A Kinetic Trapping Approach for Facile Access to 3F<sub>ax</sub>Neu5Ac and a Photo-Cross-Linkable Sialyltransferase Probe
Bibliographic record
Abstract
Sialic acid (Neu5Ac) is installed onto glycoconjugates by sialyltransferases (STs) using cytidine monophosphate-Neu5Ac (CMP-β- d -Neu5Ac) as their donor. The only class of cell-active ST inhibitors are those based on a 3F ax Neu5Ac scaffold, which is metabolically converted into CMP-3F ax Neu5Ac within cells. It is essential for the fluorine to be axial, yet stereoselective installation of fluorine in this specific orientation is challenging. Sialic acid aldolase can convert 3-fluoropyruvate and 2-acetamido-2-deoxy- d -mannopyranose (ManNAc) to 3FNeu5Ac, but stereocontrol of the fluorine in the product has not been possible. We hypothesized that the 3F ax kinetic product of a sialic acid aldolase reaction could be trapped by coupling with CMP-sialic acid synthetase to yield CMP-3F ax Neu5Ac. Here, we report that highly active CMP-sialic acid synthetase and short reaction times produce exclusively CMP-3F ax Neu5Ac. Removal of CMP from CMP-3F ax Neu5Ac under acidic conditions unexpectedly led to 3-fluoro-β- d -Neu5Ac 2-phosphate (3F ax Neu5Ac-2P). Alkaline phosphatase successfully converted 3F ax Neu5Ac-2P to 3F ax Neu5Ac, enabling stereochemically controlled access to 3F ax Neu5Ac, which is effective in lowering the sialoglycan ligands for Siglecs on cells. Moreover, our kinetic trapping approach could be used to access CMP-3F ax Neu5Ac with modifications at the C5, C9, or both positions, which enabled the chemoenzymatic synthesis of a photo-cross-linkable version of CMP-3F ax Neu5Ac that selectively photo-cross-linked to ST6GAL1 over two other STs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.001 | 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".