Semi-Markov Models for Brownian Dynamics Simulation Algorithms in Biological Ion Channels
PrePrint
ISSN: 1545-5963
DOI Bookmark:
http://doi.ieeecomputersociety.org/10.1109/TCBB.2008.136
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, 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 is computationally intractable. Numerical studies on the simulation of gramicidin A ion channels are presented.
Index Terms:
Large scale stochastic simulation, Brownian dynamics, semi-Markov Models
Citation:
Vikram Krishnamurthy, Kai-Yiu Luk, "Semi-Markov Models for Brownian Dynamics Simulation Algorithms in Biological Ion Channels," IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19 Dec. 2008. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/TCBB.2008.136>
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