Carbohydrate Recognition by a Large Sialidase Toxin from <i>Clostridium perfringens</i>
Bibliographic record
Abstract
Myonecrotic isolates of Clostridium perfringens secrete multimodular sialidases, often termed "large sialidases", that contribute to the virulence of this bacterium. NanJ is the largest of the two secreted sialidases at 1173 amino acids and comprises 6 different modules which are, from the N-terminus, a family 32 carbohydrate binding module (CBM), a family 40 CBM, a family 33 glycoside hydrolase, a module of unknown function, a family 82 "X-module" of unknown function, and a module with amino acid similarity to fibronectin type III domains. The hydrolase activity of clostridial sialidases is quite well documented; however, the functions of their accessory domains are entirely uninvestigated. Here we describe the carbohydrate binding activity of the isolated family 32 CBM (CBM32) and the isolated family 40 CBM (CBM40). CBM32 is shown to bind galactose or N-acetylgalactosamine, while CBM40 is sialic acid specific, though both CBMs appear to bind with very low affinities. The crystal structure of CBM32 was determined at 2.25 A in complex with galactose. This revealed what appears to be a very simple galactose binding site. The crystal structure of CBM40 was determined at 2.20 A in complex with a sialic acid containing molecule that it fortuitously crystallized with, revealing the molecular details of the CBM40-sialic acid interaction. Overall, the results indicate that NanJ contains carbohydrate specific binding modules that likely function to target the enzyme to molecules or cells bearing mixed populations of glycans that terminate in either galactose/N-acetylgalactosamine or sialic acid.
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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) | 0.001 | 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".