Antigenic mapping reveals sites of vulnerability on α-HCoV spike protein
Bibliographic record
Abstract
Understanding the antigenic signatures of all human coronaviruses (HCoVs) Spike (S) proteins is imperative for pan-HCoV epitopes identification and broadly effective vaccine development. To depict the currently elusive antigenic signatures of α-HCoVs S proteins, we isolated a panel of antibodies against the HCoV-229E S protein and characterized their epitopes and neutralizing potential. We found that the N-terminal domain of HCoV-229E S protein is antigenically dominant wherein an antigenic supersite is present and appears conserved in HCoV-NL63, which holds potential to serve as a pan-α-HCoVs epitope. In the receptor binding domain, a neutralizing epitope is captured in the end distal to the receptor binding site, reminiscent of the locations of the SARS-CoV-2 RBD cryptic epitopes. We also identified a neutralizing antibody that recognizes the connector domain, thus representing the first S2-directed neutralizing antibody against α-HCoVs. The unraveled HCoVs S proteins antigenic similarities and variances among genera highlight the challenges faced by pan-HCoV vaccine design while supporting the feasibility of broadly effective vaccine development against a subset of HCoVs.
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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".