scholarly journals Neural Network Differential Equations For Ion Channel Modelling

2021 ◽  
Vol 12 ◽  
Author(s):  
Chon Lok Lei ◽  
Gary R. Mirams
Keyword(s):  
Neural Network ◽  
Ion Channels ◽  
Ion Channel ◽  
Conformational Changes ◽  
Traditional Approach ◽  
Equation Model ◽  
State Transitions ◽  
Abstract Description ◽  
Potential Applications ◽  
Model Discrepancy

Mathematical models of cardiac ion channels have been widely used to study and predict the behaviour of ion currents. Typically models are built using biophysically-based mechanistic principles such as Hodgkin-Huxley or Markov state transitions. These models provide an abstract description of the underlying conformational changes of the ion channels. However, due to the abstracted conformation states and assumptions for the rates of transition between them, there are differences between the models and reality—termed model discrepancy or misspecification. In this paper, we demonstrate the feasibility of using a mechanistically-inspired neural network differential equation model, a hybrid non-parametric model, to model ion channel kinetics. We apply it to the hERG potassium ion channel as an example, with the aim of providing an alternative modelling approach that could alleviate certain limitations of the traditional approach. We compare and discuss multiple ways of using a neural network to approximate extra hidden states or alternative transition rates. In particular we assess their ability to learn the missing dynamics, and ask whether we can use these models to handle model discrepancy. Finally, we discuss the practicality and limitations of using neural networks and their potential applications.

scholarly journals A Heuristic Derived from Analysis of the Ion Channel Structural Proteome Permits the Rapid Identification of Hydrophobic Gates

2018 ◽  
Author(s):  
Shanlin Rao ◽  
Gianni Klesse ◽  
Phillip J. Stansfeld ◽  
Stephen J. Tucker ◽  
Mark S.P. Sansom
Keyword(s):  
Machine Learning ◽  
Ion Channels ◽  
Ion Channel ◽  
Functional State ◽  
Conformational Changes ◽  
Rapid Identification ◽  
Ion Permeation ◽  
Ionic Flux ◽  
Easy Method ◽  
Channel Structures

AbstractIon channel proteins control ionic flux across biological membranes through conformational changes in their transmembrane pores. An exponentially increasing number of channel structures captured in different conformational states are now being determined. However, these newly-resolved structures are commonly classified as either open or closed based solely on the physical dimensions of their pore and it is now known that more accurate annotation of their conductive state requires an additional assessment of the effect of pore hydrophobicity. A narrow hydrophobic gate region may disfavour liquid-phase water, leading to local de-wetting which will form an energetic barrier to water and ion permeation without steric occlusion of the pore. Here we quantify the combined influence of radius and hydrophobicity on pore de-wetting by applying molecular dynamics simulations and machine learning to nearly 200 ion channel structures. This allows us to propose a simple simulation-free heuristic model that rapidly and accurately predicts the presence of hydrophobic gates. This not only enables the functional annotation of new channel structures as soon as they are determined, but may also facilitate the design of novel nanopores controlled by hydrophobic gates.Significance statementIon channels are nanoscale protein pores in cell membranes. An exponentially increasing number of structures for channels means that computational methods for predicting their functional state are needed. Hydrophobic gates in ion channels result in local de-wetting of pores which functionally closes them to water and ion permeation. We use simulations of water behaviour within nearly 200 different ion channel structures to explore how the radius and hydrophobicity of pores determine their hydration vs. de-wetting behaviour. Machine learning-assisted analysis of these simulations enables us to propose a simple model for this relationship. This allows us to present an easy method for the rapid prediction of the functional state of new channel structures as they emerge.

scholarly journals RPnet: A Reverse Projection Based Neural Network for Coarse-graining Metastable Conformational States for Protein Dynamics

2021 ◽  
Author(s):  
Hanlin Gu ◽  
Wei Wang ◽  
Siqin Cao ◽  
Ilona Christy UNARTA ◽  
Yuan Yao ◽  
...  
Keyword(s):  
Neural Network ◽  
Loss Function ◽  
Conformational Changes ◽  
Conformational Dynamics ◽  
Coarse Graining ◽  
State Transitions ◽  
Biological Macromolecules ◽  
Projection Scheme ◽  
Long Time ◽  
Transition Modes

Markov State Model (MSM) is a powerful tool for modeling the long timescale dynamics based on numerous short molecular dynamics (MD) simulation trajectories, which makes it a useful tool for elucidating the conformational changes of biological macromolecules. By partitioning the phase space into discretized states and estimate the probabilities of inter-state transitions based on short MD trajectories, one can construct a kinetic network model that could be used to extrapolate long time kinetics if the Markovian condition is met. However, meeting the Markovian condition often requires hundreds or even thousands of states (microstates), which greatly hinders the comprehension of conformational dynamics of complex biomolecules. Kinetic lumping algorithms can coarse grain numerous microstates into a handful of metastable states (macrostates), which would greatly facilitate the elucidation of biological mechanisms. In this work, we have developed a reverse projection based neural network (RPnet) method to lump microstates into macrostates, by making use of a physics-based loss function based on the projection operator framework of conformational dynamics. By recognizing that microstate and macrostate transition modes can be related through a projection process, we have developed a reverse projection scheme to directly compare the microstate and macrostate dynamics. Based on this reverse projection scheme, we designed a loss function that allows effectively assess the quality of a given kinetic lumping. We then make use of a neural network to efficiently minimize this loss function to obtain an optimized set of macrostates. We have demonstrated the power of our RPnet in analyzing the dynamics of a numerical 2D potential, alanine dipeptide, and the clamp opening of an RNA polymerase. In all these systems, we have illustrated that our method could yield comparable or better results than competing methods in terms of state partitioning and reproduction of slow dynamics. We expect that our RPnet holds promise in analyzing conformational dynamics of biological macromolecules.

Metal bridges to probe membrane ion channel structure and function

2015 ◽  
Vol 6 (3) ◽  
pp. 191-203 ◽  
Author(s):  
Paul Linsdell
Keyword(s):  
Ion Channels ◽  
Ion Channel ◽  
Conformational Changes ◽  
Three Dimensional ◽  
Structure And Function ◽  
Side Chains ◽  
Channel Protein ◽  
Conformational Rearrangements ◽  
And Function ◽  
Different Parts

AbstractIon channels are integral membrane proteins that undergo important conformational changes as they open and close to control transmembrane flux of different ions. The molecular underpinnings of these dynamic conformational rearrangements are difficult to ascertain using current structural methods. Several functional approaches have been used to understand two- and three-dimensional dynamic structures of ion channels, based on the reactivity of the cysteine side-chain. Two-dimensional structural rearrangements, such as changes in the accessibility of different parts of the channel protein to the bulk solution on either side of the membrane, are used to define movements within the permeation pathway, such as those that open and close ion channel gates. Three-dimensional rearrangements – in which two different parts of the channel protein change their proximity during conformational changes – are probed by cross-linking or bridging together two cysteine side-chains. Particularly useful in this regard are so-called metal bridges formed when two or more cysteine side-chains form a high-affinity binding site for metal ions such as Cd2+ or Zn2+. This review describes the use of these different techniques for the study of ion channel dynamic structure and function, including a comprehensive review of the different kinds of conformational rearrangements that have been studied in different channel types via the identification of intra-molecular metal bridges. Factors that influence the affinities and conformational sensitivities of these metal bridges, as well as the kinds of structural inferences that can be drawn from these studies, are also discussed.

scholarly journals CORRELATIONAL PATCH-CLAMP SPECTROMETRY OF THE ION CHANNELS

2017 ◽  
Author(s):  
Oleg Gradov
Keyword(s):  
Ion Channels ◽  
Patch Clamp ◽  
Ion Channel ◽  
Conformational Changes ◽  
Metal Ion ◽  
Ion Selectivity ◽  
Special Kind ◽  
Channel Structure ◽  
Spectral Processing ◽  
Electrophysiological Response

Membrane ion channels operate in accordance with the main principles of coordination chemistry. Coordination number is known to determine the ion selectivity of the sodium and potassium channels. there are known both ligand-dependent and ligand-controlled ion channels operating within the supramolecular coordination fixation principles. The channel-forming ionophores form the structures which bind cations via coordination bonds leading to the conformational changes with the adjustment of the whole supramolecular architecture providing the ion channel selectivity. Such kind of non-covalent systems underlie the electrogenic membrane functions and the potential-controlled transmembrane ion transfer systems. They can be studied by means of the path-clamp method (i.e. the local membrane potential fixation), such as the «anion clamp», applied together with the analysis of the metal ion coordination geometry with the ion channels. However, such methods are not capable to register the ion channel conformational state in situ - during the ion coordination - with the molecular resolution of the ion channel structure. In this regard there is a need to develop dynamical methods capable of the simultaneous registration of the conformational and metallomic / elementomic coordination parameters and the electrophysiological response to the ion coordination. We propose to develop for this purpose a special kind of spectroscopic systems providing registration of the electrophysiological parameters and the single ion channel response by means of the local potential fixation techniques (patch-clamp / voltage-clamp) with the advanced spectral processing and the subsequent data mining, with the simultaneous spectral detection of the ion channel state as a coordination and conformationally labile supramolecular structure, with the final data processing results presented not as the single spectra, but as the spectral correlogram.Градов О. В., Орехов Ф. К. Корреляционная патч-кламп-спектрометрия ионных каналов – сочетание спектрального анализа электрофизиологического отклика каналома в нежестком реальном времени и методов спектроскопии ионных каналов как координационных (комплексных) структур // Биомедицинская инженерия и электроника. — 2016. — № 2(13). — С. 5–28.

scholarly journals Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System

2018 ◽  
Vol 28 (09) ◽  
pp. 1850007
Author(s):  
Francisco Zamora-Martinez ◽  
Maria Jose Castro-Bleda
Keyword(s):  
Neural Network ◽  
Machine Translation ◽  
Language Processing ◽  
Traditional Approach ◽  
Computational Cost ◽  
Integrated Approach ◽  
Language Models ◽  
Translation System ◽  
Neural Net ◽  
Network Language

Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding stage, breaking the traditional approach based on [Formula: see text]-best list rescoring. The neural net models (both language models (LMs) and translation models) are fully coupled in the decoding stage, allowing to more strongly influence the translation quality. Computational issues were solved by using a novel idea based on memorization and smoothing of the softmax constants to avoid their computation, which introduces a trade-off between LM quality and computational cost. These ideas were studied in a machine translation task with different combinations of neural networks used both as translation models and as target LMs, comparing phrase-based and [Formula: see text]-gram-based systems, showing that the integrated approach seems more promising for [Formula: see text]-gram-based systems, even with nonfull-quality NNLMs.

Time Fractional Differential Equation Model With Random Derivative Order

2009 ◽  
Author(s):  
Hongguang Sun ◽  
Yangquan Chen ◽  
Wen Chen
Keyword(s):  
Differential Equation ◽  
Fractional Differential Equation ◽  
Diffusion Processes ◽  
Time Derivative ◽  
Equation Model ◽  
Differential Equation Model ◽  
New Model ◽  
Potential Applications ◽  
Fractional Differential ◽  
Derivative Order

This paper proposes a new type of fractional differential equation model, named time fractional differential equation model, in which noise term is included in the time derivative order. The new model is applied to anomalous relaxation and diffusion processes suffering noisy field. The analysis and numerical simulation results show that our model can well describes the feature of these processes. We also find that the scale parameter and the frequency of the noise play a crucial role in the behaviors of these systems. At the end, we recognize some potential applications of this new model.

scholarly journals TOK Homologue in Neurospora crassa: First Cloning and Functional Characterization of an Ion Channel in a Filamentous Fungus

2003 ◽  
Vol 2 (1) ◽  
pp. 181-190 ◽  
Author(s):  
Stephen K. Roberts
Keyword(s):  
Ion Channels ◽  
Ion Channel ◽  
Neurospora Crassa ◽  
Filamentous Fungus ◽  
Single Channel ◽  
Functional Characterization ◽  
Reversal Potential ◽  
Channel Activity ◽  
Biophysical Properties ◽  
Patch Clamp Technique

ABSTRACT In contrast to animal and plant cells, very little is known of ion channel function in fungal physiology. The life cycle of most fungi depends on the “filamentous” polarized growth of hyphal cells; however, no ion channels have been cloned from filamentous fungi and comparatively few preliminary recordings of ion channel activity have been made. In an attempt to gain an insight into the role of ion channels in fungal hyphal physiology, a homolog of the yeast K+ channel (ScTOK1) was cloned from the filamentous fungus, Neurospora crassa. The patch clamp technique was used to investigate the biophysical properties of the N. crassa K+ channel (NcTOKA) after heterologous expression of NcTOKA in yeast. NcTOKA mediated mainly time-dependent outward whole-cell currents, and the reversal potential of these currents indicated that it conducted K+ efflux. NcTOKA channel gating was sensitive to extracellular K+ such that channel activation was dependent on the reversal potential for K+. However, expression of NcTOKA was able to overcome the K+ auxotrophy of a yeast mutant missing the K+ uptake transporters TRK1 and TRK2, suggesting that NcTOKA also mediated K+ influx. Consistent with this, close inspection of NcTOKA-mediated currents revealed small inward K+ currents at potentials negative of EK. NcTOKA single-channel activity was characterized by rapid flickering between the open and closed states with a unitary conductance of 16 pS. NcTOKA was effectively blocked by extracellular Ca2+, verapamil, quinine, and TEA+ but was insensitive to Cs+, 4-aminopyridine, and glibenclamide. The physiological significance of NcTOKA is discussed in the context of its biophysical properties.

Ion channel activities of cultured rat mesangial cells

1991 ◽  
Vol 261 (5) ◽  
pp. F808-F814 ◽  
Author(s):  
H. Matsunaga ◽  
N. Yamashita ◽  
Y. Miyajima ◽  
T. Okuda ◽  
H. Chang ◽  
...  
Keyword(s):  
Angiotensin Ii ◽  
Ion Channels ◽  
Patch Clamp ◽  
Ion Channel ◽  
Arginine Vasopressin ◽  
Mesangial Cells ◽  
Cation Channel ◽  
K Channel ◽  
Patch Clamp Technique ◽  
Inside Out

We used the patch-clamp technique to clarify the nature of ion channels in renal mesangial cells in culture. In the cell-attached mode most patches were silent in the absence of agonists. In some patches a 25-pS nonselective channel was observed. This 25-pS cation channel was consistently observed in inside-out patches, and it was activated by intracellular Ca2+. Excised patch experiments also revealed the existence of a 40-pS K+ channel, which was activated by intracellular Ca2+. This 40-pS K+ channel was observed infrequently in the cell-attached mode. The activities of both channels were increased by arginine vasopressin or angiotensin II, resulting from an increase in intracellular Ca2+ concentration.

scholarly journals Proper Voltage-Dependent Ion Channel Function in Dysferlin-Deficient Cardiomyocytes

2015 ◽  
Vol 36 (3) ◽  
pp. 1049-1058 ◽  
Author(s):  
Lena Rubi ◽  
Vaibhavkumar S. Gawali ◽  
Helmut Kubista ◽  
Hannes Todt ◽  
Karlheinz Hilber ◽  
...  
Keyword(s):  
Ion Channels ◽  
Muscular Dystrophy ◽  
Ion Channel ◽  
Cardiac Electrophysiology ◽  
Cardiac Complications ◽  
Membrane Repair ◽  
Patch Clamp Technique ◽  
Cardiac Ion Channels ◽  
Ventricular Cardiomyocytes ◽  
Voltage Dependent

Background/Aims: Dysferlin plays a decisive role in calcium-dependent membrane repair in myocytes. Mutations in the encoding DYSF gene cause a number of myopathies, e.g. limb-girdle muscular dystrophy type 2B (LGMD2B). Besides skeletal muscle degenerative processes, dysferlin deficiency is also associated with cardiac complications. Thus, both LGMD2B patients and dysferlin-deficient mice develop a dilated cardiomyopathy. We and others have recently reported that dystrophin-deficient ventricular cardiomyocytes from mouse models of Duchenne muscular dystrophy show significant abnormalities in voltage-dependent ion channels, which may contribute to the pathophysiology in dystrophic cardiomyopathy. The aim of the present study was to investigate if dysferlin, like dystrophin, is a regulator of cardiac ion channels. Methods and Results: By using the whole cell patch-clamp technique, we compared the properties of voltage-dependent calcium and sodium channels, as well as action potentials in ventricular cardiomyocytes isolated from the hearts of normal and dysferlin-deficient (dysf) mice. In contrast to dystrophin deficiency, the lack of dysferlin did not impair the ion channel properties and left action potential parameters unaltered. In connection with normal ECGs in dysf mice these results suggest that dysferlin deficiency does not perturb cardiac electrophysiology. Conclusion: Our study demonstrates that dysferlin does not regulate cardiac voltage-dependent ion channels, and implies that abnormalities in cardiac ion channels are not a universal characteristic of all muscular dystrophy types.

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