Team:UIUC Illinois

Viralizer UIUC_Illinois

Viralizer

Modeling SARS-CoV-2 mutations and binding energies to design antibodies.
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About Viralizer

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 spike protein virus is highly mutative, making it very difficult to design reliable treatments and to prevent reinfection.

We have created a database of mutated spike proteins and their models, using them to design antibodies that can bind to the highest number of mutated spike proteins.

Database

Our database has over 20,000 mutated SARS-CoV-2 spike protein sequences as well as their corresponding crystal structures.

The crystal structures were determined using homology modeling. Our modeling methods were shown to be more accurate than several premier online modeling tools such as SwissFold.

This database also contains several hundred potential antibodies designed by our team that can neutralize the spike protein of SARS-CoV-2.

Phylogenetics

Over an epidemic, pathogens naturally accumulate inevitable, random mutations to their genomes. Since different genomes typically pick up different mutations, they can be used as a marker of transmission in which closely related genomes indicate closely related infections.

Using the database we built, we identified mutations that occurred in several samples around the world and visualized the data using a phylogenetic tree.

The tree displays 538 sequences and characterizes the progression of the pandemic over space and time.

Antibody Design

This is the most ambitious aspect of our project. Using an existing antibody, we induced random point mutations to it and analyzed its binding affinity with the spike protein.

Then, we used a genetic algorithm to increase to select for point mutations that had an increased binding affinity.

We compared the antibodies’ binding affinity with the mutated spike proteins in our database, allowing us to identify the antibodies that can bind to the greatest number of mutants.

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