Identification of non random motifs in loops using a structural alphabet

Proceedings of the 2006 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB'06

Volumn , Issue , 2006, Pages 92-100

  Regad, L ^a   Martin, J ^a,b   Camproux, A C ^a  

^a Université Parix VII Paris   (France)

^b CEMAGREF   (France)

Author keywords

Loops; Protein structure; Structural alphabet; Structural motif

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOCOMMUNICATIONS; CONFORMATIONS; FORECASTING; HIDDEN MARKOV MODELS; INFORMATION SCIENCE; INTELLIGENT CONTROL; MARKOV PROCESSES; THREE DIMENSIONAL;

CHALLENGING PROBLEM; COMPUTATIONAL BIOLOGY; COMPUTATIONAL INTELLIGENCE; HIDDEN MARKOV MODELING; LOOP CONFORMATION; LOOP REGIONS; LOOPS; PROTEIN STRUCTURE; PROTEIN STRUCTURES; SEQUENCE SPECIFICITY; STRUCTURAL ALPHABET; STRUCTURAL MOTIF; STRUCTURAL MOTIFS;

BIOINFORMATICS;

EID: 40549105179     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIBCB.2006.331017     Document Type: Conference Paper

References (30)

1. A. V. Efimov. Standard structures in proteins. Prog Biophys Mol Biol, 60:201-239, 1993.
2. B. Oliva, P. A. Bates, E. Querol, F. X. Aviles, and M. J. Sternberg. An automated classification of the structure of protein loops. J Mol Biol, 266:814-830, 1997.
3. D. F. Burke, C. M. Deane, and T. L. Blundell. Browsing the sloop database of structurally classified loops connecting elements of protein secondary structure. Bioinformatics, 16:513-519, 2000.
4. J. Hutchinson, E.G.and Thornton. A revised set of potentials for β-turn formation in proteins. Protein Sci, 3:2207-2216, 1994.
5. J. Wojcik, J. P. Mornon, and J. Chomilier. New efficient statistical sequence-dependent structure prediction of short to medium-sized protein loops based on an exhaustive loop classification. J Mol Biol, 289:1469-1490, 1999.
6. J.S. Fetrow. Omega loops: nonregular secondary structures significant in protein function and stability. FASEB J, 9:708-717, 1995.
7. E. Y. Jones, J. Tormo, S.W . Reid, and D. I. Stuart. Recognition surfaces of MHC class I. Immunol Rev, 163:121-128, 1998.
8. A. R. Panchenko and T. Madej. Structural similarity of loops in protein families: toward the understanding of protein evolution. BMC Evol Biol, 5:10-17, 2005.
9. S. A. Benner, M. A. Cohen, and G. H. Gonnet. Empirical and structural models for insertions and deletions in the divergent evolution of proteins. J Mol Biol, 229:1065-1082, 1993.
10. N. C. Fitzkee, P. J. Fleming, and G. D. Rose. The protein coil library: a structural database of nonhelix, nonstrand fragments derived from the pdb. Proteins, 58:852-854, 2005.
11. M. P. Jacobson, D. L. Pincus, C. S. Rapp, T. J. F. Day, B. Honig, D. E. Shaw, and R. A. Friesner. A hierarchical approach to all-atom protein loop prediction. Proteins, 55:351-367, 2004.
12. M. Monnigmann and C. A. Floudas. Protein loop structure prediction with flexible stem geometries. Proteins, 61:748-762, 2005.
13. C. A. Rohl, C. E. M. Strauss, D. Chivian, and D. Baker. Modeling structurally variable regions in homologous proteins with rosetta. Proteins, 55:656-677, 2004.
14. A. C. Camproux, P. Tufféry, J. P. Chevrolat, J. F. Boisvieux, and S. Hazout. Hidden Markov model approach for identifying the modular framework of the protein backbone. Protein Eng, 12:1063-1073, 1999.
15. C. Wang and R. Dunbrack. Pisces: a protein sequence culling server. Bioinformatics, 19:1589-1591, 2003.
16. A. C. Camproux, R. Gautier, and T. Tufféry. A hidden Markov model derivated structural alphabet for proteins. J Mol Biol, 339:561-605, 2004.
17. D. Frishman and P. Argos. Knowledge-based protein secondary structure assignment. Proteins, 23:566-579, 1995.
18. S. Robin, S. Schbath, and F. Rodolphe. DNA, words and models, Statistics of exceptional words. Cambridge University Press, 2005.
19. G. Nuel. S-spatt: simple statistics for patterns on Markov chains. Bioinformatics, 21:3051-3052, 2005.
20. S. Kullback and R. A. Leibler. On information and sufficiency. Annals of Mathematics and Statistics, 22:79-86, 1951.
21. L. Fourrier, C. Benros, and A. G. de Brevern. Use of a structural alphabet for analysis of short loops connecting repetitive structures. BMC Bioinformatics, 5:58-70, 2004.
22. O. Sander, S. Ingolf, and T. Lengauer. Local protein structure prediction using discriminative models. BMC Bioinformatics, 7:14-26, 2006.
23. C. G. Hunter and S. Subramaniam. Protein fragment clustering and canonical local shapes. Proteins, 50:580-588, 2003.
24. P. Fuchs and J. F. Alain J. P. Alix. High accuracy prediction of beta-turns and their types using propensities and multiple alignments. Proteins, 59:828-839, 2005. http://bioserv.rpbs.jussieu.fr/RPBS/.
25. C. Bystroff and D. Baker. Prediction of local structure in proteins using a library of sequence-structure motifs. J Mol Biol, 281:567-577, 1998.
26. A. C. Camproux, T. Tufféry, L. Buffat, C. André, J. F. Boisvieux, and S. Hazout. Analyzing patterns between regular secondary structures using short structural building blocks dend by a hidden Markov model. Theor Chem Acc, 101:33-40, 1999.
27. C. Benros, A. G. de Brevern, C. Etchebest, and S. Hazout. Assessing a novel approach for predicting local 3D protein structures from sequence. Proteins, 62:865-880, 2006.
28. F. Guyon, A. C. Camproux, J. Hochez, and P. Tufféry. SA-Search: a web tool for protein structure mining based on a structural alphabet. Nucleic Acids Res., 32(Web Server issue):W545-W548, 2004.
29. J. Soding and A. N. Lupas. More than the sum of their parts: on the evolution of proteins from peptides. Bioessays, 25:837-846, 2003.
30. S.D. Rufino, L.E. Donate, L.H. Canard, and T.L. Blundell. Predicting the conformational class of short and medium size loops connecting regular secondary structures: application to comparative modelling. J Mol Biol, 267:352-367, 1997.