A broadly protective anti-influenza neuraminidase monoclonal antibody (VAC11P.1100)
Bibliographic record
Abstract
Abstract Hemagglutinin (HA) and neuraminidase (NA) are the major surface glycoproteins of influenza viruses and the main targets of vaccine-induced antibodies (Abs). While several broadly neutralizing anti-HA Abs can cross-protect against diverse influenza subtypes, NA-specific Abs could only protect partially against strains from the same subtype. Through comprehensive bioinformatics analyses of all publicly available influenza A and B NA sequences, we found a universally conserved 9-mer peptide (ILRTQESEC) amongst all influenza NA proteins (amino acids 222-230). Growth kinetics of recombinant viruses with single alanine substitutions within this epitope proved its crucial roles in viral fitness and replication. Importantly, a monoclonal Ab (HCA-2 mAb) raised against this sequence showed broad in vitro inhibition against multiple strains from all influenza A NA subtypes (N1-N9) and influenza B lineages. It also provided in vivo heterosubtypic protection against lethal doses of H1N1 and H3N2 strains. Amino acid residues I222 and E227, located in close proximity to the active site, were found to be indispensable for inhibition by HCA-2 mAb. These findings reveal the essential role of this highly-conserved sequence in NA function and viral replication and show that it is sufficiently exposed to allow access of inhibitory Abs during the course of infection. Thus, it could represent a potential target for novel antivirals or vaccines against diverse strains of influenza A and B 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".