellular space, whereas little to no block of ivabradine is observed during the intracellular application of the drug. The dynamic conformational rearrangement of the F656 appears to regulate the translocation of ivabradine into the central cavity. M651T mutation appears to disrupt this entry pathway by altering the molecular conformation of F656.

The Study on the hERG Blocker Prediction Using Chemical Fingerprint Analysis

Human ether-a-go-go-related gene (hERG) potassium channel blockage by small molecules may cause severe cardiac side effects. Thus, it is crucial to screen compounds for activity on the hERG channels early in the drug discovery process. In this study, we collected 5299 hERG inhibitors with diverse chemical structures from a number of sources. Based on this dataset, we evaluated different machine learning (ML) and deep learning (DL) algorithms using various integer and binary type fingerprints. A training set of 3991 compounds was used to develop quantitative structure-activity relationship (QSAR) models. The performance of the developed models was evaluated using a test set of 998 compounds. Models were further validated using external set 1 (263 compounds) and external set 2 (47 compounds). Overall, models with integer type fingerprints showed better performance than models with no fingerprints, converted binary type fingerprints or original binary type fingerprints. Comparison of ML and DL algorithms revealed that integer type fingerprints are suitable for ML, whereas binary type fingerprints are suitable for DL. The outcomes of this study indicate that the rational selection of fingerprints is important for hERG blocker prediction.

Hydrophobic Drug/Toxin Binding Sites in Voltage-Dependent K+ and Na+ Channels

In the Na_v channel family the lipophilic drugs/toxins binding sites and the presence of fenestrations in the channel pore wall are well defined and categorized. No such classification exists in the much larger K_v channel family, although certain lipophilic compounds seem to deviate from binding to well-known hydrophilic binding sites. By mapping different compound binding sites onto 3D structures of Kv channels, there appear to be three distinct lipid-exposed binding sites preserved in K_v channels: the front and back side of the pore domain, and S2-S3/S3-S4 clefts. One or a combination of these sites is most likely the orthologous equivalent of neurotoxin site 5 in Na_v channels. This review describes the different lipophilic binding sites and location of pore wall fenestrations within the K_v channel family and compares it to the knowledge of Na_v channels.

Structures Illuminate Cardiac Ion Channel Functions in Health and in Long QT Syndrome

The cardiac action potential is critical to the production of a synchronized heartbeat. This electrical impulse is governed by the intricate activity of cardiac ion channels, among them the cardiac voltage-gated potassium (Kv) channels KCNQ1 and hERG as well as the voltage-gated sodium (Nav) channel encoded by SCN5A. Each channel performs a highly distinct function, despite sharing a common topology and structural components. These three channels are also the primary proteins mutated in congenital long QT syndrome (LQTS), a genetic condition that predisposes to cardiac arrhythmia and sudden cardiac death due to impaired repolarization of the action potential and has a particular proclivity for reentrant ventricular arrhythmias. Recent cryo-electron microscopy structures of human KCNQ1 and hERG, along with the rat homolog of SCN5A and other mammalian sodium channels, provide atomic-level insight into the structure and function of these proteins that advance our understanding of their distinct functions in the cardiac action potential, as well as the molecular basis of LQTS. In this review, the gating, regulation, LQTS mechanisms, and pharmacological properties of KCNQ1, hERG, and SCN5A are discussed in light of these recent structural findings.

hERG toxicity assessment: Useful guidelines for drug design

All along the drug development process, one of the most frequent adverse side effects, leading to the failure of drugs, is the cardiac arrhythmias. Such failure is mostly related to the capacity of the drug to inhibit the human ether-à-go-go-related gene (hERG) cardiac potassium channel. The early identification of hERG inhibition properties of biological active compounds has focused most of attention over the years. In order to prevent the cardiac side effects, a great number of in silico, in vitro and in vivo assays have been performed. The main goal of these studies is to understand the reasons of these effects, and then to give information or instructions to scientists involved in drug development to avoid the cardiac side effects. To evaluate anticipated cardiovascular effects, early evaluation of hERG toxicity has been strongly recommended for instance by the regulatory agencies such as U.S. Food and Drug Administration (FDA) and European Medicines Agency (EMA). Thus, following an initial screening of a collection of compounds to find hits, a great number of pharmacomodulation studies on the novel identified chemical series need to be performed including activity evaluation towards hERG. We provide in this concise review clear guidelines, based on described examples, illustrating successful optimization process to avoid hERG interactions as cases studies and to spur scientists to develop safe drugs.

Estrogen and calcium handling proteins: new discoveries and mechanisms in cardiovascular diseases

Estrogen deficiency is considered to be an important factor leading to cardiovascular diseases (CVDs). Indeed, the prevalence of CVDs in postmenopausal women exceeds that of premenopausal women and men of the same age. Recent research findings provide evidence that estrogen plays a pivotal role in the regulation of calcium homeostasis and therefore fine-tunes normal cardiomyocyte contraction and relaxation processes. Disruption of calcium homeostasis is closely associated with the pathological mechanism of CVDs. Thus, this paper maps out and summarizes the effects and mechanisms of estrogen on calcium handling proteins in cardiac myocytes, including L-type Ca²⁺ channel, the sarcoplasmic reticulum Ca²⁺ release channel named ryanodine receptor, sarco(endo)plasmic reticulum Ca²⁺-ATPase, and sodium-calcium exchanger. In so doing, we provide theoretical and experimental evidence for the successful design of estrogen-based prevention and treatment therapies for CVDs.

An Update on the Structure of hERG

The human voltage-sensitive K⁺ channel hERG plays a fundamental role in cardiac action potential repolarization, effectively controlling the QT interval of the electrocardiogram. Inherited loss- or gain-of-function mutations in hERG can result in dangerous “long” (LQTS) or “short” QT syndromes (SQTS), respectively, and the anomalous susceptibility of hERG to block by a diverse range of drugs underlies an acquired LQTS. A recent open channel cryo-EM structure of hERG should greatly advance understanding of the molecular basis of hERG channelopathies and drug-induced LQTS. Here we describe an update of recent research that addresses the nature of the particular gated state of hERG captured in the new structure, and the insight afforded by the structure into the molecular basis for high affinity drug block of hERG, the binding of hERG activators and the molecular basis of hERG's peculiar gating properties. Interpretation of the pharmacology of natural SQTS mutants in the context of the structure is a promising approach to understanding the molecular basis of hERG inactivation, and the structure suggests how voltage-dependent changes in the membrane domain may be transmitted to an extracellular “turret” to effect inactivation through aromatic side chain motifs that are conserved throughout the KCNH family of channels.

Revealing Molecular Determinants of hERG Blocker and Activator Binding

The Kv11.1 potassium channel, encoded by the human ether-a-go-go-related gene (hERG), plays an essential role in the cardiac action potential. hERG blockade by small molecules can induce "torsade de pointes" arrhythmias and sudden death; as such, it is an important off-target to avoid during drug discovery. Recently, a cryo-EM structure of the open channel state of hERG was reported, opening the door to in silico docking analyses and interpretation of hERG structure-activity relationships, with a view to avoiding blocking activity. Despite this, docking directly to this cryo-EM structure has been reported to yield binding modes that are unable to explain known mutagenesis data. In this work, we use molecular dynamics simulations to sample a range of channel conformations and run ensemble docking campaigns at the known hERG binding site below the selectivity filter, composed of the central cavity and the four deep hydrophobic pockets. We identify a hERG conformational state allowing discrimination of blockers vs nonblockers from docking; furthermore, the binding pocket agrees with mutagenesis data, and blocker binding modes fit the hERG blocker pharmacophore. We then use the same protocol to identify a binding pocket in the hERG channel pore for hERG activators, again agreeing with the reported mutagenesis. Our approach may be useful in drug discovery campaigns to prioritize candidate compounds based on hERG liability via virtual docking screens.

Calculation of absolute binding free energies between the hERG channel and structurally diverse drugs

The human ether-a-go-go-related gene (hERG) encodes a voltage-gated potassium channel that plays an essential role in the repolarization of action potentials in cardiac muscle. However, various drugs can block the ion current by binding to the hERG channel, resulting in potentially lethal cardiac arrhythmia. Accordingly, in silico studies are necessary to clarify the mechanisms of how these drugs bind to the hERG channel. Here, we used the experimental structure of the hERG channel, determined by cryo-electron microscopy, to perform docking simulations to predict the complex structures that occur between the hERG channel and structurally diverse drugs. The absolute binding free energies for the models were calculated using the MP-CAFEE method; calculated values were well correlated with experimental ones. By applying the regression equation obtained here, the affinity of a drug for the hERG channel can be accurately predicted from the calculated value of the absolute binding free energy.

The molecular determinants of R-roscovitine block of hERG channels

Human ether-à-go-go-related gene (Kv11.1, or hERG) is a potassium channel that conducts the delayed rectifier potassium current (I_Kr) during the repolarization phase of cardiac action potentials. hERG channels have a larger pore than other K⁺channels and can trap many unintended drugs, often resulting in acquired LQTS (aLQTS). R-roscovitine is a cyclin-dependent kinase (CDK) inhibitor that induces apoptosis in colorectal, breast, prostate, multiple myeloma, other cancer cell lines, and tumor xenografts, in micromolar concentrations. It is well tolerated in phase II clinical trials. R-roscovitine inhibits open hERG channels but does not become trapped in the pore. Two-electrode voltage clamp recordings from Xenopus oocytes expressing wild-type (WT) or hERG pore mutant channels (T623A, S624A, Y652A, F656A) demonstrated that compared to WT hERG, T623A, Y652A, and F656A inhibition by 200 μM R-roscovitine was ~ 48%, 29%, and 73% weaker, respectively. In contrast, S624A hERG was inhibited more potently than WT hERG, with a ~ 34% stronger inhibition. These findings were further supported by the IC₅₀ values, which were increased for T623A, Y652A and F656A (by ~5.5, 2.75, and 42 fold respectively) and reduced 1.3 fold for the S624A mutant. Our data suggest that while T623, Y652, and F656 are critical for R-roscovitine-mediated inhibition, S624 may not be. Docking studies further support our findings. Thus, R-roscovitine’s relatively unique features, coupled with its tolerance in clinical trials, could guide future drug screens.

LUF7244, an allosteric modulator/activator of Kv 11.1 channels, counteracts dofetilide-induced torsades de pointes arrhythmia in the chronic atrioventricular block dog model

BACKGROUND AND PURPOSE

K_v 11.1 (hERG) channel blockade is an adverse effect of many drugs and lead compounds, associated with lethal cardiac arrhythmias. LUF7244 is a negative allosteric modulator/activator of K_v 11.1 channels that inhibits early afterdepolarizations in vitro. We tested LUF7244 for antiarrhythmic efficacy and potential proarrhythmia in a dog model.

EXPERIMENTAL APPROACH

LUF7244 was tested in vitro for (a) increasing human I_Kv11.1 and canine I_Kr and (b) decreasing dofetilide-induced action potential lengthening and early afterdepolarizations in cardiomyocytes derived from human induced pluripotent stem cells and canine isolated ventricular cardiomyocytes. In vivo, LUF7244 was given intravenously to anaesthetized dogs in sinus rhythm or with chronic atrioventricular block.

KEY RESULTS

LUF7244 (0.5-10 μM) concentration dependently increased I_Kv11.1 by inhibiting inactivation. In vitro, LUF7244 (10 μM) had no effects on I_KIR2.1 , I_Nav1.5 , I_Ca-L , and I_Ks , doubled I_Kr , shortened human and canine action potential duration by approximately 50%, and inhibited dofetilide-induced early afterdepolarizations. LUF7244 (2.5 mg·kg^-1 ·15 min^-1 ) in dogs with sinus rhythm was not proarrhythmic and shortened, non-significantly, repolarization parameters (QTc: -6.8%). In dogs with chronic atrioventricular block, LUF7244 prevented dofetilide-induced torsades de pointes arrhythmias in 5/7 animals without normalization of the QTc. Peak LUF7244 plasma levels were 1.75 ± 0.80 during sinus rhythm and 2.34 ± 1.57 μM after chronic atrioventricular block.

CONCLUSIONS AND IMPLICATIONS

LUF7244 counteracted dofetilide-induced early afterdepolarizations in vitro and torsades de pointes in vivo. Allosteric modulators/activators of K_v 11.1 channels might neutralize adverse cardiac effects of existing drugs and newly developed compounds that display QTc lengthening.

Histidine at position 462 determines the low quinine sensitivity of ether-à-go-go channel superfamily member Kv 12.1

BACKGROUND AND PURPOSE

The ether-à-go-go (Eag) Kv superfamily comprises closely related Kv 10, Kv 11, and Kv 12 subunits. Kv 11.1 (termed hERG in humans) gained much attention, as drug-induced inhibition of these channels is a frequent cause of sudden death in humans. The exclusive drug sensitivity of Kv 11.1 can be explained by central drug-binding pockets that are absent in most other channels. Currently, it is unknown whether Kv 12 channels are equipped with an analogous drug-binding pocket and whether drug-binding properties are conserved in all Eag superfamily members.

EXPERIMENTAL APPROACH

We analysed sensitivity of recombinant Kv 12.1 channels to quinine, a substituted quinoline that blocks Kv 10.1 and Kv 11.1 at low micromolar concentrations.

KEY RESULTS

Quinine inhibited Kv 12.1, but its affinity was 10-fold lower than for Kv 11.1. Contrary to Kv 11.1, quinine inhibited Kv 12.1 in a largely voltage-independent manner and induced channel opening at more depolarised potentials. Low sensitivity of Kv 12.1 and characteristics of quinine-dependent inhibition were determined by histidine 462, as site-directed mutagenesis of this residue into the homologous tyrosine of Kv 11.1 conferred Kv 11.1-like quinine block to Kv 12.1(H462Y). Molecular modelling demonstrated that the low affinity of Kv 12.1 was determined by only weak interactions of residues in the central cavity with quinine. In contrast, more favourable interactions can explain the higher quinine sensitivity of Kv 12.1(H462Y) and Kv 11.1 channels.

CONCLUSIONS AND IMPLICATIONS

The quinoline-binding "motif" is not conserved within the Eag superfamily, although the overall architecture of these channels is apparently similar. Our findings highlight functional and pharmacological diversity in this group of evolutionary-conserved channels.

Potent hERG channel inhibition by sarizotan, an investigative treatment for Rett Syndrome

Rett Syndrome (RTT) is an X-linked neurodevelopmental disorder associated with respiratory abnormalities and, in up to ~40% of patients, with prolongation of the cardiac QT_c interval. QT_c prolongation calls for cautious use of drugs with a propensity to inhibit hERG channels. The STARS trial has been undertaken to investigate the efficacy of sarizotan, a 5-HT_1A receptor agonist, at correcting RTT respiratory abnormalities. The present study investigated whether sarizotan inhibits hERG potassium channels and prolongs ventricular repolarization. Whole-cell patch-clamp measurements were made at 37 °C from hERG-expressing HEK293 cells. Docking analysis was conducted using a recent cryo-EM structure of hERG. Sarizotan was a potent inhibitor of hERG current (I_hERG; IC₅₀ of 183 nM) and of native ventricular I_Kr from guinea-pig ventricular myocytes. 100 nM and 1 μM sarizotan prolonged ventricular action potential (AP) duration (APD₉₀) by 14.1 ± 3.3% (n = 6) and 29.8 ± 3.1% (n = 5) respectively and promoted AP triangulation. High affinity I_hERG inhibition by sarizotan was contingent upon channel gating and intact inactivation. Mutagenesis experiments and docking analysis implicated F557, S624 and Y652 residues in sarizotan binding, with weaker contribution from F656. In conclusion, sarizotan inhibits I_Kr/I_hERG, accessing key binding residues on channel gating. This action and consequent ventricular AP prolongation occur at concentrations relevant to those proposed to treat breathing dysrhythmia in RTT. Sarizotan should only be used in RTT patients with careful evaluation of risk factors for QT_c prolongation.

Temperature effect on the magnetic oscillations in 2D materials

We study the magnetic oscillations (MO) in 2D materials with a buckled honeycomb lattice, considering a perpendicular electric and magnetic field. At zero temperature the MO consist of the sum of four sawtooth oscillations, with two unique frequencies and phases. The values of these frequencies depend on the Fermi energy and electric field, which in turn determine the condition for a beating phenomenon in the MO. We analyse the temperature effect in the MO by considering its local corrections over each magnetization peak, given by Fermi-Dirac like functions. We show that the width of these functions is related to the minimum temperature necessary to observe the spin and valley properties in the MO. In particular, we find that in order to observe the spin splitting, the width must be lower than the MO phase difference. Likewise, in order to observe valley mixing effects, the width must be lower than the MO period. We also show that at high temperatures, all the maxima and minima in the MO shift to a constant value, in which case we obtain a simple expression for the MO and its envelope. The results obtained show unique features in the MO in 2D materials, given by the interplay between the valley and spin.

TASK Channels Pharmacology: New Challenges in Drug Design

Rational drug design targeting ion channels is an exciting and always evolving research field. New medicinal chemistry strategies are being implemented to explore the wild chemical space and unravel the molecular basis of the ion channels modulators binding mechanisms. TASK channels belong to the two-pore domain potassium channel family and are modulated by extracellular acidosis. They are extensively distributed along the cardiovascular and central nervous systems, and their expression is up- and downregulated in different cancer types, which makes them an attractive therapeutic target. However, TASK channels remain unexplored, and drugs designed to target these channels are poorly selective. Here, we review TASK channels properties and their known blockers and activators, considering the new challenges in ion channels drug design and focusing on the implementation of computational methodologies in the drug discovery process.

On the potential of in vitro organ-chip models to define temporal pharmacokinetic-pharmacodynamic relationships

Functional human-on-a-chip systems hold great promise to enable quantitative translation to in vivo outcomes. Here, we explored this concept using a pumpless heart only and heart:liver system to evaluate the temporal pharmacokinetic/pharmacodynamic (PKPD) relationship for terfenadine. There was a time dependent drug-induced increase in field potential duration in the cardiac compartment in response to terfenadine and that response was modulated using a metabolically competent liver module that converted terfenadine to fexofenadine. Using this data, a mathematical model was developed to predict the effect of terfenadine in preclinical species. Developing confidence that microphysiological models could have a transformative effect on drug discovery, we also tested a previously discovered proprietary AstraZeneca small molecule and correctly determined the cardiotoxic response to its metabolite in the heart:liver system. Overall our findings serve as a guiding principle to future investigations of temporal concentration response relationships in these innovative in vitro models, especially, if validated across multiple time frames, with additional pharmacological mechanisms and molecules representing a broad chemical diversity.

The Pore-Lipid Interface: Role of Amino-Acid Determinants of Lipophilic Access by Ivabradine to the hERG1 Pore Domain

Abnormal cardiac electrical activity is a common side effect caused by unintended block of the promiscuous drug target human ether-à-go-go-related gene (hERG1), the pore-forming domain of the delayed rectifier K⁺ channel in the heart. hERG1 block leads to a prolongation of the QT interval, a phase of the cardiac cycle that underlies myocyte repolarization detectable on the electrocardiogram. Even newly released drugs such as heart-rate lowering agent ivabradine block the rapid delayed rectifier current I_Kr, prolong action potential duration, and induce potentially lethal arrhythmia known as torsades de pointes. In this study, we describe a critical drug-binding pocket located at the lateral pore surface facing the cellular membrane. Mutations of the conserved M651 residue alter ivabradine-induced block but not by the common hERG1 blocker dofetilide. As revealed by molecular dynamics simulations, binding of ivabradine to a lipophilic pore access site is coupled to a state-dependent reorientation of aromatic residues F557 and F656 in the S5 and S6 helices. We show that the M651 mutation impedes state-dependent dynamics of F557 and F656 aromatic cassettes at the protein-lipid interface, which has a potential to disrupt drug-induced block of the channel. This fundamentally new mechanism coupling the channel dynamics and small-molecule access from the membrane into the hERG1 intracavitary site provides a simple rationale for the well established state-dependence of drug blockade. SIGNIFICANCE STATEMENT: The drug interference with the function of the cardiac hERG channels represents one of the major sources of drug-induced heart disturbances. We found a novel and a critical drug-binding pocket adjacent to a lipid-facing surface of the hERG1 channel, which furthers our molecular understanding of drug-induced QT syndrome.

Identification of a novel potassium channel (GiK) as a potential drug target in Giardia lamblia: Computational descriptions of binding sites

Background

The protozoan Giardia lamblia is the causal agent of giardiasis, one of the main diarrheal infections worldwide. Drug resistance to common antigiardial agents and incidence of treatment failures have increased in recent years. Therefore, the search for new molecular targets for drugs against Giardia infection is essential. In protozoa, ionic channels have roles in their life cycle, growth, and stress response. Thus, they are promising targets for drug design. The strategy of ligand-protein docking has demonstrated a great potential in the discovery of new targets and structure-based drug design studies.

Methods

In this work, we identify and characterize a new potassium channel, GiK, in the genome of Giardia lamblia. Characterization was performed in silico. Because its crystallographic structure remains unresolved, homology modeling was used to construct the three-dimensional model for the pore domain of GiK. The docking virtual screening approach was employed to determine whether GiK is a good target for potassium channel blockers.

Results

The GiK sequence showed 24–50% identity and 50–90% positivity with 21 different types of potassium channels. The quality assessment and validation parameters indicated the reliability of the modeled structure of GiK. We identified 110 potassium channel blockers exhibiting high affinity toward GiK. A total of 39 of these drugs bind in three specific regions.

Discussion

The GiK pore signature sequence is related to the small conductance calcium-activated potassium channels (SKCa). The predicted binding of 110 potassium blockers to GiK makes this protein an attractive target for biological testing to evaluate its role in the life cycle of Giardia lamblia and potential candidate for the design of novel antigiardial drugs.