A computer-aided strategy for structure-function relation study of food proteins using unsupervised data mining

International Journal of Food Properties

Volumn 6, Issue 1, 2003, Pages 25-47

  Nakai, Shuryo ^a   Ogawa, Masahiro ^a   Nakamura, Soichiro ^b   Dou, Jingli ^a   Funane, Kazumi ^c  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b SHIMANE UNIVERSITY   (Japan)

^c NATIONAL FOOD RESEARCH INSTITUTE   (Japan)

Author keywords

Data mining; Neural networks; Principal component similarity; Random centroid optimization; Site directed mutagenesis; Unsupervised learning

Indexed keywords

AMINO ACIDS; DATA MINING; NEURAL NETWORKS; OPTIMIZATION; PRINCIPAL COMPONENT ANALYSIS; PROTEINS;

RANDOM-CENTROID OPTIMIZATION (RCO);

FOOD PRODUCTS;

EID: 0037370771     PISSN: 10942912     EISSN: None     Source Type: Journal    
DOI: 10.1081/JFP-120016622     Document Type: Article

References (30)

1. Bishop, C.M. Neural Networks for Pattern Recognition; Clarendon Press: Oxford, UK, 1995; 17 and 385-387.
2. Yuan, B.; Wang, X.Z.; Morris, T. Software analyzer design using data mining technology for toxicity prediction of aqueous effluents. Waste Manag. (Oxford) 2000, 20, 677-686.
3. Tropsha, A.; Cho, S.J.; Zheng, W. "New tricks for an old dog": development and application of novel QSAR methods for rational design of combinatorial chemical libraries and database mining. In Rational Drug Design; Parrill, A.L., Reddy, M.R., Eds.; American Chemical Society: Washington, DC. 1999; 198-211.
4. Heckerman, D. Bayesian networks for data mining. Data Min. Knowl. Disc. 1997, 1, 79-119.
5. Burden, F.R.; Winkler, D.A. A QSAR model for the acute toxicity of substituted benzenes to Tetrahymena pyriformis using Bayesian-regulated neural networks. Chem. Res. Toxicol. 2000, 13, 436-440.
6. Statsoft, Statistica Neural Networks & Addendum for Version 4; Starsoft: Tulsa OK, 1999; www.statsoft.com.
7. Vodovotz, Y.; Arteaga, G.E.; Nakai, S. Principal component similarity analysis for classification and its application to GC data of mango. Food Res. Int. 1993, 26, 355-363.
8. Wang, Z.H.; Dou, J.; Macura, D.; Durance, T.D.; Nakai, S. Solid phase extraction for GC analysis of benny flavor in soymilk. Food Res. Int. 1998, 30, 503-511.
9. Kellner, R.; Mermet, J.M.; Otto, M.; Widner, H.M. Analytical Chemistry; Wiley-VCH: Weinheim, Germany, 1998; 775-808.
10. Guo, Q.; Wu, W.; Questier, F.; Massart, D.L.; Boucon, C.; de Jong, S. Sequential projection pursuit using genetic algorithms for data mining of analytical data. Anal. Chem. 2000, 72, 2846-2855.
11. Nakai, S.; Amantea, G.; Nakai, H.; Ogawa, M.; Kanagawa, S. Definition of outliers using unsupervised principal component similarity analysis for sensory evaluation of foods. Int. J. Food Properties 2002, 5, 289-306.
12. Nakai, S.; Dou, J.; Richards, J.F. New multivariate strategy for panel evaluation using principal component similarity. Int. J. Food Properties 2000, 3, 149-164.
13. Buydens, L.M.C.; Reijmers, T.H.; Beckers, M.L.M.; Wehrens, R. Molecular data-mining: A challenge for chemometics. Chemom. Intell. Lab. Syst. 1999, 49, 121-133.
14. Krzanewski, W.J. Principles of Multivariate Analysis: A User's Perspective; Clarendon Press: Oxford, UK, 1988.
15. Nakai, S.; Dou, J.; Lo, K.V.; Scaman, C.H. Optimization of site-directed mutagenesis. 1. A new random-centroid optimization program for Windows useful in research and development. J. Agric. Food Chem. 1998a, 46, 1642-1654.
16. Nakai, S.; Nakamura, S.; Scaman, C.H. Ibid, 2. Application of random-centroid optimization to one-site mutation of B. sterothermophilus neutral protease for improving thermostability. J. Agric. Food Chem. 1998b, 46, 1655-1661. The RCO and RCG programs both can be downloaded from ftp://ftp.agsci.ubc.ca/foodsci/and run on Windows.
17. Nakai, S.; Saeki, H.; Nakamura, K. A graphical solution of multimodal optimization to improve food properties. Int. J. Food Properties 1999, 2, 277-294.
18. Rekdal, Ø.; Andersen, J.; Vorland, L.H.; Sevendsen, J.S. Construction and synthesis of lactoferrin derivatives with enhanced antibacterial activity. J. Peptide Sci. 1999, 5, 32-45.
19. Falla, T.J.; Hancock, R.E.W. Improved activity of a synthetic indolicidin analog. Antimicrog. Agents Chemoth. 1997, 41, 771-775.
20. Kang, J.H.; Lee, M.K.; Kim, K.L.; Hahn, K.-K. Structure-biological activity relationships of 11-residue highly basic peptide segment of bovin lactoferrin. Int. J. Peptide Protein Res. 1996, 48, 357-363.
21. Nakamura, S.; Tanaka, T.; Yada, R.; Nakai, S. Improving the thermostability of B. stearothermophilus neutral protease by introducing proline into the active site helix. Protein Eng. 1997, 10, 1283-1269.
22. Ogawa, M.; Nakamura, S.; Scaman, C.H.; Jing, J.; Kitts, D.D.; Dou, J.; Nakai, S. Enhancement of proteinase inhibitory activity of recombinant human cystatin C using random-centroid optimization. Biochim. Biophys. Acta 2002, 1599, 115-124.
23. Björk, I.; Brieditis, I.; Abrahamson, M. Probing the functional role of the N-terminal region of cystatins by equilibrium and kinetic studies of the binding of Gly-11 variants of recombinant human cystatin C to target proteinases. Biochem. J. 1995, 306, 513-518.
24. Takahashi, Y.; Ueno, A.; Mihara, H. Design of a peptide undergoing α-β structure transition and amyloid fibrilogenesis by the introduction of a hydrophobic defect. Chem. Eur. J. 1998, 4, 2475-2483.
25. Hall, A.; Håkannson, K.; Mason, R.W.; Grubb, A.; Abramson, M. Structural basis for the biological specificity of cystatin C. J. Biol. Chem. 1995, 270, 5115-5121.
26. Lou, W.; Nakai, S. Artificial neural network-based predictive model for bacterial growth in a simulated medium of modified atmosphere packed cooked meat products. J. Agric. Food Chem. 2001a, 49, 1799-1804.
27. Lou, W.; Nakai, S. Application of artificial neural networks for predicting thermal inactivation of bacteria. A combined effect of temperature, pH and water activity. Food Res. Int. 2001b, 34, 573-579.
28. Arteaga, G.E.; Nakai, S. Prediction of protein functionality using artificial neural networks: Foaming and emulsifying properties. J. Food Sci. 1993, 58, 1152-1156.
29. Kramer, M.A. Nonlinear principal component analysis using autoassociative neural networks. AIChe J. 1991, 37, 233-243.
30. Gromiha, M.M.; Ponnuswamy, P.K. Relationship between amino acid properties and protein compressibility. J. Theor. Biol. 1993, 165, 87-100.