Identification and Inhibitory Properties of Multifunctional Peptides from Pea Protein Hydrolysate
Bibliographic record
Abstract
Pea protein isolate was hydrolyzed with alcalase, and the hydrolysate passed through a 1 kDa cutoff ultrafiltration membrane. The permeate was freeze-dried and fractionated on a cationic solid-phase extraction (SPE) column. All fractions were tested for their inhibitory activities against angiotensin-converting enzyme (ACE), renin, and calmodulin-dependent phosphodiesterase 1 (CaMPDE). With the exception of the first eluted fraction, inhibitory properties of the SPE fractions against CaMPDE (but not ACE and renin) were directly related to cationic character (residence time on the column). However, the fraction that eluted with 1% ammonium hydroxide (SPE 1%) had the highest peptide yield and was subsequently fractionated using two consecutive rounds of reversed-phase high-performance liquid chromatography to obtain three peaks with major peptides identified as IR, KF, and EF by ultra performance liquid chromatography-tandem mass spectrometry. The three dipeptides showed weak inhibitory properties toward CaMPDE but strong inhibitions (IC50 values <25 mM) of ACE and renin. In general, the peptides had higher potency against ACE than against renin. It is indicated from our results that these peptides may be used as potential ingredients to formulate multifunctional food products and nutraceuticals.
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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 | 0.000 |
| 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".