Computational redesign of Fab CC12.3 with substantially better predicted binding affinity to SARS-CoV-2 than human ACE2 receptor.

SARS-CoV-2 is responsible for COVID-19 pandemic, causing large numbers of cases and deaths. It initiates entry into human cells by binding to the peptidase domain of angiotensin-converting enzyme 2 (ACE2) receptor via its receptor binding domain of S1 subunit of spike protein (SARS-CoV-2-RBD). Employing neutralizing antibodies to prevent binding between SARS-CoV-2-RBD and ACE2 is an effective COVID-19 therapeutic solution. Previous studies found that CC12.3 is a highly potent neutralizing antibody that was isolated from a SARS-CoV-2 infected patient, and its Fab fragment (Fab CC12.3) bound to SARS-CoV-2-RBD with comparable binding affinity to ACE2. To enhance its binding affinity, we employed computational protein design to redesign all CDRs of Fab CC12.3 and molecular dynamics (MD) to validate their predicted binding affinities by the MM-GBSA method. MD results show that the predicted binding affinities of the three best designed Fabs CC12.3 (CC12.3-D02, CC12.3-D05, and CC12.3-D08) are better than those of Fab CC12.3 and ACE2. Additionally, our results suggest that enhanced binding affinities of CC12.3-D02, CC12.3-D05, and CC12.3-D08 are caused by increased SARS-CoV-2-RBD binding interactions of CDRs L1 and L3. This study redesigned neutralizing antibodies with better predicted binding affinities to SARS-CoV-2-RBD than Fab CC12.3 and ACE2. They are promising candidates as neutralizing antibodies against SARS-CoV-2.

Computational design of SARS-CoV-2 peptide binders with better predicted binding affinities than human ACE2 receptor.

SARS-CoV-2 is coronavirus causing COVID-19 pandemic. To enter human cells, receptor binding domain of S1 subunit of SARS-CoV-2 (SARS-CoV-2-RBD) binds to peptidase domain (PD) of angiotensin-converting enzyme 2 (ACE2) receptor. Employing peptides to inhibit binding between SARS-CoV-2-RBD and ACE2-PD is a therapeutic solution for COVID-19. Previous experimental study found that 23-mer peptide (SBP1) bound to SARS-CoV-2-RBD with lower affinity than ACE2. To increase SBP1 affinity, our previous study used residues 21-45 of α1 helix of ACE2-PD (SPB25) to design peptides with predicted affinity better than SBP1 and SPB25 by increasing interactions of residues that do not form favorable interactions with SARS-CoV-2-RBD. To design SPB25 with better affinity than ACE2, we employed computational protein design to increase interactions of residues reported to form favorable interactions with SARS-CoV-2-RBD and combine newly designed mutations with the best single mutations from our previous study. Molecular dynamics show that predicted binding affinities of three peptides (SPB25Q22R, SPB25F8R/K11W/L25R and SPB25F8R/K11F/Q22R/L25R) are better than ACE2. Moreover, their predicted stabilities may be slightly higher than SBP1 as suggested by their helicities. This study developed an approach to design SARS-CoV-2 peptide binders with predicted binding affinities better than ACE2. These designed peptides are promising candidates as SARS-CoV-2 inhibitors.

Computational Design of 25-mer Peptide Binders of SARS-CoV-2.

SARS-CoV-2 is the novel coronavirus causing the COVID-19 pandemic. To enter human cells, the receptor-binding domain (RBD) of the S1 subunit of SARS-CoV-2 (SARS-CoV-2-RBD) initially binds to the peptidase domain of angiotensin-converting enzyme 2 receptor (ACE2-PD). Using peptides to inhibit SARS-CoV-2-RBD binding to ACE2 is a potential therapeutic solution for COVID-19. A previous study identified a 23-mer peptide (SBP1) that bound to SARS-CoV-2-RBD with comparable KD to ACE2. We employed computational protein design and molecular dynamics (MD) to design SARS-CoV-2-RBD 25-mer peptide binders (SPB25) with better predicted binding affinity than SBP1. Using residues 21-45 of the α1 helix of ACE2-PD as the template, our strategy is employing Rosetta to enhance SPB25 binding affinity to SARS-CoV-2-RBD and avoid disrupting existing favorable interactions by using residues that have not been reported to form favorable interactions with SARS-CoV-2-RBD as designed positions. Designed peptides with better predicted binding affinities, by Rosetta, than SPB25 were subjected to MD validation. The MD results show that five designed peptides (SPB25F8N, SPB25F8R, SPB25L25R, SPB25F8N/L25R, and SPB25F8R/L25R) have better predicted binding affinities, by the MM-GBSA method, than SPB25 and SBP1. This study developed an approach to design SARS-CoV-2-RBD peptide binders, and these peptides may be promising candidates as potential SARS-CoV-2 inhibitors.