Development and characterization of peptides with antidiabetic activities from oat protein
Bibliographic record
Abstract
Type 2 diabetes mellitus (T2DM) occurs when the cells in the body are unable to respond to the effect of insulin, resulting in a state of hyperglycemia that could involve other health complications. The prevalence of this disease generates a great concern worldwide and suggests a move towards prevention through diet and lifestyle modifications. For instance, oats consumption has been related to blood lipid and glucose regulation, mostly from its fiber and phenolic compounds. Recently, oat protein content started gaining importance due to its functional capacities and glucose regulatory effects; however, research is still limited. Exploring oat protein health benefits could leverage the Canadian oat production process to obtain value-added products since western provinces are known to be the major oat producers in the country. Therefore, this research aimed to generate antidiabetic peptides from oat protein to inhibit α-amylase, α-glucosidase, and dipeptidyl peptidase (DPP)-IV enzymes. In this study, oat protein hydrolysates were prepared by alcalase and flavourzyme treatment and then fractionated based on their different molecular weight and hydrophobicity. Enzyme inhibition assays in vitro indicated that the relatively hydrophobic fraction with a molecular weight of 1-5 kDa inhibited enzymes that regulate glucose digestion, absorption, and metabolism activities. Identification of oat peptides from the most effective sequence was made using LC-MS/MS. The analysis disclosed the presence of two 8 amino acid sequences from the most effective fractions, identified from 12S oat globulin (GDVVALPA and DVVALPAG) and new de novo sequences rich in amino acids like proline, leucine, valine, phenylalanine, and glutamine. The results suggest that proline plays a crucial inhibitory role and may favor hydrophobic interactions and hydrogen bonding at these enzymes' active site. Hydrophobic characteristics combined with the presence of amino acids like proline, valine, and leucine, especially the enclosed Leu-Pro sequence found in potent DPP-IV inhibitors, might have conferred their antidiabetic effect. α-Amylase, α-glucosidase, and DPP4 inhibitors are used as targets in the development of antidiabetic drugs. Thus, the ability to generate peptides with antidiabetic activities from oat represents a strategy to develop natural healthy products or functional foods for T2DM prevention and management.
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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".