Designed Protein Degradation Method Based on
Trim21 And Nanobody
Basic Work
Introduction
Compared with general model whose circuit directly express the protein and functions, the construction of model is not complicated. Our trim21-antibody system needs to bind to target protein after expressing trim21 and antibody to complete the task. So we made the following design for the model:As is shown in the flow chart, we split the whole process into three parts: the plasmid expresses GFP antibody and trim21, antibody binds to antigen, the ubiquitination by Trim21 to the final degradation, which are connected by bridges (concentration of antibody and complex).Then the final ODE equations are constructed.
About the model:
1、The energy in the medium is sufficient. 1、The e3 enzyme in the body is ignored, as considering it has already begun to function before the plasmid introduction. 2、The expression rate of related proteins in the system before and after cell proliferation remains unchanged, as the expression of intracellular proteins has a steady state as a result of the limitation of various enzymes. 3、The reaction rate can be described by the law of mass action. About the data 1. The data we obtain from wet-lab experiment are reliable. 2. All the results are trustworthy in the process of statistical processing and data calculation.
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This is the sign of the famous game!
The least squares method is a mathematical optimization technique,which finds the best function match for the data by minimizing the sum of the squares of the errors. In 1829, Gauss proved that no unbiased estimator would be superior to the ordinary least squares estimator. Moreover, in the case where the error conforms to the normal distribution, the least squares is equivalent to the maximum likelihood, which minimizes the empirical risk .In the parameter estimation, the least squares method and the partial derivative are used to obtain the parameters with zero gradient. This method can easily obtain the unknown data while ensuring the accuracy, which is explicit to be expressed by formula. Simbiology offers the parameter fitting method based on the least squares method, which combines with the equations with unknown parameters in the model to use the data we obtained from the laboratory. We used it to combine our data for parameter fitting and got the following results.
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Further more, the models we built are so complicated that we believe the results of the least squares method also need to be tested due to the limitations of the algorithm and the amount of data. To validate and further ensure the validity of the model, we next use another method--the neural network in machine learning, to analyze the model and find a direct link between input and output. Neural networks have the ability to learn and construct models of nonlinear complex relationships after learning from the initialization inputs and their relationships.It can also infer the unknown relationships between the data, allowing the model to generalize and predict unknown data. This method simplifies the complexity of the model,rather than specifically considering each parameter and each step of the reaction. Generally, it does not have strict requirements like the least squares method for the accuracy of the equation, which could obtain the mapping relation between the plasmid dosage and protein degradation rate more directly.
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name | city | |
---|---|---|
Tanmay | Bangalore | 560001 |
Sachin | Mumbai | 400003 |
Uma | Pune | 411027 |