Computational design of nanomolar-binding antibodies specific to multiple SARS-CoV-2 variants by engineering a specificity switch of antibody 80R using RosettaAntibodyDesign (RAbD) results in potential generalizable therapeutic antibodies for novel SARS-CoV-2 virus

Nancy E. Hernandez, Wojciech Jankowski, Rahel Frick, Simon P. Kelow, Joseph H. Lubin, Vijaya Simhadri, Jared Adolf-Bryfogle, Sagar D. Khare, Roland L. Dunbrack, Jeffrey J. Gray, Zuben E. Sauna

Research output: Contribution to journalArticlepeer-review

Abstract

The human infectious disease COVID-19 caused by the SARS-CoV-2 virus has become a major threat to global public health. Developing a vaccine is the preferred prophylactic response to epidemics and pandemics. However, for individuals who have contracted the disease, the rapid design of antibodies that can target the SARS-CoV-2 virus fulfils a critical need. Further, discovering antibodies that bind multiple variants of SARS-CoV-2 can aid in the development of rapid antigen tests (RATs) which are critical for the identification and isolation of individuals currently carrying COVID-19. Here we provide a proof-of-concept study for the computational design of high-affinity antibodies that bind to multiple variants of the SARS-CoV-2 spike protein using RosettaAntibodyDesign (RAbD). Well characterized antibodies that bind with high affinity to the SARS-CoV-1 (but not SARS-CoV-2) spike protein were used as templates and re-designed to bind the SARS-CoV-2 spike protein with high affinity, resulting in a specificity switch. A panel of designed antibodies were experimentally validated. One design bound to a broad range of variants of concern including the Omicron, Delta, Wuhan, and South African spike protein variants.

Original languageEnglish (US)
Article numbere15032
JournalHeliyon
Volume9
Issue number4
DOIs
StatePublished - Apr 2023

Keywords

  • Computational antibody design
  • Coronavirus Disease 2019
  • Diagnostic
  • Monoclonal antibody therapeutics
  • Protein engineering

ASJC Scopus subject areas

  • General

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