With the recent availability of high-resolution structure 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 the problem, we have developed Biology Monte Carlo (BioMOCA), a three-dimensional coarse-grained particle ion channel simulator based on the Boltzmann Transport Monte Carlo (BTMC) methodology.

The BioMOCA code has progressed steadily to become a flexible tool for investigation of ionic transport that can be used as a complement of more expensive Molecular Dynamics simulations. The picture shown here on the left contains results from a simulation of ompf porin ionic channel. The volumes occupied by traversal trajectories followed by a K+ ion (green) and a Cl− ion (grey) show how cation and anion occupy different portion of the pore, reflecting the highly charge nature of the protein forming the channel. Available Molecular Dynamics simulations can only give a hint of such behavior, since time-resolution is restricted by computational cost. The information is very valuable for the analysis of pioneering devices that incorporate membranes with porin channels. A prototype device has been realized recently, for instance, at Arizona State University.

Computational Electronics Group, University of Illinois at Urbanca-Champign. This work funded by NSF.

If you reference this work in a publication, please cite as follows:

• T.A. Vad Der Straaten, G. Kathawala, A. Trellakis, R.S. Eisenberg, and U. Ravaioli, "BioMOCA - a Boltzmann transport Monte Carlo model for ion channel simulations," Molecular Simulatin, Vol. 31, No. 2-3, pp 151-171 (2005).

• Toghraee, Reza; Ravaioli, Umberto (2008), "BioMOCA," doi: 10254/nanohub-r1497.1.

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In addition, we would appreciate it if you would add the following acknowledgment to your publication:

• Simulation services for results presented here were provided by the Network for Computational Nanotechnology (NCN) at nanoHUB.org

1. bio
2. Illinois
3. ion channels
4. Monte Carlo
5. nano
6. nano/bio
7. nanobio applications
8. nanomedicine
9. transport/Boltzmann
10. uIllinois
11. uiuc