Our protein modeling team has described our process of redesigning a protein for target ligands on the modeling page. This information will be very helpful to any future teams that are trying to use Rosetta, which is the program we used for our protein modeling. Additionally, on our modeling page and engineering page, we detail our protein modeling work involving protein-ligand docking. Our workflow for protein-ligand docking will be useful for future iGEM teams who want to use Rosetta for protein-ligand docking.
We used the protein visualization software PyMol to manually dock target ligands to the active site of selected proteins and Chimera to generate Mol2 files. In our modeling page we have described some commands and actions that can be performed in PyMol and Chimera. This includes the use of pairfitting function, mutating individual amino acid residues and generating param files for ligands.
Rosetta is an important software commonly used for protein design. We have attached all the scripts used and described how we could run them and the output they generate. Our troubleshooting process has also been well documented in the modeling page. Additionally, we have also defined some of the terms and criterias used by Rosetta to score designs. This would help future iGEM teams have an easier time understanding and executing some of the functions of Rosetta.
Our wetlab team developed the protocols and plasmids necessary to test PCB breakdown in E. coli. Though our results are not yet conclusive, the protocols and parts used by our team can be used by future teams who work with PCB breakdown.
We designed plasmids for our protein that have been codon optimized for us in E. Coli. These sequences will be helpful for those looking to recreate and extend our work.
We established a protocol for ascertaining the effectiveness of the dehalogenase protein in terms of its ability to degrade PCBs. This will be a helpful resource for future teams trying to improve on our protein design, and serve as a tool to contextualize our results.
Our Kinetics Modeling team has described our process of creating models for our Wetlab team on the modeling page. This information will be useful for any other teams who are trying to create models based on limited data.
GitHub is a tool we used to share scripts between team members who were working remotely. After any updates to our script, we would push our changes to github so that others could check our models. Github is traditionally used in software development, and thus was chosen for our code so that we could track all changes made.
The COBRA toolbox is a flux balance analysis tool used to create constraints based metabolic models. Gurobi optimization was used in conjunction with the COBRA toolbox to optimize our model allowing us to simulate organisms under selection for rapid growth. Future teams could use our methodology to compare pathways and their effect on their organisms or model the growth rate of their organisms given uptake data.
Python is a computer programming language that is often used to build software in scientific research. We used Python to create many of our simple models, such as our PCB and nitrogen uptake models.
MATLAB is a programming platform designed for scientists and engineers, and was used in place of Python for some of our models.