Clinical grade ACE2 effectively inhibits SARS-CoV-2 Omicron infections
Bibliographic record
Abstract
Abstract The recent emergence of the SARS-CoV-2 variant Omicron has caused considerable concern due to reduced vaccine efficacy and escape from neutralizing antibody therapeutics. Omicron is spreading rapidly around the globe and is suspected to account for most new COVID-19 cases in several countries, though the severity of Omicron-mediated disease is still under debate. It is therefore paramount to identify therapeutic strategies that inhibit the Omicron SARS-CoV-2 variant. Here we report using 3D structural modelling that Spike of Omicron can still associate with human ACE2. Sera collected after the second mRNA-vaccination did not exhibit a protective effect against Omicron while strongly neutralizing infection of VeroE6 cells with the reference Wuhan strain, confirming recent data by other groups on limited vaccine and convalescent sera neutralization efficacy against Omicron. Importantly, clinical grade recombinant human soluble ACE2, a drug candidate currently in clinical development, potently neutralized Omicron infection of VeroE6 cells with markedly enhanced potency when compared to reference SARS-CoV-2 isolates. These data show that SARS-CoV-2 variant Omicron can be readily inhibited by soluble ACE2, providing proof of principle of a viable and effective therapeutic approach against Omicron infections.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".