Kinetic and Structural Evaluation of Selected Active Site Mutants of the <i>Aspergillus fumigatus</i> KDNase (Sialidase)
Bibliographic record
Abstract
Aspergillus fumigatus is an airborne fungal pathogen. We previously cloned and characterized an exo-sialidase from A. fumigatus and showed that it preferred 2-keto-3-deoxynononic acid (KDN) as a substrate to N-acetylneuraminic acid (Neu5Ac). The purpose of this study was to investigate the structure-function relationships of critical catalytic site residues. Site-directed mutagenesis was used to create three mutant recombinant enzymes: the catalytic nucleophile (Y358H), the general acid/base catalyst (D84A), and an enlargement of the binding pocket to attempt to accommodate the N-acetyl group of Neu5Ac (R171L). Crystal structures for all enzymes were determined. The D84A mutation had an effect in decreasing the activity of AfKDNase that was stronger than that of the same mutation in the structurally similar sialidase from the bacterium Micromonospora viridifaciens. These data suggest that the catalytic acid is more important in the reaction of AfKDNase and that catalysis is less dependent on nucleophilic or electrostatic stabilization of the developing positive charge at the transition state for hydrolysis. Removal of the catalytic nucleophile (Y358H) significantly lowered the activity of the enzyme, but this mutant remained a retaining glycosidase as demonstrated by nuclear magnetic resonance spectroscopic analysis. This is a novel finding that has not been shown with other sialidases. Kinetic activity measured at pH 5.2 revealed that R171L had higher activity on a Neu5Ac-based substrate than wild-type KDNase; hence, leucine in place of arginine in the binding pocket improved catalysis toward Neu5Ac substrates. Hence, whether a sialidase is primarily a KDNase or a neuraminidase is due in part to the presence of an amino acid that creates a steric clash with the N-acetyl group.
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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".