Optimal data collection for correlated mutation analysis

Proteins: Structure, Function and Bioinformatics

Volumn 74, Issue 3, 2009, Pages 545-555

  Ashkenazy, Haim ^a,b   Unger, Ron ^b   Kliger, Yossef ^a  

^a Compugen LTD ^*  (Israel)

^b BAR ILAN UNIVERSITY   (Israel)

Author keywords

Ab initio structure prediction; Contact prediction; Correlated mutations; Protein structure prediction; Residue covariation

Indexed keywords

PROTEIN;

AB INITIO CALCULATION; ARTICLE; CORRELATION ANALYSIS; MUTATIONAL ANALYSIS; ORTHOLOGY; PARALOGY; PREDICTION; PRIORITY JOURNAL; PROTEIN DETERMINATION; SEQUENCE ALIGNMENT; ANIMAL; CHEMISTRY; COMPUTER SIMULATION; GENETICS; HUMAN; INFORMATION PROCESSING; METHODOLOGY; MUTATION; PROTEIN DATABASE; SEQUENCE ANALYSIS;

ANIMALS; COMPUTER SIMULATION; DATA COLLECTION; DATABASES, PROTEIN; HUMANS; MUTATION; PROTEINS; SEQUENCE ANALYSIS, PROTEIN;

EID: 59849106575     PISSN: 08873585     EISSN: 10970134     Source Type: Journal    
DOI: 10.1002/prot.22168     Document Type: Article

References (47)

1. Gobel U, Sander C, Schneider R, Valencia A. Correlated mutations and residue contacts in proteins. Proteins 1994; 18:309-317.
2. Choi SS, Li W, Lahn BT. Robust signals of coevolution of interacting residues in mammalian proteomes identified by phylogeny- aided structural analysis. Nat Genet 2005; 37:1367-1371.
3. Eyal E, Frenkel-Morgenstern M, Sobolev V, Pietrokovski S. A pair- to-pair amino acids substitution matrix and its applications for protein structure prediction. Proteins 2007; 67:142-153.
4. Fleishman SJ, Yifrach O, Ben-Tal N. An evolutionarily conserved network of mino acids mediates gating in voltage-dependent potassium channels. J Mol Biol 2004; 340:307-318.
5. Kass I, Horovitz A. Mapping pathways of allosteric communication in GroEL by analysis of correlated mutations. Proteins 2002; 48:611-617.
6. Martin LC, Gloor GB, Dunn SD, Wahl LM. Using information theory to search for co-evolving residues in proteins. Bioinformatics 2005; 21:4116-4124.
7. Singer MS, Vriend G, Bywater RP. Prediction of protein residue contacts with a PDB-derived likelihood matrix. Protein Eng 2002; 15:721-725.
8. Fariselli P, Olmea O, Valencia A, Casadio R. Progress in predicting inter-residue contacts of proteins with neural networks and correlated mutations. Proteins 2001; Suppl 5:157-162.
9. Halperin I, Wolfson H, Nussinov R. Correlated mutations: advances and limitations. A study on fusion proteins and on the Cohesin-Dockerin families. Proteins 2006; 63:832-845.
10. Noivirt O, Eisenstein M, Horovitz A. Detection and reduction of evolutionary noise in correlated mutation analysis. Protein Eng Des Sel 2005; 18:247-253.
11. Dimmic MW, Hubisz MJ, Bustamante CD, Nielsen R. Detecting coevolving amino acid sites using Bayesian mutational mapping. Bioinformatics 2005; 21 (Suppl 1):i126-i135.
12. Dutheil J, Pupko T, Jean-Marie A, Galtier N. A model-based approach for detecting coevolving positions in a molecule. Mol Biol Evol 2005; 22:1919-1928.
13. Gloor GB, Martin LC, Wahl LM, Dunn SD. Mutual information in protein multiple sequence alignments reveals two classes of coevolving positions. Biochemistry 2005; 44:7156-7165.
14. Wollenberg KR, Atchley WR. Separation of phylogenetic and functional associations in biological sequences by using the parametric bootstrap. Proc Natl Acad Sci USA 2000; 97:3288-3291.
15. Dunn SD, Wahl LM, Gloor GB. Mutual information without the influence of phylogeny or entropy dramatically improves residue contact prediction. Bioinformatics 2008; 24:333-340.
16. Fodor AA, Aldrich RW. Influence of conservation on calculations of amino acid covariance in multiple sequence alignments. Proteins 2004; 56:211-221.
17. Pazos F, Olmea O, Valencia A. A graphical interface for correlated mutations and other protein structure prediction methods. Comput Appl Biosci 1997; 13:319-321.
18. McLachlan AD. Tests for comparing related amino-acid sequences. Cytochrome c and cytochrome c 551. J Mol Biol 1971; 61:409-424.
19. Olmea O, Valencia A. Improving contact predictions by the combination of correlated mutations and other sources of sequence information. Fold Des 1997; 2:S25-S32.
20. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997; 25:3389-3402.
21. Kundrotas PJ, Alexov EG. Predicting residue contacts using pragmatic correlated mutations method: reducing the false positives. BMC Bioinformatics 2006; 7:503.
22. Perez-Jimenez R, Godoy-Ruiz R, Parody-Morreale A, Ibarra-Molero B, Sanchez-Ruiz JM. A simple tool to explore the distance distribution of correlated mutations in proteins. Biophys Chem 2006; 119:240-246.
23. Pazos F, Helmer-Citterich M, Ausiello G, Valencia A. Correlated mutations contain information about protein-protein interaction. J Mol Biol 1997; 271:511-523.
24. Vicatos S, Reddy BV, Kaznessis Y. Prediction of distant residue contacts with the use of evolutionary information. Proteins 2005; 58:935-949.
25. Wang G, Dunbrack RL, Jr. PISCES: a protein sequence culling server. Bioinformatics 2003; 19:1589-1591.
26. Izarzugaza JM, Grana O, Tress ML, Valencia A, Clarke ND. Assessment of intramolecular contact predictions for CASP7. Proteins 2007; 69:152-158.
27. Grana O, Baker D, MacCallum RM, Meiler J, Punta M, Rost B, Tress ML, Valencia A. CASP6 assessment of contact prediction. Proteins 2005; 61 (Suppl 7):214-224.
28. Ortiz AR, Kolinski A, Rotkiewicz P, Ilkowski B, Skolnick J. Ab initio folding of proteins using restraints derived from evolutionary information. Proteins 1999; 37:177-185.
29. Olmea O, Rost B, Valencia A. Effective use of sequence correlation and conservation in fold recognition. J Mol Biol 1999; 293:1221-1239.
30. Cheng J, Baldi P. A machine learning information retrieval approach to protein fold recognition. Bioinformatics 2006; 22:1456-1463.
31. Grana O, Eyrich VA, Pazos F, Rost B, Valencia A. EVAcon: a protein contact prediction evaluation service. Nucleic Acids Res 2005; 33 (Web Server issue):W347-W351.
32. Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Wheeler DL. GenBank. Nucleic Acids Res 2006; 34 (Database issue):D16-D20.
33. 33.Holm L, Sander C. Removing near-neighbour redundancy from large protein sequence collections. Bioinformatics 1998; 14:423-429.
34. Do CB, Mahabhashyam MS, Brudno M, Batzoglou S. ProbCons:probabilistic consistency-based multiple sequence alignment. Genome Res 2005; 15:330-340.
35. Katoh K, Kuma K, Toh H, Miyata T. MAFFT version 5: improvement in accuracy of multiple sequence alignment. Nucleic Acids Res 2005; 33:511-518.
36. Schwartz AS, Pachter L. Multiple alignment by sequence annealing. Bioinformatics 2007; 23:e24-e29.
37. Wallace IM, O'Sullivan O, Higgins DG, Notredame C. M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res 2006; 34:1692-1699.
38. Dekker JP, Fodor A, Aldrich RW, Yellen G. A perturbation-based method for calculating explicit likelihood of evolutionary co- variance in multiple sequence alignments. Bioinformatics 2004; 20: 1565-1572.
39. Shackelford G, Karplus K. Contact prediction using mutual information and neural nets. Proteins 2007; 69 (Suppl 8):159-164.
40. Boeckmann B, Bairoch A, Apweiler R, Blatter MC, Estreicher A, Gasteiger E, Martin MJ, Michoud K, O'Donovan C, Phan I, Pilbout S, Schneider M. The SWISS-PROT protein knowledgebase and its supplement TrEMBL in 2003. Nucleic Acids Res 2003; 31:365-370.
41. Release 8.3 UniProtKB/Swiss-Prot Headlines: of mice and men: over 10,000 orthologous sequence pairs in UniProtKB/Swiss-Prot. 2006. http://www.uniprot. org/news/2006/07/11/release
42. Finn RD, Mistry J, Schuster-Bockler B, Griffiths-Jones S, Hollich V, Lassmann T, Moxon S, Marshall M, Khanna A, Durbin R, Eddy SR, Sonnhammer EL, Bateman A. Pfam: clans, web tools and services. Nucleic Acids Res 2006; 34 (Database issue):D247-D251.
43. Nuin PAS, Wang Z, Tillier ERM. The accuracy of several multiple sequence alignment programs for proteins. BMC Bioinformatics 2006; 7:471.
44. Stajich JE, Block D, Boulez K, Brenner SE, Chervitz SA, Dagdigian C, Fuellen G, Gilbert JG, Korf I, Lapp H, Lehvaslaiho H, Matsalla C, Mungall CJ, Osborne BI, Pocock MR, Schattner P, Senger M, Stein LD, Stupka E, Wilkinson MD, Birney E. The Bioperl toolkit: Perl modules for the life sciences. Genome Res 2002; 12:1611-1618.
45. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The protein data bank. Nucl Acids Res 2000; 28:235-242.
46. Sobolev V, Sorokine A, Prilusky J, Abola EE, Edelman M. Automated analysis of interatomic contacts in proteins. Bioinformatics 1999; 15:327-332.
47. Jesse D, Mark G. The relationship between Precision-Recall and ROC curves. Proceedings of the 23rd international conference on Machine learning. Pittsburgh, Pennsylvania: ACM; 2006.