Literature DB >> 31930566

Quantitative analysis of the relationship between structure and antioxidant activity of tripeptides.

Shinya Uno1, Daisuke Kodama1, Hiroko Yukawa1, Hiroyuki Shidara1, Miki Akamatsu2.   

Abstract

Peptides from enzymatic hydrolysates of food proteins exhibit significant antioxidant activity. Several studies have attempted to determine the factors contributing to the antioxidant activity of peptides; however, the physicochemical properties and factors essential for the antioxidant activity of peptides are still unclear. In this study, in order to clarify the factors important for peptide antioxidant activity based on the properties of component amino acids, 55 tripeptides were synthesized from 20 natural amino acids and their antioxidant activity was measured using the Trolox equivalent antioxidant capacity (TEAC) assay system. The tripeptides were divided into two data sets: a training set comprising 50 compounds and a validated set comprising five compounds. The structure-activity relationship of the training set was then analyzed using classical quantitative structure-activity relationship (QSAR) analysis. The study findings demonstrate that the presence of a cysteine residue at any position, an aromatic amino acid at the C-terminus, higher hydrophobicity of the N-terminal residue, and smaller HOMO-LUMO energy gap of the middle residue can significantly enhance the antioxidant activity. The activities of the five validated compounds were predicted using the constructed QSAR model, and a good correlation between measured and predicted activities was observed. The information obtained from the QSAR model could be useful for effective production of antioxidant peptides from food proteins such as egg white proteins.
© 2020 European Peptide Society and John Wiley & Sons, Ltd.

Entities:  

Keywords:  ABTS assay; QSAR; TEAC; antioxidant peptide; cysteine

Year:  2020        PMID: 31930566     DOI: 10.1002/psc.3238

Source DB:  PubMed          Journal:  J Pept Sci        ISSN: 1075-2617            Impact factor:   1.905


  4 in total

1.  Comprehensive Evaluation and Comparison of Machine Learning Methods in QSAR Modeling of Antioxidant Tripeptides.

Authors:  Zhenjiao Du; Donghai Wang; Yonghui Li
Journal:  ACS Omega       Date:  2022-07-15

2.  Identification of Antioxidant Peptides Derived from Tilapia (Oreochromis niloticus) Skin and Their Mechanism of Action by Molecular Docking.

Authors:  Yueyun Ma; Dandan Zhang; Mengqi Liu; Yingrou Li; Rui Lv; Xiang Li; Qiukuan Wang; Dandan Ren; Long Wu; Hui Zhou
Journal:  Foods       Date:  2022-08-25

3.  Machine learning screening of bile acid-binding peptides in a peptide database derived from food proteins.

Authors:  Kento Imai; Kazunori Shimizu; Hiroyuki Honda
Journal:  Sci Rep       Date:  2021-08-09       Impact factor: 4.379

4.  A Novel Insight into Screening for Antioxidant Peptides from Hazelnut Protein: Based on the Properties of Amino Acid Residues.

Authors:  Chenshan Shi; Miaomiao Liu; Hongfei Zhao; Zhaolin Lv; Lisong Liang; Bolin Zhang
Journal:  Antioxidants (Basel)       Date:  2022-01-06
  4 in total

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