Structural Analysis of the α-2,3-Sialyltransferase Cst-I from <i>Campylobacter jejuni</i> in Apo and Substrate-Analogue Bound Forms<sup>,</sup>
Bibliographic record
Abstract
Sialic acid is an essential sugar in biology that plays key roles in numerous cellular processes and interactions. The biosynthesis of sialylated glycoconjugates is catalyzed by five distinct families of sialyltransferases. In the last 25 years, there has been much research on the enzymes themselves, their genes, and their reaction products, but we still do not know the precise molecular mechanism of action for this class of glycosyltransferase. We previously reported the first detailed structural and kinetic characterization of Cst-II, a bifunctional sialyltransferase (CAZy GT-42) from the bacterium Campylobacter jejuni [Chiu et al. (2004) Nat. Struct. Mol. Biol. 11, 163-170]. This enzyme can use both Gal-beta-1,3/4-R and Neu5Ac-alpha-2,3-Gal-beta-1,3/4-R as acceptor sugars. A second sialyltransferase from this bacterium, Cst-I, has been shown to utilize solely Gal-beta-1,3/4-R as the acceptor sugar in its transferase reaction. We report here the structural and kinetic characterization of this monofunctional enzyme, which belongs to the same sialyltransferase family as Cst-II, in both apo and substrate bound form. Our structural data show that Cst-I adopts a similar GTA-type glycosyltransferase fold to that of the bifunctional Cst-II, with conservation of several key noncharged catalytic residues. Significant differences are found, however, between the two enzymes in the lid domain region, which is critical to the creation of the acceptor sugar binding site. Furthermore, molecular modeling of various acceptor sugars within the active sites of these enzymes provides significant new insights into the structural basis for substrate specificities within this biologically important enzyme class.
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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 | 0.001 |
| 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".