Targeting Norovirus Infection—Multivalent Entry Inhibitor Design Based on NMR Experiments
Bibliographic record
Abstract
Noroviruses attach to their host cells through histo blood group antigens (HBGAs), and compounds that interfere with this interaction are likely to be of therapeutic or diagnostic interest. It is shown that NMR binding studies can simultaneously identify and differentiate the site for binding HBGA ligands and complementary ligands from a large compound library, thereby facilitating the design of potent heterobifunctional ligands. Saturation transfer difference (STD) NMR experiments, spin-lock filtered NMR experiments, and interligand NOE (ILOE) experiments in the presence of virus-like particles (VLPs), identified compounds that bind to the HBGA binding site of human norovirus. Based on these data two multivalent prototype entry-inhibitors against norovirus infection were synthesized. A surface plasmon resonance based inhibition assay showed avidity gains of 1000 and one million fold over a millimolar univalent ligand. This suggests that further rational design of multivalent inhibitors based on our strategy will identify potent entry-inhibitors against norovirus infections.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".