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

J Chem Inf Model. 2020 Dec 28;60(12):5794-5802. doi: 10.1021/acs.jcim.0c00679. Epub 2020 Aug 31.

Abstract

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.

MeSH terms

  • Amino Acid Sequence
  • Angiotensin-Converting Enzyme 2 / metabolism*
  • Binding Sites
  • COVID-19 / metabolism*
  • Humans
  • Molecular Dynamics Simulation
  • Mutagenesis / genetics
  • Mutation
  • Protein Binding
  • Protein Conformation
  • SARS-CoV-2 / metabolism*
  • Spike Glycoprotein, Coronavirus / genetics*
  • Spike Glycoprotein, Coronavirus / metabolism*
  • Thermodynamics

Substances

  • Spike Glycoprotein, Coronavirus
  • ACE2 protein, human
  • Angiotensin-Converting Enzyme 2