Difference between revisions of "Team:NUS Singapore-Sci/enzyme kinetics"
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| − | <li>Simulate the RESCUE system under different relative concentrations of substrates and enzymes to determine the concentrations that might yield maximum efficiency.</li> | + | <li>1. Simulate the RESCUE system under different relative concentrations of substrates and enzymes to determine the concentrations that might yield maximum efficiency.</li> |
| − | <li>Determine the change in the binding and catalytic efficiency when spacer length and mismatch distance is varied, which will help in the design of gRNA for more efficient base editing. | + | <li>2. Determine the change in the binding and catalytic efficiency when spacer length and mismatch distance is varied, which will help in the design of gRNA for more efficient base editing. |
</li> | </li> | ||
</ol> | </ol> | ||
Revision as of 18:03, 17 October 2018
Enzyme
Kinetics
Enzyme Kinetics and Least Squares Regression
The efficiency of our RESCUE system is likely to be dependent on multiple factors such as mismatch distance, length of spacer regions as with ADAR-dCas13b constructs (Cox et al., 2016), as well as the relative concentrations of the substrates/enzymes. The concept of regression models can be utilized to identify and evaluate the significance of these factors from experimental results. As such, a early build of an enzyme kinetics regression model on dCas13b-APOBEC editing efficiency may help us to gain further insights of the RESCUE system.
Goal
- 1. Simulate the RESCUE system under different relative concentrations of substrates and enzymes to determine the concentrations that might yield maximum efficiency.
- 2. Determine the change in the binding and catalytic efficiency when spacer length and mismatch distance is varied, which will help in the design of gRNA for more efficient base editing.