Affinities of recombinant norovirus P dimers for human blood group antigens
Bibliographic record
Abstract
Noroviruses (NoVs), the major cause of viral acute gastroenteritis, recognize histo-blood group antigens (HBGAs) as receptors or attachment factors. To gain a deeper understanding of the interplay between NoVs and their hosts, the affinities of recombinant P dimers (P₂'s) of a GII.4 NoV (VA387) to a library of 41 soluble analogs of HBGAs were measured using the direct electrospray ionization mass spectrometry assay. The HBGAs contained the A, B, H and Lewis epitopes, with variable sizes (2-6 residues) and different types (1-6). The results reveal that the P₂'s exhibit a broad specificity for the HBGAs and bind to all of the oligosaccharides tested. Overall, the affinities are relatively low, ranging from 400 to 3000 M⁻¹ and are influenced by the chain type: 3 > 1 ≈ 2 ≈ 4 ≈ 5 ≈ 6 for H antigens; 6 > 1 ≈ 3 ≈ 4 ≈ 5 > 2 for A antigens; 3 > 1 ≈ 4 ≈ 5 ≈ 6 > 2 for B antigens, but not by chain length. The highest-affinity ligands are B type 3 (3000 ± 300 M⁻¹) and A type 6 (2350 ± 60 M⁻¹). While the higher affinity to the type 3 H antigen was previously observed, preferential binding to the types 6 and 3 antigens with A and B epitopes, respectively, has not been previously reported. A truncated P domain dimer (lacking the C-terminal arginine cluster) exhibits similar binding. The central-binding motifs in the HBGAs were identified by molecular-docking simulations.
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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".