Structural Definition of a Unique Neutralization Epitope on the Receptor-Binding Domain of MERS-CoV Spike Glycoprotein
Bibliographic record
Abstract
The major mechanism of antibody-mediated neutralization of the Middle East respiratory syndrome coronavirus (MERS-CoV) involves competition with the cellular receptor dipeptidyl peptidase 4 (DPP4) for binding to the receptor-binding domain (RBD) of the spike (S) glycoprotein. Here, we report a unique epitope and unusual neutralizing mechanism of the isolated human antibody MERS-4. Structurally, MERS-4 approached the RBD from the outside of the RBD-DPP4 binding interface. Such binding resulted in the folding of the β5-β6 loop toward a shallow groove on the RBD interface critical for accommodating DPP4. The key residues for binding are identified through site-directed mutagenesis. Structural modeling revealed that MERS-4 binds to RBD only in the "up" position in the S trimer. Furthermore, MERS-4 demonstrated synergy with several reported antibodies. These results indicate that MERS-4 neutralizes MERS-CoV by indirect rather than direct competition with DPP4. This mechanism provides a valuable addition for the combined use of antibodies against MERS-CoV infection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".