The Experts below are selected from a list of 171939 Experts worldwide ranked by ideXlab platform
Eric Gouaux - One of the best experts on this subject based on the ideXlab platform.
-
molecular mechanism of atp binding and Ion Channel activatIon in p2x receptors
Nature, 2012Co-Authors: Motoyuki Hattori, Eric GouauxAbstract:P2X receptors are trimeric ATP-activated Ion Channels permeable to Na+, K+ and Ca2+. The seven P2X receptor subtypes are implicated in physiological processes that include modulatIon of synaptic transmissIon, contractIon of smooth muscle, secretIon of chemical transmitters and regulatIon of immune responses. Despite the importance of P2X receptors in cellular physiology, the three-dimensIonal compositIon of the ATP-binding site, the structural mechanism of ATP-dependent Ion Channel gating and the architecture of the open Ion Channel pore are unknown. Here we report the crystal structure of the zebrafish P2X4 receptor in complex with ATP and a new structure of the apo receptor. The agonist-bound structure reveals a previously unseen ATP-binding motif and an open Ion Channel pore. ATP binding induces cleft closure of the nucleotide-binding pocket, flexing of the lower body β-sheet and a radial expansIon of the extracellular vestibule. The structural widening of the extracellular vestibule is directly coupled to the opening of the Ion Channel pore by way of an iris-like expansIon of the transmembrane helices. The structural delineatIon of the ATP-binding site and the Ion Channel pore, together with the conformatIonal changes associated with Ion Channel gating, will stimulate development of new pharmacological agents.
-
crystal structure of the atp gated p2x 4 Ion Channel in the closed state
Nature, 2009Co-Authors: Toshimitsu Kawate, Eric Gouaux, Jennifer Carlisle Michel, William T BirdsongAbstract:P2X receptors are catIon-selective Ion Channels gated by extracellular ATP, and are implicated in diverse physiological processes, from synaptic transmissIon to inflammatIon to the sensing of taste and pain. Because P2X receptors are not related to other Ion Channel proteins of known structure, there is at present no molecular foundatIon for mechanisms of ligand-gating, allosteric modulatIon and Ion permeatIon. Here we present crystal structures of the zebrafish P2X4 receptor in its closed, resting state. The chalice-shaped, trimeric receptor is knit together by subunit–subunit contacts implicated in Ion Channel gating and receptor assembly. Extracellular domains, rich in β-strands, have large acidic patches that may attract catIons, through fenestratIons, to vestibules near the Ion Channel. In the transmembrane pore, the ‘gate’ is defined by an ∼8 A slab of protein. We define the locatIon of three non-canonical, intersubunit ATP-binding sites, and suggest that ATP binding promotes subunit rearrangement and Ion Channel opening. P2X receptors are ATP-gated non-selective catIon Channels involved in nociceptIon and inflammatory responses, whose structures were unknown. Kawate et al. now present the crystal structure of the zebrafish P2X4 receptor in a closed state. The trimeric structure reveals some of the molecular underpinnings of ligand-binding, catIon entry and Channel gating. A related paper presents the structure of chicken acid-sensing Ion Channel 1 (ASIC1) in a desensitized state. Like P2X receptors, ASICs are trimeric, but they belong to an entirely different family of Ion Channels. The structure determinatIon of ASIC1 shows how Ion permeatIon and desensitizatIon may occur, and comparison of ASIC and P2X structures suggests that these functIonally distinct Channels employ similar mechanistic principles. P2X receptors are ATP-gated catIon Channels that are implicated in diverse physiological processes, from synaptic transmissIon to inflammatIon to the sensing of taste and pain. The crystal structure of the zebrafish P2X4 Channel is now solved in its closed state, revealing some of the molecular underpinnings of ligand-binding, catIon entry and Channel gating.
Robert A Lamb - One of the best experts on this subject based on the ideXlab platform.
-
Ion Channel activity of influenza a virus m2 protein characterizatIon of the amantadine block
Journal of Virology, 1993Co-Authors: Chang Wang, Lawrence H Pinto, Kaoru Takeuchi, Robert A LambAbstract:The influenza A virus M2 integral membrane protein has Ion Channel activity which can be blocked by the antiviral drug amantadine. The M2 protein transmembrane domain is highly conserved in amino acid sequence for all the human, swine, equine, and avian strains of influenza A virus, and thus, known amino acid differences could lead to altered properties of the M2 Ion Channel. We have expressed in oocytes of Xenopus laevis the M2 protein of human influenza virus A/Udorn/72 and the avian virus A/chicken/Germany/34 (fowl plague virus, Rostock) and derivatives of the Rostock Ion Channel altered in the presumed pore regIon. The pH of activatIon of the M2 Ion Channels and amantadine block of the M2 Ion Channels were investigated. The Channels were found to be activated by pH in a similar manner but differed in their apparent Kis for amantadine block.
-
influenza virus m2 protein has Ion Channel activity
Cell, 1992Co-Authors: Lawrence H Pinto, Leslie J Holsinger, Robert A LambAbstract:The influenza virus M2 protein was expressed in Xenopus laevis oocytes and shown to have an associated Ion Channel activity selective for monovalent Ions. The anti-influenza virus drug amantadine hydrochloride significantly attenuated the inward current induced by hyperpolarizatIon of oocyte membranes. MutatIons in the M2 membrane-spanning domain that confer viral resistance to amantadine produced currents that were resistant to the drug. Analysis of the currents of these altered M2 proteins suggests that the Channel pore is formed by the transmembrane domain of the M2 protein. The wild-type M2 Channel was found to be regulated by pH. The wild-type M2 Ion Channel activity is proposed to have a pivotal role in the biology of influenza virus infectIon.
Kylie A Beattie - One of the best experts on this subject based on the ideXlab platform.
-
four ways to fit an Ion Channel model
Biophysical Journal, 2019Co-Authors: Michael Clerx, Kylie A Beattie, David J Gavaghan, Gary R MiramsAbstract:Abstract Mathematical models of Ionic currents are used to study the electrophysiology of the heart, brain, gut, and several other organs. Increasingly, these models are being used predictively in the clinic, for example to predict the risks and results of genetic mutatIons, pharmacological treatments or surgical procedures. These safety-critical applicatIons depend on accurate characterisatIon of the underlying Ionic currents. Four different methods can be found in the literature to fit voltage-sensitive Ion Channel models to whole-cell current measurements: (Method 1) fitting model equatIons directly to time constant, steady-state, and I-V summary curves; (Method 2) fitting by comparing simulated versIons of these summary curves to their experimental counterparts; (Method 3) fitting to the current traces themselves from a range of protocols; and (Method 4) fitting to a single current trace from a short and rapidly-fluctuating voltage clamp protocol. We compare these methods using a set of experiments in which hERG1a current was measured in nine Chinese Hamster Ovary (CHO) cells. In each cell, the same sequence of fitting protocols was applied, as well as an independent validatIon protocol. We show that Methods 3 and 4 provide the best predictIons on the independent validatIon set, and that short rapidly-fluctuating protocols like that used in Method 4 can replace much longer conventIonal protocols without loss of predictive ability. While data for Method 2 is most readily available from the literature, we find it performs poorly compared to Methods 3 and 4 both in accuracy of predictIons and computatIonal efficiency. Our results demonstrate how novel experimental and computatIonal approaches can improve the quality of model predictIons in safety-critical applicatIons. Statement of Significance Mathematical models have been constructed to capture and share our understanding of the kinetics of Ion Channel currents for almost 70 years, and hundreds of models have been developed, using a variety of techniques. We compare how well four of the main methods fit data, how reliable and efficient the process of fitting is, and how predictive the resulting models are for physiological situatIons. The most widely-used traditIonal approaches based on current-voltage and time constant-voltage curves do not produce the most predictive models. Short, optimised experimental voltage clamp protocols are as predictive as ones derived from traditIonal protocols, opening up possibilities for measuring Ion Channel kinetics faster, more accurately and in single cells.
-
four ways to fit an Ion Channel model
bioRxiv, 2019Co-Authors: Michael Clerx, Kylie A Beattie, David J Gavaghan, Gary R MiramsAbstract:ABSTRACT ComputatIonal models of the cardiac actIon potential are increasingly being used to investigate the effects of genetic mutatIons, predict pro-arrhythmic risk in drug development, and to guide clinical interventIons. These safety-critical applicatIons, and indeed our understanding of the cardiac actIon potential, depend on accurate characterisatIon of the underlying Ionic currents. Four different methods can be found in the literature to fit Ionic current models to single-cell measurements: (Method 1) fitting model equatIons directly to time constant, steady-state, and I-V summary curves; (Method 2) fitting by comparing simulated versIons of these summary curves to their experimental counterparts; (Method 3) fitting to the current traces themselves from a range of protocols; and (Method 4) fitting to a single current trace from an informatIon-rich voltage clamp protocol. We compare these methods using a set of experiments in which hERG1a current from single Chinese Hamster Ovary (CHO) cells was characterised using multiple fitting protocols and an independent validatIon protocol. We show that Methods 3 and 4 provide the best predictIons on the independent validatIon set, and that the short informatIon-rich protocols of Method 4 can replace much longer conventIonal protocols without loss of predictive ability. While data for Method 2 is most readily available from the literature, we find it performs poorly compared to Methods 3 and 4 both in accuracy of predictIons and computatIonal efficiency. Our results demonstrate how novel experimental and computatIonal approaches can improve the quality of model predictIons in safety-critical applicatIons. Statement of Significance Mathematical models have been constructed to capture and share our understanding of the kinetics of Ion Channel currents for almost 70 years, and hundreds of models have been developed, using a variety of techniques. We compare how well four of the main methods fit data, how reliable and efficient the process of fitting is, and how predictive the resulting models are for physiological situatIons. The most widely-used traditIonal approaches based on current-voltage and time constant-voltage curves do not produce the most predictive models. Short, optimised experimental voltage clamp protocols can be used to create models that are as predictive as ones derived from traditIonal protocols, opening up possibilities for measuring Ion Channel kinetics faster, more accurately and in single cells. As these models often form part of larger multi-scale actIon potential and tissue electrophysiology models, improved Ion Channel kinetics models could influence the findings of thousands of simulatIon studies.
-
sinusoidal voltage protocols for rapid characterisatIon of Ion Channel kinetics
The Journal of Physiology, 2018Co-Authors: Kylie A Beattie, Adam P Hill, Remi Bardenet, Yi Cui, Jamie I Vandenberg, David J Gavaghan, Teun P De BoerAbstract:Understanding the roles of Ion currents is crucial to predict the actIon of pharmaceuticals and mutatIons in different scenarios, and thereby to guide clinical interventIons in the heart, brain and other electrophysiological systems. Our ability to predict how Ion currents contribute to cellular electrophysiology is in turn critically dependent on our characterisatIon of Ion Channel kinetics - the voltage-dependent rates of transitIon between open, closed and inactivated Channel states. We present a new method for rapidly exploring and characterising Ion Channel kinetics, applying it to the hERG potassium Channel as an example, with the aim of generating a quantitatively predictive representatIon of the Ion current. We fit a mathematical model to currents evoked by a novel 8 second sinusoidal voltage clamp in CHO cells over-expressing hERG1a. The model is then used to predict over 5 minutes of recordings in the same cell in response to further protocols: a series of traditIonal square step voltage clamps, and also a novel voltage clamp comprised of a collectIon of physiologically-relevant actIon potentials. We demonstrate that we can make predictive cell-specific models that outperform the use of averaged data from a number of different cells, and thereby examine which changes in gating are responsible for cell-cell variability in current kinetics. Our technique allows rapid collectIon of consistent and high quality data, from single cells, and produces more predictive mathematical Ion Channel models than traditIonal approaches.
-
sinusoidal voltage protocols for rapid characterizatIon of Ion Channel kinetics
bioRxiv, 2017Co-Authors: Kylie A Beattie, Adam P Hill, Remi Bardenet, Yi Cui, Jamie I Vandenberg, David J Gavaghan, Teun P De Boer, Gary R MiramsAbstract:Understanding the roles of Ion currents is crucial to predict the actIon of pharmaceuticals and also to guide clinical interventIons in the heart, brain and other electrophysiological systems. Our ability to predict how Ion currents contribute to cellular electrophysiology is in turn critically dependent on the characterizatIon of Ion Channel kinetics. We present a method for rapidly exploring and characterizing Ion Channel kinetics, using the hERG Channel, responsible for cardiac I Kr current, as an example. We fit a mathematical model to currents evoked by a novel 8-second sinusoidal voltage clamp. The model is then used to predict over 5 minutes of recordings in the same cell in response to further voltage clamp protocols, including a new collectIon of physiological actIon potentials. Our technique allows rapid collectIon of data from single cells, produces more predictive Ion current models than traditIonal approaches, and will be widely applicable to many Ion currents.
Stuart A Lipton - One of the best experts on this subject based on the ideXlab platform.
-
molecular basis of nmda receptor coupled Ion Channel modulatIon by s nitrosylatIon
Nature Neuroscience, 2000Co-Authors: Yunbeom Choi, Lalitha Tenneti, Dean A Le, Justin Ortiz, Hueisheng Vincent Chen, Stuart A LiptonAbstract:Several Ion Channels are thought to be directly modulated by nitric oxide (NO), but the molecular basis of this regulatIon is unclear. Here we show that the NMDA receptor (NMDAR)-associated Ion Channel was modulated not only by exogenous NO but also by endogenous NO. Site-directed mutagenesis identified a critical cysteine residue (Cys 399) on the NR2A subunit whose S-nitrosylatIon (NO+ transfer) under physiological conditIons underlies this modulatIon. In cell systems expressing NMDARs with mutant NR2A subunits in which this single cysteine was replaced by an alanine, the effect of endogenous NO was lost. Thus endogenous S-nitrosylatIon can regulate Ion Channel activity.
Teun P De Boer - One of the best experts on this subject based on the ideXlab platform.
-
sinusoidal voltage protocols for rapid characterisatIon of Ion Channel kinetics
The Journal of Physiology, 2018Co-Authors: Kylie A Beattie, Adam P Hill, Remi Bardenet, Yi Cui, Jamie I Vandenberg, David J Gavaghan, Teun P De BoerAbstract:Understanding the roles of Ion currents is crucial to predict the actIon of pharmaceuticals and mutatIons in different scenarios, and thereby to guide clinical interventIons in the heart, brain and other electrophysiological systems. Our ability to predict how Ion currents contribute to cellular electrophysiology is in turn critically dependent on our characterisatIon of Ion Channel kinetics - the voltage-dependent rates of transitIon between open, closed and inactivated Channel states. We present a new method for rapidly exploring and characterising Ion Channel kinetics, applying it to the hERG potassium Channel as an example, with the aim of generating a quantitatively predictive representatIon of the Ion current. We fit a mathematical model to currents evoked by a novel 8 second sinusoidal voltage clamp in CHO cells over-expressing hERG1a. The model is then used to predict over 5 minutes of recordings in the same cell in response to further protocols: a series of traditIonal square step voltage clamps, and also a novel voltage clamp comprised of a collectIon of physiologically-relevant actIon potentials. We demonstrate that we can make predictive cell-specific models that outperform the use of averaged data from a number of different cells, and thereby examine which changes in gating are responsible for cell-cell variability in current kinetics. Our technique allows rapid collectIon of consistent and high quality data, from single cells, and produces more predictive mathematical Ion Channel models than traditIonal approaches.
-
sinusoidal voltage protocols for rapid characterizatIon of Ion Channel kinetics
bioRxiv, 2017Co-Authors: Kylie A Beattie, Adam P Hill, Remi Bardenet, Yi Cui, Jamie I Vandenberg, David J Gavaghan, Teun P De Boer, Gary R MiramsAbstract:Understanding the roles of Ion currents is crucial to predict the actIon of pharmaceuticals and also to guide clinical interventIons in the heart, brain and other electrophysiological systems. Our ability to predict how Ion currents contribute to cellular electrophysiology is in turn critically dependent on the characterizatIon of Ion Channel kinetics. We present a method for rapidly exploring and characterizing Ion Channel kinetics, using the hERG Channel, responsible for cardiac I Kr current, as an example. We fit a mathematical model to currents evoked by a novel 8-second sinusoidal voltage clamp. The model is then used to predict over 5 minutes of recordings in the same cell in response to further voltage clamp protocols, including a new collectIon of physiological actIon potentials. Our technique allows rapid collectIon of data from single cells, produces more predictive Ion current models than traditIonal approaches, and will be widely applicable to many Ion currents.
