Brownian dynamics simulations of ion transport through the VDAC.

Kyu Il Lee, Huan Rui, Richard W Pastor, Wonpil Im

Journal: Biophysical journal 2011;100(3):611-619

PMID: 21281575

Abstract

It is important to gain a physical understanding of ion transport through the voltage-dependent anion channel (VDAC) because this channel provides primary permeation pathways for metabolites and electrolytes between the cytosol and mitochondria. We performed grand canonical Monte Carlo/Brownian dynamics (GCMC/BD) simulations to explore the ion transport properties of human VDAC isoform 1 (hVDAC1; PDB:2K4T) embedded in an implicit membrane. When the MD-derived, space-dependent diffusion constant was used in the GCMC/BD simulations, the current-voltage characteristics and ion number profiles inside the pore showed excellent agreement with those calculated from all-atom molecular-dynamics (MD) simulations, thereby validating the GCMC/BD approach. Of the 20 NMR models of hVDAC1 currently available, the third one (NMR03) best reproduces both experimental single-channel conductance and ion selectivity (i.e., the reversal potential). In addition, detailed analyses of the ion trajectories, one-dimensional multi-ion potential of mean force, and protein charge distribution reveal that electrostatic interactions play an important role in the channel structure and ion transport relationship. Finally, the GCMC/BD simulations of various mutants based on NMR03 show good agreement with experimental ion selectivity. The difference in ion selectivity between the wild-type and the mutants is the result of altered potential of mean force profiles that are dominated by the electrostatic interactions.

Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Address: Center for Bioinformatics, University of Kansas, Lawrence, Kansas; Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas.; Laboratory of Computational Biology, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland.; Center for Bioinformatics, University of Kansas, Lawrence, Kansas; Department of Molecular Biosciences, University of Kansas, Lawrence, Kansas. Electronic address: [email protected].
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