Structure-guided glyco-engineering of ACE2 for improved potency as soluble SARS-CoV-2 decoy receptor
Abstract
Infection and viral entry of SARS-CoV-2 crucially depends on the binding of its Spike protein to angiotensin converting enzyme 2 (ACE2) presented on host cells. Glycosylation of both proteins is critical for this interaction. Recombinant soluble human ACE2 can neutralize SARS-CoV-2 and is currently undergoing clinical tests for the treatment of COVID-19. We used 3D structural models and molecular dynamics simulations to define the ACE2 N-glycans that critically influence Spike-ACE2 complex formation. Engineering of ACE2 N-glycosylation by site-directed mutagenesis or glycosidase treatment resulted in enhanced binding affinities and improved virus neutralization without notable deleterious effects on the structural stability and catalytic activity of the protein. Importantly, simultaneous removal of all accessible N-glycans from recombinant soluble human ACE2 yields a superior SARS-CoV-2 decoy receptor with promise as effective treatment for COVID-19 patients.
Data availability
Molecular models and simulation trajectories are available through the BioExcel COVID-19 Molecular Structure and Therapeutics Hub (https://covid.bioexcel.eu/simulations/).
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Author details
Funding
Austrian Science Fund (W1224-B09)
- Nikolaus Ferdinand Kienzl
- Daniel Maresch
- Lukas Mach
- Chris Oostenbrink
Vienna Science and Technology Fund (COV20-015)
- Tümay Capraz
- Chris Oostenbrink
Innovative Medicines Initiative 2 Joint Undertaking (101005026)
- Vanessa Monteil
- Ali Mirazimi
- Josef M Penninger
DOC fellowship of the Academy of Sciences (24987)
- Jan W Perthold
T. von Zastrow foundation
- Josef M Penninger
- Johannes Stadlmann
Austrian Science Fund (Z271-B19)
- Josef M Penninger
- Johannes Stadlmann
Canada Research Chairs (F18-0133)
- Josef M Penninger
Canadian Institutes of Health Research (F20-02343)
- Josef M Penninger
Canadian Institutes of Health Research (F20-02015)
- Josef M Penninger
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Capraz et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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