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In silico comparison of SARS-CoV-2 spike protein-ACE2 binding affinities across species and implications for virus origin

Title	In silico comparison of SARS-CoV-2 spike protein-ACE2 binding affinities across species and implications for virus origin
Authors	Sakshi Piplani, Puneet Kumar Singh, David A. Winkler, Nikolai Petrovsky
Magazine	Scientific Reports
Date	06/24/2021
DOI	https://doi.org/10.1038/s41598-021-92388-5
Introduction	The COVID-19 pandemic, caused by SARS-coronavirus 2 (SARS-CoV-2), has prompted significant inquiries into its origins and human transmission mechanisms. A key area of investigation concerned whether companion or commercial animals could serve as SARS-CoV-2 vectors, with initial data indicating species-specific susceptibility. To enhance understanding of SARS-CoV-2 susceptibility across species, this study employed an in silico approach involving structural homology modelling, protein-protein docking, and molecular dynamics simulations. The goal was to analyse the SARS-CoV-2 spike protein's capacity to bind angiotensin converting enzyme 2 (ACE2) from various relevant species. The spike protein demonstrated the strongest binding to human (h)ACE2 among all species assessed, forming the highest number of hydrogen bonds. Notably, pangolin ACE2 exhibited the second highest binding affinity despite relatively low sequence homology, while monkey ACE2 showed considerably lower affinity despite high sequence similarity to hACE2. These observations underscore the benefit of a structural perspective over a sequence-based one for cross-species analyses. ACE2 species falling within the upper range of predicted binding affinity (including monkey, hamster, dog, ferret, and cat) have been confirmed as permissive to SARS-CoV-2 infection, supporting a relationship between binding affinity and infection susceptibility. These results indicate that the earliest known SARS-CoV-2 isolates were well-adapted for strong binding to human ACE2, which helps account for its efficient human-to-human respiratory transmission. This research illustrates the utility of in silico structural modelling methods for promptly generating insights into novel viruses, assisting in predicting their behaviour and supporting countermeasure development.
Quote	Piplani, S., Singh, P. K., Winkler, D. A., & Petrovsky, N. (2021). In silico comparison of SARS-CoV-2 spike protein-ACE2 binding affinities across species and implications for virus origin. Scientific Reports, 11(1), 13063. https://doi.org/10.1038/s41598-
Industry	Research & Laboratory , Pharmaceutical Industry

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