A generic method for assignment of reliability scores applied to solvent accessibility predictions

BMC Structural Biology

Volumn 9, Issue , 2009, Pages

  Petersen, Bent ^a   Petersen, Thomas Nordahl ^a   Andersen, Pernille ^a,b   Nielsen, Morten ^a   Lundegaard, Claus ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^b UNIVERSITY OF COPENHAGEN   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID; PROTEIN; SOLVENT;

AMINO ACID SEQUENCE; ARTICLE; ARTIFICIAL NEURAL NETWORK; CALCULATION; CONTROLLED STUDY; CORRELATION COEFFICIENT; EVALUATION; PERFORMANCE; PREDICTION; PROTEIN STRUCTURE; RELIABILITY; SCORING SYSTEM; SOLVENT ACCESSIBILITY; STRUCTURE ANALYSIS; Z SCORE; ALGORITHM; BIOLOGY; CHEMISTRY; PROTEIN DATABASE;

ALGORITHMS; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; NEURAL NETWORKS (COMPUTER); PROTEINS; SOLVENTS;

EID: 68949213019     PISSN: None     EISSN: 14726807     Source Type: Journal    
DOI: 10.1186/1472-6807-9-51     Document Type: Article

References (37)

1. Modeling the adaptive immune system: predictions and simulations. C Lundegaard O Lund C Kesmir S Brunak M Nielsen, Bioinformatics 2007 23 24 3265 3275 10.1093/bioinformatics/btm471 18045832
2. PHD: predicting one-dimensional protein structure by profile-based neural networks. B Rost, Methods Enzymol 1996 266 525 539 full-text 8743704
3. Analytical molecular surface calculation. M Connolly, Journal of Applied Crystallography 1983 16 5 548 558 10.1107/S0021889883010985
4. The nature of the accessible and buried surfaces in proteins. C Chothia, J Mol Biol 1976 105 1 1 12 10.1016/0022-2836(76)90191-1 994183
5. Real value prediction of solvent accessibility from amino acid sequence. S Ahmad MM Gromiha A Sarai, Proteins 2003 50 4 629 635 10.1002/prot.10328 12577269
6. Analysis of protein-protein interaction sites using surface patches. S Jones JM Thornton, J Mol Biol 1997 272 1 121 132 10.1006/jmbi.1997.1234 9299342
7. Prediction of protein-protein interaction sites using patch analysis. S Jones JM Thornton, J Mol Biol 1997 272 1 133 143 10.1006/jmbi.1997.1233 9299343
8. Prediction of residues in discontinuous B-cell epitopes using protein 3D structures. P Haste Andersen M Nielsen O Lund, Protein Sci 2006 15 11 2558 2567 10.1110/ps.062405906 17001032
9. Prediction of functional sites by analysis of sequence and structure conservation. AR Panchenko F Kondrashov S Bryant, Protein Sci 2004 13 4 884 892 10.1110/ps.03465504 15010543
10. Bioinformatics approaches and resources for single nucleotide polymorphism functional analysis. S Mooney, Brief Bioinform 2005 6 1 44 56 10.1093/bib/6.1.44 15826356
11. Prediction of coordination number and relative solvent accessibility in proteins. G Pollastri P Baldi P Fariselli R Casadio, Proteins 2002 47 2 142 153 10.1002/prot.10069 11933061
12. SCRATCH: a protein structure and structural feature prediction server. J Cheng AZ Randall MJ Sweredoski P Baldi, Nucleic Acids Research 2005 33 Web Server W72 W76 10.1093/nar/gki396 15980571
13. Accurate prediction of solvent accessibility using neural networks-based regression. R Adamczak A Porollo J Meller, Proteins: Structure, Function, and Bioinformatics 2004 56 4 753 767 10.1002/prot.20176
14. Predicting residue solvent accessibility from protein sequence by considering the sequence environment. O Carugo, Protein Eng 2000 13 9 607 609 10.1093/protein/13.9.607 11054454
15. Real value prediction of solvent accessibility in proteins using multiple sequence alignment and secondary structure. A Garg H Kaur GPS Raghava, Proteins 2005 61 2 318 324 10.1002/prot.20630 16106377
16. Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information. G Pollastri AJM Martin C Mooney A Vullo, BMC Bioinformatics 2007 8 201 10.1186/1471-2105-8-201 17570843
17. SVM-Cabins: prediction of solvent accessibility using accumulation cutoff set and support vector machine. J-Y Wang H-M Lee S Ahmad, Proteins 2007 68 1 82 91 10.1002/prot.21422 17436325
18. QBES: Predicting real values of solvent accessibility from sequences by efficient, constrained energy optimization. Z Xu C Zhang S Liu Y Zhou, Proteins: Structure, Function, and Bioinformatics 2006 63 4 961 966 10.1002/prot.20934
19. Prediction of protein solvent accessibility using support vector machines. Z Yuan K Burrage JS Mattick, Proteins 2002 48 3 566 570 10.1002/prot.10176 12112679
20. Prediction of protein accessible surface areas by support vector regression. Z Yuan B Huang, Proteins 2004 57 3 558 564 10.1002/prot.20234 15382233
21. Achieving 80% ten-fold cross-validated accuracy for secondary structure prediction by large-scale training. O Dor Y Zhou, Proteins 2007 66 4 838 845 10.1002/prot.21298 17177203
22. Real-SPINE: an integrated system of neural networks for real-value prediction of protein structural properties. O Dor Y Zhou, Proteins 2007 68 1 76 81 10.1002/prot.21408 17397056
23. Improving the prediction accuracy of residue solvent accessibility and real-value backbone torsion angles of proteins by guided-learning through a two-layer neural network. E Faraggi B Xue Y Zhou, Proteins 2009 74 4 847 856 10.1002/prot.22193 18704931
24. Two-stage support vector regression approach for predicting accessible surface areas of amino acids. MN Nguyen JC Rajapakse, Proteins 2006 63 3 542 550 10.1002/prot.20883 16456847
25. Jpred Distribution material. G Barton, 2007 http://www.compbio.dundee.ac. uk/∼www-jpred/data/
26. Evaluation and improvement of multiple sequence methods for protein secondary structure prediction. JA Cuff GJ Barton, Proteins 1999 34 4 508 519 10.1002/(SICI)1097-0134(19990301)34:4<508::AID-PROT10>3.0.CO;2-4 10081963
27. Prediction of protein secondary structure at better than 70% accuracy. B Rost C Sander, J Mol Biol 1993 232 2 584 599 10.1006/jmbi.1993.1413 8345525
28. The Protein Data Bank. HM Berman J Westbrook Z Feng G Gilliland TN Bhat H Weissig IN Shindyalov PE Bourne, Nucl Acids Res 2000 28 1 235 242 10.1093/nar/28.1.235 10592235
29. PISCES: a protein sequence culling server. G Wang RLJ Dunbrack, Bioinformatics 2003 19 12 1589 1591 10.1093/bioinformatics/btg224 12912846
30. Dictionary of Protein Secondary Structure: pattern recognition of hydrogen-bonded and geometrical features. W Kabsch C Sander, Biopolymers 1983 22 12 2577 2637 10.1002/bip.360221211 6667333
31. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. SF Altschul TL Madden AA Schäffer J Zhang Z Zhang W Miller DJ Lipman, Nucleic Acids Res 1997 25 17 3389 3402 10.1093/nar/25.17.3389 9254694
32. Clustering of highly homologous sequences to reduce the size of large protein databases. W Li L Jaroszewski A Godzik, Bioinformatics 2001 17 3 282 283 10.1093/bioinformatics/17.3.282 11294794
33. Learning internal representations by error propagation. D Rumelhart G Hinton R Williams, Parallel distributed processing MIT Press Cambridge 1986 318 363
34. Immunological Bioinformatics. O Lund M Nielsen C Lundegaard C KeSmir S Brunak, The MIT Press, Cambridge, Massachusetts, London, England 2005
35. The proof and measurement of association between two things. C Spearman, J Psychol 1904 15 72 101 10.2307/1412159
36. Prediction of protein secondary structure at 80% accuracy. TN Petersen C Lundegaard M Nielsen H Bohr J Bohr S Brunak G Gippert O Lund, Proteins 2000 41 1 17 20 10.1002/1097-0134(20001001)41:1<17::AID-PROT40>3.0.CO;2-F 10944389
37. Selection of representative protein data sets. U Hobohm M Scharf R Schneider C Sander, Protein Sci 1992 1 409 417 1304348