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Broadly effective ACE2 decoy proteins protect mice from lethal SARS-CoV-2 infection (preprint)
biorxiv; 2023.
Preprint in English | bioRxiv | ID: ppzbmed-10.1101.2023.02.22.529625
ABSTRACT
As SARS-CoV-2 variants have been causing increasingly serious drug resistance problem, development of broadly effective and hard-to-escape anti-SARS-CoV-2 agents is in urgent need. Here we describe further development and characterization of two SARS-CoV-2 receptor decoy proteins, ACE2-Ig-95 and ACE2-Ig-105/106. We found that both proteins had potent and robust in vitro neutralization activities against diverse SARS-CoV-2 variants including Omicron, with an average IC50 of up to 37 pM. In a stringent lethal SARS-CoV-2 infection mouse model, both proteins lowered lung viral load by up to ~1000 fold, prevented the emergence of clinical signs in >75% animals, and increased animal survival rate from 0% (untreated) to >87.5% (treated). These results demonstrate that both proteins are good drug candidates for protecting animals from severe COVID-19. In a head-to-head comparison of these two proteins with five previously-described ACE2-Ig constructs, we found that two of these constructs, each carrying five surface mutations in the ACE2 region, had partial loss of neutralization potency against three SARS-CoV-2 variants. These data suggest that extensively mutating ACE2 residues near the RBD-binding interface should be avoided or performed with extra caution. Further, we found that both ACE2-Ig-95 and ACE2-Ig-105/106 could be produced to gram/liter level, demonstrating the developability of them as biologic drug candidates. Stress-condition stability test of them further suggests that more studies are required in the future to improve the stability of these proteins. These studies provide useful insight into critical factors for engineering and preclinical development of ACE2 decoys as broadly effective therapeutics against diverse ACE2-utilizing coronaviruses.
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Full text: Available Collection: Preprints Database: bioRxiv Main subject: COVID-19 Language: English Year: 2023 Document Type: Preprint

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Full text: Available Collection: Preprints Database: bioRxiv Main subject: COVID-19 Language: English Year: 2023 Document Type: Preprint