Literature DB >> 16448176

Structural requirements of Angiotensin I-converting enzyme inhibitory peptides: quantitative structure-activity relationship study of di- and tripeptides.

Jianping Wu1, Rotimi E Aluko, Shuryo Nakai.   

Abstract

A database consisting of 168 dipeptides and 140 tripeptides was constructed from published literature to study the quantitative structure--activity relationships of angiotensin I-converting enzyme (ACE) inhibitory peptides. Two models were computed using partial least squares regression based on the three z-scores of 20 coded amino acids and further validated by cross-validation and permutation tests. The two-component model could explain 73.2% of the Y-variance (inhibitor concentration that reduced enzyme activity by 50%, IC50) with the predictive ability of 71.1% for dipeptides, while the single-component model could explain 47.1% of the Y-variance with the predictive ability of 43.3% for tripeptides. Amino acid residues with bulky side chains as well as hydrophobic side chains were preferred for dipeptides. For tripeptides, the most favorable residues for the carboxyl terminus were aromatic amino acids, while positively charged amino acids were preferred for the middle position, and hydrophobic amino acids were preferred for the amino terminus. According to the models, the IC50 values of seven new peptides with matchable primary sequences within pea protein, bovine milk protein, and soybean were predicted. The predicted peptides were synthesized, and their IC50 values were validated through laboratory determination of inhibition of ACE activity.

Entities:  

Mesh:

Substances:

Year:  2006        PMID: 16448176     DOI: 10.1021/jf051263l

Source DB:  PubMed          Journal:  J Agric Food Chem        ISSN: 0021-8561            Impact factor:   5.279


  57 in total

1.  QSAR study on angiotensin-converting enzyme inhibitor oligopeptides based on a novel set of sequence information descriptors.

Authors:  Xiaoyu Wang; Juan Wang; Yong Lin; Yuan Ding; Yuanqiang Wang; Xiaoming Cheng; Zhihua Lin
Journal:  J Mol Model       Date:  2010-10-13       Impact factor: 1.810

2.  Sustainable use of silver warehou (Seriollela punctata): effects of storage, processing conditions and simulated gastrointestinal digestion on selected in-vitro bioactivities.

Authors:  V Manikkam; M L Mathai; W A Street; O N Donkor; T Vasiljevic
Journal:  J Food Sci Technol       Date:  2016-09-13       Impact factor: 2.701

Review 3.  Current Perspectives on Antihypertensive Probiotics.

Authors:  Eric Banan-Mwine Daliri; Byong H Lee; Deog H Oh
Journal:  Probiotics Antimicrob Proteins       Date:  2017-06       Impact factor: 4.609

4.  Casein fermentate of Lactobacillus animalis DPC6134 contains a range of novel propeptide angiotensin-converting enzyme inhibitors.

Authors:  M Hayes; C Stanton; H Slattery; O O'Sullivan; C Hill; G F Fitzgerald; R P Ross
Journal:  Appl Environ Microbiol       Date:  2007-05-04       Impact factor: 4.792

5.  Identification of ACE pharmacophore in the phosphonopeptide metabolite K-26.

Authors:  Ioanna Ntai; Brian O Bachmann
Journal:  Bioorg Med Chem Lett       Date:  2007-12-05       Impact factor: 2.823

6.  Characterization of ACE Inhibitory Peptides Prepared from Pyropia pseudolinearis Protein.

Authors:  Yuya Kumagai; Keigo Toji; Satoshi Katsukura; Rie Morikawa; Toshiki Uji; Hajime Yasui; Takeshi Shimizu; Hideki Kishimura
Journal:  Mar Drugs       Date:  2021-04-01       Impact factor: 5.118

7.  Chemometric analysis of the amino acid requirements of antioxidant food protein hydrolysates.

Authors:  Chibuike C Udenigwe; Rotimi E Aluko
Journal:  Int J Mol Sci       Date:  2011-05-13       Impact factor: 5.923

8.  Modeling the QSAR of ACE-Inhibitory Peptides with ANN and Its Applied Illustration.

Authors:  Ronghai He; Haile Ma; Weirui Zhao; Wenjuan Qu; Jiewen Zhao; Lin Luo; Wenxue Zhu
Journal:  Int J Pept       Date:  2011-06-09

9.  Antihypertensive effect of long-term oral administration of jellyfish (Rhopilema esculentum) collagen peptides on renovascular hypertension.

Authors:  Yongliang Zhuang; Liping Sun; Yufeng Zhang; Gaoxiang Liu
Journal:  Mar Drugs       Date:  2012-02-15       Impact factor: 6.085

10.  Artificial neural network models for prediction of intestinal permeability of oligopeptides.

Authors:  Eunkyoung Jung; Junhyoung Kim; Minkyoung Kim; Dong Hyun Jung; Hokyoung Rhee; Jae-Min Shin; Kihang Choi; Sang-Kee Kang; Min-Kook Kim; Cheol-Heui Yun; Yun-Jaie Choi; Seung-Hoon Choi
Journal:  BMC Bioinformatics       Date:  2007-07-11       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.