The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Structural Requirements of Angiotensin I-Converting Enzyme Inhibitory Peptides: Quantitative Structure−Activity Relationship Study of Di- and Tripeptides
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.
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Cites
PLS-regression: a basic tool of chemometrics
Wold, S., Sjöström, M., & Eriksson, L. (2001) · Chemometrics and Intelligent Laboratory Systems · doi:10.1016/s0169-7439(01)00155-1 · Cited by 10,084
Spectrophotometric assay and properties of the angiotensin-converting enzyme of rabbit lung
Cushman, D. W., & Cheung, H. S. (1971) · Biochemical Pharmacology · doi:10.1016/0006-2952(71)90292-9 · Cited by 2,625
Cheung, H. S., Wang, F. L., Ondetti, M. A., Sabo, E. F., & Cushman, D. W. (1980) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(19)86187-2 · Cited by 745
Hypotensive Peptides from Milk Proteins
FitzGerald, R. J., Murray, B. A., & Walsh, D. J. (2004) · The Journal of Nutrition · doi:10.1093/jn/134.4.980s · Cited by 724
Sandberg, M., Eriksson, L., Jonsson, J., Sjöström, M., & Wold, S. (1998) · Journal of Medicinal Chemistry · doi:10.1021/jm9700575 · Cited by 678
Seppo, L., Jauhiainen, T., Poussa, T., & Korpela, R. (2003) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/77.2.326 · Cited by 666
Chemometric methods in molecular design
Waterbeemd, H. V. D. (1995) · Medical Entomology and Zoology · Cited by 561
Peptide quantitative structure-activity relationships, a multivariate approach
Hellberg, S., Sjoestroem, M., Skagerberg, B., & Wold, S. (1987) · Journal of Medicinal Chemistry · doi:10.1021/jm00390a003 · Cited by 544
Iroyukifujita, H., Eiichiyokoyama, K., & Yoshikawa, M. (2000) · Journal of Food Science · doi:10.1111/j.1365-2621.2000.tb16049.x · Cited by 543
A placebo-controlled study of the effect of sour milk on blood pressure in hypertensive subjects
Hata, Y., Yamamoto, M., Ohni, M., Nakajima, K., Nakamura, Y., & Takano, T. (1996) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/64.5.767 · Cited by 509
Research works printed but not linked: 32
- Wyvratt M. J, 1988, Clin. Physiol. Biochem., 6, 219
- Wimart M. C., 2000, Heart, 84, i14
- Skeggs L. T., 1956, J. Exp. Med., 103, 299
- Yang H. Y. T., 1970, Biochim. Biophys. Acta, 214, 376
- Nakamura Y., 1996, Biosci., Biotechnol., Biochem., 60, 489
- Nakamura Y., 1995, J. Dairy Sci., 78, 783
- Maruyama S., 1987, Agric. Biol. Chem., 51, 1586
- Yano S., 1996, Biosci., Biotechnol., Biochem., 60, 663
- Fujita H., 2000, J. Food Sci., 5, 569
- Fujita H., 1999, Immunopharmacology, 44, 127
- Miyoshi S., 1991, Agric. Biol. Chem., 55, 1318
- Yang Y., 2003, J. Agric. Food Chem., 51, 4902
- Kohama Y., 1991, Agric. Biol. Chem., 55, 2170
- Kohama Y., 1989, Biochem. Biophys. Res. Commun., 161, 460, 10.1016/0006-291X(89)92620-X · doi:10.1016/0006-291x(89)92620-x
- Matsui T., 2002, J. Nutr. Biochem., 13, 86, 10.1016/S0955-2863(01)00198-X · doi:10.1016/s0955-2863(01)00198-x
- Nomura A., 2002, Fish. Sci., 68, 956, 10.1046/j.1444-2906.2002.00518.x · doi:10.1046/j.1444-2906.2002.00518.x
- Mimura T., 1991, Octopeptide exhibiting antihypertensive activity. U.S. Patent 5,071,955
- Saito S., 1994, Biosci., Biotechnol., Biochem., 58, 1771
- Kohmura M., 1990, Agric. Biol. Chem., 54, 836
- Matsumura N., 1993, Biosci., Biotechnol., Biochem., 57, 1744
- Li C. H., 2002, J. Pept. Sci., 8, 274
- Cushman D. W., 1973, Experientia, 29, 1035, 10.1007/BF01930447 · doi:10.1007/bf01930447
- Cheung H. S., 1973, Biochim. Biophy. Acta, 293, 463
- Cheung H. S., 1980, J. Biol. Chem., 255, 407
- Siebert K. J, 2003, J. Agric. Food Chem., 51, 7797, 10.1021/jf0342775 · doi:10.1021/jf0342775
- User Guide, 2002, Sweden
- Mathews D. M., 1976, Gastroenterology, 71, 161
- Buydens L. M. C., 1999, Chemom. Intell. Lab. Syst., 49, 133
- Wold S., 2001, Chemom. Intell. Lab. Syst., 58, 130
- Andersson P. M., 1998, Chemom. Intell. Lab. Syst., 42, 50
- Wu J. P., 2002, Food Res. Int., 35, 375
- Yust M. M., 2003, Food Chem., 81, 369
Cited by
Bioactive peptides in cereals and legumes: agronomical, biochemical and clinical aspects.
Malaguti, M., Dinelli, G., Leoncini, E., Bregola, V., Bosi, S., Cicero, A., & Hrelia, S. (2014) · International Journal of Molecular Sciences · doi:10.3390/ijms151121120 · Cited by 180
Girgih, A. T., Udenigwe, C. C., Li, H., Adebiyi, A. P., & Aluko, R. E. (2011) · Journal of the American Oil Chemists' Society · doi:10.1007/s11746-011-1841-9 · Cited by 174
Self-citationNew developments and applications of bacteriocins and peptides in foods
Mills, S., Stanton, C., Hill, C., & Ross, R. P. (2011) · Annual Review of Food Science and Technology · doi:10.1146/annurev-food-022510-133721 · Cited by 153
De Leo, F., Panarese, S., Gallerani, R., & Ceci, L. (2009) · Current Pharmaceutical Design · doi:10.2174/138161209789271834 · Cited by 149
Ricci-Cabello, I., Olalla Herrera, M., & Artacho, R. (2012) · Nutrition Reviews · doi:10.1111/j.1753-4887.2011.00448.x · Cited by 142
Metadata
- Authors
- Wu, J., Aluko, R. E., & Nakai, S.
- Venue
- Journal of Agricultural and Food Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2006-01-04
- Volume
- 54
- Issue
- 3
- Pages
- 732-738
- ISSN
- 0021-8561 (ISSN-L)
- 1520-5118
- OpenAlex
- W2049066334
- Cited by
- 561
- References
- 40
- FWCI
- 3.68
- Type
- journal article
- Language
- en
- Open access
- closed
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