Team:UIUC Illinois/Description
Description
Background:
COVID-19 is the disease caused by the SARS-CoV-2 virus and is the centre of the 2020 coronavirus pandemic. As of October 27, the pandemic has resulted in over 44 million cases and over 1.1 million deaths around the world. The virus uses the ACE2 receptor on host cells to infect them. The binding of the spike protein with the ACE2 receptor is extremely important, as this mechanism alone is essential in allowing the virus to infect the host. Despite access to good technology, effective treatment and vaccines have been hard to make since the virus is highly mutative. The mutations are especially important when looking at the spike protein of the virus, which is the protein that allows SARS-CoV-2 to enter the host cell. Due to the high rate of mutation present in this strain of virus, researchers have been unable to find a reliable treatment that can neutralize the various mutated spike proteins that exist.
New mutations of the virus pop up almost every day, though most aren’t very prevalent. Despite the speed with which these new mutations can be sequenced, obtaining the crystal structure of the protein is a different matter as it is expensive and time consuming. Due to this, it’s difficult for researchers to determine how mutations could potentially change the structure of the spike protein. Without understanding what the spike protein will look like, it is impossible for researchers to know whether a potential antibody or vaccine will be effective against the virus.
Inspiration:
The pandemic has obviously changed the way the majority of the world lives, and our team members felt that we should do something to help contribute to the fight against coronavirus. Since we didn’t have access to a wet lab, we resolved to help researchers from outside the lab. We identified the ability of software modeling tools to help model the thousands of mutations that exist and decided to use homology modeling to discern their respective crystal structures. We also wanted to be able to directly contribute to the fight via synthesizing our own antibodies that can neutralize the spike protein of the virus.
Out Solution: Viralizer
Our project, Viralizer, aims to tackle many of these issues. The first component of our project is a database of more than 20,000 mutated spike protein sequences as well as their corresponding protein models. Using this data, we designed antibodies that can bind to the majority of spike protein sequences we analyzed. The database also contributed to the development of a phylogenetic tree that characterizes the propagation of the virus over the course of the pandemic. The tree allows researchers to track particular strains as well as sort the mutations by location and date.