Dynamics accelerate the kinetics of ion diffusion through channels: Continuous-time random walk models beyond the mean field approximation

Author:

Mondal Ronnie12ORCID,Vaissier Welborn Valerie12ORCID

Affiliation:

1. Department of Chemistry, Virginia Tech 1 , Blacksburg, Virginia 24061, USA

2. Macromolecules Innovation Institute, Virginia Tech 2 , Blacksburg, Virginia 24061, USA

Abstract

Ion channels are proteins that play a significant role in physiological processes, including neuronal excitability and signal transduction. However, the precise mechanisms by which these proteins facilitate ion diffusion through cell membranes are not well understood. This is because experimental techniques to characterize ion channel activity operate on a time scale too large to understand the role of the various protein conformations on diffusion. Meanwhile, computational approaches operate on a time scale too short to rationalize the observed behavior at the microscopic scale. In this paper, we present a continuous-time random walk model that aims to bridge the scales between the atomistic models of ion channels and the experimental measurement of their conductance. We show how diffusion slows down in complex systems by using 3D lattices that map out the pore geometry of two channels: Nav1.7 and gramicidin. We also introduce spatial and dynamic site disorder to account for system heterogeneity beyond the mean field approximation. Computed diffusion coefficients show that an increase in spatial disorder slows down diffusion kinetics, while dynamic disorder has the opposite effect. Our results imply that microscopic or phenomenological models based on the potential of mean force data overlook the functional importance of protein dynamics on ion diffusion through channels.

Funder

Virginia Tech Department Faculty Start-up Funds

Advanced Research Computing at Virginia Tech

Publisher

AIP Publishing

Reference73 articles.

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