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Missense variants in human ACE2 strongly affect binding to SARS-CoV-2 Spike providing a mechanism for ACE2 mediated genetic risk in Covid-19: a case study in affinity predictions of interface variants

Abstract:
SARS-CoV-2 Spike (Spike) binds to human angiotensin-converting enzyme 2 (ACE2) and the strength of this interaction could influence parameters relating to virulence. To explore whether population variants in ACE2 influence Spike binding and hence infection, we selected 10 ACE2 variants based on affinity predictions and prevalence in gnomAD and measured their affinities and kinetics for Spike receptor binding domain through surface plasmon resonance (SPR) at 37°C. We discovered variants that reduce and enhance binding, including three ACE2 variants that strongly inhibited (p.Glu37Lys, ΔΔG = -1.33 ± 0.15 kcal mol-1 and p.Gly352Val, predicted ΔΔG = -1.17 kcal mol-1) or abolished (p.Asp355Asn) binding. We also identified two variants with distinct population distributions that enhanced affinity for Spike. ACE2 p.Ser19Pro (ΔΔG = 0.59 ± 0.08 kcal mol-1) is predominant in the gnomAD African cohort (AF = 0.003) whilst p.Lys26Arg (ΔΔG = 0.26 ± 0.09 kcal mol-1) is predominant in the Ashkenazi Jewish (AF = 0.01) and European non-Finnish (AF = 0.006) cohorts. We compared ACE2 variant affinities to published SARS-CoV-2 pseudotype infectivity data and confirmed that ACE2 variants with reduced affinity for Spike can protect cells from infection. The effect of variants with enhanced Spike affinity remains unclear, but we propose a mechanism whereby these alleles could cause greater viral spreading across tissues and cell types, as is consistent with emerging understanding regarding the interplay between receptor affinity and cell-surface abundance. Finally, we compared mCSM-PPI2 ΔΔG predictions against our SPR data to assess the utility of predictions in this system. We found that predictions of decreased binding were well-correlated with experiment and could be improved by calibration, but disappointingly, predictions of highly enhanced binding were unreliable. Recalibrated predictions for all possible ACE2 missense variants at the Spike interface were calculated and used to estimate the overall burden of ACE2 variants on Covid-19.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.pcbi.1009922

Authors

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Role:
Author
ORCID:
0000-0003-4233-5071
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Institution:
University of Oxford
Division:
MSD
Department:
Pathology Dunn School
Role:
Author
ORCID:
0000-0002-9263-6481
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Institution:
University of Oxford
Division:
MSD
Department:
Pathology Dunn School
Role:
Author
ORCID:
0000-0003-3386-4350
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Pathology Dunn School
Role:
Author
ORCID:
0000-0001-5847-5226
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Pathology Dunn School
Oxford college:
Brasenose College
Role:
Author
ORCID:
0000-0001-9902-6590


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Funder identifier:
https://ror.org/029chgv08
Grant:
207537/Z/17/Z
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Funder identifier:
https://ror.org/00cwqg982
Grant:
BB/J019364/1


Publisher:
Public Library of Science
Journal:
PLoS Computational Biology More from this journal
Volume:
18
Issue:
3
Article number:
e1009922
Place of publication:
United States
Publication date:
2022-03-02
Acceptance date:
2022-02-13
DOI:
EISSN:
1553-7358
ISSN:
1553-734X
Pmid:
35235558


Language:
English
Keywords:
Pubs id:
1242516
Local pid:
pubs:1242516
Deposit date:
2025-01-13
ARK identifier:

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