Angiotensin-Converting Enzyme 2 Metabolizes and Partially Inactivates Pyr-Apelin-13 and Apelin-17
Bibliographic record
Abstract
Apelin peptides mediate beneficial effects on the cardiovascular system and are being targeted as potential new drugs. However, apelin peptides have extremely short biological half-lives, and improved understanding of apelin peptide metabolism may lead to the discovery of biologically stable analogues with therapeutic potential. We examined the ability of angiotensin-converting enzyme 2 (ACE2) to cleave and inactivate pyr-apelin 13 and apelin 17, the dominant apelin peptides. Computer-assisted modeling shows a conserved binding of pyr-apelin 13 and apelin 17 to the ACE2 catalytic site. In ACE2 knockout mice, hypotensive action of pyr-apelin 13 and apelin 17 was potentiated, with a corresponding greater elevation in plasma apelin levels. Similarly, pharmacological inhibition of ACE2 potentiated the vasodepressor action of apelin peptides. Biochemical analysis confirmed that recombinant human ACE2 can cleave pyr-apelin 13 and apelin 17 efficiently, and apelin peptides are degraded slower in ACE2-deficient plasma. The biological relevance of ACE2-mediated proteolytic processing of apelin peptides was further supported by the reduced potency of pyr-apelin 12 and apelin 16 on the activation of signaling pathways and nitric oxide production from endothelial cells. Importantly, although pyr-apelin 13 and apelin 17 rescued contractile function in a myocardial ischemia-reperfusion model, ACE2 cleavage products, pyr-apelin 12 and 16, were devoid of these cardioprotective effects. We designed and synthesized active apelin analogues that were resistant to ACE2-mediated degradation, thereby confirming that stable apelin analogues can be designed as potential drugs. We conclude that ACE2 represents a major negative regulator of apelin action in the vasculature and heart.
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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".