Moh. Faizal Fajri Al Amin1 , Adita Sutresno 1, Freddy Haryanto 1
1Nuclear Physics and Biophysics Research Division in Bandung Institute of Technology,
Ganesha Street Number 10, Bandung 40132, Indonesia
Preliminary Study of the Diffusion Process for Two Different
Molecules Using Monte Carlo Simulation Cell (MCell)
INTRODUCTION
Diffusion play fundamental role in bio-chemical processes in living cells. In this study, simulation of diffusion molecule, using Monte Carlo-based software, known as Monte Carlo Cell (MCell). In general, MCell uses Monte Carlo algorithms to simulate simultaneous diffusion and chemical reactions of molecules in complex 3-D spaces. The diffusing molecules move according to a 3-D random walk that recapitulates net displacements arising from Brownian motion during time-step intervals. Application of Mcell is to simulate the biological signal on the atomic level. By using MCell we can predict the spread of simulation diffusion of molecules. The molecule movement can also identified and estimated to determine time process in the simulation.
RESULT AND DISCUSSION
METHODS
CONCLUSION
Monte Carlo Cell (MCell) was able to simulate the diffusion of molecule in biological scale and to study the process of diffusion depend on input parameter.
ACKNOWLEDGEMENTS
This work is partially supported by ITB and JICA under the contract number: 1575/I1.C01/PL/2014, and the author would like to thank AOCMP & SEACOMP which provide facilities, so this poster can be presented.
REFERENCES
1) J. P. Dilger, "Monte Carlo Simulation of Buffered Diffusion into and out of a Model Synapse," Biophysics Journal, vol. 98, pp. 959-967, 2010
2) B. M. Regner, "Anomalous Diffusion of Single Particle in Cytoplasm,"
BIOPHYSICAL JOURNAL, pp. 1652-1660, 2013.
3) E. Tajkhorshid, A. Aksimentiev, M. G. Ilya Balabin, B. Isralewitz, J. C. Phillips, F. Zhu and K. Schulten, "Large scale simulation of protein mechanics and function," in Advances in protein chemistry 66, California, Elsevier Academic Press, 2003, pp. 195-248.
4) J. Crank, The Mathematic of Diffusion, London: Oxford University Press , 1956
MCell software is divided in two stages, modeling and simulation. Modeling is to create geometry, surface, molecule and input parameter. Simulation is process of input parameter into visualization of simulation.
AOCMP & SEACOMP 2014
The 14th Asia-Oceania Congress of Medical Physics & The 12th South East Asia Congress of Medical Physics
Medical Physics for Advanced Medicine Ho Chi Minh City, Vietnam
October 23th-25th 2014
Organized by: Supported by:
MCell simulation use Fick’s Law of diffusion. Molecular species is present at a concentration c(r, t) and is free to undergo random thermal motion in a fluid. The time evolution of concentration of that species is given by the diffusion equation :
�
�� = ���
In particular, a single molecule is at the origin at time t = 0 and diffuses away with diffusion constant D. Then it can be shown from the diffusion equation that :
�, � ∝
���� / −�∙�/���
1. Modelling
2. Simulation
Cube, cylinder and icosphere is used as a geometry model for this simulation. There are two types of molecule, volume molecule and surface molecule. Volume molecule can diffuse in space, and surface molecule only diffuse in surface.
The effect of variations in the number of molecules for 1000-10000 molecules is not significant in the simulation process. Based on data (A), the variation of molecule have same value after being normalized. The effect of the thickness field of 0.1 - 1 �m (B), and the variation of geometry (C) is linear, due to the longer time to reach 50% of diffusion molecule for the thicker areas, and different volume in geometry.
Fig 3. Normalized Value for Number of Molecule Fig 4. Time to 50% for different thickness cube
Fig 5. Time to 50% for different geometry
