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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.
MacGowan, Stuart A; Barton, Michael I; Kutuzov, Mikhail; Dushek, Omer; van der Merwe, P Anton; Barton, Geoffrey J.
  • MacGowan SA; Division of Computational Biology, School of Life Sciences, University of Dundee, Dow Street, Dundee, Scotland, United Kingdom.
  • Barton MI; Sir William Dunn School of Pathology, South Parks Road, University of Oxford, Oxford, Oxfordshire, United Kingdom.
  • Kutuzov M; Sir William Dunn School of Pathology, South Parks Road, University of Oxford, Oxford, Oxfordshire, United Kingdom.
  • Dushek O; Sir William Dunn School of Pathology, South Parks Road, University of Oxford, Oxford, Oxfordshire, United Kingdom.
  • van der Merwe PA; Sir William Dunn School of Pathology, South Parks Road, University of Oxford, Oxford, Oxfordshire, United Kingdom.
  • Barton GJ; Division of Computational Biology, School of Life Sciences, University of Dundee, Dow Street, Dundee, Scotland, United Kingdom.
PLoS Comput Biol ; 18(3): e1009922, 2022 03.
Article in English | MEDLINE | ID: covidwho-1724747
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Mutation, Missense / Spike Glycoprotein, Coronavirus / Angiotensin-Converting Enzyme 2 / COVID-19 Type of study: Case report / Cohort study / Observational study / Prognostic study Topics: Variants Limits: Humans Language: English Journal: PLoS Comput Biol Journal subject: Biology / Medical Informatics Year: 2022 Document Type: Article Affiliation country: Journal.pcbi.1009922

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Mutation, Missense / Spike Glycoprotein, Coronavirus / Angiotensin-Converting Enzyme 2 / COVID-19 Type of study: Case report / Cohort study / Observational study / Prognostic study Topics: Variants Limits: Humans Language: English Journal: PLoS Comput Biol Journal subject: Biology / Medical Informatics Year: 2022 Document Type: Article Affiliation country: Journal.pcbi.1009922