SVM-based method for protein structural class prediction using secondary structural content and structural information of amino acids

Journal of Bioinformatics and Computational Biology

Volumn 9, Issue 4, 2011, Pages 489-502

  Mohammad, Tabrez Anwar Shamim ^a,b   Nagarajaram, Hampapathalu Adimurthy ^a  

^a CENTRE FOR DNA FINGERPRINTING AND DIAGNOSTICS   (India)

^b UNIVERSITY OF TEXAS HEALTH SCIENCE CENTER AT SAN ANTONIO   (United States)

Author keywords

Protein structural class prediction; structural information of amino acids; SVM

Indexed keywords

AMINO ACID; PROTEIN;

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; BIOLOGY; CHEMISTRY; CLASSIFICATION; COMPARATIVE STUDY; EVALUATION; GENETICS; PROTEIN DATABASE; PROTEIN SECONDARY STRUCTURE; STRUCTURAL HOMOLOGY; SUPPORT VECTOR MACHINE; VALIDATION STUDY;

ALGORITHMS; AMINO ACID SEQUENCE; AMINO ACIDS; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; PROTEIN STRUCTURE, SECONDARY; PROTEINS; STRUCTURAL HOMOLOGY, PROTEIN; SUPPORT VECTOR MACHINES;

EID: 79960352702     PISSN: 02197200     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0219720011005422     Document Type: Article

References (25)

1. Levitt M, Chothia C, Structural patterns in globular proteins, Nature 261:552-558, 1976.
2. Murzin AG, Brenner SE, Hubbard T, Chothia C, SCOP: A structural classification of proteins database for the investigation of sequences and structures, J Mol Biol 247:536-540, 1995.
3. Orengo CA et al., CATH - A hierarchic classification of protein domain structures, Structure 5:1093-1108, 1997. (Pubitemid 27393093)
4. Eisenhaber F, Frommel C, Argos P, Prediction of secondary structural content of proteins from their amino acid composition alone. II. The paradox with secondary structural class, Proteins 25:169-179, 1996. (Pubitemid 26231107)
5. Chou KC, A novel approach to predicting protein structural classes in a (20-1)-D amino acid composition space, Proteins 21:319-344, 1995.
6. Cai YD, Liu XJ, Xu XB, Chou KC, Support vector machines for prediction of protein domain structural class, J Theor Biol 221:115-120, 2003.
7. Kurgan L, Chen K, Prediction of protein structural class for the twilight zone sequences, Biochem Biophys Res Commun 357:453-460, 2007. (Pubitemid 46603153)
8. Jahandideh S, Abdolmaleki P, Jahandideh M, Hayatshahi SH, Novel hybrid method for the evaluation of parameters contributing in determination of protein structural classes, J Theor Biol 244:275-281, 2007. (Pubitemid 44794504)
9. Kurgan L, Cios K, Chen K, SCPRED: Accurate prediction of protein structural class for sequences of twilight-zone similarity with predicting sequences, BMC Bioinformatics 9:226, 2008.
10. Shamim MT, Anwaruddin M, Nagarajaram HA, Support vector machinebased classification of protein folds using the structural properties of amino acid residues and amino acid residue pairs, Bioinformatics 23:3320-3327, 2007. (Pubitemid 350238884)
11. Kedarisetti KD, Kurgan L, Dick S, Classifier ensembles for protein structural class prediction with varying homology, Biochem Biophys Res Commun 348:981-988, 2006. (Pubitemid 44233512)
12. Hobohm U, Sander C, Enlarged representative set of protein structures, Protein Sci 3:522-524, 1994. (Pubitemid 24103723)
13. Kurgan L, 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 Recognition 39:2323-2343, 2006. (Pubitemid 44344741)
14. Cortes C, Vapnik V, Support-vector networks, Mach Lear 20:273-297, 1995.
15. Chang CC, Lin CJ, LIBSVM: A library for support vector machines. Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm, 2001.
16. McGuffin LJ, Bryson K, Jones DT, The PSIPRED protein structure prediction server, Bioinformatics 16:404-405, 2000. (Pubitemid 30417087)
17. Cheng J, Randall AZ, Sweredoski MJ, Baldi P, SCRATCH: A protein structure and structural feature prediction server, Nucleic Acids Res 33:W72-W76, 2005. (Pubitemid 44529882)
18. Murphy LR, Wallqvist A, Levy RM, Simplified amino acid alphabets for protein fold recognition and implications for folding, Protein Eng 13:149-152, 2000. (Pubitemid 30237589)
19. Solis AD, Rackovsky S, Optimized representations and maximal information in proteins, Proteins 38:149-164, 2000. (Pubitemid 30051415)
20. Li T, Fan K, Wang J, Wang W, Reduction of protein sequence complexity by residue grouping, Protein Eng 16:323-330, 2003. (Pubitemid 36806923)
21. Wang J,Wang W, A computational approach to simplifying the protein folding alphabet, Nat Struct Biol 6:1033-1038, 1999.
22. Rost B, Sander C, Prediction of protein secondary structure at better than 70% accuracy, J Mol Biol 232:584-599, 1993. (Pubitemid 23251181)
23. Cai YD, Feng KY, Lu WC, Chou KC, Using LogitBoost classifier to predict protein structural classes, J Theor Biol 238:172-176, 2006.
24. Dong L, Yuan Y, Cai Y, Using Bagging classifier to predict protein domain structural class, J Biomol Struct Dyn 24:239-242, 2006. (Pubitemid 44871528)
25. Yang J, Peng Z, Chen X, Prediction of protein structural classes for low-homology sequences based on predicted secondary structure, BMC Bioinformatics 11:S9, 2010.