Difference between revisions of "Team:Queens Canada/Model"
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<a href="http://https://2018.igem.org/Team:Queens_Canada/Linker_Development"><img src="https://static.igem.org/mediawiki/2018/b/b6/T--Queens_Canada--PyMOLNoLinker.jpg" alt='nolinker' style="height=50%"/></a> | <a href="http://https://2018.igem.org/Team:Queens_Canada/Linker_Development"><img src="https://static.igem.org/mediawiki/2018/b/b6/T--Queens_Canada--PyMOLNoLinker.jpg" alt='nolinker' style="height=50%"/></a> | ||
| − | <br><font size="6px"><a href=https://2018.igem.org/Team:Queens_Canada/Linker_Development">Linker Development</a></font> | + | <br><font size="6px"><a href="https://2018.igem.org/Team:Queens_Canada/Linker_Development">Linker Development</a></font> |
<p>As a part of our construct it is necessary to build linkers to connect the intein halves with the target receptor. The challenge in developing linkers for the system is that they must be of a specific length that will allow association of the intein halves in the bound conformation of the receptor but will not allow association of the intein halves in the unbound conformation of the receptor. In addition, the flexibility of the linkers must be adjusted for the same purpose. Therefore we performed extensive in-silico modelling of nuclear receptor Ligand Binding domains, and numerous purposed linkers</p> | <p>As a part of our construct it is necessary to build linkers to connect the intein halves with the target receptor. The challenge in developing linkers for the system is that they must be of a specific length that will allow association of the intein halves in the bound conformation of the receptor but will not allow association of the intein halves in the unbound conformation of the receptor. In addition, the flexibility of the linkers must be adjusted for the same purpose. Therefore we performed extensive in-silico modelling of nuclear receptor Ligand Binding domains, and numerous purposed linkers</p> | ||
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Revision as of 03:33, 14 October 2018
Modelling
At team Queens Canada, we believe that proper preparation is the best way to reach a desired outcome. Accordingly, we sought to model many aspects of our project which aided in making the right choices in the lab and receiving positive results. Through the help of student on our team specializing in biomedical computing, applied mathematics, and chemical engineering, we created a number of different models that were crucial to our project design.
Molecular Dynamic Simulations
One of our constructs relied on linkers of sufficient length and flexibility to convert a conformational change, into signal transduction. We have achieved this through firstly modelling with PyMol and then performing molecular dynamic simulations of the root-mean-square deviation of atomic position.
Linker Development
As a part of our construct it is necessary to build linkers to connect the intein halves with the target receptor. The challenge in developing linkers for the system is that they must be of a specific length that will allow association of the intein halves in the bound conformation of the receptor but will not allow association of the intein halves in the unbound conformation of the receptor. In addition, the flexibility of the linkers must be adjusted for the same purpose. Therefore we performed extensive in-silico modelling of nuclear receptor Ligand Binding domains, and numerous purposed linkers
Michaelis - Menten kinetics
Michaelis - Menten kinetics is a model used to examine enzyme kinetic. Luciferase's activity can be modeled by Michaelis-Menten kinetics as they perform the simple conversion of a substrate into a product and a photon. Our project relied on the light producing NanoLuc Luciferase as a signal in our devices. We were able to model this relationship with MATLAB. The governing equations for this model were compiled in the MATLAB, with the goal of creating a generic calculator which teams may use in the future. Known values for concentrations and reactions rates are used as inputs, and the file produces the various rates of change with respect to the concentrations.
Fluid Dynamics
The ultimate application of our work from this year will be in the form of a diagnostic pacifier capable of collecting saliva, mixing with an internal biosensor and generating a signal for salivary hormone quantification. Therefore we sought to model many aspects of the pacifier including: saliva flow rate, flow turbulence, and particle mixing.
Computer Aided Design
We created relevant hardware for our project including a 3D printed pacifier to passively collect saliva samples. Before 3D printing any iterations of our design, we modeled our device on Computer Aided Design Software.