Over the course of this iGEM season, we formed a valuable and successful partnership with the iGEM team Edinburgh-UHAS_Ghana 2022. Weekly meetings gave us a chance to share updates on our projects, and to exchange experiences and challenges while discovering and profiting from the possibilities of bioinformatics. The goal of our collaborative work was an automated pipeline for an in silico investigation and optimization of molecular dockings. You can read the methods and results of our team's modeling, which partly implements this pipeline, on our Modeling page.
In addition to the joint effort to create a molecular docking simulation, we made a contribution for future iGEM teams by writing a step-by-step guide on how to perform in silico simulations as well as evaluating each other's human practices and education activities.
Together, this enabled both teams to highly profit from this partnership by advancing several objectives of the respective projects. With this exchange we… Our experiences shaped the way the other team interpreted the results of metallothionein-directed evolution and hydrogel immobilization and helped them validate that a novel transcription factor submitted to the part’s repository could in fact be used in a biosensor the way we had intended. The process as well as the results of our simulations can be found on our modeling page.
We met team Edinburgh-UHAS_Ghana in the beginning of July at the European Meetup, organized by the iGEM team Hamburg. During the poster session, we presented our respective projects to each other and concluded that our projects have little in common — with us working on improving CAR T-cell therapy, which is a part of red biotechnology, and team Edinburgh-UHAS_Ghan working with cell-free systems and dealing exclusively with prokaryotes to improve water quality as a part of gray biotechnology. Nevertheless, the interdisciplinarity and modularity of synthetic biology allowed us to find a common functionality in both our projects: transcription factors regulating our respective systems.
Both our teams planned to computationally simulate and optimize the binding of the transcription factor to the DNA as well as to a small molecule — metallothioneins in the case of team Edinburgh-UHAS_Ghana, and tetracycline for our project. We therefore decided to work collaboratively on this proposition, ranging from researching and testing tools over performing the simulations to analyze the results. However, our teamwork quickly exceeded the boundaries of modeling and resulted in collaboratively working on more aspects of our project than originally outlined.
In July, guided by supervisors from both of our teams, we started by clearly defining the objectives of our partnership:
Subsequently, we started researching tools that would allow us to achieve these goals. This was more complicated than anticipated due to the vast quantity of available tools, causing careful review and research in order to pick the optimal tool for each task to become necessary.
In August, we started testing the tools we found to be best suited for our purposes. While doing this, we faced the difficulty that many tools were not available, as some websites were no longer accessible or the tools wouldn't run on modern versions of operating systems. Here, it helped that we had the joint manpower of two teams, as this meant that each team could try out an allocated set of certain tools in parallel and consult each other regarding the efficacy/results, especially when facing problems using a tool.
Another advantage of our partnership was that supervisors from both teams could assist us with their respective experience concerning the availability and performance of docking tools. We are convinced that without our joint resources in researching and testing tools, we could not have ended up with the fine selection of tools we used in the end that optimally fulfilled each team's needs.
For instance, we decided to use AutoDock to simulate the transcription factor — small molecule docking. However, it took us several weeks to get AutoDock running — especially the preprocessing steps required for preparing the protein and the small molecule — and we believe it was the complementary skill sets of the two teams that enabled/actualized this achievement.
In addition to getting the necessary tools running, we obtained the structures for our proteins in August. If a structure was unknown because of a lack of homologous protein in the Protein Data Bank (PDB), as was the case especially for team Edinburgh-UHAS_Ghana, we used the program AlphaFold to predict the structures. We tried out several Jupyter notebooks, which make the AlphaFold predictor publicly usable, because several versions threw an error when reading the structures of our proteins. However, with joint forces we managed to pinpoint an implementation that would allow both teams to obtain high-resolution structure predictions.
After having obtained structures for all our proteins and small molecules, our work in September focused mainly on programming an automated pipeline for the mutation of the transcription factor and the subsequent docking of it to our ligand. While team Edinburgh-UHAS_Ghana mainly took care of the docking automation using command line tools, our team used python scripts to introduce mutations into the structure of our transcription factors through PyMol. We helped solve errors in each other's codes and reflected on how to make the code as widely useful/effective (and simple)as possible, so that our automated pipeline wouldn't work exclusively for our proteins, but any simulation future groups might find necessary.
Towards the end of September, our scripts were finished and we were able to perform all of the docking simulations with the goal to optimize the docking by assessing the effects of mutating the transcription factor.
Seeing as the docking simulations were completed early October, we used our time to advance other areas of our project separate from the modeling. We made a contribution to future iGEM teams by writing a detailed description, including the code necessary to perform in silico docking simulations. You can find further information on this on our Contribution page.
Check out our tutorial here!With the Wiki freeze in sight, we additionally evaluated each other's activities for human practices and proofread the according Wiki pages. We critically assessed whether the respective other team fulfilled all of the criteria listed in the Judging handbook and made suggestions on what parts could profit from more in-depth descriptions and/or review in order to make all rationale behind activities easy to comprehend for non-team members.
Our partnership with team Edinburgh-UHAS_Ghana enabled both teams to benefit from the joint knowledge and resources. We consulted experts in our respective institutions and shared the information and tips we received from them. Importantly, our prior knowledge as well as our skills complemented each others’: While our team does not have any experience in scripting with bash, Maarten from team Edinburgh-UHAS_Ghana was able to quickly write a command line tool for our docking pipeline using bash. Meanwhile, Lilly from our team could focus on her strength — coding in python — by implementing the mutation script for our automated pipeline. Even though all involved team members gained a lot of knowledge and skills, this division of labor in accordance with preexisting qualifications allowed us to efficiently achieve all of our goals as defined in July.
We supported each other with the docking simulations, helped each other out when a team faced a problem, and provided motivational support. Thanks to these benefits, we were able to make fast progress while still enjoying our work. We are convinced that without our partnership, we wouldn't have been able to take our modeling to the level that we accomplished.
Additionally, both teams profited from taking the partnership beyond the boundaries of modeling. After working intensively together for several months, we reviewed each other's Wiki pages for clarity of intentions and carefully incorporated suggested improvements.
In order to enable future iGEM teams to profit from our collaborative work, too, we additionally decided to design a tutorial on docking simulation.
We would like to conclude this valuable partnership with a big thank you to team Edinburgh-UHAS_Ghana and every single one who accompanied us on our journey together.