Team:AFCM-Egypt/Contribution
Contributions
The Pipeline
Teams all around the world have been heavily impacted by the COVID-19 pandemic, quarantines and campus closures. In our project, we attempted to circumvent this challenge by creating a computational pipeline for multiepitope vaccines. This pipeline elucidated in our Design page can be used to provide further validation and facilitate phase-2 work which can help other teams to have more flexibility dealing with experimental restrictions.
New Parts
We added 24 parts to the registry in which variated between 20 basic parts and 4 composite parts that all would provide an addition to the registry that would help teams and provide them with parts allowing to create a modular DREP vector that they can use in any field all of which are shown in the Parts page. We added modeling data and simulations to our parts pages and supported our designs by literature thus enabling upcoming teams with lab access to utilize and test our parts as best as possible.
New Documentation
We also added documentation and proposed to improve the part BBa K1537016 by Inserting GSG and SGS linkers, V5 epitope tag and 3xFlag epitope tag immediately preceding 2A has been shown to improve 2A cleavage efficiency & also We characterized this part BBa_K511101. by structural modelling and simulation of interaction between ff4 and its binding site to be confirmed in our phase II.
Improving upon an existing software solution (AFCMEasyModel)
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AFCMEasy Model was a tool developed as a part of Team AFCM-Egypt’s 2017 IGEM project. It is an interactive web tool that embeds R Codes used for modeling ceRNA networks to solve ODEs easily, specify parameters, rates and reaction species. The tool aimed to help other teams model their projects in an easy interactive way without facing technical issues.
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Thus, to further improve the tool, we modified the tool source code provided in Github to include the equations and parameters simulating replicon amplification which is the core. Furthermore, as an added functionality, you may save your plot as an image.
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The tool depends on a set of differential equations inspired by previous literature and further developed by our team. To make the simulations representative of the conditions that we wanted to test, we modified the parameters based on literature experimental values and fitting.
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The process of manual manipulation of parameter values is not flexible enough and also challenging in terms of time and computational power. That’s why we wanted to create and further enhance a tool that allowed us to manipulate the values easily to test different conditions in less time.
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That’s why we created RepliconModel hence achieving our aim and helping other teams model future projects using replicons or different Designs. We also provided the source code on Github and hosted our tool online at LINK.