Protein Scaffold‐Based Multimerization of Soluble ACE2 Efficiently Blocks SARS‐CoV‐2 Infection In Vitro and In Vivo
Bibliographic record
Abstract
Abstract Soluble ACE2 (sACE2) decoys are promising agents to inhibit SARS‐CoV‐2, as their efficiency is unlikely to be affected by escape mutations. However, their success is limited by their relatively poor potency. To address this challenge, multimeric sACE2 consisting of SunTag or MoonTag systems is developed. These systems are extremely effective in neutralizing SARS‐CoV‐2 in pseudoviral systems and in clinical isolates, perform better than the dimeric or trimeric sACE2, and exhibit greater than 100‐fold neutralization efficiency, compared to monomeric sACE2. SunTag or MoonTag fused to a more potent sACE2 (v1) achieves a sub‐nanomolar IC 50 , comparable with clinical monoclonal antibodies. Pseudoviruses bearing mutations for variants of concern, including delta and omicron, are also neutralized efficiently with multimeric sACE2. Finally, therapeutic treatment of sACE2(v1)‐MoonTag provides protection against SARS‐CoV‐2 infection in an in vivo mouse model. Therefore, highly potent multimeric sACE2 may offer a promising treatment approach against SARS‐CoV‐2 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) | 0.001 | 0.000 |
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".