The scorpion toxin BeKm-1 blocks hERG cardiac potassium channels using an indispensable arginine residue.

BeKm-1 is a peptide toxin from scorpion venom that blocks the pore of the potassium channel hERG (Kv11.1) in the human heart. Although individual protein structures have been resolved, the structure of the complex between hERG and BeKm-1 is unknown. Here, we used molecular dynamics and ensemble docking, guided by previous double-mutant cycle analysis data, to obtain an in silico model of the hERG-BeKm-1 complex. Adding to the previous mutagenesis study of BeKm-1, our model uncovers the key role of residue Arg20, which forms three interactions (a salt bridge and hydrogen bonds) with the channel vestibule simultaneously. Replacement of this residue even by lysine weakens the interactions significantly. In accordance, the recombinantly produced BeKm-1R20K mutant exhibited dramatically decreased activity on hERG. Our model may be useful for future drug design attempts.

hERG1 channel subunit composition mediates proton inhibition of rapid delayed rectifier potassium current (IKr) in cardiomyocytes derived from hiPSCs.

The voltage-gated channel, hERG1, conducts the rapid delayed rectifier potassium current (IKr) and is critical for human cardiac repolarization. Reduced IKr causes long QT syndrome and increases the risk for cardiac arrhythmia and sudden death. At least two subunits form functional hERG1 channels, hERG1a and hERG1b. Changes in hERG1a/1b abundance modulate IKr kinetics, magnitude, and drug sensitivity. Studies from native cardiac tissue suggest that hERG1 subunit abundance is dynamically regulated, but the impact of altered subunit abundance on IKr and its response to external stressors is not well understood. Here, we used a substrate-driven human-induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) maturation model to investigate how changes in relative hERG1a/1b subunit abundance impact the response of native IKr to extracellular acidosis, a known component of ischemic heart disease and sudden infant death syndrome. IKr recorded from immatured hiPSC-CMs displays a 2-fold greater inhibition by extracellular acidosis (pH 6.3) compared with matured hiPSC-CMs. Quantitative RT-PCR and immunocytochemistry demonstrated that hERG1a subunit mRNA and protein were upregulated and hERG1b subunit mRNA and protein were downregulated in matured hiPSC-CMs compared with immatured hiPSC-CMs. The shift in subunit abundance in matured hiPSC-CMs was accompanied by increased IKr. Silencing hERG1b's impact on native IKr kinetics by overexpressing a polypeptide identical to the hERG1a N-terminal Per-Arnt-Sim domain reduced the magnitude of IKr proton inhibition in immatured hiPSC-CMs to levels comparable to those observed in matured hiPSC-CMs. These data demonstrate that hERG1 subunit abundance is dynamically regulated and determines IKr proton sensitivity in hiPSC-CMs.

Molecular dynamics simulations suggest possible activation and deactivation pathways in the hERG channel.

The elusive activation/deactivation mechanism of hERG is investigated, a voltage-gated potassium channel involved in severe inherited and drug-induced cardiac channelopathies, including the Long QT Syndrome. Firstly, the available structural data are integrated by providing a homology model for the closed state of the channel. Secondly, molecular dynamics combined with a network analysis revealed two distinct pathways coupling the voltage sensor domain with the pore domain. Interestingly, some LQTS-related mutations known to impair the activation/deactivation mechanism are distributed along the identified pathways, which thus suggests a microscopic interpretation of their role. Split channels simulations clarify a surprising feature of this channel, which is still able to gate when a cut is introduced between the voltage sensor domain and the neighboring helix S5. In summary, the presented results suggest possible activation/deactivation mechanisms of non-domain-swapped potassium channels that may aid in biomedical applications.

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.

H1153Y-KCNH2 Mutation Identified in a Sudden Arrhythmic Death Syndrome Case Alters Channel Gating.

Long QT syndrome is one of the most common hereditary channelopathies inducing fatal arrhythmias and sudden cardiac death. We identified in a sudden arrhythmic death syndrome case a C-term KCNH2 mutation (c.3457C > T; p.His1153Tyr) classified as variant of unknown significance and functional impact. Heterologous expression in HEK293 cells combined with western-blot, flow-cytometry, immunocytochemical and microscope analyses shows no modification of channel trafficking to the cell membrane. Electrophysiological studies reveal that the mutation causes a loss of HERG channel function through an alteration of channel biophysical properties that reduces the current density leading to LQT2. These results provide the first functional evidence for H1153Y-KCNH2 mutation-induced abnormal channel properties. They concur with previous biophysical and clinical presentations of a survived patient with another variant that is G1036D. Therefore, the present report importantly highlights the potential severity of variants that may have useful implications for treatment, surveillance, and follow-up of LQT2 patients.

Machine learning models for classification tasks related to drug safety.

In this review, we outline the current trends in the field of machine learning-driven classification studies related to ADME (absorption, distribution, metabolism and excretion) and toxicity endpoints from the past six years (2015-2021). The study focuses only on classification models with large datasets (i.e. more than a thousand compounds). A comprehensive literature search and meta-analysis was carried out for nine different targets: hERG-mediated cardiotoxicity, blood-brain barrier penetration, permeability glycoprotein (P-gp) substrate/inhibitor, cytochrome P450 enzyme family, acute oral toxicity, mutagenicity, carcinogenicity, respiratory toxicity and irritation/corrosion. The comparison of the best classification models was targeted to reveal the differences between machine learning algorithms and modeling types, endpoint-specific performances, dataset sizes and the different validation protocols. Based on the evaluation of the data, we can say that tree-based algorithms are (still) dominating the field, with consensus modeling being an increasing trend in drug safety predictions. Although one can already find classification models with great performances to hERG-mediated cardiotoxicity and the isoenzymes of the cytochrome P450 enzyme family, these targets are still central to ADMET-related research efforts.

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 KV11.1 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.

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.

Toward in vivo-relevant hERG safety assessment and mitigation strategies based on relationships between non-equilibrium blocker binding, three-dimensional channel-blocker interactions, dynamic occupancy, dynamic exposure, and cellular arrhythmia.

The human ether-a-go-go-related voltage-gated cardiac ion channel (commonly known as hERG) conducts the rapid outward repolarizing potassium current in cardiomyocytes (IKr). Inadvertent blockade of this channel by drug-like molecules represents a key challenge in pharmaceutical R&D due to frequent overlap between the structure-activity relationships of hERG and many primary targets. Building on our previous work, together with recent cryo-EM structures of hERG, we set about to better understand the energetic and structural basis of promiscuous blocker-hERG binding in the context of Biodynamics theory. We propose a two-step blocker binding process consisting of: The initial capture step: diffusion of a single fully solvated blocker copy into a large cavity lined by the intra-cellular cyclic nucleotide binding homology domain (CNBHD). Occupation of this cavity is a necessary but insufficient condition for ion current disruption.The IKr disruption step: translocation of the captured blocker along the channel axis, such that: The head group, consisting of a quasi-rod-shaped moiety, projects into the open pore, accompanied by partial de-solvation of the binding interface.One tail moiety packs along a kink between the S6 helix and proximal C-linker helix adjacent to the intra-cellular entrance of the pore, likewise accompanied by mutual de-solvation of the binding interface (noting that the association barrier is comprised largely of the total head + tail group de-solvation cost).Blockers containing a highly planar moiety that projects into a putative constriction zone within the closed channel become trapped upon closing, as do blockers terminating prior to this region.A single captured blocker copy may conceivably associate and dissociate to/from the pore many times before exiting the CNBHD cavity. Lastly, we highlight possible flaws in the current hERG safety index (SI), and propose an alternate in vivo-relevant strategy factoring in: Benefit/risk.The predicted arrhythmogenic fractional hERG occupancy (based on action potential (AP) simulations of the undiseased human ventricular cardiomyocyte).Alteration of the safety threshold due to underlying disease.Risk of exposure escalation toward the predicted arrhythmic limit due to patient-to-patient pharmacokinetic (PK) variability, drug-drug interactions, overdose, and use for off-label indications in which the hERG safety parameters may differ from their on-label counterparts.

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.

Evaluation of QSAR Equations for Virtual Screening.

Quantitative Structure Activity Relationship (QSAR) models can inform on the correlation between activities and structure-based molecular descriptors. This information is important for the understanding of the factors that govern molecular properties and for designing new compounds with favorable properties. Due to the large number of calculate-able descriptors and consequently, the much larger number of descriptors combinations, the derivation of QSAR models could be treated as an optimization problem. For continuous responses, metrics which are typically being optimized in this process are related to model performances on the training set, for example, R2 and QCV2. Similar metrics, calculated on an external set of data (e.g., QF1/F2/F32), are used to evaluate the performances of the final models. A common theme of these metrics is that they are context -" ignorant". In this work we propose that QSAR models should be evaluated based on their intended usage. More specifically, we argue that QSAR models developed for Virtual Screening (VS) should be derived and evaluated using a virtual screening-aware metric, e.g., an enrichment-based metric. To demonstrate this point, we have developed 21 Multiple Linear Regression (MLR) models for seven targets (three models per target), evaluated them first on validation sets and subsequently tested their performances on two additional test sets constructed to mimic small-scale virtual screening campaigns. As expected, we found no correlation between model performances evaluated by "classical" metrics, e.g., R2 and QF1/F2/F32 and the number of active compounds picked by the models from within a pool of random compounds. In particular, in some cases models with favorable R2 and/or QF1/F2/F32 values were unable to pick a single active compound from within the pool whereas in other cases, models with poor R2 and/or QF1/F2/F32 values performed well in the context of virtual screening. We also found no significant correlation between the number of active compounds correctly identified by the models in the training, validation and test sets. Next, we have developed a new algorithm for the derivation of MLR models by optimizing an enrichment-based metric and tested its performances on the same datasets. We found that the best models derived in this manner showed, in most cases, much more consistent results across the training, validation and test sets and outperformed the corresponding MLR models in most virtual screening tests. Finally, we demonstrated that when tested as binary classifiers, models derived for the same targets by the new algorithm outperformed Random Forest (RF) and Support Vector Machine (SVM)-based models across training/validation/test sets, in most cases. We attribute the better performances of the Enrichment Optimizer Algorithm (EOA) models in VS to better handling of inactive random compounds. Optimizing an enrichment-based metric is therefore a promising strategy for the derivation of QSAR models for classification and virtual screening.

Long QT Syndrome Type 2: Emerging Strategies for Correcting Class 2 KCNH2 (hERG) Mutations and Identifying New Patients.

Significant advances in our understanding of the molecular mechanisms that cause congenital long QT syndrome (LQTS) have been made. A wide variety of experimental approaches, including heterologous expression of mutant ion channel proteins and the use of inducible pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) from LQTS patients offer insights into etiology and new therapeutic strategies. This review briefly discusses the major molecular mechanisms underlying LQTS type 2 (LQT2), which is caused by loss-of-function (LOF) mutations in the KCNH2 gene (also known as the human ether-à-go-go-related gene or hERG). Almost half of suspected LQT2-causing mutations are missense mutations, and functional studies suggest that about 90% of these mutations disrupt the intracellular transport, or trafficking, of the KCNH2-encoded Kv11.1 channel protein to the cell surface membrane. In this review, we discuss emerging strategies that improve the trafficking and functional expression of trafficking-deficient LQT2 Kv11.1 channel proteins to the cell surface membrane and how new insights into the structure of the Kv11.1 channel protein will lead to computational approaches that identify which KCNH2 missense variants confer a high-risk for LQT2.

Serine mutation of a conserved threonine in the hERG K+ channel S6-pore region leads to loss-of-function through trafficking impairment.

The human Ether-à-go-go Related Gene (hERG) encodes a potassium channel responsible for the cardiac rapid delayed rectifier K+ current, IKr, which regulates ventricular repolarization. Loss-of-function hERG mutations underpin the LQT2 form of congenital long QT syndrome. This study was undertaken to elucidate the functional consequences of a variant of uncertain significance, T634S, located at a highly conserved position at the top of the S6 helix of the hERG channel. Whole-cell patch-clamp recordings were made at 37 °C of hERG current (IhERG) from HEK 293 cells expressing wild-type (WT) hERG, WT+T634S and hERG-T634S alone. When the T634S mutation was expressed alone little or no IhERG could be recorded. Co-expressing WT and hERG-T634S suppressed IhERG tails by ∼57% compared to WT alone, without significant alteration of voltage dependent activation of IhERG. A similar suppression of IhERG was observed under action potential voltage clamp. Comparable reduction of IKr in a ventricular AP model delayed repolarization and led to action potential prolongation. A LI-COR® based On/In-Cell Western assay showed that cell surface expression of hERG channels in HEK 293 cells was markedly reduced by the T634S mutation, whilst total cellular hERG expression was unaffected, demonstrating impaired trafficking of the hERG-T634S mutant. Incubation with E-4031, but not lumacaftor, rescued defective hERG-T634S channel trafficking and IhERG density. In conclusion, these data identify hERG-T634S as a rescuable trafficking defective mutation that reduces IKr sufficiently to delay repolarization and, thereby, potentially produce a LQT2 phenotype.

HERG channel and cancer: A mechanistic review of carcinogenic processes and therapeutic potential.

The human ether-à-go-go related gene (HERG) encodes the alpha subunit of Kv11.1, which is a voltage-gated K+ channel protein mainly expressed in heart and brain tissue. HERG plays critical role in cardiac repolarization, and mutations in HERG can cause long QT syndrome. More recently, evidence has emerged that HERG channels are aberrantly expressed in many kinds of cancer cells and play important roles in cancer progression. HERG could therefore be a potential biomarker for cancer and a possible molecular target for anticancer drug design. HERG affects a number of cellular processes, including cell proliferation, apoptosis, angiogenesis and migration, any of which could be affected by dysregulation of HERG. This review provides an overview of available information on HERG channel as it relates to cancer, with focus on the mechanism by which HERG influences cancer progression. Molecular docking attempts suggest two possible protein-protein interactions of HERG with the ß1-integrin receptor and the transcription factor STAT-1 as novel HERG-directed therapeutic targeting which avoids possible cardiotoxicity. The role of epigenetics in regulating HERG channel expression and activity in cancer will also be discussed. Finally, given its inherent extracellular accessibility as an ion channel, we discuss regulatory roles of this molecule in cancer physiology and therapeutic potential. Future research should be directed to explore the possibilities of therapeutic interventions targeting HERG channels while minding possible complications.

A Computational Pipeline to Predict Cardiotoxicity: From the Atom to the Rhythm.

RATIONALE: Drug-induced proarrhythmia is so tightly associated with prolongation of the QT interval that QT prolongation is an accepted surrogate marker for arrhythmia. But QT interval is too sensitive a marker and not selective, resulting in many useful drugs eliminated in drug discovery. OBJECTIVE: To predict the impact of a drug from the drug chemistry on the cardiac rhythm. METHODS AND RESULTS: In a new linkage, we connected atomistic scale information to protein, cell, and tissue scales by predicting drug-binding affinities and rates from simulation of ion channel and drug structure interactions and then used these values to model drug effects on the hERG channel. Model components were integrated into predictive models at the cell and tissue scales to expose fundamental arrhythmia vulnerability mechanisms and complex interactions underlying emergent behaviors. Human clinical data were used for model framework validation and showed excellent agreement, demonstrating feasibility of a new approach for cardiotoxicity prediction. CONCLUSIONS: We present a multiscale model framework to predict electrotoxicity in the heart from the atom to the rhythm. Novel mechanistic insights emerged at all scales of the system, from the specific nature of proarrhythmic drug interaction with the hERG channel, to the fundamental cellular and tissue-level arrhythmia mechanisms. Applications of machine learning indicate necessary and sufficient parameters that predict arrhythmia vulnerability. We expect that the model framework may be expanded to make an impact in drug discovery, drug safety screening for a variety of compounds and targets, and in a variety of regulatory processes.

Chlorpromazine binding to the PAS domains uncovers the effect of ligand modulation on EAG channel activity.

Ether-a-go-go (EAG) potassium selective channels are major regulators of neuronal excitability and cancer progression. EAG channels contain a Per-Arnt-Sim (PAS) domain in their intracellular N-terminal region. The PAS domain is structurally similar to the PAS domains in non-ion channel proteins, where these domains frequently function as ligand-binding domains. Despite the structural similarity, it is not known whether the PAS domain can regulate EAG channel function via ligand binding. Here, using surface plasmon resonance, tryptophan fluorescence, and analysis of EAG currents recorded in Xenopus laevis oocytes, we show that a small molecule chlorpromazine (CH), widely used as an antipsychotic medication, binds to the isolated PAS domain of EAG channels and inhibits currents from these channels. Mutant EAG channels that lack the PAS domain show significantly lower inhibition by CH, suggesting that CH affects currents from EAG channels directly through the binding to the PAS domain. Our study lends support to the hypothesis that there are previously unaccounted steps in EAG channel gating that could be activated by ligand binding to the PAS domain. This has broad implications for understanding gating mechanisms of EAG and related ERG and ELK K+ channels and places the PAS domain as a new target for drug discovery in EAG and related channels. Up-regulation of EAG channel activity is linked to cancer and neurological disorders. Our study raises the possibility of repurposing the antipsychotic drug chlorpromazine for treatment of neurological disorders and cancer.

Selectivity filter modalities and rapid inactivation of the hERG1 channel.

The human ether-á-go-go-related gene (hERG1) channel conducts small outward K+ currents that are critical for cardiomyocyte membrane repolarization. The gain-of-function mutation N629D at the outer mouth of the selectivity filter (SF) disrupts inactivation and K+-selective transport in hERG1, leading to arrhythmogenic phenotypes associated with long-QT syndrome. Here, we combined computational electrophysiology with Markov state model analysis to investigate how SF-level gating modalities control selective cation transport in wild-type (WT) and mutant (N629D) hERG1 variants. Starting from the recently reported cryogenic electron microscopy (cryo-EM) open-state channel structure, multiple microseconds-long molecular-dynamics (MD) trajectories were generated using different cation configurations at the filter, voltages, electrolyte concentrations, and force-field parameters. Most of the K+ permeation events observed in hERG1-WT simulations occurred at microsecond timescales, influenced by the spontaneous dehydration/rehydration dynamics at the filter. The SF region displayed conductive, constricted, occluded, and dilated states, in qualitative agreement with the well-documented flickering conductance of hERG1. In line with mutagenesis studies, these gating modalities resulted from dynamic interaction networks involving residues from the SF, outer-mouth vestibule, P-helices, and S5-P segments. We found that N629D mutation significantly stabilizes the SF in a state that is permeable to both K+ and Na+, which is reminiscent of the SF in the nonselective bacterial NaK channel. Increasing the external K+ concentration induced "WT-like" SF dynamics in N629D, in qualitative agreement with the recovery of flickering currents in experiments. Overall, our findings provide an understanding of the molecular mechanisms controlling selective transport in K+ channels with a nonconventional SF sequence.

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.

Toward a Structural View of hERG Activation by the Small-Molecule Activator ICA-105574.

Outward current conducted by human ether-à-go-go-related gene type 1 (hERG1) K+ channels is important for action potential repolarization in the human ventricle. Rapid, voltage-dependent inactivation greatly reduces outward currents conducted by hERG1 channels and involves conformational changes in the ion selectivity filter (SF). Recently, compounds have been found that activate hERG1 channel function by modulating gating mechanisms such as reducing inactivation. Such activating compounds could represent a novel approach to prevent arrhythmias associated with prolonged ventricular repolarization associated with inherited or acquired long QT syndrome. ICA-105574 (ICA), a 3-nitro-n-(4-phenoxyphenyl) benzamide derivative activates hERG1 by strongly attenuating pore-type inactivation. We previously mapped the putative binding site for ICA to a hydrophobic pocket located between two adjacent subunits. Here, we used the recently reported cryoelectron microscopy structures of hERG1 to elucidate the structural mechanisms by which ICA influences the stability of the SF. By combining molecular dynamics simulations, voltage-clamp electrophysiology, and the synthesis of novel ICA derivatives, we provide atomistic insights into SF dynamics and propose a structural link between the SF and S6 segments. Further, our study highlights the importance of the nitro moiety, at the meta position of the benzamide ring, for the activity of ICA and reveals that the (bio)isosteric substitution of this side chain can switch the activity to weak inhibitors. Our findings indicate that ICA increases the stability of the SF to attenuate channel inactivation, and this action requires a fine-tuned compound geometry.

Identification of a proton sensor that regulates conductance and open time of single hERG channels.

The hERG potassium channel influences ventricular action potential duration. Extracellular acidosis occurs in pathological states including cardiac ischaemia. It reduces the amplitude of hERG current and speeds up deactivation, which can alter cardiac excitability. This study aimed to identify the site of action by which extracellular protons regulate the amplitude of macroscopic hERG current. Recordings of macroscopic and single hERG1a and 1b channel activity, mutagenesis, and the recent cryoEM structure for hERG were employed. Single hERG1a and 1b channels displayed open times that decreased with membrane depolarization, suggestive of a blocking mechanism that senses approximately 20% of the membrane electric field. This mechanism was sensitive to pH; extracellular acidosis reduced both hERG1a and1b channel open time and conductance. The effects of acidosis on macroscopic current amplitude and deactivation displayed different sensitivities to protons. Point mutation of a pair of residues (E575/H578) in the pore turret abolished the acidosis-induced decrease of current amplitude, without affecting the change in current deactivation. In single hERG1a channel recordings, the conductance of the double-mutant channel was unaffected by extracellular acidosis. These findings identify residues in the outer turret of the hERG channel that act as a proton sensor to regulate open time and channel conductance.