Zika-specific neutralizing antibodies targeting inter-dimer envelope epitopes
Bibliographic record
Abstract
Zika virus (ZIKV) is an emerging pathogen that causes devastating congenital defects. The overlapping epidemiology and immunologic cross-reactivity between ZIKV and dengue virus (DENV) pose complex challenges to vaccine design, given the potential for antibody-dependent enhancement of disease. Therefore, classification of ZIKV-specific antibody targets is of notable value. From a ZIKV-infected rhesus macaque, we identify ZIKV-reactive B cells and isolate potent neutralizing monoclonal antibodies (mAbs) with no cross-reactivity to DENV. We group these mAbs into four distinct antigenic groups targeting ZIKV-specific cross-protomer epitopes on the envelope glycoprotein. Co-crystal structures of representative mAbs in complex with ZIKV envelope glycoprotein reveal envelope-dimer epitope and unique dimer-dimer epitope targeting. All four specificities are serologically identified in convalescent humans following ZIKV infection, and representative mAbs from all four groups protect against ZIKV replication in mice. These results provide key insights into ZIKV-specific antigenicity and have implications for ZIKV vaccine, diagnostic, and therapeutic development.
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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".