ACE2 engagement exposes the fusion peptide to pan-coronavirus neutralizing antibodies
Bibliographic record
Abstract
Abstract Coronaviruses use diverse Spike (S) glycoproteins to attach to host receptors and fuse with target cells. Using a broad screening approach, we isolated from SARS-CoV-2 immune donors seven monoclonal antibodies (mAbs) that bind to all human alpha and beta coronavirus S proteins. These mAbs recognize the fusion peptide and acquire high affinity and breadth through somatic mutations. Despite targeting a conserved motif, only some mAbs show broad neutralizing activity in vitro against alpha and beta coronaviruses, including Omicron BA.1 variant and bat WIV-1, and reduce viral titers and pathology in vivo. Structural and functional analyses show that the fusion peptide-specific mAbs bind with different modalities to a cryptic epitope which is concealed by prefusion-stabilizing ‘2P’ mutations and becomes exposed upon binding of ACE2 or ACE2-mimicking mAbs. This study identifies a new class of pan-coronavirus neutralizing mAbs and reveals a receptor-induced conformational change in the S protein that exposes the fusion peptide region.
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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 | 0.000 |
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".