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Probing Affinity, Avidity, Anti-Cooperativity, and Competition in Antibody and Receptor Binding to the SARS-CoV-2 Spike by Single Particle Mass Analyses
Victor C Yin; Szu-Hsueh Lai; Tom G Caniels; Philip J.M. Brouwer; Yoann Aldon; Hejun Liu; Meng Yuan; Ian A. Wilson; Rogier W Sanders; Marit van Gils; Albert J.R. Heck.
Afiliación
  • Victor C Yin; Utrecht University
  • Szu-Hsueh Lai; Utrecht University
  • Tom G Caniels; Amsterdam UMC
  • Philip J.M. Brouwer; Amsterdam UMC
  • Yoann Aldon; Amsterdam UMC
  • Hejun Liu; The Scripps Research Institute
  • Meng Yuan; The Scripps Research Institute
  • Ian A. Wilson; The Scripps Research Institute
  • Rogier W Sanders; Amsterdam UMC
  • Marit van Gils; Amsterdam UMC
  • Albert J.R. Heck; Utrecht University
Preprint en En | PREPRINT-BIORXIV | ID: ppbiorxiv-448939
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ABSTRACT
Determining how antibodies interact with the spike (S) protein of the SARS-CoV-2 virus is critical for combating COVID-19. Structural studies typically employ simplified, truncated constructs that may not fully recapitulate the behaviour of the original complexes. Here, we combine two single particle mass analysis techniques (mass photometry and charge-detection mass spectrometry) to enable measurement of full IgG binding to the trimeric SARS-CoV-2 S ectodomain. Our experiments reveal that antibodies targeting the S-trimer typically prefer stoichiometries lower than the symmetry-predicted 31 binding. We determine that this behaviour arises from the interplay of steric clashes and avidity effects that are not reflected in common antibody constructs (i.e. Fabs). Surprisingly, these sub-stoichiometric complexes are fully effective at blocking ACE2 binding despite containing free receptor binding sites. Our results highlight the importance of studying antibody/antigen interactions using complete, multimeric constructs and showcase the utility of single particle mass analyses in unraveling these complex interactions.
Licencia
cc_by_nc_nd
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-BIORXIV Tipo de estudio: Prognostic_studies Idioma: En Año: 2021 Tipo del documento: Preprint
Texto completo: 1 Colección: 09-preprints Base de datos: PREPRINT-BIORXIV Tipo de estudio: Prognostic_studies Idioma: En Año: 2021 Tipo del documento: Preprint