Reservoir Boundaries in Brownian Dynamics Simulations of Ion Channels

Corry, Ben; Hoyles, Matthew; Allen, Toby W.; Walker, Michael J.; Kuyucak, Serdar; Chung, Shin-Ho

doi:10.1016/s0006-3495(02)75546-x

Cited by 62 publications

(76 citation statements)

References 39 publications

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“…Simulations of these effects would be interesting (using one of the electrostatic algorithms of Refs. [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][44][45][46][47] and can be the topic of future studies. However, the main conclusions of this study would not change.…”

Section: Discussionmentioning

confidence: 99%

Dynamic Monte Carlo Simulation of Coupled Transport through a Narrow Multiply-Occupied Pore

et al. 2013

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Dynamic Monte Carlo simulations are used to study coupled transport (co-transport) through sub-nanometer-diameter pores. In this classic Hodgkin-Keynes mechanism, an ion species uses the large flux of an abundant ion species to move against its concentration gradient. The efficiency of co-transport is examined for various pore parameters so that synthetic nanopores can be engineered to maximize this effect. In general, the pore must be narrow enough that ions cannot pass each other and the charge of the pore large enough to attract many ions so that they exchange momentum. Co-transport efficiency increases as pore length increases, but even very short pores exhibit co-transport, in contradiction to the usual perception that long pores are necessary. The parameter ranges where co-transport occurs is consistent with current and near-future synthetic nanopore geometry parameters, suggesting that co-transport of ions may be a new application of nanopores.

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Section: Discussionmentioning

confidence: 99%

Dynamic Monte Carlo Simulation of Coupled Transport through a Narrow Multiply-Occupied Pore

et al. 2013

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“…The electric field and potential, which are effects of the dielectric boundary created by the water-protein interaction, as well as the reaction field, which represents the interaction of ions with charges on the channel wall, are calculated prior to the simulation and interpolate the required values during simulation [74][75][76]. Membrane potential, which is a driving force for K + ions passing through the pore, can be expressed with either a uniform electric field across the system or a grand canonical Monte Carlo method [77,78]. Under these conditions, ion conduction has been examined for the bacterial KcsA channel [68,70,76,79].…”

Section: In Silico Prediction Systems For Chemical Block Of Hergmentioning

confidence: 99%

In Silico Prediction of the Chemical Block of Human Ether-a-Go-Go-Related Gene (hERG) K+ Current

et al. 2008

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A variety of compounds with different chemical properties directly interact with the cardiac repolarizing K + channel encoded by the human ether-a-go-go-related gene (hERG). This causes acquired forms of QT prolongation, which can result in lethal cardiac arrhythmias, including torsades de pointes one of the most serious adverse effects of various therapeutic agents. Prediction of this phenomenon will improve the safety of pharmacological therapy and also facilitate the process of drug development. Here we propose a strategy for the development of an in silico system to predict the potency of chemical compounds to block hERG. The system consists of two sequential processes. The first process is a ligand-based prediction to estimate half-maximal concentrations for the block of compounds inhibiting hERG current using the relationship between chemical features and activities of compounds. The second process is a protein-based prediction that comprises homology modeling of hERG, docking simulation of chemical-channel interaction, analysis of the shape of the channel pore cavity, and Brownian dynamics simulation to estimate hERG currents in the presence and absence of chemical blockers. Since each process is a combination of various calculations, the criterion for assessment at each calculation and the strategy to integrate these steps are significant for the construction of the system to predict a chemical's block of hERG current and also to predict the risk of inducing cardiac arrhythmias from the chemical information. The principles and criteria of elemental computations along this strategy are described.Key words: hERG, quantitative structure-activity relationship, molecular docking, Brownian dynamics simulation.Many ion channels and ion transporting systems contribute to the generation of the action potential of the heart. The ventricular action potential possesses a longlasting plateau that is terminated by the activation of repolarizing K + currents, I Kr and I Ks . The disturbance of these currents causes prolongation of the action potential duration and thus the QT interval of the electrocardiogram, and in many cases a worsening of transmural dispersion of repolarization [1][2][3]. These are the substrates for generation of life-threatening cardiac arrhythmias, including torsades de pointes. Many compounds inhibit I Kr , whose pore-forming subunit is the human ether-a-gogo-related gene (hERG) product. This can cause acquired forms of long QT syndrome [4][5][6]. The compounds exhibit a broad spectrum, including not only cardiac ion channel blockers, but also antipsychotic agents, antidepressant agents, antimicrobial agents, phosphodiesterase inhibitors, topoisomerase II inhibitors, and antagonists for G protein-coupled receptors, such as nonsedating antihistamine H 1 receptor blockers and β blockers [6]. The development of methods that could predict this phenomenon would improve the safety of pharmacological therapy and also facilitate the process of drug development.Here we propose an in silico str...

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“…nanochannels ranges from 6 to 20 Å and the unique phenomenon of ion transport is shown. 20 23 24 According to reports, under higher voltages, the nanochannel is too narrow for ions to pass each other in a shorter time, 23 and congestion is the main reason for the special characteristics that have been observed in such small nanochannels. It is obvious that these phenomenons are correlated with the small dimension of nanochannels, as well as the influence of external applied voltage on the distribution of ions in nanochannels.…”

Section: Introductionmentioning

confidence: 99%

Ion Distribution in a 3 nm in Diameter Nanopore

Ge¹,

An²,

Kang³

et al. 2015

j comput theor nanosci

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The influence of surface charge density and applied bias on the ion distribution of a 3 nm in diameter nanofluidic pore was investigated using molecular dynamics simulations. Our simulation results indicate that the radial ion distribution profile with different surface charge density under applied bias is similar to that without applied bias except that the first peak of the ion distribution appears to become small and far away from the solid wall under applied bias. This unusual observation is attributed to the principle that with a higher applied bias, ions have more kinetic energy and relocate to an area farther away from the wall. Considering that ion mobility along a radius is asymmetric, it is can be concluded, that by changing the ion radial distribution, the applied bias will cause a change in ion selectivity in a nanopore.

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Reservoir Boundaries in Brownian Dynamics Simulations of Ion Channels

Cited by 62 publications

References 39 publications

Dynamic Monte Carlo Simulation of Coupled Transport through a Narrow Multiply-Occupied Pore

Dynamic Monte Carlo Simulation of Coupled Transport through a Narrow Multiply-Occupied Pore

In Silico Prediction of the Chemical Block of Human Ether-a-Go-Go-Related Gene (hERG) K+ Current

Ion Distribution in a 3 nm in Diameter Nanopore

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