BioMOCA—a Boltzmann transport Monte Carlo model for ion channel simulation

Abstract

With the recent availability of high-resolution structural information for several key ion channel proteins and large-scale computational resources, Molecular Dynamics has become an increasingly popular tool for ion channel simulation. However, the CPU requirements for simulating ion transport on time scales relevant to conduction still exceed the resources presently available. To address this problem, we have developed Biology Monte Carlo (BioMOCA), a three-dimensional (3D) coarse-grained particle ion channel simulator based on the Boltzmann Transport Monte Carlo (BTMC) methodology. Although this approach is widely employed in the engineering community to study charge transport in electron devices, its application to molecular biology and electrolytes in general is new and hence must be validated. The pair correlation function, which is a measure of the microscopic structure of matter, provides a suitable benchmark to compare the BTMC method against the well-established Equilibrium Monte Carlo (EMC) approach. For validation purposes BioMOCA is used to simulate several simple homogeneous equilibrium electrolytes at concentrations of physiological interest. The ion–ion pair correlation functions computed from these simulations compare very well with those obtained from EMC simulations. We also demonstrate several performance-improving techniques that result in a several-fold speed-up without compromising the pair correlation function. BioMOCA is then used to perform full 3D simulations of ion transport in the gramicidin A channel in situ in a membrane environment, as well as to study the link between the electrostatic and dielectric properties of the protein and the channel's selectivity.

Keywords:

• Ion channels
• Nanodevices
• Gramicidin
• Monte Carlo simulations

Acknowledgements

This work was supported by financial grants from the National Science Foundation — Network for Computational Nanotechnology (Grant No. EEC-0228390), Defense Advanced Research Projects Agency (DARPA SIMBIOSYS AF NA 0533) and by the National Center for Supercomputing Applications (NCSA).

Notes

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