Potent Neutralization of Omicron and other SARS-CoV-2 Variants of Concern by Biparatopic Human VH Domains
Bibliographic record
Abstract
Abstract The emergence of SARS-CoV-2 variants of concern (VOCs) requires the development of next-generation biologics that are effective against a variety of strains of the virus. Herein, we characterize a human V H domain, F6, which we generated by sequentially panning large phage displayed V H libraries against receptor binding domains (RBDs) containing VOC mutations. Cryo-EM analyses reveal that F6 has a unique binding mode that spans a broad surface of the RBD and involves the antibody framework region. Attachment of an Fc region to a fusion of F6 and ab8, a previously characterized V H domain, resulted in a construct (F6-ab8-Fc) that neutralized Omicron pseudoviruses with a half-maximal neutralizing concentration (IC 50 ) of 4.8 nM in vitro . Additionally, prophylactic treatment using F6-ab8-Fc reduced live Beta (B.1.351) variant viral titers in the lungs of a mouse model. Our results provide a new potential therapeutic against SARS-CoV-2 VOCs - including the recently emerged Omicron variant - and highlight a vulnerable epitope within the spike protein RBD that may be exploited to achieve broad protection against circulating variants.
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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".