Evidence map›Paper›PMID 36766167›Full record

ReviewFoods (Basel, Switzerland)2023

In Vitro Assessment Methods for Antidiabetic Peptides from Legumes: A Review.

Alia Rahmi, Jayashree Arcot

Abstract readReview
In one paragraph

Review in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Influence ofFoods (Basel, Switzerland) · 2024
    Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Alia RahmiFood and Health Group, School of Chemical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.ORCID 0000-0002-4211-4191
Jayashree ArcotFood and Health Group, School of Chemical Engineering, UNSW Sydney, Sydney, NSW 2052, Australia.ORCID 0000-0002-4254-7288

Funding

Indonesian Endowment Fund for Education (LPDP) Scholarships 2019-2023
6 · The paper itself

Abstract

Almost 65% of the human protein supply in the world originates from plants, with legumes being one of the highest contributors, comprising between 20 and 40% of the protein supply. Bioactive peptides from various food sources including legumes have been reported to show efficacy in modulating starch digestion and glucose absorption. This paper will provide a comprehensive review on recent in vitro studies that have been performed on leguminous antidiabetic peptides, focusing on the α-amylase inhibitor, α-glucosidase inhibitor, and dipeptidyl peptidase-IV (DPP-IV) inhibitor. Variations in legume cultivars and methods affect the release of peptides. Different methods have been used, such as in sample preparation, including fermentation (t, T), germination (t), and pre-cooking; in protein extraction, alkaline extraction, isoelectric precipitation, phosphate buffer extraction, and water extraction; in protein hydrolysis enzyme types and combination, enzyme substrate ratio, pH, and time; and in enzyme inhibitory assays, positive control type and concentration, inhibitor or peptide concentration, and the unit of inhibitory activity. The categorization of the relative scale of inhibitory activities among legume samples becomes difficult because of these method differences. Peptide sequences in samples were identified by means of HPLC/MS. Software and online tools were used in bioactivity prediction and computational modelling. The identification of the types and locations of chemical interactions between the inhibitor peptides and enzymes and the type of enzyme inhibition were achieved through computational modelling and enzyme kinetic studies.

Indexed as

diabetes managementglucose absorption inhibitorlegume peptidestarch digestion inhibitor

Identifiers

PMID36766167
PMCPMC9914741

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.