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Record W3215676416 · doi:10.7939/r3-s4xc-7a66

Development and characterization of peptides with antidiabetic activities from oat protein

2021· article· en· W3215676416 on OpenAlexaboutno aff
L Fuentes

Bibliographic record

VenueUniversity of Alberta Library · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsnot available
Fundersnot available
KeywordsChemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.277

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.150
Teacher spread0.146 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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