PT  - JOURNAL ARTICLE
AU  - Alison C. Leonard
AU  - Jonathan J. Weinstein
AU  - Paul J. Steiner
AU  - Annette H. Erbse
AU  - Sarel J. Fleishman
AU  - Timothy A. Whitehead
TI  - Stabilization of the SARS-CoV-2 Receptor Binding Domain by Protein Core Redesign and Deep Mutational Scanning
AID  - 10.1101/2021.11.22.469552
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.11.22.469552
4099  - http://biorxiv.org/content/early/2021/11/24/2021.11.22.469552.short
4100  - http://biorxiv.org/content/early/2021/11/24/2021.11.22.469552.full
AB  - Stabilizing antigenic proteins as vaccine immunogens or diagnostic reagents is a stringent case of protein engineering and design as the exterior surface must maintain recognition by receptor(s) and antigen—specific antibodies at multiple distinct epitopes. This is a challenge, as stability-enhancing mutations must be focused on the protein core, whereas successful computational stabilization algorithms typically select mutations at solvent-facing positions. In this study we report the stabilization of SARS-CoV-2 Wuhan Hu-1 Spike receptor binding domain (S RBD) using a combination of deep mutational scanning and computational design, including the FuncLib algorithm. Our most successful design encodes I358F, Y365W, T430I, and I513L RBD mutations, maintains recognition by the receptor ACE2 and a panel of different anti-RBD monoclonal antibodies, is between 1-2°C more thermally stable than the original RBD using a thermal shift assay, and is less proteolytically sensitive to chymotrypsin and thermolysin than the original RBD. Our approach could be applied to the computational stabilization of a wide range of proteins without requiring detailed knowledge of active sites or binding epitopes, particularly powerful for cases when there are multiple or unknown binding sites.Competing Interest StatementThe authors have declared no competing interest.