A quantitative, high-throughput method identifies protein–glycan interactions via mass spectrometry
Bibliographic record
Abstract
Abstract Glycan binding by glycan-binding proteins and processing by carbohydrate-active enzymes is implicated in physiological and pathophysiological processes. Comprehensive mapping of glycan interactions is essential to understanding of glycan-mediated biology and can guide the development of new diagnostics and therapeutics. Here, we introduce the competitive universal proxy receptor assay (CUPRA), which combines electrospray ionization mass spectrometry, competitive binding and heterobifunctional glycan-based ligands to give a quantitative high-throughput method for screening glycan libraries against glycan-binding and glycan-processing proteins. Application of the assay to human (siglec-2), plant ( Sambucus nigra and Maackia amurensis lectins) and bacterial (cholera toxin, and family 51 carbohydrate binding module) proteins allowed for the identification of ligands with affinities ( K d ) ≤ 1 mM. The assay is unprecedentedly versatile and can be applied to natural libraries and, when implemented in a time-resolved manner, provides a quantitative measure of the activities and substrate specificity of carbohydrate-active enzymes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".