Generalized Methodology for the Quick Prediction of Variant SARS-CoV-2 Spike Protein Binding Affinities with Human Angiotensin-Converting Enzyme II

Alexander H. Williams, Chang Guo Zhan

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Variants of the SARS-CoV-2 virus continue to remain a threat 2 years from the beginning of the pandemic. As more variants arise, and the B.1.1.529 (Omicron) variant threatens to create another wave of infections, a method is needed to predict the binding affinity of the spike protein quickly and accurately with human angiotensin-converting enzyme II (ACE2). We present an accurate and convenient energy minimization/molecular mechanics Poisson-Boltzmann surface area methodology previously used with engineered ACE2 therapeutics to predict the binding affinity of the Omicron variant. Without any additional data from the variants discovered after the publication of our first model, the methodology can accurately predict the binding of the spike/ACE2 variant complexes. From this methodology, we predicted that the Omicron variant spike has a Kd of ∼22.69 nM (which is very close to the experimental Kd of 20.63 nM published during the review process of the current report) and that spike protein of the new "Stealth"Omicron variant (BA.2) will display a Kd of ∼12.9 nM with the wild-type ACE2 protein. This methodology can be used with as-yet discovered variants, allowing for quick determinations regarding the variant's infectivity versus either the wild-type virus or its variants.

Original languageEnglish
Pages (from-to)2353-2360
Number of pages8
JournalJournal of Physical Chemistry B
Volume126
Issue number12
DOIs
StatePublished - Mar 31 2022

Bibliographical note

Funding Information:
This work was supported in part by the funding of the Molecular Modeling and Biopharmaceutical Center at the University of Kentucky College of Pharmacy, the National Science Foundation (NSF grant CHE-1111761), and the National Institutes of Health (P20 GM130456). The authors also acknowledge the Computer Center at University of Kentucky for supercomputing time on their Lipscomb Compute Cluster, and their NVIDIA V100 nodes.

Publisher Copyright:
© 2022 American Chemical Society.

ASJC Scopus subject areas

  • Physical and Theoretical Chemistry
  • Surfaces, Coatings and Films
  • Materials Chemistry

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