Overview

In the 2022 NAU-CHINA project, we developed our modeling from both molecular and mathematical perspectives.

By building molecular models, we predicted the secondary and tertiary structures of key proteins in the project, which helped us to better understand the structure and properties of the proteins used and optimize the experimental design. By building mathematical models, we simulated the whole reaction system with mathematical formulas, and found the optimal initial concentration of CDCA, which reduced the cost of our experiments and improved the experimental efficiency.

Molecular Modeling

In molecular modeling, we established Support Vector Machine model to predict the secondary structure of proteins. In this model, we coded 20 amino acids and obtained the secondary structures of the conjunction between CDCA & FXR as well as CDCA-FXR & RXR by the method of sample learning and classifying, with the accuracy up to 99.24%. Using AlphaFlod2, SwissDock and ZDOCK, we have obtained the tertiary structures of FXR+linker+ddRFPA1, RXR+linker+ddRFPB1, CDCA-FXR and CDCA-FXR+RXR, which provided a great help to our experiment.

Mathematical Modeling

In the mathematical modeling, we simulated the biological expression process by using the \(\tau-leaping\) algorithm. The initial concentration of CDCA was 0μmol/L, 10μmol/L, 25μmol/L, 30μmol/L, 50μmol/L, 70μmol/L and 100μmol/L, and the optimal initial concentration of CDCA was determined by smoothing spline fitting. The efficiency of the experiment had been greatly improved. At the same time, Ordinary Differential Equations were established for stability analysis.