Methods for optimizing the structure alphabet sequences of proteins

Computers in Biology and Medicine

Volumn 37, Issue 11, 2007, Pages 1610-1616

  Dong, Qi wen ^a   Wang, Xiao long ^a   Lin, Lei ^a  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

Dynamic programming algorithm; Greedy algorithm; Local protein structure prediction; Structure alphabet

Indexed keywords

ALGORITHMS; CONFORMATIONS; DYNAMIC PROGRAMMING; MOLECULAR STRUCTURE; OPTIMIZATION;

CARTESIAN SPACES; GREEDY ALGORITHMS; LOCAL PROTEIN STRUCTURE PREDICTION; STRUCTURAL ALPHABET;

PROTEINS;

PROTEIN;

ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; DATA BASE; METHODOLOGY; PREDICTION; PRIORITY JOURNAL; PROTEIN CONFORMATION; PROTEIN STRUCTURE; STRUCTURAL PROTEOMICS;

ALGORITHMS; AMINO ACID SEQUENCE; DATABASES, PROTEIN; PEPTIDE FRAGMENTS; PROTEINS;

EID: 34548406068     PISSN: 00104825     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2007.03.002     Document Type: Article

References (36)

1. Baker D., and Sali A. Protein structure prediction and structural genomics. Science 294 (2001) 93
2. Levitt M., and Warshel A. Computer simulation of protein folding. Nature 253 (1975) 694
3. Zintzaras E., Brown N.P., and Kowald A. Non-parametric classification of protein secondary structures. Comput. Biol. Med. 36 (2006) 145
4. Kouranov A., Xie L., de la Cruz J., Chen L., Westbrook J., Bourne P.E., and Berman H.M. The RCSB PDB information portal for structural genomics. Nucleic Acids Res. 34 (2006) D302
5. Reddy Ch S., Vijayasarathy K., Srinivas E., Sastry G.M., and Sastry G.N. Homology modeling of membrane proteins: a critical assessment. Comput. Biol. Chem. 30 (2006) 120
6. Solis A.D., and Rackovsky S. Improvement of statistical potentials and threading score functions using information maximization. Proteins 62 (2006) 892
7. Rai B.K., and Fiser A. Multiple mapping method: a novel approach to the sequence-to-structure alignment problem in comparative protein structure modeling. Proteins 63 (2006) 644
8. Fujitsuka Y., Chikenji G., and Takada S. SimFold energy function for de novo protein structure prediction: consensus with Rosetta. Proteins 62 (2006) 381
9. Vincent J.J., Tai C.H., Sathyanarayana B.K., and Lee B. Assessment of CASP6 predictions for new and nearly new fold targets. Proteins 61 Suppl 7 (2005) 67
10. Jones D.T., Bryson K., Coleman A., McGuffin L.J., Sadowski M.I., Sodhi J.S., and Ward J.J. Prediction of novel and analogous folds using fragment assembly and fold recognition. Proteins 61 Suppl 7 (2005) 143
11. Chivian D., Kim D.E., Malmstrom L., Schonbrun J., Rohl C.A., and Baker D. Prediction of CASP6 structures using automated Robetta protocols. Proteins 61 Suppl 7 (2005) 157
12. Benros C., de Brevern A.G., Etchebest C., and Hazout S. Assessing a novel approach for predicting local 3D protein structures from sequence. Proteins 62 (2006) 865
13. Bystroff C., and Baker D. Prediction of local structure in proteins using a library of sequence-structure motifs. J. Mol. Biol. 281 (1998) 565
14. Bystroff C., Thorsson V., and Baker D. HMMSTR: a hidden Markov model for local sequence-structure correlations in proteins. J. Mol. Biol. 301 (2000) 173
15. Camproux A.C., Tuffery P., Chevrolat J.P., Boisvieux J.F., and Hazout S. Hidden Markov model approach for identifying the modular framework of the protein backbone. Protein Eng. 12 (1999) 1063
16. Camproux A.C., Gautier R., and Tuffery P. A hidden Markov model derived structural alphabet for proteins. J. Mol. Biol. 339 (2004) 591
17. Guyon F., Camproux A.C., Hochez J., and Tuffery P. SA-Search: a web tool for protein structure mining based on a Structural Alphabet. Nucleic Acids Res. 32 (2004) W545
18. de Brevern A.G., Etchebest C., and Hazout S. Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks. Proteins 41 (2000) 271
19. Etchebest C., Benros C., Hazout S., and de Brevern A.G. A structural alphabet for local protein structures: improved prediction methods. Proteins 59 (2005) 810
20. Karchin R., Cline M., and Karplus K. Evaluation of local structure alphabets based on residue burial. Proteins 55 (2004) 508
21. Kolodny R., Koehl P., Guibas L., and Levitt M. Small libraries of protein fragments model native protein structures accurately. J. Mol. Biol. 323 (2002) 297
22. Wang L.Y. Covariation analysis of local amino acid sequences in recurrent protein local structures. J. Bioinform. Comput. Biol. 3 (2005) 1391
23. Sander O., Sommer I., and Lengauer T. Local protein structure prediction using discriminative models. BMC Bioinformatics 7 (2006) 14
24. Lee J., Kim S.Y., and Lee J. Protein structure prediction based on fragment assembly and parameter optimization. Biophys. Chem. 115 (2005) 209
25. Grishaev A., Steren C.A., Wu B., Pineda-Lucena A., Arrowsmith C., Llinas M., and ABACUS. a direct method for protein NMR structure computation via assembly of fragments. Proteins 61 (2005) 36
26. Tuffery P., Guyon F., and Derreumaux P. Improved greedy algorithm for protein structure reconstruction. J. Comput. Chem. 26 (2005) 506
27. Tuffery P., and Derreumaux P. Dependency between consecutive local conformations helps assemble protein structures from secondary structures using Go potential and greedy algorithm. Proteins 61 (2005) 732
28. Lee J., Kim S.Y., Joo K., Kim I., and Lee J. Prediction of protein tertiary structure using PROFESY, a novel method based on fragment assembly and conformational space annealing. Proteins 56 (2004) 704
29. Deshpande N., Addess K.J., Bluhm W.F., Merino-Ott J.C., Townsend-Merino W., Zhang Q., Knezevich C., Xie L., Chen L., Feng Z., Green R.K., Flippen-Anderson J.L., Westbrook J., Berman H.M., and Bourne P.E. The RCSB Protein Data Bank: a redesigned query system and relational database based on the mmCIF schema. Nucleic Acids Res. 33 (2005) D233
30. Wang G., and Dunbrack Jr. R.L. PISCES: a protein sequence culling server. Bioinformatics 19 (2003) 1589
31. Holmes J.B., and Tsai J. Some fundamental aspects of building protein structures from fragment libraries. Protein Sci. 13 (2004) 1636
32. Kabsch W. A solution for the best rotation to relate two sets of vectors. Acta Cryst. A 32 (1976) 922
33. Park B.H., and Levitt M. The complexity and accuracy of discrete state models of protein structure. J. Mol. Biol. 249 (1995) 493
34. Bystroff C., Simons K.T., Han K.F., and Baker D. Local sequence-structure correlations in proteins. Curr. Opin. Biotechnol. 7 (1996) 417
35. Hunter C.G., and Subramaniam S. Protein fragment clustering and canonical local shapes. Proteins 50 (2003) 580
36. Frishman D., and Arogos P. Knowledge-based protein secondary structure assignment. Proteins 23 (1995) 566