Abstract

We use stochastic simulations to investigate the performance of two recently developed methods for calculating the free energy profiles of ion channels and their electrophysiological properties, such as current–voltage dependence and reversal potential, from molecular dynamics simulations at a single applied voltage. These methods require neither knowledge of the diffusivity nor simulations at multiple voltages, which greatly reduces the computational effort required to probe the electrophysiological properties of ion channels. They can be used to determine the free energy profiles from either forward or backward one-sided properties of ions in the channel, such as ion fluxes, density profiles, committor probabilities, or from their two-sided combination. By generating large sets of stochastic trajectories, which are individually designed to mimic the molecular dynamics crossing statistics of models of channels of trichotoxin, p7 from hepatitis C and a bacterial homolog of the pentameric ligand-gated ion channel, GLIC, we find that the free energy profiles obtained from stochastic simulations corresponding to molecular dynamics simulations of even a modest length are burdened with statistical errors of only 0.3 kcal/mol. Even with many crossing events, applying two-sided formulas substantially reduces statistical errors compared to one-sided formulas. With a properly chosen reference voltage, the current–voltage curves can be reproduced with good accuracy from simulations at a single voltage in a range extending for over 200 mV. If possible, the reference voltages should be chosen not simply to drive a large current in one direction, but to observe crossing events in both directions.

Highlights

  • Ion channels are ubiquitous in living systems in which they mediate ion transport across cell walls [1,2,3]

  • The single-channel conductance of a bacterial homolog of pentameric ligand gated ion channels, GLIC, which consists of 317 residues per subunit is 8 pS [4], similar to the lowest conductance level of a channel made of antimicrobial peptide, alamethicin, which is built of 20 amino acids [5]

  • These results strongly suggest that the proposed model does not represent the native structure of the channel, demonstrating that computational electrophysiology can be used to support and to disprove structural models of ion channels

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Summary

Introduction

Ion channels are ubiquitous in living systems in which they mediate ion transport across cell walls [1,2,3]. In a few cases in which errors are available by way of either direct estimates or comparisons of PMF obtained via different methods [20,24,25,62,63,64,65,66,67,68] they are of the order of 0.2–0.7 kcal/mol, which is similar to what is expected to be the intrinsic accuracy of the formalisms studied here This means that if there were differences between electrophysiological properties obtained from MD simulations at several applied voltages and reconstructed from simulations at a single voltage it would not be possible to determine whether these differences were due to insufficient accuracy of the simulations or to inaccurate reconstruction from the new methods. We fully concentrate on assessing the accuracy of the underlying theory

Theory and Method
Calculating the Potential of Mean Force
Calculating I-V Dependence from Simulation at a Single Voltage
Stochastic Simulations
Connection with Molecular Dynamics
Committor Probabilities
The Potential of Mean Force
Current-Voltage Dependence
Reversal Potential
Conclusions
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