A simplified approach to disulfide connectivity prediction from protein sequences

BMC Bioinformatics

Volumn 9, Issue , 2008, Pages

  Vincent, Marc ^a   Passerini, Andrea ^a   Labbé, Matthieu ^a   Frasconi, Paolo ^a  

^a UNIVERSITY OF FLORENCE   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

1-NEAREST NEIGHBOR; CONNECTIVITY PATTERN; CONNECTIVITY PREDICTIONS; DISULFIDE CONNECTIVITIES; EXPERIMENTAL COMPARISON; FUNCTIONAL PROPERTIES; MULTI-CLASS CLASSIFIER; PREDICTION ACCURACY;

AMINO ACIDS; CHAINS; COVALENT BONDS; LEARNING ALGORITHMS; PROTEINS; SULFUR COMPOUNDS;

FORECASTING;

AMINO ACID; CYSTEINE DERIVATIVE; DISULFIDE; PROTEIN;

ACCURACY; AMINO ACID ANALYSIS; AMINO ACID SEQUENCE; ANALYTICAL PARAMETERS; ARTICLE; CONTROLLED STUDY; DATA ANALYSIS; KERNEL METHOD; PREDICTION; PROTEIN BINDING; PROTEIN STRUCTURE; SEQUENCE HOMOLOGY; ALGORITHM; BINDING SITE; CHEMICAL MODEL; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER SIMULATION; METHODOLOGY; MOLECULAR GENETICS; SEQUENCE ANALYSIS;

ALGORITHMS; AMINO ACID SEQUENCE; BINDING SITES; COMPUTER SIMULATION; DISULFIDES; MODELS, CHEMICAL; MODELS, MOLECULAR; MOLECULAR SEQUENCE DATA; PROTEIN BINDING; PROTEINS; SEQUENCE ANALYSIS, PROTEIN;

EID: 41549168582     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-9-20     Document Type: Article

References (32)

1. Fariselli P Casadio R Prediction of disulfide connectivity in proteins Bioinformatics 2001, 17(10):957-964 10.1093/bioinformatics/17.10.957 11673241
2. Ferrè F Clote P DiANNA 1.1: An extension of the DiANNA web server for ternary cysteine classification Nucleic Acids Research 2006, 34:W182-W185 1538812 16844987 10.1093/nar/gkl189
3. Tsai CH Chen BJ Chan CH Liu HL Kao CY Improving disulfide connectivity prediction with sequential distance between oxidized cysteines Bioinformatics 2005, 21(24):4416-4419 10.1093/bioinformatics/bti715 16223789
4. Cheng J Randall AZ Sweredoski MJ Baldi P SCRATCH: A protein structure and structural feature prediction server Nucleic Acids Res 2005 33 Web Server W72-W76 1160157 15980571 10.1093/nar/gki396
5. Ceroni A Passerini A Vullo A Frasconi P DISULFIND: A Disulfide Bonding State and Cysteine Connectivity Prediction Server Nucleic Acids Research 2006, 34 Web Server W177-W181 1538823 16844986 10.1093/nar/gkl266
6. Cheng J Saigo H Baldi P Large-scale prediction of disulphide bridges using kernel methods, two-dimensional recursive neural networks, and weighted graph matching Proteins 2006, 62(3):617-629 10.1002/prot.20787 16320312
7. Fiser A Cserzo M Tudos E Simon I Different sequence environments of cysteines and half cystines in proteins. Application to predict disulfide forming residues FEBS Lett 1992, 302(2):117-20 10.1016/ 0014-5793(92)80419-H 1633841
8. Fariselli P Riccobelli P Casadio R Role of evolutionary information in predicting the disulfide-bonding state of cysteine in proteins Proteins 1999, 36(3):340-346 10.1002/ (SICI)1097-0134(19990815)36:3<340::AID-PROT8>3.0.CO;2-D 10409827
9. Fiser A Simon I Predicting the oxidation state of cysteines by multiple sequence alignment Bioinformatics 2000, 16(3):251-256 10.1093/ bioinformatics/16.3.251 10869018
10. Mucchielli-Giorgi M Hazout S Tuffery P Predicting the Disulfide Bonding State of Cysteines Using Protein Descriptors Proteins 2002, 46:243-249 10.1002/prot.10047 11835499
11. Ceroni A Frasconi P Passerini A Vullo A Predicting the Disulfide Bonding State of Cysteines with Combinations of Kernel Machines Journal of VLSI Signal Processing 2003, 35(3):287-295 [ps/jvlsi-03-cys.pdf] 10.1023/ B:VLSI.0000003026.58068.ce
12. Song JN Wang ML Li WJ Xu WB Prediction of the disulfide-bonding state of cysteines in proteins based on dipeptide composition Biochem Biophys Res Commun 2004, 318:142-147 10.1016/j.bbrc.2004.03.189 15110765
13. Martelli PL Fariselli P Casadio R Prediction of disulfide-bonded cysteines in proteomes with a hidden neural network Proteomics 2004, 4(6):1665-1671 10.1002/pmic.200300745 15174135
14. Chen YC Lin YS Lin CJ Hwang JK Prediction of the bonding states of cysteines using the support vector machines based on multiple feature vectors and cysteine state sequences Proteins 2004, 55(4):1036-1042 10.1002/prot.20079 15146500
15. Vullo A Frasconi P Disulfide connectivity prediction using recursive neural networks and evolutionary information Bioinformatics 2004, 20(5):653-659 10.1093/bioinformatics/btg463 15033872
16. Taskar B Chatalbashev V Koller D Guestrin C Learning Structured Prediction Models: A Large Margin Approach Proceedings of the Twenty Second International Conference on Machine Learning (ICML05) 2005
17. Ferrè F Clote P Disulfide connectivity prediction using secondary structure information and diresidue frequencies Bioinformatics 2005, 21(10):2336-2346 10.1093/bioinformatics/bti328 15741247
18. Zhao E Liu HL Tsai CH Tsai HK hsiung Chan C Kao CY Cysteine separations profiles on protein sequences infer disulfide connectivity Bioinformatics 2005, 21(8):1415-1420 10.1093/bioinformatics/bti179 15585533
19. Chen YC Hwang JK Prediction of disulfide connectivity from protein sequences Proteins 2005, 61(3):507-512 10.1002/prot.20627 16170781
20. Chen BJ Tsai CH Chan CH Kao CY Disulfide connectivity prediction with 70% accuracy using two-level models Proteins 2006, 64:246-252 10.1002/ prot.20972 16615141
21. Lu CH Chen YC Yu CS Hwang JK Predicting disulfide connectivity patterns Proteins 2007, 67(2):262-270 10.1002/prot.21309 17285623
22. Gold C Sollich P Model Selection for Support Vector Machine Classification Neurocomputing 2003, 55:221 [doi:10.1016/ S0925-2312(03)00375-8] 10.1016/S0925-2312(03)00375-8
23. Joachims T Making large-Scale SVM Learning Practical Advances in Kernel Methods - Support Vector Learning MIT Press Schölkopf B, Burges C, Smola A 1999 http://svmlight.joachims.org/
24. Hobohm U Scharf M Schneider R Sander C Selection of a representative set of structures from the Brookhaven Protein Data Bank Protein Science 1992, 1:409-417 2142204 1304348
25. Hobohm U Sander C Enlarged representative set of protein structures Protein Science 1994, 3:522 2142698 8019422
26. PDBselect http://bioinfo.tg.fh-giessen.de/pdbselect/
27. Hobohm U Sander C Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features Biopolymers 1983, 22:2577-2637 10.1002/bip.360221211 6667333
28. DIpro http://contact.ics.uci.edu/intro.html
29. CysPred http://www.biocomp.unibo.it/piero/cyspred/cysdataset.tgz
30. Altschul S Madden T Schaffer A Zhang J Zhang Z Miller W Lipman D Gapped BLAST and PSI-BLAST: A new generation of protein database search programs Nucleic Acids Research 1997, 25(17):3389-3402 146917 9254694 10.1093/nar/25.17.3389
31. Haussler D Convolution Kernels on Discrete Structures Tech Rep UCSC-CRL-99-10 University of California, Santa Cruz 1999
32. Platt J Probabilistic outputs for support vector machines and comparison to regularized likelihood methods Advances in Large Margin Classiers MIT Press Smola A, Bartlett P, Scholkopf B, Schurmans D 1999