Quantitative Structure-Activity Relationship Analysis of Angiotensin-Converting Enzyme Inhibitory Pentapeptides Based on Amino Acid Descriptors

被引：0
|
作者：
Guo X. [1 ,2 ]
Li Y. [2 ]
Ma J. [1 ,2 ]
Zhang Y. [1 ,2 ]
Li H. [1 ,2 ]
Yang J. [1 ,2 ]
Fan P. [3 ]
Gao D. [1 ,2 ]
机构：
[1] China-Malaysia National Joint Laboratory, Biomedical Research Center, Northwest Minzu University, Lanzhou
[2] Life Science and Engineering College, Northwest Minzu University, Lanzhou
[3] College of Chemistry, Sichuan University, Chengdu
来源：
Shipin Kexue/Food Science | / 45卷 / 13期
关键词：
amino acid structure descriptors; angiotensin-converting enzyme; partial least squares; peptides; quantitative structure-activity relationship;
D O I：
10.7506/spkx1002-6630-20230613-106
中图分类号：
学科分类号：
摘要：
This study aimed to investigate the structure-function relationship of angiotensin-converting enzyme (ACE) inhibitory peptides and to elucidate the action mechanism of food-derived ACE inhibitory peptides. Based on the amino acid sequences of recently reported ACE inhibitory pentapeptides and their half-maximal inhibitory concentration (IC50) values, a library of ACE inhibitory pentapeptides was generated and the structures of the ACE inhibitory pentapeptides were characterized using three amino acid descriptors, Z-scales, VHSE and SVHEHS. A partial least square (PLS) model for describing the quantitative structure-activity relationship (QSAR) of the ACE inhibitory peptides with the hydrophobic properties, steric properties, and electrical properties of amino acids as the independent variables and the lg IC50 of the ACE inhibitory pentapeptides as the dependent variable was established using Matlab software. The results showed that the R2 and Q2 of the QSAR model based on Z-scales descriptor were 0.641 1 and 0.536 9, respectively, and Gln-Arg-Pro-Asn-Met showed higher ACE inhibitory activity as predicted by this model. The predicted and measured IC50 were 0.051 7 and (0.040 0 ± 0.008 3) μmol/L, respectively, and the error between them was 0.011 7 μmol/L. The R2 and Q2 of the QSAR model based on VHSE descriptor were 0.763 6 and 0.508 1, respectively, and Leu-Arg-Ala-Phe-Gln exhibited better ACE inhibitory activity as predicted by this model. The predicted and measured IC50 were 0.043 8 and (0.027 3 ± 0.005 3) μmol/L, respectively, and the error between them was 0.016 5 μmol/L. The R2 and Q2 of the QSAR model based on SVHEHS descriptor were 0.840 5 and 0.400 5, respectively, and Leu-Arg-Ala-Phe-Gln displayed better ACE inhibitory activity as predicted by this model. The predicted and measured IC50 were 0.005 5 and (0.031 2 ± 0.004 2) μmol/L, and the error between them was 0.025 7 μmol/L. Among the three QSAR models, the one based on SVHEHS descriptor had the strongest fitting capability but weak predictive capacity, while the models based on Z-scales and VHSE descriptors could allow good QSAR analysis of the pentapeptides. Our modeling analysis showed that the activity of the ACE inhibitory peptides was negatively correlated with the hydrophobic characteristics of amino acids and positively correlated with the steric characteristics of amino acids. Molecular docking of three ACE inhibitory peptides to ACE protein (2X8J) showed that all the ACE inhibitory peptides could bind to ACE protein. This study provides a new tool for developing ACE inhibitory peptides and a theoretical basis for the development and application of food-derived ACE inhibitory peptides. © 2024 Chinese Chamber of Commerce. All rights reserved.
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页码：38 / 48
页数：10
相关论文
共 20 条
  • [1] GU D F, REYNOLDS K, WU X G, Et al., Prevalence, awareness, treatment, and control of hypertension in China, Hypertension, 40, 6, pp. 920-927, (2002)
  • [2] WANG J P, HU J N, CUI J Z, Et al., Purification and identification of a ACE inhibitory peptide from oyster proteins hydrolysate and the antihypertensive effect of hydrolysate in spontaneously hypertensive rats, Food Chemistry, 111, 2, pp. 302-308, (2008)
  • [3] LI G H, LE G W, SHI Y H, Et al., Angiotensin I-converting enzyme inhibitory peptides derived from food proteins and their physiological and pharmacological effects, Nutrition Research, 24, 7, pp. 469-486, (2004)
  • [4] PUJIASTUTI D Y, AMIN M N G, ALAMSJAH M A, Et al., Marine organisms as potential sources of bioactive peptides that inhibit the activity of angiotensin I-converting enzyme: a review, Molecules, 24, 14, (2019)
  • [5] KO S C, JANG J Y, YE B R, Et al., Purification and molecular docking study of angiotensin I-converting enzyme (ACE) inhibitory peptides from hydrolysates of marine sponge Stylotella aurantium, Process Biochemistry, 54, 1, pp. 180-187, (2017)
  • [6] ZHANG J, YANG L B, TIAN Z Q, Et al., Large-scale screening of antifungal peptides based on quantitative structure-activity relationship, ACS Medicinal Chemistry Letters, 13, 1, pp. 99-104, (2021)
  • [7] KIDERA A, KONISHI Y, OKA M, Et al., Statistical analysis of the physical properties of the 20 naturally occurring amino acids, Journal of Protein Chemistry, 4, 1, pp. 23-55, (1985)
  • [8] JONSSON J, ERIKSSON L, HELLBERG S, Et al., Multivariate parametrization of 55 coded and non-coded amino acids, Quantitative Structure-Activity Relationships, 8, 3, pp. 204-209, (1989)
  • [9] COCCHI M, JOHANSSON E., Amino acids characterization by GRID and multivariate data analysis, Quantitative Structure-Activity Relationships, 12, 1, pp. 1-8, (1993)
  • [10] 28, 1, (2012)
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