Probing the acyl‐binding pocket of aminoacylase‐1
Bibliographic record
Abstract
In the metallopeptidase family M20, remodeling of a common scaffold has given rise to various amidohydrolases that feature a homodimerization domain nested within the Zn‐binding domain. Residues from both dimerization domains and one of the two Zn‐binding domains, respectively, contribute to the active sites. One such enzyme, the mammalian aminoacylase‐1 (Acy1), functions in the salvage of acetylated amino acids. The related Pseudomonas carboxypeptidase G2 (CPG2) is used in cancer therapy. CPG2 and Acy1 both deacylate amino acids, but with distinct selectivities toward the acyl portion: CPG2 prefers bulky acyl moieties whereas Acy1 selects for acetyl and small acyl groups. To map the apparently more restricted acyl‐binding pocket of Acy1, we designed and assayed a series of aliphatic acyl‐Met substrates for the human and porcine enzymes. 3D‐QSAR models were derived to relate measured substrate binding affinities (p K M ) to molecular topologies of the acyl fragments. The results indicate subtle differences between the two Acy1 enzymes. Docking of the 3D‐QSAR map for human Acy1 in the crystal structure of its Zn‐binding domain associates the I177, T347 and L372 side chains with detrimental contributions to the binding of larger acyl groups. We probed these predictions by site‐directed mutagenesis and enzymatic characterization. Lower K M values for T347S and L372V indicate improved binding affinities toward apposite acyl moieties. This strengthens our prediction that T347 and L372 specifically restrict the acyl‐binding pocket, and shows the potential for engineering of substrate specificity. Supported by the National Research Council Canada
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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".