Identification of modulating residues defining the catalytic cleft of insulin-regulated aminopeptidase
Bibliographic record
Abstract
Inhibition of insulin-regulated aminopeptidase (IRAP) has been demonstrated to facilitate memory in rodents, making IRAP a potential target for the development of cognitive enhancing therapies. In this study, we generated a 3-D model of the catalytic domain of IRAP based on the crystal structure of leukotriene A4 hydrolase (LTA4H). This model identified two key residues at the 'entrance' of the catalytic cleft of IRAP, Ala427 and Leu483, which present a more open arrangement of the S1 subsite compared with LTA4H. These residues may define the size and 3-D structure of the catalytic pocket, thereby conferring substrate and inhibitor specificity. Alteration of the S1 subsite by the mutation A427Y in IRAP markedly increased the rate of substrate cleavage V of the enzyme for a synthetic substrate, although a corresponding increase in the rate of cleavage of peptide substrates Leu-enkephalin and vasopressin was was not apparent. In contrast, [L483F]IRAP demonstrated a 30-fold decrease in activity due to changes in both substrate affinity and rate of substrate cleavage. [L483F]IRAP, although capable of efficiently cleaving the N-terminal cysteine from vasopressin, was unable to cleave the tyrosine residue from either Leu-enkephalin or Cyt6-desCys1-vasopressin (2-9), both substrates of IRAP. An 11-fold reduction in the affinity of the peptide inhibitor norleucine1-angiotensin IV was observed, whereas the affinity of angiotensin IV remained unaltered. In additionm we predict that the peptide inhibitors bind to the catalytic site, with the NH2-terminal P1 residue occupying the catalytic cleft (S1 subsite) in a manner similar to that proposed for peptide substrates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".