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Computationally Designed ACE2 Decoy Receptor Binds SARS-CoV-2 Spike (S) Protein with Tight Nanomolar Affinity.
Havranek, Brandon; Chan, Kui K; Wu, Austin; Procko, Erik; Islam, Shahidul M.
Afiliação
  • Havranek B; Department of Chemistry, University of Illinois at Chicago, Chicago, Illinois 60607, United States.
  • Chan KK; Orthogonal Biologics Inc., Urbana, Illinois 61801, United States.
  • Wu A; Department of Computer Science, Northwestern University, Evanston, Illinois 60208, United States.
  • Procko E; Department of Biochemistry and Cancer Center at Illinois, University of Illinois, Urbana, Illinois 61801, United States.
  • Islam SM; Department of Chemistry, University of Illinois at Chicago, Chicago, Illinois 60607, United States.
J Chem Inf Model ; 61(9): 4656-4669, 2021 09 27.
Article em En | MEDLINE | ID: mdl-34427448
ABSTRACT
Even with the availability of vaccines, therapeutic options for COVID-19 still remain highly desirable, especially in hospitalized patients with moderate or severe disease. Soluble ACE2 (sACE2) is a promising therapeutic candidate that neutralizes SARS CoV-2 infection by acting as a decoy. Using computational mutagenesis, we designed a number of sACE2 derivatives carrying three to four mutations. The top-predicted sACE2 decoy based on the in silico mutagenesis scan was subjected to molecular dynamics and free-energy calculations for further validation. After illuminating the mechanism of increased binding for our designed sACE2 derivative, the design was verified experimentally by flow cytometry and BLI-binding experiments. The computationally designed sACE2 decoy (ACE2-FFWF) bound the receptor-binding domain of SARS-CoV-2 tightly with low nanomolar affinity and ninefold affinity enhancement over the wild type. Furthermore, cell surface expression was slightly greater than wild-type ACE2, suggesting that the design is well-folded and stable. Having an arsenal of high-affinity sACE2 derivatives will help to buffer against the emergence of SARS CoV-2 variants. Here, we show that computational methods have become sufficiently accurate for the design of therapeutics for current and future viral pandemics.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: SARS-CoV-2 / COVID-19 Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: SARS-CoV-2 / COVID-19 Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article