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Potassium Channel

Potassium Channels are membrane-spanning proteins that allow the selective passage of potassium ions across the cell membrane.
They play a crucial role in regulating cellular excitability, ion homeostasis, and signaling pathways in a wide range of cell types.
Potassium Channels are involved in many physiological processes, such as nerve impulse propagation, muscle contraction, hormone secretion, and epithelial transport.
Dysfunctions in Potassium Channels have been implicated in various diseases, including cardiac arrhythmias, epilepsy, and neurodegenerative disorders.
Reseach on Potassium Channels is essential for understanding their structure, function, and potential therapeutic applications.

Most cited protocols related to «Potassium Channel»

1
Mapping Protein Conservation Scores Using ConSurf
Cited 102 times
After the calculation begins, ConSurf produces a status page indicating the computation parameters along with the different stages of the server activity. The main result of a ConSurf calculation is under the link ‘View ConSurf Results with Protein Explorer’, which leads to the graphic visualization of the query protein, color coded by conservation scores, through the Protein Explorer interface (9 (link)). The continuous conservation scores of each of the amino acid positions are available under the link ‘Amino Acid Conservation Scores’, along with the color grades and additional data. The script command for viewing the 3D structure of the query protein, color coded by conservation scores, is available under the link ‘RasMol coloring script source’. This file can be downloaded and used locally with the RasMol program (10 (link)), thus producing the same color-coded scheme generated by the server. A PDB file, in which the conservation scores are specified in the temperature (B) factor field, can be downloaded through the link: ‘The PDB file updated with the conservation scores in the tempFactor field’. Thus, any 3D protein viewer, such as the RasMol program (10 (link)), which is capable of presenting the B factors, is suitable for mapping the conservation scores on the structure.
The ConSurf output also includes links to the PSI-BLAST results, the homologous sequences along with a link to their SWISS-PROT entry page, the MSA and the phylogenetic tree used in the calculation.
As an example, we provide in Figure 2 the main output of a ConSurf run of the Kcsa potassium-channel (11 (link)), a transmembrane protein from Streptomyces Lividans. Kcsa is a homotetramer with a 4-fold symmetry axis about its pore. The ConSurf calculations demonstrate the high level of conservation of the pore region as compared with the rest of the protein. The pore architecture provides the unique stereochemistry which is required for efficient and selective conduction of potassium ions (11 (link)). The biological importance of this stereochemistry is reflected by a strong evolutionary pressure to resist amino acid replacements in the pore. In contrast, the regions that surround the pore and face the extracellular matrix are highly variable.
Landau M., Mayrose I., Rosenberg Y., Glaser F., Martz E., Pupko T, & Ben-Tal N. (2005). ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures. Nucleic Acids Research, 33(Web Server issue), W299-W302.
Publication 2005
Amino Acids Biological Evolution Biopharmaceuticals Complement Factor B Electric Conductivity Epistropheus Extracellular Matrix Face Homologous Sequences Integral Membrane Proteins Ions Potassium Potassium Channel Pressure Proteins Streptomyces lividans Surgical Replantation
2
Annotation of Biologically Relevant Ligands
Manuscript provided by user Cited 37 times
In most crystal structures low molecular weight ligands are observed, but only some of those are functionally or structurally relevant for the protein. Instead of their natural ligands, some structures contain synthetic analogues or inhibitors which occupy competitively the same binding site. Often, buffer or precipitant molecules are encountered, which are added by experimentalists to facilitate crystallization. SMTL implements a two-stage process to annotate biologically relevant ligands and synthetic analogues. The first stage uses a list of rules to automatically categorize the ligands based on their chemical identity. For example, all potassium ions are classified as solvent at this stage. In a second stage, the SMTL web interface provides a way to change the ligand classification manually. For example, in case of a potassium channel structure some of the before-mentioned potassium ions may be re-annotated as biologically relevant. While re-annotations can be suggested by any SWISS-MODEL user, before taking effect in SMTL, the annotations are reviewed by a curator to guarantee high quality of annotations.
Biasini M., Bienert S., Waterhouse A., Arnold K., Studer G., Schmidt T., Kiefer F., Cassarino T.G., Bertoni M., Bordoli L, & Schwede T. (2014). SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Nucleic Acids Research, 42(Web Server issue), W252-W258.
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Publication Author's manuscript 2014
Binding Sites Buffers Crystallization inhibitors Ions Ligands Potassium Potassium Channel Proteins Solvents
3
Multiobjective Optimization of Basket Cell Model
Cited 16 times
Simulations were performed using NEURON 5.9 (http://www.neuron.yale.edu; Carnevale and Hines, 2005 ). The cell used as the basis for the model was a reconstructed nest basket cell interneuron (Figure 1C). The model was composed of 301 compartments. Voltage-dependent ion channels were inserted only at the model soma; for simplicity dendrites and axon were considered to be passive. Dynamics of the ion channels were taken from the experimental literature (see below). When possible they were obtained from studies performed on cortical neurons. Ion channels were kept in their original mathematical description. The value for the maximal conductance of each ion channel type was left as a free parameter to be fitted by the MOO algorithm. The 10 ion channels that were used are listed below along with the bounds of the maximal conductance. The lower bound was always zero. The upper bound (UB) was selected based on estimates on reasonable physiological bounds and later verified by checking that the acceptable solutions of the fitting are not affected by increasing the UB value. Unless otherwise noted, UB was 1000 mS/cm2.
The following ion channels were used: persistent sodium channel, Nap (Magistretti and Alonso, 1999 (link)); UB = 100 mS/cm2. All upper bounds following will be in the same units. Fast inactivating sodium channel, Nat (Hamill et al., 1991 (link)); Fast-inactivating potassium channel, Kfast (Korngreen and Sakmann, 2000 (link)); Slow inactivating potassium channel, Kslow, (Korngreen and Sakmann, 2000 (link)); A-type potassium channel IA (Bekkers, 2000b (link)); Fast non-inactivating Kv 3.1 potassium channel, Kv3.1 (Rudy and McBain, 2001 (link)); M-type potassium channel Im (Bibbig et al., 2001 (link)); UB 100. High-voltage-activated calcium channel, Ca (Reuveni et al., 1993 (link)); UB 100. Calcium dependent small-conductance potassium channel, SK (Kohler et al., 1996 (link)); UB 100. Hyperploarization-activated cation current Ih (Kole et al., 2006 (link)); UB 100.
We found that the range of the window current of the transient sodium channel was too hyperpolarized for fitting the AP features. Consequently, the voltage-dependence of this channel was shifted by 10 mV in the depolarized direction. For the same reason, the voltage-dependence of the Kslow channels was shifted by 20 mV in the depolarized direction.
The MOO algorithm was run on parallel computers, either on a cluster consisting of 28 Sun x4100, dual AMD 64 bit Opteron 280 dual core (total of 112 processors), running Linux 2.6, or on a Bluegene/L supercomputer (Adiga et al., 2002 ). Average run time of a single fitting job on the cluster was less than 1 day. Runtime on 256 processors of the Bluegene/L was roughly equivalent to that of the cluster. Nearly linear speedup was achieved for 512 processors by allowing multiple processors to simulate the different step currents of the same organism.
Druckmann S., Banitt Y., Gidon A., Schürmann F., Markram H, & Segev I. (2007). A Novel Multiple Objective Optimization Framework for Constraining Conductance-Based Neuron Models by Experimental Data. Frontiers in Neuroscience, 1(1), 7-18.
Publication 2007
Axon Calcium Calcium Channel Carisoprodol Cells Cortex, Cerebral Dendrites Interneurons Ion Channel Neurons physiology Potassium Potassium Channel Sodium Channel Transients
4
Gating Current Measurements of Ion Channels
Cited 13 times
The gating current measurements were performed on a cut-open oocyte voltage clamp set-up (CA-1B; Dagan Corporation) as described previously (Muroi et al., 2010 (link); Lacroix and Bezanilla, 2011 (link)). For the potassium channel gating current measurement, the external solution was 115 mM NMG-MES (N-methyl-d-glucamine methanesulfonate), 2 mM Ca-MES, and 10 mM Hepes, pH 7.4. For the sodium channel gating current measurement, the external solution was 115 mM Na-MES, 2 mM Ca-MES, and 10 mM Hepes, pH 7.4. In the latter case, all ionic currents were blocked by the application of 10 µM tetrodotoxin to the external and middle chambers. For both channels, the internal solution was 115 mM NMG-MES, 2 mM EGTA, and 10 mM Hepes, pH 7.4. The recording pipette resistance was 0.3–0.5 MΩ. Analogue signals were sampled at 250 kHz with a Digidata 1440 interface (Molecular Devices) and low-pass filtered at 10 kHz. The capacitive transient currents were subtracted online using the P/4 method with a subtraction holding potential of −120 mV for the potassium channels and 50 mV for the sodium channels. Gating currents were obtained by applying a depolarizing pulse (50 ms for potassium and 20 ms for sodium channels) to voltages from −120 to 10 mV (at 5-mV intervals) for the potassium channels and −160 to 30 mV (at 10-mV intervals) for the sodium channels. The holding potential was −90 mV, and a 50-ms-long pre- and postpulse at −130 mV was used.
Chowdhury S, & Chanda B. (2012). Estimating the voltage-dependent free energy change of ion channels using the median voltage for activation. The Journal of General Physiology, 139(1), 3-17.
Publication 2012
Dagan Egtazic Acid HEPES Ion Transport Medical Devices methanesulfonate Oocytes Potassium-50 Potassium Channel Pulse Rate Sodium-20 Sodium Channel Subtraction Technique Tetrodotoxin Transients
5
Membrane Protein Dynamics in a Realistic Plasma Membrane
Cited 12 times
The detailed methods are described in the Supporting Information. In summary, we embedded 10 membrane proteins in
a previously characterized model of the plasma membrane.20 (link) The starting structures of the 10 membrane proteins
simulated in this study were taken from the Protein Data Bank or obtained
from the corresponding publication: aquaporin-1 (AQP1, PDB ID 1J4N);98 (link) prostaglandin H2 synthase (COX1, PDB ID 1Q4G);99 (link) the dopamine transporter (DAT, PDB ID 4M48);44 (link) the epidermal growth factor receptor (EGFR);77 (link) AMPA-sensitive glutamate receptor 2 (GluA2,
PDB ID 3KG2);100 (link) glucose transporter 1 (GluT1, PDB ID 4PYP);101 (link) voltage-dependent Shaker potassium channel 1.2 (Kv1.2,
PDB ID 3LUT,102 (link) residues 32 to 4421 for each monomer); sodium,
potassium pump (Na,K-ATPase, PDB ID 4HYT);103 (link) δ-opioid
receptor (δ-OPR, PDB ID 4N6H);104 (link) and P-glycoprotein
(P-gp, PDB ID 4M1M).105 (link) In each system, four copies of each
protein were included and positioned at a distance of ca. 20 nm from
each other. Proteins were simulated using standard Martini protocols
with minor variations between systems to accommodate system-specific
issues (Supporting Information). The following
lipid classes were included: cholesterol (CHOL), in both leaflets;
charged lipids phosphatidylserine (PS), phosphatidic acid (PA), phosphatidylinositol
(PI), and the PI-phosphate, PI-bisphosphate, and PI-trisphosphate
(PIPs) placed in the inner leaflet; and ganglioside (GM) in the outer
leaflet. The zwitterionic phosphatidylcholine (PC), phosphatidylethanolamine
(PE), and sphingomyelin (SM) lipids were placed in both leaflets,
with PC and SM primarily in the outer leaflet and PE in the inner
leaflet. Ceramide (CER), diacylglycerol (DAG), and lysophosphatidylcholine
(LPC) lipids were also included, with all the LPC in the inner leaflet,
and CER and DAG primarily in the outer leaflet. The details of the
Martini lipids used in this study can be found on the Martini Lipidome
webpage (http://www.cgmartini.nl/index.php/force-field-parameters/lipids) and are described by Ingolfsson et al., and Wassenaar et al.20 (link),106 (link) The exact lipid composition of each system is given in the Supporting Information. The systems are ca. 42
× 42 nm in the membrane plane (x and y), including 4 proteins and ca. 6000 lipids.
Production
runs were performed in the presence of weak position
restraints applied to the protein backbone beads, with a force constant
of 1 kJ mol–1 nm–2, preventing
proteins from associating with each other. Each of the systems has
been simulated for 30 μs, which turned out to be adequate to
obtain convergence of major lipid components in the lipid shells around
the individual copies of the proteins (Supporting Information). Additional control simulations were performed
in the AQP1 system, in order to test the effects of simulation length,
position restraints on the proteins, lipid composition, and water
model on the results of lipid composition near the proteins (Supporting Information).
Simulations were
performed using the GROMACS simulation package
version 4.6.3,107 (link) with the Martini v2.2
force field parameters,62 (link),63 (link) and standard simulation
settings.108 (link) Additional details are provided
in Supporting Information. All the analyses
were performed on the last 5 μs of each simulation system.
Corradi V., Mendez-Villuendas E., Ingólfsson H.I., Gu R.X., Siuda I., Melo M.N., Moussatova A., DeGagné L.J., Sejdiu B.I., Singh G., Wassenaar T.A., Delgado Magnero K., Marrink S.J, & Tieleman D.P. (2018). Lipid–Protein Interactions Are Unique Fingerprints for Membrane Proteins. ACS Central Science, 4(6), 709-717.
Publication 2018
Adenosinetriphosphatase alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid AMPA Receptors AQP1 protein, human Aquaporin 1 Cell Membrane Proteins Ceramides Cholesterol Debility Diacylglycerol Dopamine Transporter Epidermal Growth Factor Receptor Gangliosides Glucose Transporter Glutamate Glutamate Receptor Lipids Lysophosphatidylcholines Na(+)-K(+)-Exchanging ATPase P-Glycoproteins Phosphates Phosphatidic Acid Phosphatidylcholines phosphatidylethanolamine Phosphatidylinositols Phosphatidylserines Potassium Channel Proteins PTGS1 protein, human SLC2A1 protein, human Sphingomyelins Tissue, Membrane Vertebral Column

Most recents protocols related to «Potassium Channel»

1
Validating Neuronal Activation by DREADDs
Although previous studies have validated the use of the CAV2-PRS construct using a range of actuators, including excitatory and inhibitory opsins, as well as potassium channels (Howorth et al., 2009a (link); Howorth et al., 2009b (link); Hickey et al., 2014 (link); Li et al., 2016 (link)), we used a separate cohort of rats to verify the functional effect of our DREADDs construct in vivo by quantifying changes in the expression of c-Fos, a recognized marker of neuronal activation, upon administration of DCZ. In order to obtain a high baseline of c-Fos activation, rats underwent a stress procedure. As shown in Figure 4—figure supplement 1B, rats were administered i.p. with either vehicle or DCZ (0.1 mg/kg) 45 min before being placed in a Plexiglas shock chamber equipped with stainless steel rods on the floor and a circuit generator connected to a scrambler and a timing unit. Rats received five shocks (0.5 s, 0.8 mA) randomly interspersed over 10 min (stress condition). As a control of c-Fos activation, we included in the experimental design animals administered with vehicle, but left untouched in their home cage (no stress condition). Rats were perfused 90 min after the procedure and coronal slices collected as described in the Histology section. For hM4Di/c-Fos colocalization analysis, sections were taken (see Figure 4—figure supplement 1—source data 1) from antero-posterior levels of the LC from –9.50 to –10.0 mm from Bregma (vehicle/no stress, n=2; vehicle-stress, n=4; DCZ-stress, n=4). Quantification of the percentage of LC hM4Di-positive cells (mCherry, red) that co-express c-Fos (Alexa 488, green) was performed by a trained observer blind to the experimental conditions.
Cerpa J.C., Piccin A., Dehove M., Lavigne M., Kremer E.J., Wolff M., Parkes S.L, & Coutureau E. (2023). Inhibition of noradrenergic signalling in rodent orbitofrontal cortex impairs the updating of goal-directed actions. eLife, 12, e81623.
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Publication 2023
Animals, Laboratory CAV2 protein, human Cells Dietary Supplements Neurons Opsins Plexiglas Potassium Channel Proto-Oncogene Proteins c-fos Psychological Inhibition Rattus norvegicus Rod Photoreceptors Shock Stainless Steel Stress Disorders, Traumatic Visually Impaired Persons
2
Quantifying Gene Expression in Leaf Epidermis
Cited 1 time
The leaf epidermis tissue (100 mg) was homogenized with liquid nitrogen, and total RNA was extracted using Trizol reagent (Invitrogen, San Diego, CA, USA) according to the manufacturer’s protocol. First-strand cDNA was synthesized following the instructions of the HiScript III RT SuperMix for qPCR (Vazyme). Real-time quantitative PCR was performed using ChamQ SYBR qPCR Master mix (Vazyme) in a Bio-Rad iCycler iQ5 fluorescence real-time PCR system (Bio-Rad, Hercules, CA, USA). The annealing temperatures of the target genes were all optimized to 58°C. The primers for quick-activating anion channel 1 (QUAC1), slow-activating anion channel (SLAC1), malate transport ATPase (ABCB14), potassium ion inflow channel (KAT1), potassium ion efflux channel (KOR1), calcineurin binding protein (CBL1), calmodulin kinase (CIPK23) are shown in Table S1. To normalize results, the Cq (quantification cycle value) was calculated as the relative expression level of each target gene and the housekeeping gene (Actin) in each sample.
Yang M., He J., Sun Z., Li Q., Cai J., Zhou Q., Wollenweber B., Jiang D, & Wang X. (2023). Drought priming mechanisms in wheat elucidated by in-situ determination of dynamic stomatal behavior. Frontiers in Plant Science, 14, 1138494.
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Publication 2023
Actins Adenosinetriphosphatase Anions Binding Proteins Calcineurin DNA, Complementary Epidermis Fluorescence Gene Expression Genes Genes, Housekeeping malate Nitrogen Oligonucleotide Primers Plant Leaves Potassium Channel Protein Kinase, Calcium-Calmodulin-Dependent Real-Time Polymerase Chain Reaction Tissues trizol
3
Mechanism of Potent Vasodilator's Action

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Publication 2023
Aorta ATP8A2 protein, human Biopharmaceuticals Calcium Deoxycholic Acid Endothelium Krebs-Henseleit solution Pharmaceutical Preparations Phenylephrine Potassium Channel Saline Solution Synapsin I Tetraethylammonium Chloride Vasodilation Verapamil Hydrochloride
4
Intrinsic Clearance and hERG Inhibition
The intrinsic clearance of UK4b in liver microsomes (human) was determined by Eurofins Panlabs (St. Charles, MO) through their standard protocol, including measurements at five time-points (0, 15, 30, 45, and 60 min) in order to estimate the intrinsic clearance (CLint) and half-life (t1/2). The inhibitory activity of UK4b at 10 μM against potassium channel hERG was tested by Eurofins Cerep (France) using the standard Cerep protocol.
Stewart M.J., Weaver L.M., Ding K., Kyomuhangi A., Loftin C.D., Zheng F, & Zhan C.G. (2023). Analgesic effects of a highly selective mPGES-1 inhibitor. Scientific Reports, 13, 3326.
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Publication 2023
Homo sapiens Microsomes, Liver Potassium Channel Psychological Inhibition
5
Computational Docking of Bioactive Ligands
Docking experiments were carried out using the full-length predicted structures of the target proteins, with the most optimal quality parameters. The simulations were performed using the AutoDock Vina v1.1.2 algorithm [42 (link)], integrated within the YASARA Structure. In the case of SERCA2b, the docking grid box included a potential binding pocket situated at the interface between the transmembrane and cytosolic domains, overlapping with the binding site of SERCA inhibitor BHQ (2,5-di-tert-butylbenzene-1,4-diol) [25 (link)]. The binding pocket was chosen based on previous studies, which suggested that the binding site of BHQ might overlap with the potential binding pocket of hypericin, a photosensitizing agent with a large molecule, similar to porphyrinic derivatives [43 (link)]. For potassium channels KCa1.1 and KATP, the grid box was set around the residues involved in heme binding, which were confirmed through previous mutation studies [21 (link),22 (link),44 (link)]. BHQ and heme were used as positive controls.
Both protein and ligand structures were protonated according to the physiological pH. The docking experiments were performed with flexible residues, and 12 docking runs were executed for each ligand. The predicted protein-ligand complexes were refined by minimization with AMBER14 force field. The results were retrieved as the binding energy (ΔG, kcal/mol) and predicted dissociation constant (Kd, µM). The predicted binding poses and molecular interactions were analyzed using ChimeraX v1.4 [45 (link)] and BIOVIA Discovery Studio Visualizer (BIOVIA, Discovery Studio Visualizer, Version 17.2.0, Dassault Systèmes, 2016, San Diego, CA, USA).
Mihai D.P., Boscencu R., Manda G., Burloiu A.M., Vasiliu G., Neagoe I.V., Socoteanu R.P, & Lupuliasa D. (2023). Interaction of Some Asymmetrical Porphyrins with U937 Cell Membranes–In Vitro and In Silico Studies. Molecules, 28(4), 1640.
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Publication 2023
Binding Sites Cytosol derivatives Heme hypericin Ligands Mutation Photosensitizing Agents physiology Potassium Channel Proteins Protein Targeting, Cellular tert-butylbenzene

Top products related to «Potassium Channel»

1
Fluxor potassium ion channel assay by Thermo Fisher Scientific
Sourced in United States
The FluxOR potassium ion channel assay is a fluorescence-based tool used to measure potassium ion channel activity. It enables the monitoring of potassium ion flux across the cell membrane in a real-time, high-throughput manner.
2
Fluxor 2 green potassium ion channel assay by Thermo Fisher Scientific
Sourced in United Kingdom, Poland, Germany
The FluxOR™ II Green Potassium Ion Channel Assay is a fluorescence-based tool for measuring potassium ion channel activity. It utilizes a proprietary green fluorescent dye that responds to changes in potassium ion concentration, allowing for the real-time monitoring of potassium channel function.
3
Prism 5 by GraphPad
Sourced in United States, Germany, United Kingdom, Israel, Canada, Austria, Belgium, Poland, Lao People's Democratic Republic, Japan, China, France, Brazil, New Zealand, Switzerland, Sweden, Australia
GraphPad Prism 5 is a data analysis and graphing software. It provides tools for data organization, statistical analysis, and visual representation of results.
4
Multiclamp 700b amplifier by Molecular Devices
Sourced in United States, United Kingdom, Germany, Australia, Japan, Hungary
The Multiclamp 700B amplifier is a versatile instrument designed for electrophysiology research. It provides high-quality amplification and signal conditioning for a wide range of intracellular and extracellular recording applications. The Multiclamp 700B offers advanced features and precise control over signal acquisition, enabling researchers to obtain reliable and accurate data from their experiments.
5
Dimethyl sulfoxide (dmso) by Merck Group
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DMSO is a versatile organic solvent commonly used in laboratory settings. It has a high boiling point, low viscosity, and the ability to dissolve a wide range of polar and non-polar compounds. DMSO's core function is as a solvent, allowing for the effective dissolution and handling of various chemical substances during research and experimentation.
6
Rneasy mini kit by Qiagen
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The RNeasy Mini Kit is a laboratory equipment designed for the purification of total RNA from a variety of sample types, including animal cells, tissues, and other biological materials. The kit utilizes a silica-based membrane technology to selectively bind and isolate RNA molecules, allowing for efficient extraction and recovery of high-quality RNA.
7
Trizol reagent by Thermo Fisher Scientific
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TRIzol reagent is a monophasic solution of phenol, guanidine isothiocyanate, and other proprietary components designed for the isolation of total RNA, DNA, and proteins from a variety of biological samples. The reagent maintains the integrity of the RNA while disrupting cells and dissolving cell components.
8
Glibenclamide by Merck Group
Sourced in United States, Germany, United Kingdom, Spain, Brazil, Mexico, Japan, Sao Tome and Principe, India
Glibenclamide is a medication used as a lab equipment product. It is a sulfonylurea drug that helps regulate blood sugar levels. The core function of Glibenclamide is to stimulate the release of insulin from the pancreas, which can be useful in research and laboratory settings.
9
Discovery studio 4 by Dassault Systèmes
Sourced in United States, China
Discovery Studio 4.5 is a comprehensive software platform for molecular modeling, simulation, and analysis. It provides a suite of tools for visualizing, modeling, and analyzing molecular structures and interactions. The software is designed for researchers and scientists working in the fields of computational chemistry, structural biology, and drug discovery.
10
Iberiotoxin by Merck Group
Sourced in United States
Iberiotoxin is a selective blocker of large-conductance calcium-activated potassium (BK) channels. It is a polypeptide toxin derived from the venom of the scorpion Buthus tamulus. Iberiotoxin binds with high affinity to the BK channel, inhibiting its activity. It is commonly used as a research tool to investigate the physiological roles of BK channels in various biological systems.

More about "Potassium Channel"

Potassium (K+) channels are a diverse family of membrane-spanning proteins that selectively allow the passage of potassium ions across the cell membrane.
These ion channels play a crucial role in regulating cellular excitability, ion homeostasis, and signaling pathways in a wide range of cell types, including neurons, muscle cells, and epithelial cells.
Potassium channels are involved in many physiological processes, such as nerve impulse propagation, muscle contraction, hormone secretion, and epithelial transport.
Dysfunctions in potassium channels have been implicated in various diseases, including cardiac arrhythmias, epilepsy, and neurodegenerative disorders.
Research on potassium channels is essential for understanding their structure, function, and potential therapeutic applications.
Techniques like the FluxOR potassium ion channel assay and the FluxOR™ II Green Potassium Ion Channel Assay can be used to measure potassium channel activity and screen for potential modulators.
Additionally, tools like GraphPad Prism 5 and the Multiclamp 700B amplifier can be utilized for data analysis and electrophysiological recordings, respectively.
Researchers may also use compounds like DMSO, RNeasy Mini Kit, TRIzol reagent, Glibenclamide, and Iberiotoxin to study potassium channel function and regulation.
Computational tools, such as Discovery Studio 4.5, can aid in structural modeling and virtual screening of potassium channel-targeting compounds.
By leveraging these techniques and tools, scientists can gain a deeper understanding of potassium channel structure, function, and their role in health and disease, ultimately paving the way for the development of novel therapeutic strategies.