Streamlining Sulfated Oligosaccharide and Glycan Synthesis with Engineered Mutant 6-SulfoGlcNAcases
Bibliographic record
Abstract
Sulfation is a common, but poorly understood, post-glycosylational modification (PGM) used to modulate biological function. To deepen our understanding of the roles of various sulfated glycoforms and their relevant binding proteins, we must expand our enzymatic toolkit for their synthesis. Here, we bypass the need for both sulfotransferases and glycosyltransferases by engineering a series of mutants of a 6-SulfoGlcNAcase, from Streptococcus pneumoniae, to directly and efficiently synthesize not only the ubiquitous 6S-GlcNAc-β-1,3-Gal linkage prevalent within host glycans, but also the 6S-GlcNAc-β-1,6-GalNAc commonly observed within core-6 O-glycans, and the more exotic 6S-GlcNAc-β-1,4-GalNAc linkage. We further elaborate these into complex sulfated N-glycan and O-glycan structures of biological relevance. By utilizing the cost-effective activated donor pNP-6S-GlcNAc in conjunction with mutant GH185 6-SulfoGlcNAcases we demonstrate a simple yet powerful in vitro method for generating well-defined sulfated oligosaccharides and glycoforms for use in a variety of applications including glycan arrays, glycan remodeling, and specificity studies with carbohydrate binding proteins such as lectins.
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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) | 0.000 | 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".