![](https://static.igem.org/mediawiki/2019/2/25/T--SZU-CHINA--left_arrow.png)
Models
In the project, we used Pymol and Discovery studio to perform molecular docking and virtual amino acid mutations on β-glucosidase to improve its enzymatic activity. In order to predict the optimal harvest time of β-glucosidase, we established a gene expression model. At the same time, we established a BP neural network model based on the orthogonal test to predict the production of gardenia blue, and then used genetic algorithm to optimize.
![](https://static.igem.org/mediawiki/2020/5/55/T--SZU-CHINA--Model-icon1.png)
Virtual amino acid mutation
![](https://static.igem.org/mediawiki/2020/a/a7/T--SZU-CHINA--Model-icon2.png)
Expression model
![](https://static.igem.org/mediawiki/2020/4/4b/T--SZU-CHINA--Model-icon3.png)
Orthogonal test
![](https://static.igem.org/mediawiki/2020/e/e9/T--SZU-CHINA--Model-icon4.png)