Mesoscopic-level Simulation of Dynamics and Interactions of Biological Molecules Using Monte Carlo Simulation
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A mesoscopic-level method for clarifying living cell dynamics is described that uses Monte Carlo simulation of biological molecule interactions. The molecules are described as particles that take a random walk in 3-dimensional discrete space. Many kinds of molecules (including complex forms) are supported, so complex reactions with enzymes can be simulated. Also described is an field programmable gate array system with reconfigurable hardware that that will support complete modeling of an entire cell. Two-phase processing (migration and reaction) is used to simulate the complex reactions, so the method can be implemented in a limited amount of hardware. The migration and reaction circuits are deeply pipelined, resulting in high performance. Estimated performance is 30 times faster than with a 3.2-GHz Pentium 4 computer. This approach should make it possible to eventually simulate cell interactions involving one billion particles.
KeywordsMonte Carlo simulation signal transduction pathways FPGA
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- 1.M. Kanehisa, “Toward Pathway Engineering: A New Database of Genetic and Molecular Pathways,” Sci. Technol. Jpn., vol. 59, 1996, pp. 34–38.Google Scholar
- 2.G. Michal, Biochemical Pathways: An Atlas of Biochemistry and Molecular Biology, John Wiley & Sons, 1998.Google Scholar
- 3.STKE’s connection map database. http://stke.sciencemag.org/cm/, 2007.
- 4.KEGG: Kyoto Encyclopedia of Genes and Genomes. http://www.genome.jp/kegg, 2007.
- 5.Signaling Pathway Database. http://www.grt.kyushu-u.ac.jp/grt-docs/mogt/sub_study_contents_06.html, 2007.
- 6.Metabolic Pathways of Biochemistry. http://www.gwu.edu/~mpb/, 1998.
- 7.Encyclopedia of Escherichia coli K12 Genes and Metabolism. http://www.ecocyc.org/, 2007.
- 12.J.F. Keane, C. Bradley and C. Ebeling, “A Compiled Accelerator for Biological Cell Signaling Simulations,” in Proc. FPGA2004, 2004, pp. 233–241.Google Scholar
- 14.M. Yoshimi, Y. Osana, T. Fukushima and H. Amano, “Stochastic Simulation for Biochemical Reactions on FPGA,” Proc. FPL2004, LNCS3203, 2004, pp. 105–114.Google Scholar
- 19.A. Suenaga, M. Hatakeyama, M. Ichikawa, X. Yu, N. Futatsugi, T. Narumi, K. Fukui, T. Terada, M. Taiji, M. Shirouzu, S. Yokoyama, and A. Konagaya, “Molecular Dynamics, Free Energy, and SPR Analyses of the Interactions between the SH2 Domain of Grb2 and ErbB Phosphotyrosyl Peptides,” Biochemistry, vol. 42, 2003, pp. 5195–5200.CrossRefGoogle Scholar
- 20.M. Taiji, T. Narumi, Y. Ohno, N. Futatsugi, A. Suenaga, N. Takada, and A. Konagaya, “Protein Explorer: A Petaflops Special-purpose Computer System for Molecular Dynamics Simulations,” in Proc. Supercomputing 2003, 2003, CD-ROM.Google Scholar
- 21.J.R. Weimar, “Cellular Automata Approaches to Enzymatic Reaction Networks,” in Proc. Fifth International Conference on Cellular Automata for Research and Industry, LNCS2493, 2002, pp. 294–303.Google Scholar
- 22.R. Azuma, K. Tetsuji, H. Kobayashi, and A. Konagaya, “Particle Simulation Approach for Subcellular Dynamics and Interactions of Biological Molecules,” BMC Bioinformatics, vol. 7, Suppl. 4, 2006, pp. S20–1–S20–13.Google Scholar
- 23.D.P. Landau and K. Binder, A Guide to Monte Carlo Simulations in Statistical Physics, Cambridge University Press, 2000.Google Scholar
- 24.T.C. Meng, S. Somani, and P. Dhar, “Modeling and Simulation of Biological Systems with Stochasticity,” In Silico Biol., vol. 4, no. 3, 2004, pp. 293–309.Google Scholar
- 25.P.D. Coddington, “Random Number Generators for Parallel Computers”, in Proc. Supercomputing 1996, NHSE Review 1996(2), 1997.Google Scholar
- 26.M. Barel, “Fast Hardware Random Number Generator for the Tausworthe Sequence,” in Proc. the 16th Annual Symposium on Simulation, 1983, pp. 121–135.Google Scholar
- 28.Y. Yamaguchi, T. Maruyama, and T. Hoshino, “High Speed Hardware Computation of Co-evolution Models,” in Proc. European Conference on Artificial Life, LNCS1674, 1999, pp. 566–574.Google Scholar