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ACE2-Based Decoy Receptors for SARS Coronavirus 2
  • Wenyang Jing,
  • Erik Procko
Wenyang Jing
University of Illinois at Urbana-Champaign
Author Profile
Erik Procko
University of Illinois at Urbana-Champaign
Author Profile

Abstract

SARS-CoV-2 is neutralized by proteins that block receptor-binding sites on spikes that project from the viral envelope. In particular, substantial research investment has advanced monoclonal antibody therapies to the clinic where there are signs of partial efficacy in reducing viral burden and hospitalization. An alternative is to use the host entry receptor, ACE2, as a soluble decoy that broadly blocks SARS-associated coronaviruses with limited potential for viral escape. Here, we summarize efforts to engineer higher affinity variants of soluble ACE2 that rival the potency of affinity-matured antibodies. Strategies have also been used to increase the valency of ACE2 decoys for avid spike interactions and to improve pharmacokinetics via IgG fusions. Finally, the intrinsic catalytic activity of ACE2 for the turnover of the vasoconstrictor angiotensin II may directly address COVID-19 symptoms and protect against lung and cardiovascular injury, conferring dual mechanisms of action unachievable by monoclonal antibodies. Soluble ACE2 derivatives therefore have the potential to be next generation therapeutics for addressing the immediate needs of the current pandemic and possible future outbreaks.

Peer review status:Published

02 Nov 2020Submitted to PROTEINS: Structure, Function, and Bioinformatics
03 Nov 2020Submission Checks Completed
03 Nov 2020Assigned to Editor
27 Nov 2020Reviewer(s) Assigned
27 Dec 2020Review(s) Completed, Editorial Evaluation Pending
31 Jan 2021Editorial Decision: Revise Major
16 Feb 20211st Revision Received
17 Feb 2021Submission Checks Completed
17 Feb 2021Assigned to Editor
17 Feb 2021Reviewer(s) Assigned
23 Apr 2021Review(s) Completed, Editorial Evaluation Pending
23 Apr 2021Editorial Decision: Accept
10 May 2021Published in Proteins: Structure, Function, and Bioinformatics. 10.1002/prot.26140