A ‘glyco-fluorine’ code revealing differential recognition by glycan binding partners
Bibliographic record
Abstract
Biosensing or diagnostics using glycan sequences as targets is limited by glycan cross-reactivities. As binding sites of different proteins that all recognise a given glycan will not be identical, we introduce application of a library of synthetic analogues of a single glycan ligand as a powerful approach to obtain fingerprint binding profiles. We report the enzymatic synthesis of a 150-member library of fluorinated Lewisx analogues (‘glycofluoroforms’) using naturally occurring enzymes and fluorinated monosaccharide building blocks, and the incorporation of a subset into lipid-linked glycan probes or into glyconanoparticles for probing protein binding both in solid-phase high-throughput glycan microarray screening analyses and in solution-phase nanoparticle-based interaction studies. These fluorinated Lewisx analogues, which NMR studies showed to have very similar 3D structures compared to the nonfluorinated Lewisx, gave variously increased or decreased binding with a set of proteins, the different proteins having different preferences and tolerances for binding.
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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) | 0.002 | 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 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".