Abstract
SARS-CoV-2, the virus responsible for the ongoing COVID-19 pandemic, was first discovered in a human population in 2019, likely the result of cross-species transmission from bats to humans. While it is widely accepted that SARS-CoV-2 originated from an animal host, little is currently known about the role animal hosts play in the transmission of the disease. Due to the serious nature of the pandemic, there is an urgent need to identify potential animal host species of the virus. in order to gain entry into host cells, the receptor binding domain(RBD) on the spike protein of the virus must be able to dock to angiotensin converting enzyme 2(ACE2), a membrane protein found in the cells of many organisms. Therefore, a calculation of the binding affinity of the RBD with the ACE2receptor of an organism can allow us to predict the susceptibility of an organism toSARS-CoV-2. in this study, we developed a computational pipeline to predict the binding affinity of the RBD with the ACE2receptor of animal species, with a focus on North American rodents. Sequences of the ACE2protein for more than100North American rodent species were obtained, and homology modeling was used to generate structures of the ACE2receptor for each sequence, using available humanACE2structures as a template. Protein-protein docking tools were then used to dock the RBD against the snapshots, generated using molecular dynamics simulations, of each ACE2homology model. The docking score for eachRBD-ACE2docked complex was used to compile a short list of North American rodents for empirical testing. We expect our data to be vital in the identification of potentially susceptible animal species, in understanding the cross-species transmission of CoVs, animal surveillance, and the development of animal therapies and vaccines.
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