Acetylcholinesterase and butyrylcholinesterase inhibitory activities of antioxidant peptides obtained from enzymatic pea protein hydrolysates and their ultrafiltration peptide fractions
Bibliographic record
Abstract
This study optimized the enzymatic hydrolysis of yellow field pea proteins using alcalase (ACH), chymotrypsin (CHH), flavourzyme (FZH), pancreatin (PCH), pepsin (PEH), and trypsin (TPH) to obtain hydrolysates and ultrafiltered fractions (<1, 1-3, 3-5 and 5-10 kDa) that possess antioxidant plus acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibitory activities. The hydrolysates exhibited varying degrees of radical scavenging and inhibition of linoleic acid peroxidation, as well as cholinesterase inhibition activities but the potency generally improved by >10% after UF separation into peptide fractions. ACH, FZH, and PEH exhibited significantly (p < .05) higher (20%-30% increases) radical scavenging activities than the other hydrolysates. The 1 and 3 kDa UF fractions of ACH, FZH, and PEH inhibited ~20%-30% AChE activity, while ACH, PCH, TPH, and PEH inhibited ~20%-40% BuChE activity. We conclude that the pea protein hydrolysates and their peptide fractions possess multifunctional properties with potential use against neurodegenerative disorders. PRACTICAL APPLICATIONS: Alzheimer's disease (AD) has multiple pathological pathways in addition to the loss of acetylcholine (ACh) catalyzed by acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE). The presence of severe oxidative stress triggered by lipid peroxidation and formation of free radicals is a common trait in AD patients. The concept of AChE and BuChE inhibition as an approach toward AD amelioration involves the use of compounds with a similar structure to ACh, the natural substrate. Peptides derived from food proteins consist of ester bonds with structural similarity to ACh and theoretically possess the ability to interact with AChE and BuChE. Results from the present study imply that pea protein-derived peptides are potential candidates for use as inhibitors of AChE and BuChE activities, with application in the prevention and management of AD.
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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) | 0.000 | 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 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".