Structural and enzymatic characterization of NanS (YjhS), a 9‐<i>O</i>‐Acetyl <i>N</i>‐acetylneuraminic acid esterase from <i>Escherichia coli O157:H7</i>
Bibliographic record
Abstract
There is a high prevalence of sialic acid in a number of different organisms, resulting in there being a myriad of different enzymes that can exploit it as a fermentable carbon source. One such enzyme is NanS, a carbohydrate esterase that we show here deacetylates the 9 position of 9-O-sialic acid so that it can be readily transported into the cell for catabolism. Through structural studies, we show that NanS adopts a SGNH hydrolase fold. Although the backbone of the structure is similar to previously characterized family members, sequence comparisons indicate that this family can be further subdivided into two subfamilies with somewhat different fingerprints. NanS is the founding member of group II. Its catalytic center contains Ser19 and His301 but no Asp/Glu is present to form the classical catalytic triad. The contribution of Ser19 and His301 to catalysis was confirmed by mutagenesis. In addition to structural characterization, we have mapped the specificity of NanS using a battery of substrates.
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".