SARS coronavirus 2 (SARS-CoV-2) is the causative agent of the COVID-19 global pandemic. Highly infectious variants have emerged over the course of the pandemic as the virus continued to replicate and mutate. Key mutations often take place in the spike protein, and can increase the likelihood of an interaction between the virus and the human ACE2 receptor (binding affinity) or or reduce its susceptibility to attack by human immune cells (immune escape). To computationally explore the contagiousness of these variants, we used EVEscape to determine immune escape and MM/GBSA to quantify binding affinity. We also utilized the PyR0 pipeline from Obermeyer et al. (2022) to identify dominant COVID-19 variants and their associated mutations. Change in binding affinity, immune escape, and overall fitness was determined for mutations and compared to the wildtype (original) SARS-Cov-2 virus. Our data suggests that both immune escape and binding affinity are crucial factors to consider when determining contagiousness, and occur in similar regions throughout the genome. Currently, we are developing a model that integrates population data, binding affinity, and immune escape calculations to predict the transmissibility (R0) of different variants. We anticipate that this model will lead to more accurate and reliable predictions of viral spread.
Author(s): Sarah Johnson, Microbiology and Premedical Studies Major
Shane Schroeder, Computer Science Major
Bella Wilson, Computer Science Major
Advisor(s): Chun Liang, Department of Biology
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