ANGIOTENSIN I-CONVERTING ENZYME (ACE) INHIBITORY PEPTIDES FROM WHEY FERMENTED BY LACTOBACILLUS SPECIES
Bibliographic record
Abstract
ABSTRACT From 2% (w/w) whey powder in growth media, inhibitory peptides against angiotensin I-converting enzyme (ACE) were studied with nine Lactobacillus species. Lb. brevis, Lb. helveticus and Lb. paracasei were proved to be the most effective strains in liberating ACE inhibitory peptides from whey protein. The inhibition rates of these peptides against ACE ranging from 93.3 to 100%. Several distinct peaks were eluted when the whey proteins were fractionated on a Delta Pak C18 column by reversed phase-high performance liquid chromatography (RP-HPLC). Among ACE inhibitory activities of 14 peptides purified by dialysis and by fractionation using RP-HPLC, two peptide fractions (H5 and H7) of Lb. helveticus showing IC50 values of 5.3 and 7.8 were the most potent ACE inhibitors. All of these peptides including some other peptides (H1 and B1), having strong inhibitory activities against ACE were pentapeptides positioning with Ala at their N-terminal and these petapeptides had mostly hydrophobic (Pro, Val and Leu) or aromatic (Phe) amino acids at the C-terminal. PRACTICAL APPLICATIONS There is a significant amount of research and interest in developing and charactering the peptides that inhibit angiotensin I-converting enzyme (ACE) activity as these natural products may have a role in blood pressure control in man. This study revealed that the identification of peptides, mostly composed of pentapeptides following fermentation of whey protein in growth medium with different strains have the ACE inhibitory activities. These peptides may have antihypertensive effect as natural and safe nutraceutical/functional ingredients, though the exact potency of the pentapeptides isolated in this experiment has not been determined.
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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".