Hydrogen–Deuterium Exchange Epitope Mapping Reveals Distinct Neutralizing Mechanisms for Two Monoclonal Antibodies against Diphtheria Toxin
Bibliographic record
Abstract
The diphtheria toxoid (DT) antigen is one of the major components in pediatric and booster combination vaccines and is known to raise a protective humoral immune response upon vaccination. However, a structurally resolved analysis of diphtheria toxin (DTx) epitopes with underlying molecular mechanisms of antibody neutralization has not yet been reported. Using hydrogen-deuterium exchange mass spectrometry (HDX-MS) and Biolayer Interferometry (BLI) assays, we have characterized two neutralizing anti-DTx monoclonal antibodies (mAbs), 2-25 and 2-18, by identifying the specific epitopes on the diphtheria toxin responsible for antibody binding. Our results show that both epitopes are conformational, and mechanistically distinct. Monoclonal antibody 2-25 binds selectively to the B-subunit (translocation and receptor domain) of DTx, blocking the heparin-binding EGF-like growth factor (HBEGF) binding site. In contrast, mAb 2-18 binds to the A-subunit (catalytic domain), partially covering the catalytic loop region that shuttles NAD during catalysis. The results are discussed in the context of antigen neutralization mechanisms and can ultimately help to reveal the underlying factors that contribute to Diptheria vaccine efficacy.
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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) | 0.000 | 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".