Brownian dynamics theory for predicting internal and external blockages of tetraethylammonium in the KcsA potassium channel

Computational methods of studying the binding of toxins from venomous animals to biological ion channels: theory and applications

The discovery of new drugs that selectively block or modulate ion channels has great potential to provide new treatments for a host of conditions. One promising avenue revolves around modifying or mimicking certain naturally occurring ion channel modulator toxins. This strategy appears to offer the prospect of designing drugs that are both potent and specific. The use of computational modeling is crucial to this endeavor, as it has the potential to provide lower cost alternatives for exploring the effects of new compounds on ion channels. In addition, computational modeling can provide structural information and theoretical understanding that is not easily derivable from experimental results. In this review, we look at the theory and computational methods that are applicable to the study of ion channel modulators. The first section provides an introduction to various theoretical concepts, including force-fields and the statistical mechanics of binding. We then look at various computational techniques available to the researcher, including molecular dynamics, brownian dynamics, and molecular docking systems. The latter section of the review explores applications of these techniques, concentrating on pore blocker and gating modifier toxins of potassium and sodium channels. After first discussing the structural features of these channels, and their modes of block, we provide an in-depth review of past computational work that has been carried out. Finally, we discuss prospects for future developments in the field.

Engineering aspects of biological ion channels--from biosensors to computational models for permeation

This paper presents two important engineering aspects of biological ion channels-how to build sensors out of gramicidin channels and how to construct computational models for ion channel permeation. We describe our recent research in these areas, potential challenges and possible solutions.

Semi-Markov models for brownian dynamics permeation in biological ion channels

Constructing accurate computational models that explain how ions permeate through a biological ion channel is an important problem in biophysics and drug design. Brownian dynamics simulations are large-scale interacting particle computer simulations for modeling ion channel permeation but can be computationally prohibitive. In this paper, we show the somewhat surprising result that a small-dimensional semi-Markov model can generate events (such as conduction events and dwell times at binding sites in the protein) that are statistically indistinguishable from brownian dynamics computer simulation. This approach enables the use of extrapolation techniques to predict channel conduction when performing the actual brownian dynamics simulation that is computationally intractable. Numerical studies on the simulation of gramicidin A ion channels are presented.

An asymmetric approach to modeling ion channels using finite element analysis

Biological ion channels are water filled pores in the cell membrane. They regulate the flow of ions in and out of the cell. Modeling the dynamics of these channels and relating their structure to functionality is crucial in understanding the mechanisms by which they conduct. This paper proposes a novel Finite Element Method (FEM) based simulation framework for modeling of ion channels that does not assume channel symmetry. This is the first framework that allows the use of multiple dielectric constants inside such channels without assuming geometrical symmetry thus providing a more realistic model of the channel. Due to the run-time complexity of the problem, lookup tables must be constructed in memory to store pre-calculated electric potential information. The large number of elements involved in FEM and channel resolution requirements can potentially result in very large lookup tables leading to a performance "bottleneck". This paper answers the following question: Does the accuracy introduced by using an asymmetric model outweigh the inaccuracy caused by having to reduce the size and resolution of electric-field look-up tables? This paper compares the memory footprint of an ion channel simulator that assumes a symmetric channel model versus an asymmetric model. We show that currently available personal computers are sufficient for attaining reasonable levels of accuracy for both. Our results show diminishing returns in accuracy with tables sized greater than 8.5 GB for the asymmetric model.

Dynamics of voltage profile in enzymatic ion transporters, demonstrated in electrokinetics of proton pumping rhodopsin

H(+)-pumping rhodopsins mediate a primordial conversion of light to metabolic energy. Bacteriorhodopsin from Halobacterium salinarium is the first identified and (biochemically) best-studied H(+)-pumping rhodopsin. The electrical properties of H(+)-pumping rhodopsins, however, are known in more detail for the homolog Acetabularia rhodopsin, isolated from the eukaryotic green alga Acetabularia acetabulum. Based on data from Acetabularia rhodopsin we present a general reaction kinetic model of H(+)-pumping rhodopsins with only seven independent parameters, which fits the kinetic properties of photocurrents as functions of light, transmembrane voltage, internal and external pH, and time. The model describes fast photoisomerization of retinal with simultaneous H(+) transfer to an H(+) acceptor, reprotonation of retinal from the intracellular face via an H(+) donor, and proton release to the extracellular space via an H(+) release complex. The voltage sensitivities of the individual reaction steps and their temporal changes are treated here by a novel approach, whereby--as in an Ohmic voltage divider--the effective portions of the total transmembrane voltage decrease with the relative velocities of the individual reaction steps. This analysis quantitatively infers dynamic changes of the voltage profile and of the pK values of the H(+)-binding sites involved.