Predicting protein structural classes with pseudo amino acid composition: An approach using geometric moments of cellular automaton image

Journal of Theoretical Biology

Volumn 254, Issue 3, 2008, Pages 691-696

  Xiao, Xuan ^a   Wang, Pu ^a   Chou, Kuo Chen ^b  

^a JINGDEZHEN CERAMIC INSTITUTE   (China)

^b GORDON LIFE SCIENCE INSTITUTE   (United States)

Author keywords

Cellular automaton; Chou's invariant theorem; Covariant discriminant algorithm; Geometric invariant moment; Image texture; Pseudo amino acid composition; Space time evolution

Indexed keywords

AMINO ACID;

ALGORITHM; AMINO ACID; CELLULAR AUTOMATON; CHEMICAL COMPOSITION; COVARIANCE ANALYSIS; DISCRIMINANT ANALYSIS; NUMERICAL MODEL; PROTEIN;

AMINO ACID COMPOSITION; AMINO ACID SEQUENCE; ARTICLE; PRIORITY JOURNAL; PROTEIN FUNCTION; PROTEIN STRUCTURE;

ALGORITHMS; AMINO ACID SEQUENCE; DATABASES, PROTEIN; IMAGE PROCESSING, COMPUTER-ASSISTED; PROTEIN FOLDING; PROTEINS;

EID: 51349105695     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2008.06.016     Document Type: Article

References (83)

1. Andreeva A., Howorth D., Brenner S.E., Hubbard T.J., Chothia C., and Murzin A.G. SCOP database in 2004: refinements integrate structure and sequence family data. Nucleic Acids Res. 32 (2004) D226-D229
2. Cao Y., Liu S., Zhang L., Qin J., Wang J., and Tang K. Prediction of protein structural class with rough sets. BMC Bioinformatics 7 (2006) 20
3. Chandonia J.M., and Karplus M. Neural networks for secondary structure and structural class prediction. Protein Sci. 4 (1995) 275-285
4. Chen Y.L., and Li Q.Z. Prediction of apoptosis protein subcellular location using improved hybrid approach and pseudo amino acid composition. J. Theor. Biol. 248 (2007) 377-381
5. Chen Y.L., and Li Q.Z. Prediction of the subcellular location of apoptosis proteins. J. Theor. Biol. 245 (2007) 775-783
6. Chen C., Zhou X., Tian Y., Zou X., and Cai P. Predicting protein structural class with pseudo-amino acid composition and support vector machine fusion network. Anal. Biochem. 357 (2006) 116-121
7. Chen C., Tian Y.X., Zou X.Y., Cai P.X., and Mo J.Y. Using pseudo-amino acid composition and support vector machine to predict protein structural class. J. Theor. Biol. 243 (2006) 444-448
8. Chen K., Kurgan L.A., and Ruan J. Prediction of protein structural class using novel evolutionary collocation-based sequence representation. J. Comput. Chem. 29 (2008) 1596-1604
9. Chen K., Kurgan M., and Kurgan L. Sequence based prediction of relative solvent accessibility using two-stage support vector regression with confidence values. J. Biomed. Sci. Eng. 1 (2008) 1-9
10. Chen W.J., Huang P.T., Cheng Y.C., and Liao T.H. Putative secondary active site of bovine pancreatic deoxyribonuclease I. Protein Pept. Lett. 15 (2008) 640-646
11. Chou P.Y. Prediction of protein structural classes from amino acid composition. In: Fasman G.D. (Ed). Prediction of Protein Structure and the Principles of Protein Conformation (1989), Plenum Press, New York 549-586
12. Chou K.C. A vectorized sequence-coupling model for predicting HIV protease cleavage sites in proteins. J. Biol. Chem. 268 (1993) 16938-16948
13. Chou K.C. A novel approach to predicting protein structural classes in a (20-1)-D amino acid composition space. Proteins: Struct., Funct., Genet. 21 (1995) 319-344
14. Chou K.C. A key driving force in determination of protein structural classes. Biochem. Biophys. Res. Commun. 264 (1999) 216-224
15. Chou K.C. Prediction of protein subcellular locations by incorporating quasi-sequence-order effect. Biochem. Biophys. Res. Commun. 278 (2000) 477-483
16. Chou, K.C., 2001. Prediction of protein cellular attributes using pseudo amino acid composition. Proteins: Struct., Funct., Genet. (Erratum: ibid., 2001, vol. 44, 60) 43, 246-255.
17. Chou K.C. Using amphiphilic pseudo amino acid composition to predict enzyme subfamily classes. Bioinformatics 21 (2005) 10-19
18. Chou K.C. Review: progress in protein structural class prediction and its impact to bioinformatics and proteomics. Curr. Protein Pept. Sci. 6 (2005) 423-436
19. Chou, K.C., Cai, Y.D., 2004. Predicting protein structural class by functional domain composition. Biochem. Biophys. Res. Commun. (Corrigendum: ibid., 2005, vol. 329, 1362) 321, 1007-1009.
20. Chou K.C., and Elrod D.W. Protein subcellular location prediction. Protein Eng. 12 (1999) 107-118
21. Chou K.C., and Maggiora G.M. Domain structural class prediction. Protein Eng. 11 (1998) 523-538
22. Chou K.C., and Shen H.B. Review: recent progresses in protein subcellular location prediction. Anal. Biochem. 370 (2007) 1-16
23. Chou K.C., and Shen H.B. Cell-PLoc: a package of web-servers for predicting subcellular localization of proteins in various organisms. Nat. Protoc. 3 (2008) 153-162
24. Chou K.C., and Zhang C.T. Predicting protein folding types by distance functions that make allowances for amino acid interactions. J. Biol. Chem. 269 (1994) 22014-22020
25. Chou K.C., and Zhang C.T. Review: prediction of protein structural classes. Crit. Rev. Biochem. Mol. Biol. 30 (1995) 275-349
26. Deleage G., and Roux B. An algorithm for protein secondary structure prediction based on class prediction. Protein Eng. 1 (1987) 289-294
27. Ding Y.S., Zhang T.L., and Chou K.C. Prediction of protein structure classes with pseudo amino acid composition and fuzzy support vector machine network. Protein Pept. Lett. 14 (2007) 811-815
28. Du P., and Li Y. Prediction of protein submitochondria locations by hybridizing pseudo-amino acid composition with various physicochemical features of segmented sequence. BMC Bioinformatics 7 (2006) 518
29. Du Q.S., Wei D.Q., and Chou K.C. Correlation of amino acids in proteins. Peptides 24 (2003) 1863-1869
30. Fang Y., Guo Y., Feng Y., and Li M. Predicting DNA-binding proteins: approached from Chou's pseudo amino acid composition and other specific sequence features. Amino Acids 34 (2008) 103-109
31. Gonzalez-Diaz H., Vilar S., Santana L., and Uriarte E. Medicinal chemistry and bioinformatics-current trends in drugs discovery with networks topological indices. Curr. Top. Med. Chem. 10 (2007) 1015-1029
32. González-Díaz H., González-Díaz Y., Santana L., Ubeira F.M., and Uriarte E. Proteomics, networks, and connectivity indices. Proteomics 8 (2008) 750-778
33. Guo Y.Z., Li M., Lu M., Wen Z., Wang K., Li G., and Wu J. Classifying G protein-coupled receptors and nuclear receptors based on protein power spectrum from fast Fourier transform. Amino Acids 30 (2006) 397-402
34. Hu M.K. Visual pattern recognition by moments invariants. IRE Trans. Inf. Theory 8 (1962) 179-187
35. Jahandideh S., Abdolmaleki P., Jahandideh M., and Asadabadi E.B. Novel two-stage hybrid neural discriminant model for predicting proteins structural classes. Biophys. Chem. 128 (2007) 87-93
36. Jiang X., Wei R., Zhang T.L., and Gu Q. Using the concept of Chou's pseudo amino acid composition to predict apoptosis proteins subcellular location: an approach by approximate entropy. Protein Pept. Lett. 15 (2008) 392-396
37. Jin Y., Niu B., Feng K.Y., Lu W.C., Cai Y.D., and Li G.Z. Predicting subcellular localization with AdaBoost learner. Protein Pept. Lett. 15 (2008) 286-289
38. Kedarisetti K.D., Kurgan L.A., and Dick S. Classifier ensembles for protein structural class prediction with varying homology. Biochem. Biophys. Res. Commun. 348 (2006) 981-988
39. Klein P. Prediction of protein structural class by discriminant analysis. Biochim. Biophys. Acta 874 (1986) 205-215
40. Klein P., and Delisi C. Prediction of protein structural class from amino acid sequence. Biopolymers 25 (1986) 1659-1672
41. Kneller D.G., Cohen F.E., and Langridge R. Improvements in protein secondary structure prediction by an enhanced neural network. J. Mol. Biol. 214 (1990) 171-182
42. Kurgan L., and Homaeian L. Prediction of structural classes for protein sequences and domains-impact of prediction algorithms, sequence representation and homology, and test procedures on accuracy. Pattern Recognit. Lett. 39 (2006) 2323-2343
43. Kurgan L.A., Stach W., and Ruan J. Novel scales based on hydrophobicity indices for secondary protein structure. J. Theor. Biol. 248 (2007) 354-366
44. Kurgan, L.A., Zhang, T., Zhang, H., Shen, S., Ruan, J., 2008. Secondary structure-based assignment of the protein structural classes. Amino Acids. doi:18427716.
45. Levitt M., and Chothia C. Structural patterns in globular proteins. Nature 261 (1976) 552-557
46. Li F.M., and Li Q.Z. Predicting protein subcellular location using Chou's pseudo amino acid composition and improved hybrid approach. Protein Pept. Lett. 15 (2008) 612-616
47. Lin H. The modified Mahalanobis discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition. J. Theor. Biol. 252 (2008) 350-356
48. Lin H., and Li Q.Z. Predicting conotoxin superfamily and family by using pseudo amino acid composition and modified Mahalanobis discriminant. Biochem. Biophys. Res. Commun. 354 (2007) 548-551
49. Lin H., and Li Q.Z. Using pseudo amino acid composition to predict protein structural class: approached by incorporating 400 dipeptide components. J. Comput. Chem. 28 (2007) 1463-1466
50. Lin H., Ding H., Feng-Biao Guo F.B., Zhang A.Y., and Huang J. Predicting subcellular localization of mycobacterial proteins by using Chou's pseudo amino acid composition. Protein Pept. Lett. 15 (2008) 739-744
51. Liu W., and Chou K.C. Prediction of protein structural classes by modified Mahalanobis discriminant algorithm. J. Protein Chem. 17 (1998) 209-217
52. Luo R.Y., Feng Z.P., and Liu J.K. Prediction of protein structural class by amino acid and polypeptide composition. Eur. J. Biochem. 269 (2002) 4219-4225
53. Mahalanobis P.C. On the generalized distance in statistics. Proc. Natl. Inst. Sci. India 2 (1936) 49-55
54. Mao B., Chou K.C., and Zhang C.T. Protein folding classes: a geometric interpretation of the amino acid composition of globular proteins. Protein Eng. 7 (1994) 319-330
55. Metfessel B.A., Saurugger P.N., Connelly D.P., and Rich S.T. Cross-validation of protein structural class prediction using statistical clustering and neural networks. Protein Sci. 2 (1993) 1171-1182
56. Mondal S., Bhavna R., Mohan Babu R., and Ramakumar S. Pseudo amino acid composition and multi-class support vector machines approach for conotoxin superfamily classification. J. Theor. Biol. 243 (2006) 252-260
57. Mundra P., Kumar M., Kumar K.K., Jayaraman V.K., and Kulkarni B.D. Using pseudo amino acid composition to predict protein subnuclear localization: approached with PSSM. Pattern Recognit. Lett. 28 (2007) 1610-1615
58. Nakashima H., Nishikawa K., and Ooi T. The folding type of a protein is relevant to the amino acid composition. J. Biochem. 99 (1986) 152-162
59. Nanni L., and Lumini A. Genetic programming for creating Chou's pseudo amino acid based features for submitochondria localization. Amino Acids 34 (2008) 653-660
60. Niu B., Cai Y.D., Lu W.C., Zheng G.Y., and Chou K.C. Predicting protein structural class with AdaBoost learner. Protein Pept. Lett. 13 (2006) 489-492
61. Niu B., Jin Y.H., Feng K.Y., Liu L., Lu W.C., Cai Y.D., and Li G.Z. Predicting membrane protein types with bagging learner. Protein Pept. Lett. 15 (2008) 590-594
62. Pillai, K.C.S., 1985. Mahalanobis D2. In: Kotz, S., Johnson, N.L. (Eds.), Encyclopedia of Statistical Sciences, vol. 5. John Wiley & Sons. This reference also presents a brief biography of Mahalanobis who was a man of great originality and who made considerable contributions to statistics, New York, pp. 176-181.
63. Pu X., Guo J., Leung H., and Lin Y. Prediction of membrane protein types from sequences and position-specific scoring matrices. J. Theor. Biol. 247 (2007) 259-265
64. Pugalenthi G., Tang K., Suganthan P.N., Archunan G., and Sowdhamini R. A machine learning approach for the identification of odorant binding proteins from sequence-derived properties. BMC Bioinformatics 8 (2007) 351
65. Rizon M., Yazid H., and Saad P. Object detection using geometric invariant moment. Am. J. Appl. Sci. 2 (2006) 1876-1878
66. Shen H.B., and Chou K.C. PseAAC: a flexible web-server for generating various kinds of protein pseudo amino acid composition. Anal. Biochem. 373 (2008) 386-388
67. Shen H.B., Yang J., Liu X.J., and Chou K.C. Using supervised fuzzy clustering to predict protein structural classes. Biochem. Biophys. Res. Commun. 334 (2005) 577-581
68. Shi J.Y., Zhang S.W., Pan Q., Cheng Y.-M., and Xie J. Prediction of protein subcellular localization by support vector machines using multi-scale energy and pseudo amino acid composition. Amino Acids 33 (2007) 69-74
69. Sun X.D., and Huang R.B. Prediction of protein structural classes using support vector machines. Amino Acids 30 (2006) 469-475
70. Tan F., Feng X., Fang Z., Li M., Guo Y., and Jiang L. Prediction of mitochondrial proteins based on genetic algorithm-partial least squares and support vector machine. Amino Acids 33 (2007) 669-675
71. Wen Z., Li M., Li Y., Guo Y., and Wang K. Delaunay triangulation with partial least squares projection to latent structures: a model for G-protein coupled receptors classification and fast structure recognition. Amino Acids 32 (2007) 277-283
72. Wolfram S. Cellular automation as models of complexity. Nature 311 (1984) 419-424
73. Wolfram S. A New Kind of Science (2002), Wolfram Media Inc., Champaign, IL
74. Xiao X., and Chou K.C. Digital coding of amino acids based on hydrophobic index. Protein Pept. Lett. 14 (2007) 871-875
75. Xiao X., Shao S., Ding Y., Huang Z., Chen X., and Chou K.C. Using cellular automata to generate Image representation for biological sequences. Amino Acids 28 (2005) 29-35
76. Zhang T.L., and Ding Y.S. Using pseudo amino acid composition and binary-tree support vector machines to predict protein structural classes. Amino Acids 33 (2007) 623-629
77. Zhang C.T., Chou K.C., and Maggiora G.M. Predicting protein structural classes from amino acid composition: application of fuzzy clustering. Protein Eng. 8 (1995) 425-435
78. Zhang S.W., Pan Q., Zhang H.C., Shao Z.C., and Shi J.Y. Prediction protein homo-oligomer types by pseudo amino acid composition: approached with an improved feature extraction and naive Bayes feature fusion. Amino Acids 30 (2006) 461-468
79. Zhang S.W., Zhang Y.L., Yang H.F., Zhao C.H., and Pan Q. Using the concept of Chou's pseudo amino acid composition to predict protein subcellular localization: an approach by incorporating evolutionary information and von Neumann entropies. Amino Acids 34 (2008) 565-572
80. Zhou G.P. An intriguing controversy over protein structural class prediction. J. Protein Chem. 17 (1998) 729-738
81. Zhou G.P., and Assa-Munt N. Some insights into protein structural class prediction. Proteins: Struct., Funct., Genet. 44 (2001) 57-59
82. Zhou G.P., and Doctor K. Subcellular location prediction of apoptosis proteins. Proteins: Struct., Funct., Genet. 50 (2003) 44-48
83. Zhou X.B., Chen C., Li Z.C., and Zou X.Y. Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes. J. Theor. Biol. 248 (2007) 546-551