Difference between revisions of "Team:Warwick/BindingAffinity"

 
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<h4>Binding Affinity Modelling</h4>
 
<h4>Binding Affinity Modelling</h4>
 
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<p><img src="https://static.igem.org/mediawiki/2015/6/64/Warwickbubbles1.png" height="120px" width="800px" border="1px"></p>
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So you have a bunch of cells and binding sites that you want to join together. But it’s not that simple. There’s also a chance that they’ll unbind, and so this means that the binding and unbinding will form an equilibrium. This is exactly what we have tried to model. Ka represents the chance that they bind, and kd is the chance that they unbind. Here A represents the amount of cells, and B the amount of DNA binding sites.
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Once we find ka and kd, we use this information to tell biologists about expense, times for reactions, and what values for A and B they should use.
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We have found said differential equation and then analytically solved it. After substituting in empirical data from the experiments, it is impossible to solve the equations to find the binding and unbinding constants (association and disassociation constants). Instead, we used a computational method to find these constants. Put simply this involved trying all the possible combinations of the constants (to the first significant figure) to find which best matches the empirical data. These results tell the biologists which zinc fingers have the best binding ability.<br>
 
We have found said differential equation and then analytically solved it. After substituting in empirical data from the experiments, it is impossible to solve the equations to find the binding and unbinding constants (association and disassociation constants). Instead, we used a computational method to find these constants. Put simply this involved trying all the possible combinations of the constants (to the first significant figure) to find which best matches the empirical data. These results tell the biologists which zinc fingers have the best binding ability.<br>
Another piece of code then uses these new found values to find out how much reactant to use, the related expenses, and how long the reaction will take.<br>
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<br>Another piece of code then uses these new found values to find out how much reactant to use, the related expenses, and how long the reaction will take.<br>
 
We are currently working on a piece of code that will test the DNA sequence to see if they are viable options for our experiment.
 
We are currently working on a piece of code that will test the DNA sequence to see if they are viable options for our experiment.
  
 
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<br><b>Stochastic Modelling for Cell Growth</b>
 
<br>We wanted to understand how the placement of cells changes as time progresses. Cells divide, roughly in the same direction in which they were formed. To model cell division we imagined them situated on a Cartesian coordinate system, and division to place on a polar coordinate system with the original cell as the origin. The population count is modelled with the Gompertz function. To decide which direction the division occur we used two criteria:
 
<br>1.      It must not overlap other cells or DNA
 
<br>2.      The probability is weighted by a normal distribution with the peak in the same direction as the previous generational division
 
<br>The user inputs the DNA structure, the standard deviation for the normal distribution, and the maximum number of cells it should model. It then outputs an animation of the cell community as it develops.
 
  
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<br><b>The Equations</b><br>
 
<br><b>The Equations</b><br>
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We will call the amount (concentration multiplied by volume) of the bacteria A, and the amount of binding site on the DNA (concentration multiplied by volume multiplied by binding sites per DNA sequence) as B.  
 
We will call the amount (concentration multiplied by volume) of the bacteria A, and the amount of binding site on the DNA (concentration multiplied by volume multiplied by binding sites per DNA sequence) as B.  
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<br><i>The rate of change of A= the rate of unbinding-the rate of binding. </i>
 
<br><i>The rate of change of A= the rate of unbinding-the rate of binding. </i>
 
<br>These rates are proportional to the amount of unbinded or binded molecules there are.
 
<br>These rates are proportional to the amount of unbinded or binded molecules there are.
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<br>By letting
 
<br>By letting
  
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<p><img src="https://static.igem.org/mediawiki/2015/2/25/Warwickmodeling2.png" align="left" height="300px" width="400px" border="1px"></p>
 
<p><img src="https://static.igem.org/mediawiki/2015/2/25/Warwickmodeling2.png" align="left" height="300px" width="400px" border="1px"></p>
 
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<br>We can solve this differential equation using separation of variables.
 
<br>We can solve this differential equation using separation of variables.
  
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<br>Where χ is an unknown constant. To find χ we set A=A_0  at t=0.
 
<br>Where χ is an unknown constant. To find χ we set A=A_0  at t=0.
  
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<br>Note that 4ac-b^2 is negative, so the square root cannot be calculated. We now rearrange to cancel out imaginary parts.
 
<br>Note that 4ac-b^2 is negative, so the square root cannot be calculated. We now rearrange to cancel out imaginary parts.
  
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<p><img src="https://static.igem.org/mediawiki/2015/6/66/Warwickmodeling5.png" align="left" height="320px" width="450px" border="1px"></p><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>
 
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<br>Therefore
 
<br>Therefore
  
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<br>Substituting the values for a, b, and c.
 
<br>Substituting the values for a, b, and c.
  
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<br>Let
 
<br>Let
  
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<br>Then
 
<br>Then
  
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<video id="ModellingClip" src="https://static.igem.org/mediawiki/2015/4/48/Warwickmodellingvideo.mp4" controls></video>
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<p><img src="https://static.igem.org/mediawiki/2015/3/37/Warwickmodeling10.png" align="left" height="500px" width="700px" border="1px"></p>
 
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<video id="ModellingClip" src="https://static.igem.org/mediawiki/2015/4/48/Warwickmodellingvideo.mp4" controls></video>
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Latest revision as of 12:52, 17 September 2015

Warwick iGEM 2015