Chemoenzymatic Synthesis of Chito-oligosaccharides with Alternating <i>N</i>-<scp>d</scp>-Acetylglucosamine and <scp>d</scp>-Glucosamine
Bibliographic record
Abstract
Chito-oligosaccharides (CHOS) are homo- or hetero-oligomers of N -acetylglucosamine (GlcNAc, A) and d -glucosamine (GlcN, D). Production of well-defined CHOS-mixtures, or even pure CHOS, with specific lengths and sugar compositions, is of great interest since these oligosaccharides have interesting bioactivities. While direct chemical synthesis of CHOS is not straightforward, chemo-enzymatic approaches have shown some promise. We have used engineered glycoside hydrolases to catalyze oligomerization of activated DA building blocks through transglycosylation reactions. The building blocks were generated from readily available (GlcNAc) 2 - para -nitrophenol through deacetylation of the nonreducing end sugar with a recombinantly expressed deacetylase from Aspergillus niger ( An CDA9). This approach, using a previously described hyper-transglycosylating variant of ChiA from Serratia marcescens ( Sm ChiA) and a newly generated transglycosylating variant of Chitinase D from Serratia proteamaculans ( Sp ChiD), led to production of CHOS containing up to ten alternating D and A units [(DA) 2, (DA) 3, (DA) 4, and (DA) 5 ]. The most abundant compounds were purified and characterized. Finally, we demonstrate that (DA) 3 generated in this study may serve as a specific inhibitor of the human chitotriosidase. Inhibition of this enzyme has been suggested as a therapeutic strategy against systemic sclerosis.
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) | 0.000 | 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) | 0.001 | 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".