Mutations Strengthened SARS-CoV-2 Infectivity

J Mol Biol. 2020 Sep 4;432(19):5212-5226. doi: 10.1016/j.jmb.2020.07.009. Epub 2020 Jul 23.

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infectivity is a major concern in coronavirus disease 2019 (COVID-19) prevention and economic reopening. However, rigorous determination of SARS-CoV-2 infectivity is very difficult owing to its continuous evolution with over 10,000 single nucleotide polymorphisms (SNP) variants in many subtypes. We employ an algebraic topology-based machine learning model to quantitatively evaluate the binding free energy changes of SARS-CoV-2 spike glycoprotein (S protein) and host angiotensin-converting enzyme 2 receptor following mutations. We reveal that the SARS-CoV-2 virus becomes more infectious. Three out of six SARS-CoV-2 subtypes have become slightly more infectious, while the other three subtypes have significantly strengthened their infectivity. We also find that SARS-CoV-2 is slightly more infectious than SARS-CoV according to computed S protein-angiotensin-converting enzyme 2 binding free energy changes. Based on a systematic evaluation of all possible 3686 future mutations on the S protein receptor-binding domain, we show that most likely future mutations will make SARS-CoV-2 more infectious. Combining sequence alignment, probability analysis, and binding free energy calculation, we predict that a few residues on the receptor-binding motif, i.e., 452, 489, 500, 501, and 505, have high chances to mutate into significantly more infectious COVID-19 strains.

Keywords: COVID-19; mutation; protein-protein interaction; spike protein; viral infectivity.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Amino Acid Sequence
  • Angiotensin-Converting Enzyme 2
  • Betacoronavirus / classification
  • Betacoronavirus / genetics*
  • Betacoronavirus / pathogenicity*
  • COVID-19
  • Cluster Analysis
  • Coronavirus Infections / virology*
  • DNA Mutational Analysis
  • Evolution, Molecular*
  • Genotype
  • Geographic Mapping
  • Humans
  • Machine Learning
  • Models, Molecular
  • Mutation*
  • Pandemics
  • Peptidyl-Dipeptidase A / metabolism
  • Pneumonia, Viral / virology*
  • Polymorphism, Single Nucleotide / genetics
  • Probability
  • Protein Binding / genetics
  • Receptors, Virus / metabolism
  • SARS-CoV-2
  • Sequence Alignment
  • Severe acute respiratory syndrome-related coronavirus / chemistry
  • Severe acute respiratory syndrome-related coronavirus / genetics
  • Severe acute respiratory syndrome-related coronavirus / metabolism
  • Severe acute respiratory syndrome-related coronavirus / pathogenicity
  • Spike Glycoprotein, Coronavirus / chemistry
  • Spike Glycoprotein, Coronavirus / genetics*
  • Spike Glycoprotein, Coronavirus / metabolism
  • Thermodynamics

Substances

  • Receptors, Virus
  • Spike Glycoprotein, Coronavirus
  • spike protein, SARS-CoV-2
  • Peptidyl-Dipeptidase A
  • ACE2 protein, human
  • Angiotensin-Converting Enzyme 2