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Computational Prediction of Mutational Effects on the SARS-CoV-2 Binding by Relative Free Energy Calculations

preprint
revised on 15.07.2020 and posted on 16.07.2020 by Junjie Zou, Jian Yin, Lei Fang, Mingjun Yang, Tianyuan Wang, Weikun Wu, Michael A. Bellucci, Peiyu Zhang

The ability of coronaviruses to infect humans is invariably associated with their binding strengths to human receptor proteins. Both SARS-CoV-2, initially named 2019-nCoV, and SARS-CoV were reported to utilize angiotensin-converting enzyme 2 (ACE2) as an entry receptor in human cells. To better understand the interplay between SARS-CoV-2 and ACE2, we performed computational alanine scanning mutagenesis on the “hotspot” residues at protein-protein interfaces using relative free energy calculations. Our data suggest that the mutations in SARS-CoV-2 lead to a greater binding affinity relative to SARS-CoV. In addition, our free energy calculations provide insight into the infectious ability of viruses on a physical basis, and also provide useful information for the design of antiviral drugs.

History

Email Address of Submitting Author

jian.yin@xtalpi.com

Institution

XtalPi Inc.

Country

China

ORCID For Submitting Author

0000-0001-9668-3704

Declaration of Conflict of Interest

The authors declare no conflicts of interest

Version Notes

This is an updated version (v03)

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