Insight into substrate recognition and catalysis by the human neuraminidase 3 (NEU3) through molecular modeling and site-directed mutagenesis
Bibliographic record
Abstract
The mammalian neuraminidase (NEU) enzymes are found in diverse cellular compartments. Members of the family, such as NEU2 and NEU1, are cytosolic or lysosomal, while NEU3 and NEU4 are membrane-associated. NEU enzymes that act on substrates in the plasma membrane could modulate cellular signaling, cell surface glycoforms and the composition of plasma membrane glycolipids. Therefore, their substrates and mechanism of action are of interest for discerning their physiological roles. We have studied the structure of the human NEU3 using molecular modeling to predict residues involved in the recognition and hydrolysis of glycolipid substrates. To test the model, we have used site-directed mutagenesis of the recombinant protein. Enzymatic studies of the relative activity of these mutants, as well as their pH profiles and inhibition by 2-deoxy-2,3-dehydro-N-acetylneuraminic acid, are reported. Using nuclear magnetic resonance spectroscopy, we confirmed that the enzyme is a retaining exo-sialidase, and we propose that the key catalytic residues of the enzyme consist of the general acid-base D50 and the nucleophilic Y370-E225 pair. Mutations of residues expected to interact directly with the sialic acid N5-acetyl (A160, M87, I105) and C7-C9 glycerol side-chain (E113, Y179, Y181) reduced enzymatic activity. We identified several active mutants of the enzyme which contain modifications at the periphery of the active site. Truncations at the N- or C-terminus of more than 10 residues abolished enzyme activity. We propose a catalytic mechanism consistent with the data and identify residues that contribute to glycolipid recognition.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".