Kv1.3 in the spotlight for treating immune diseases.

INTRODUCTION: Kv1.3 is the main voltage-gated potassium channel of leukocytes from both the innate and adaptive immune systems. Channel function is required for common processes such as Ca2+ signaling but also for cell-specific events. In this context, alterations in Kv1.3 are associated with multiple immune disorders. Excessive channel activity correlates with numerous autoimmune diseases, while reduced currents result in increased cancer prevalence and immunodeficiencies. AREAS COVERED: This review offers a general view of the role of Kv1.3 in every type of leukocyte. Moreover, diseases stemming from dysregulations of the channel are detailed, as well as current advances in their therapeutic research. EXPERT OPINION: Kv1.3 arises as a potential immune target in a variety of diseases. Several lines of research focused on channel modulation have yielded positive results. However, among the great variety of specific channel blockers, only one has reached clinical trials. Future investigations should focus on developing simpler administration routes for channel inhibitors to facilitate their entrance into clinical trials. Prospective Kv1.3-based treatments will ensure powerful therapies while minimizing undesired side effects.

Isolation and structural identification of a potassium ion channel Kv4.1 inhibitor SsTx-P2 from centipede venom. / 蜈蚣毒液中钾离子通道Kv4.1抑制剂SsTx-P2的分离和结构鉴定.

OBJECTIVES: To isolate a potassium ion channel Kv4.1 inhibitor from centipede venom, and to determine its sequence and structure. METHODS: Ion-exchange chromatography and reversed-phase high-performance liquid chromatography were performed to separate and purify peptide components of centipede venom, and their inhibiting effect on Kv4.1 channel was determined by whole-cell patch clamp recording. The molecular weight of isolated peptide Kv4.1 channel inhibitor was identified with matrix assisted laser desorption ionization-time-of-flight mass spectrometry; its primary sequence was determined by Edman degradation sequencing and two-dimensional mass spectrometry; its structure was established based on iterative thread assembly refinement online analysis. RESULTS: A peptide SsTx-P2 was separated from centipede venom with the molecular weight of 6122.8, and its primary sequence consists of 53 amino acid residues NH2-ELTWDFVRTCCKLFPDKSECTKACATEFTGGDESRLKDVWPRKLRSGDSRLKD-OH. Peptide SsTx-P2 potently inhibited the current of Kv4.1 channel transiently transfected in HEK293 cell, with 1.0 µmol/L SsTx-P2 suppressing 95% current of Kv4.1 channel. Its structure showed that SsTx-P2 shared a conserved helical structure. CONCLUSIONS: The study has isolated a novel peptide SsTx-P2 from centipede venom, which can potently inhibit the potassium ion channel Kv4.1 and displays structural conservation.

Benchmarking of Small Molecule Feature Representations for hERG, Nav1.5, and Cav1.2 Cardiotoxicity Prediction.

In the field of drug discovery, there is a substantial challenge in seeking out chemical structures that possess desirable pharmacological, toxicological, and pharmacokinetic properties. Complications arise when drugs interfere with the functioning of cardiac ion channels, leading to serious cardiovascular consequences. The discontinuation and removal of numerous approved drugs from the market or at late development stages in the pipeline due to such inhibitory effects further highlight the urgency of addressing this issue. Consequently, the early prediction of potential blockers targeting cardiac ion channels during the drug discovery process is of paramount importance. This study introduces a deep learning framework that computationally determines the cardiotoxicity associated with the voltage-gated potassium channel (hERG), the voltage-gated calcium channel (Cav1.2), and the voltage-gated sodium channel (Nav1.5) for drug candidates. The predictive capabilities of three feature representations─molecular fingerprints, descriptors, and graph-based numerical representations─are rigorously benchmarked. Additionally, a novel training and evaluation data set framework is presented, enabling predictive model training of drug off-target cardiotoxicity using a comprehensive and large curated data set covering these three cardiac ion channels. To facilitate these predictions, a robust and comprehensive small molecule cardiotoxicity prediction tool named CToxPred has been developed. It is made available as open source under the permissive MIT license at https://github.com/issararab/CToxPred.

Selective block of human Kv1.1 channels and an epilepsy-associated gain-of-function mutation by AETX-K peptide.

Dysfunction of the human voltage-gated K+ channel Kv1.1 has been associated with epilepsy, multiple sclerosis, episodic ataxia, myokymia, and cardiorespiratory dysregulation. We report here that AETX-K, a sea anemone type I (SAK1) peptide toxin we isolated from a phage display library, blocks Kv1.1 with high affinity (Ki ~ 1.6 pM) and notable specificity, inhibiting other Kv channels we tested a million-fold less well. Nuclear magnetic resonance (NMR) was employed both to determine the three-dimensional structure of AETX-K, showing it to employ a classic SAK1 scaffold while exhibiting a unique electrostatic potential surface, and to visualize AETX-K bound to the Kv1.1 pore domain embedded in lipoprotein nanodiscs. Study of Kv1.1 in Xenopus oocytes with AETX-K and point variants using electrophysiology demonstrated the blocking mechanism to employ a toxin-channel configuration we have described before whereby AETX-K Lys23 , two positions away on the toxin interaction surface from the classical blocking residue, enters the pore deeply enough to interact with K+ ions traversing the pathway from the opposite side of the membrane. The mutant channel Kv1.1-L296 F is associated with pharmaco-resistant multifocal epilepsy in infants because it significantly increases K+ currents by facilitating opening and slowing closure of the channels. Consistent with the therapeutic potential of AETX-K for Kv1.1 gain-of-function-associated diseases, AETX-K at 4 pM decreased Kv1.1-L296 F currents to wild-type levels; further, populations of heteromeric channels formed by co-expression Kv1.1 and Kv1.2, as found in many neurons, showed a Ki of ~10 nM even though homomeric Kv1.2 channels were insensitive to the toxin (Ki > 2000 nM).

Facilitation of hERG Activation by Its Blocker: A Mechanism to Reduce Drug-Induced Proarrhythmic Risk.

Modulation of the human Ether-à-go-go-Related Gene (hERG) channel, a crucial voltage-gated potassium channel in the repolarization of action potentials in ventricular myocytes of the heart, has significant implications on cardiac electrophysiology and can be either antiarrhythmic or proarrhythmic. For example, hERG channel blockade is a leading cause of long QT syndrome and potentially life-threatening arrhythmias, such as torsades de pointes. Conversely, hERG channel blockade is the mechanism of action of Class III antiarrhythmic agents in terminating ventricular tachycardia and fibrillation. In recent years, it has been recognized that less proarrhythmic hERG blockers with clinical potential or Class III antiarrhythmic agents exhibit, in addition to their hERG-blocking activity, a second action that facilitates the voltage-dependent activation of the hERG channel. This facilitation is believed to reduce the proarrhythmic potential by supporting the final repolarizing of action potentials. This review covers the pharmacological characteristics of hERG blockers/facilitators, the molecular mechanisms underlying facilitation, and their clinical significance, as well as unresolved issues and requirements for research in the fields of ion channel pharmacology and drug-induced arrhythmias.

IK Channel-Independent Effects of Clotrimazole and Senicapoc on Cancer Cells Viability and Migration.

Many studies highlighted the importance of the IK channel for the proliferation and the migration of different types of cancer cells, showing how IK blockers could slow down cancer growth. Based on these data, we wanted to characterize the effects of IK blockers on melanoma metastatic cells and to understand if such effects were exclusively IK-dependent. For this purpose, we employed two different blockers, namely clotrimazole and senicapoc, and two cell lines: metastatic melanoma WM266-4 and pancreatic cancer Panc-1, which is reported to have little or no IK expression. Clotrimazole and senicapoc induced a decrease in viability and the migration of both WM266-4 and Panc-1 cells irrespective of IK expression levels. Patch-clamp experiments on WM266-4 cells revealed Ca2+-dependent, IK-like, clotrimazole- and senicapoc-sensitive currents, which could not be detected in Panc-1 cells. Neither clotrimazole nor senicapoc altered the intracellular Ca2+ concentration. These results suggest that the effects of IK blockers on cancer cells are not strictly dependent on a robust presence of the channel in the plasma membrane, but they might be due to off-target effects on other cellular targets or to the blockade of IK channels localized in intracellular organelles.

Cilostazol induces vasorelaxation through the activation of the eNOS/NO/cGMP pathway, prostanoids, AMPK, PKC, potassium channels, and calcium channels.

OBJECTIVE: This study aimed to investigate vasoactive effect mechanisms of cilostazol in rat thoracic aorta. MATERIALS AND METHODS: The vessel rings prepared from the thoracic aortas of the male rats were placed in the chambers of the isolated tissue bath system. The resting tone was adjusted to 1 g. Following the equilibration phase, potassium chloride or phenylephrine was used to contract the vessel rings. When achieving a steady contraction, cilostazol was applied cumulatively (10-8-10-4 M). In the presence of potassium channel blockers or signaling pathway inhibitors, the same experimental procedure was performed. RESULTS: Cilostazol exhibited a significant vasorelaxant effect in a concentration-dependent manner (pD2: 5.94 ± 0.94) (p < .001). The vasorelaxant effect level of cilostazol was significantly reduced by the endothelial nitric oxide synthase inhibitor L-NAME (10-4 M), soluble guanylate cyclase inhibitor methylene blue (10 µM), cyclooxygenase 1/2 inhibitor indomethacin (5 µM), adenosine monophosphate-activated protein kinase inhibitor compound C (10 µM), non-selective potassium channel blocker tetraethylammonium chloride (10 mM), large-conductance calcium-activated potassium channel blocker iberiotoxin (20 nM), voltage-gated potassium channel blocker 4-Aminopyridine (1 mM), and inward-rectifier potassium channel blocker BaCl2 (30 µM) (p < .001). Moreover, incubation of cilostazol (10-4 M) significantly reduced caffeine (10 mM), cyclopiazonic acid (10 µM), and phorbol 12-myristate 13-acetate-induced (100 µM) vascular contractions (p < .001). CONCLUSIONS: In the rat thoracic aorta, the vasodilator action level of cilostazol is quite noticeable. The vasorelaxant effects of cilostazol are mediated by the eNOS/NO/cGMP pathway, prostanoids, AMPK pathway, PKC, potassium channels, and calcium channels.

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

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

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

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

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

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

Interaction of the Inhibitory Peptides ShK and HmK with the Voltage-Gated Potassium Channel KV1.3: Role of Conformational Dynamics.

Peptide toxins that adopt the ShK fold can inhibit the voltage-gated potassium channel KV1.3 with IC50 values in the pM range and are therefore potential leads for drugs targeting autoimmune and neuroinflammatory diseases. Nuclear magnetic resonance (NMR) relaxation measurements and pressure-dependent NMR have shown that, despite being cross-linked by disulfide bonds, ShK itself is flexible in solution. This flexibility affects the local structure around the pharmacophore for the KV1.3 channel blockade and, in particular, the relative orientation of the key Lys and Tyr side chains (Lys22 and Tyr23 in ShK) and has implications for the design of KV1.3 inhibitors. In this study, we have performed molecular dynamics (MD) simulations on ShK and a close homologue, HmK, to probe the conformational space occupied by the Lys and Tyr residues, and docked the different conformations with a recently determined cryo-EM structure of the KV1.3 channel. Although ShK and HmK have 60% sequence identity, their dynamic behaviors are quite different, with ShK sampling a broad range of conformations over the course of a 5 µs MD simulation, while HmK is relatively rigid. We also investigated the importance of conformational dynamics, in particular the distance between the side chains of the key dyad Lys22 and Tyr23, for binding to KV1.3. Although these peptides have quite different dynamics, the dyad in both adopts a similar configuration upon binding, revealing a conformational selection upon binding to KV1.3 in the case of ShK. Both peptides bind to KV1.3 with Lys22 occupying the pore of the channel. Intriguingly, the more flexible peptide, ShK, binds with significantly higher affinity than HmK.

Inhibition of the hERG potassium ion channel by different non-nucleoside human cytomegalovirus polymerase antiviral inhibitor series and the exploration of variations on a pyrroloquinoline core to reduce cardiotoxicity potential.

Many non-nucleoside human cytomegalovirus (HCMV) inhibitors have been reported in patent and scientific literature, however, none have reached commercialization despite the urgent need for new HCMV treatments. Herein we report select compounds from different templates that all had low micromolar human ether-à-go-go (hERG) ion channel IC50 values. We also describe a series of pyrroloquinoline derivatives that were designed and synthesized to understand the effect of various substitution on human cytomegalovirus (HCMV) polymerase activity, antiviral activity, and hERG inhibition. These results demonstrated that hERG inhibition can be significantly altered based on the substitution on this template. An HCMV inhibitor with low hERG inhibition and reduced cytotoxicity is also described. The results suggest substitution can be fine tuned for the non-nucleoside polymerase inhibitors to reduce hERG inhibition and maintain HCMV antiviral potency.

Machine-learning technique, QSAR and molecular dynamics for hERG-drug interactions.

One of the most well-known anti-targets defining medication cardiotoxicity is the voltage-dependent hERG K + channel, which is well-known for its crucial involvement in cardiac action potential repolarization. Torsades de Pointes, QT prolongation, and sudden death are all caused by hERG (the human Ether-à-go-go-Related Gene) inhibition. There is great interest in creating predictive computational (in silico) tools to identify and weed out potential hERG blockers early in the drug discovery process because testing for hERG liability and the traditional experimental screening are complicated, expensive and time-consuming. This study used 2D descriptors of a large curated dataset of 6766 compounds and machine learning approaches to build robust descriptor-based QSAR and predictive classification models for KCNH2 liability. Decision Tree, Random Forest, Logistic Regression, Ada Boosting, kNN, SVM, Naïve Bayes, neural network and stochastic gradient classification classifier algorithms were used to build classification models. If a compound's IC50 value was between 10 µM and less, it was classified as a blocker (hERG-positive), and if it was more, it was classified as a non-blocker (hERG-negative). Matthew's correlation coefficient formula and F1score were applied to compare and track the developed models' performance. Molecular docking and dynamics studies were performed to understand the cardiotoxicity relating to the hERG-gene. The hERG residues interacting after 100 ns are LEU:697, THR:708, PHE:656, HIS:674, HIS:703, TRP:705 and ASN:709 and the hERG-ligand-16 complex trajectory showed stable behaviour with lesser fluctuations in the entire simulation of 200 ns.Communicated by Ramaswamy H. Sarma.

Structural analysis of hERG channel blockers and the implications for drug design.

The repolarizing current (Ikr) produced by the hERG potassium channel forms a major component of the cardiac action potential and blocking this current by small molecule drugs can lead to life-threatening cardiotoxicity. Understanding the mechanisms of drug-mediated hERG inhibition is essential to develop a second generation of safe drugs, with minimal cardiotoxic effects. Although various computational tools and drug design guidelines have been developed to avoid binding of drugs to the hERG pore domain, there are many other aspects that are still open for investigation. This includes the use computational modelling to study the implications of hERG mutations on hERG structure and trafficking, the interactions of hERG with hERG chaperone proteins and with membrane-soluble molecules, the mechanisms of drugs that inhibit hERG trafficking and drugs that rescue hERG mutations. The plethora of available experimental data regarding all these aspects can guide the construction of much needed robust computational structural models to study these mechanisms for the rational design of safe drugs.

A bioengineered probiotic for the oral delivery of a peptide Kv1.3 channel blocker to treat rheumatoid arthritis.

Engineered microbes for the delivery of biologics are a promising avenue for the treatment of various conditions such as chronic inflammatory disorders and metabolic disease. In this study, we developed a genetically engineered probiotic delivery system that delivers a peptide to the intestinal tract with high efficacy. We constructed an inducible system in the probiotic Lactobacillus reuteri to secrete the Kv1.3 potassium blocker ShK-235 (LrS235). We show that LrS235 culture supernatants block Kv1.3 currents and preferentially inhibit human T effector memory (TEM) lymphocyte proliferation in vitro. A single oral gavage of healthy rats with LrS235 resulted in sufficient functional ShK-235 in the circulation to reduce inflammation in a delayed-type hypersensitivity model of atopic dermatitis mediated by TEM cells. Furthermore, the daily oral gavage of LrS235 dramatically reduced clinical signs of disease and joint inflammation in rats with a model of rheumatoid arthritis without eliciting immunogenicity against ShK-235. This work demonstrates the efficacy of using the probiotic L. reuteri as a novel oral delivery platform for the peptide ShK-235 and provides an efficacious strategy to deliver other biologics with great translational potential.

Virtual screening of DrugBank database for hERG blockers using topological Laplacian-assisted AI models.

The human ether-a-go-go (hERG) potassium channel (Kv11.1) plays a critical role in mediating cardiac action potential. The blockade of this ion channel can potentially lead fatal disorder and/or long QT syndrome. Many drugs have been withdrawn because of their serious hERG-cardiotoxicity. It is crucial to assess the hERG blockade activity in the early stage of drug discovery. We are particularly interested in the hERG-cardiotoxicity of compounds collected in the DrugBank database considering that many DrugBank compounds have been approved for therapeutic treatments or have high potential to become drugs. Machine learning-based in silico tools offer a rapid and economical platform to virtually screen DrugBank compounds. We design accurate and robust classifiers for blockers/non-blockers and then build regressors to quantitatively analyze the binding potency of the DrugBank compounds on the hERG channel. Molecular sequences are embedded with two natural language processing (NLP) methods, namely, autoencoder and transformer. Complementary three-dimensional (3D) molecular structures are embedded with two advanced mathematical approaches, i.e., topological Laplacians and algebraic graphs. With our state-of-the-art tools, we reveal that 227 out of the 8641 DrugBank compounds are potential hERG blockers, suggesting serious drug safety problems. Our predictions provide guidance for the further experimental interrogation of DrugBank compounds' hERG-cardiotoxicity.

Investigating cardiotoxicity related with hERG channel blockers using molecular fingerprints and graph attention mechanism.

Human ether-a-go-go-related gene (hERG) channel blockade by small molecules is a big concern during drug development in the pharmaceutical industry. Failure or inhibition of hERG channel activity caused by drug molecules can lead to prolonging QT interval, which will result in serious cardiotoxicity. Thus, evaluating the hERG blocking activity of all these small molecular compounds is technically challenging, and the relevant procedures are expensive and time-consuming. In this study, we develop a novel deep learning predictive model named DMFGAM for predicting hERG blockers. In order to characterize the molecule more comprehensively, we first consider the fusion of multiple molecular fingerprint features to characterize its final molecular fingerprint features. Then, we use the multi-head attention mechanism to extract the molecular graph features. Both molecular fingerprint features and molecular graph features are fused as the final features of the compounds to make the feature expression of compounds more comprehensive. Finally, the molecules are classified into hERG blockers or hERG non-blockers through the fully connected neural network. We conduct 5-fold cross-validation experiment to evaluate the performance of DMFGAM, and verify the robustness of DMFGAM on external validation datasets. We believe DMFGAM can serve as a powerful tool to predict hERG channel blockers in the early stages of drug discovery and development.

Intracellular Binding of Terfenadine Competes with Its Access to Pancreatic ß-cell ATP-Sensitive K+ Channels and Human ether-à-go-go-Related Gene Channels.

Most blockers of both hERG (human ether-à-go-go-related gene) channels and pancreatic ß-cell ATP-sensitive K+ (KATP) channels access their binding sites from the cytoplasmic side of the plasma membrane. It is unknown whether binding to intracellular components competes with binding of these substances to K+ channels. The whole-cell configuration of the patch-clamp technique, a laser-scanning confocal microscope, and fluorescence correlation spectroscopy (FCS) were used to study hERG channels expressed in HEK (human embryonic kidney) 293 cells and KATP channels from the clonal insulinoma cell line RINm5F. When applied via the pipette solution in the whole-cell configuration, terfenadine blocked both hERG and KATP currents with much lower potency than after application via the bath solution, which was not due to P-glycoprotein-mediated efflux of terfenadine. Such a difference was not observed with dofetilide and tolbutamide. 37-68% of hERG/EGFP (enhanced green-fluorescent protein) fusion proteins expressed in HEK 293 cells were slowly diffusible as determined by laser-scanning microscopy in the whole-cell configuration and by FCS in intact cells. Bath application of a green-fluorescent sulphonylurea derivative (Bodipy-glibenclamide) induced a diffuse fluorescence in the cytosol of RINm5F cells under whole-cell patch-clamp conditions. These observations demonstrate the presence of intracellular binding sites for hERG and KATP channel blockers not dialyzable by the patch-pipette solution. Intracellular binding of terfenadine was not influenced by a mutated hERG (Y652A) channel. In conclusion, substances with high lipophilicity are not freely diffusible inside the cell but steep concentration gradients might exist within the cell and in the sub-membrane space.

Insight on the interaction between the scorpion toxin blocker Discrepin on potassium voltage-gated channel Kv4.3 by molecular dynamics simulations.

Discrepin is a 38-residue α-toxin extracted from the venom of the Venezuelan scorpion Tityus discrepans, which inhibits ionic transit in the voltage-dependent potassium channels (Kv) of A-type current. The effect of specific residues on the IC50 between Discrepine and Kv4.3, the main component of A-type currents, is known; however, the molecular details of the toxin-channel interaction are not known. In this work, we present interaction models between Discrepin (wt) and two peptide variants (V6K/D20K and K13A) on the pore-forming domain of the Kv4.3 channel obtained from homology, docking, and molecular dynamics modeling techniques. The free energy calculations in these models correspond to the order of the experimentally determined IC50 values. Our studies shed light on the role of the K13 residue as responsible for occluding the Kv4.3 selectivity filter and the importance of the V6K mutation in the approach and stabilization of toxin-channel complex interactions.Communicated by Ramaswamy H. Sarma.

Combining mKate2-Kv1.3 Channel and Atto488-Hongotoxin for the Studies of Peptide Pore Blockers on Living Eukaryotic Cells.

The voltage-gated potassium Kv1.3 channel is an essential component of vital cellular processes which is also involved in the pathogenesis of some autoimmune, neuroinflammatory and oncological diseases. Pore blockers of the Kv1.3 channel are considered as potential drugs and are used to study Kv1 channels' structure and functions. Screening and study of the blockers require the assessment of their ability to bind the channel. Expanding the variety of methods used for this, we report on the development of the fluorescent competitive binding assay for measuring affinities of pore blockers to Kv1.3 at the membrane of mammalian cells. The assay constituents are hongotoxin 1 conjugated with Atto488, fluorescent mKate2-tagged Kv1.3 channel, which was designed to improve membrane expression of the channel in mammalian cells, confocal microscopy, and a special protocol of image processing. The assay is implemented in the "mix and measure", format and allows the screening of Kv1.3 blockers, such as peptide toxins, that bind to the extracellular vestibule of the K+-conducting pore, and analyzing their affinity.