Difference between revisions of "Team:Kent/Modeling"

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Modeling is important as it allows us to describe the system mathematically. If we change some of the parameters we can see how this will affect the system, this is especially important when the some of the parameters are unknown. We chose to create a simulation as our project dealt with a self-assembling structure that we thought would be exciting to visualize in an interactive way. We have included our code so that other teams can play around and build upon it.
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We used the Monte Carlo method to simulate the stochastic diffusion [3] of monomers from inside a cell and how this leads to the production of amyloid nanowires. A typical E coli cell has a length, l=2μm and a diameter, d=1μm. We take a small observation cube, which looks at both the cell and the bulk outside of the cell; we can extrapolate this to describe the whole system. This has the advantage of requiring less computational power.
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The monomers initially start at the bottom of the observation volume and are allowed to stochastically diffuse. The binding site seeds are located on top of the cells membrane and when a monomer gets close enough to the binding site it may bind and form a link in the chain. Over time the chains can grow to lengths in the range of 60nm to 100μm [1][5][10], these chains are not necessarily straight and persistence length parameter dictates the angles at which particles can bind. The monomer can only interact with the monomer attached to the chain, i.e. there is no branching.
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The system has a periodic potential. When a particle leaves through the side of the observation volume, we can assume that another particle enters through the other side. When a particle reaches the bottom of the observation volume we can assume that the particle is reflected.
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The number of monomers in the system is not necessarily constant; monomers can be created and degraded. However, Hall [8] (2003) argued with the two extreme cases that either; the monomer occur on a time scale much slower than amyloid growth so the number of particles are constant; or that the amyloid growth occur on a time scale much slower than monomer degradation so we can refer to the free concentration of the monomer as constant.
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The Monte Carlo method was simulated in Matlab and visualized using Visual Molecular Dynamics (VMD).
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Revision as of 10:45, 10 September 2015


iGEM Kent 2015


Modeling

Modeling is important as it allows us to describe the system mathematically. If we change some of the parameters in our system we can see how this will affect the system, this is especially important when the some of the parameters are unknown. The main aim of our model is to demonstrate the production of our nanowires in an interactive and interesting way.



More to come soon...