Neutralizing epitopes of the SARS-CoV S-protein cluster independent of repertoire, antigen structure or mAb technology
Bibliographic record
Abstract
Neutralizing antibody responses to the surface glycoproteins of enveloped viruses play an important role in immunity. Many of these glycoproteins, including the severe acute respiratory syndrome-coronavirus (SARS-CoV) spike (S) protein form trimeric units in the membrane of the native virion. There is substantial experimental and pre-clinical evidence showing that the S protein is a promising lead for vaccines and therapeutics. Previously we generated a panel of monoclonal antibodies (mAbs) to whole inactivated SARS-CoV which neutralize the virus in vitro. Here, we define their specificity and affinity, map several of their epitopes and lastly characterise chimeric versions of them. Our data show that the neutralizing mAbs bind to the angiotensin-converting enzyme 2 (ACE2) receptor-binding domain (RBD) of the SARS S protein. Three of the chimeric mAbs retain their binding specificity while one conformational mAb, F26G19, lost its ability to bind the S protein despite high level expression. The affinity for recombinant S is maintained in all of the functional chimeric versions of the parental mAbs. Both parental mAb F26G18 and the chimeric version neutralize the TO R2 strain of SARS-CoV with essentially identical titres (2.07 and 2.47 nM, respectively). Lastly, a comparison with other neutralizing mAbs to SARS-CoV clearly shows that the dominance of a 33 amino acid residue loop of the SARS-CoV RBD is independent of repertoire, species, quaternary structure, and importantly, the technology used to derive the mAbs. In cases like this, the dominance of a compact RBD antigenic domain and the central role of the S protein in pathogenesis may inherently create immunoselection pressure on viruses to evolve more complex evasion strategies or die out of a host species. The apparent simplicity of the mechanism of SARS-CoV neutralization is in stark contrast to the complexity shown by other enveloped viruses.
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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".