Multidimensional mutual information methods for the analysis of covariation in multiple sequence alignments

BMC Bioinformatics

Volumn 15, Issue 1, 2014, Pages

  Clark, Greg W ^a   Ackerman, Sharon H ^b   Tillier, Elisabeth R ^a   Gatti, Domenico L ^b  

^a UNIVERSITY OF TORONTO   (Canada)

^b WAYNE STATE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EVOLUTIONARY HISTORY; MULTIPLE SEQUENCE ALIGNMENTS; MUTUAL INFORMATION METHOD; MUTUAL INFORMATIONS; PROTEIN FAMILY; PROTEIN SEQUENCES; SIMILAR NUMBERS; X-RAY STRUCTURE;

PROTEINS;

PROTEIN;

ARTICLE; CHEMISTRY; CLASSIFICATION; METHODOLOGY; PROTEIN SECONDARY STRUCTURE; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS; STATISTICAL MODEL;

MODELS, STATISTICAL; PROTEIN STRUCTURE, SECONDARY; PROTEINS; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN;

EID: 84902081454     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-15-157     Document Type: Article

References (39)

1. Horner DS, Pirovano W, Pesole G. Correlated substitution analysis and the prediction of amino acid structural contacts. Brief Bioinform 2008, 9(1):46-56.
2. Caporaso JG, Smit S, Easton B, Hunter L, Huttley G, Knight R. Detecting coevolution without phylogenetic trees? Tree-ignorant metrics of coevolution perform as well as tree-aware metrics. BMC Evol Biol 2008, 8(1):327. 10.1186/1471-2148-8-327, 2637866, 19055758.
3. Codoner FM, Fares MA. Why should we care about molecular coevolution?. Evol Bioinform Online 2008, 4:29-38. 2614197, 19204805.
4. Ackerman SH, Tillier ER, Gatti DL. Accurate simulation and detection of coevolution signals in multiple sequence alignments. PLoS One 2012, 7(10):e47108. 10.1371/journal.pone.0047108, 3473043, 23091608.
5. de Juan D, Pazos F, Valencia A. Emerging methods in protein co-evolution. Nat Re Genet 2013, 14(4):249-261.
6. Dunn SD, Wahl LM, Gloor GB. Mutual information without the influence of phylogeny or entropy dramatically improves residue contact prediction. Bioinformatics 2008, 24(3):333-340. 10.1093/bioinformatics/btm604, 18057019.
7. Little DY, Chen L. Identification of coevolving residues and coevolution potentials emphasizing structure, bond formation and catalytic coordination in protein evolution. PLoS One 2009, 4(3):e4762. 10.1371/journal.pone.0004762, 2651771, 19274093.
8. Gloor GB, Tyagi G, Abrassart DM, Kingston AJ, Fernandes AD, Dunn SD, Brandl CJ. Functionally compensating coevolving positions are neither homoplasic nor conserved in clades. Mol Biol Evol 2010, 27(5):1181-1191. 10.1093/molbev/msq004, 20065119.
9. Burger L, van Nimwegen E. Disentangling direct from indirect co-evolution of residues in protein alignments. PLoS Comput Biol 2010, 6(1):e1000633. 10.1371/journal.pcbi.1000633, 2793430, 20052271.
10. Morcos F, Pagnani A, Lunt B, Bertolino A, Marks DS, Sander C, Zecchina R, Onuchic JN, Hwa T, Weigt M. Direct-coupling analysis of residue coevolution captures native contacts across many protein families. Proc Natl Acad Sci U S A 2011, 108(49):E1293-E1301. 10.1073/pnas.1111471108, 3241805, 22106262.
11. Marks DS, Colwell LJ, Sheridan R, Hopf TA, Pagnani A, Zecchina R, Sander C. Protein 3D structure computed from evolutionary sequence variation. PLoS One 2011, 6(12):e28766. 10.1371/journal.pone.0028766, 3233603, 22163331.
12. Hopf TA, Colwell LJ, Sheridan R, Rost B, Sander C, Marks DS. Three-dimensional structures of membrane proteins from genomic sequencing. Cell 2012, 149(7):1607-1621. 10.1016/j.cell.2012.04.012, 3641781, 22579045.
13. Marks DS, Hopf TA, Sander C. Protein structure prediction from sequence variation. Nat Biotechnol 2012, 30(11):1072-1080. 10.1038/nbt.2419, 23138306.
14. Jones DT, Buchan DW, Cozzetto D, Pontil M. PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments. Bioinformatics 2012, 28(2):184-190. 10.1093/bioinformatics/btr638, 22101153.
15. Nugent T, Jones DT. Accurate de novo structure prediction of large transmembrane protein domains using fragment-assembly and correlated mutation analysis. Proc Natl Acad Sci U S A 2012, 109(24):E1540-E1547. 10.1073/pnas.1120036109, 3386101, 22645369.
16. Balakrishnan S, Kamisetty H, Carbonell JG, Lee SI, Langmead CJ. Learning generative models for protein fold families. Proteins 2011, 79(4):1061-1078. 10.1002/prot.22934, 21268112.
17. Ekeberg M, Lovkvist C, Lan Y, Weigt M, Aurell E. Improved contact prediction in proteins: using pseudolikelihoods to infer Potts models. Phys Rev E Stat Nonlin Soft Matter Phys 2013, 87(1):012707.
18. Kamisetty H, Ovchinnikov S, Baker D. Assessing the utility of coevolution-based residue-residue contact predictions in a sequence- and structure-rich era. Proc Natl Acad Sci U S A 2013, 110(39):15674-15679. 10.1073/pnas.1314045110, 3785744, 24009338.
19. Cocco S, Monasson R, Weigt M. From principal component to direct coupling analysis of coevolution in proteins: low-eigenvalue modes are needed for structure prediction. PLoS Comput Biol 2013, 9(8):e1003176. 10.1371/journal.pcbi.1003176, 3749948, 23990764.
20. McGill WJ. Multivariate information transmission. Psychometrika 1954, 19:97-116.
21. Fano RM. Transmission of information: a statistical theory of communications 1961, Cambridge, MA: MIT Press.
22. Han TS. Multiple mutual information and multiple interactions in frequency data. Inform Contr 1980, 46:26-45.
23. Hekstra AP, Willems FMJ. Dependence balance bounds for single-output two-way channels. IEEE Trans Inform Theor 1989, 35(1):44-53.
24. Dickson RJ, Wahl LM, Fernandes AD, Gloor GB. Identifying and seeing beyond multiple sequence alignment errors using intra-molecular protein covariation. PLoS One 2010, 5(6):e11082. 10.1371/journal.pone.0011082, 2893159, 20596526.
25. Dickson RJ, Gloor GB. Protein sequence alignment analysis by local covariation: coevolution statistics detect benchmark alignment errors. PLoS One 2012, 7(6):e37645. 10.1371/journal.pone.0037645, 3371027, 22715369.
26. Bell AJ. The co-information lattice. Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Source Separation (ICA2003) 2003, L3A-6:921-926. Nara, Japan, http://www.kecl.ntt.co.jp/icl/signal/ica2003/cdrom/data/0187.pdf.
27. Ollikainen N, Kortemme T. Computational protein design quantifies structural constraints on amino acid covariation. PLoS Comput Biol 2013, 9(11):e1003313. 10.1371/journal.pcbi.1003313, 3828131, 24244128.
28. Ludlam A, Brunzelle J, Pribyl T, Xu X, Gatti DL, Ackerman SH. Chaperones of F1-ATPase. J Biol Chem 2009, 284(25):17138-17146. 10.1074/jbc.M109.002568, 2719352, 19383603.
29. Gatti DL, Palfey BA, Lah MS, Entsch B, Massey V, Ballou DP, Ludwig ML. The mobile flavin of 4-OH benzoate hydroxylase. Science 1994, 266(5182):110-114. 10.1126/science.7939628, 7939628.
30. Zhou T, Radaev S, Rosen BP, Gatti DL. Structure of the ArsA ATPase: the catalytic subunit of a heavy metal resistance pump. Embo J 2000, 19(17):4838-4845. 10.1093/emboj/19.17.4838, 302053, 10970874.
31. Gassner GT, Ludwig ML, Gatti DL, Correll CC, Ballou DP. Structure and mechanism of the iron-sulfur flavoprotein phthalate dioxygenase reductase. FASEB J 1995, 9(14):1411-1418.
32. Martin P, DeMel S, Shi J, Gladysheva T, Gatti DL, Rosen BP, Edwards BF. Insights into the structure, solvation, and mechanism of ArsC arsenate reductase, a novel arsenic detoxification enzyme. Structure 2001, 9(11):1071-1081. 10.1016/S0969-2126(01)00672-4, 11709171.
33. Radaev S, Dastidar P, Patel M, Woodard RW, Gatti DL. Structure and mechanism of 3-deoxy-D-manno-octulosonate 8-phosphate synthase. J Biol Chem 2000, 275(13):9476-9484. 10.1074/jbc.275.13.9476, 10734095.
34. Ackerman SH, Gatti DL. Biapenem inactivation by B2 metallo β-lactamases: energy landscape of the hydrolysis reaction. PLoS One 2013, 8(1):e55136. 10.1371/journal.pone.0055136, 3556986, 23372827.
35. Sukumar N, Xu Y, Gatti DL, Mitra B, Mathews FS. Structure of an active soluble mutant of the membrane-associated (S)-mandelate dehydrogenase. Biochemistry 2001, 40(33):9870-9878. 10.1021/bi010938k, 11502180.
36. Notredame C, Higgins DG, Heringa J. T-coffee: a novel method for fast and accurate multiple sequence alignment. J Mol Biol 2000, 302(1):205-217. 10.1006/jmbi.2000.4042, 10964570.
37. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 2004, 32(5):1792-1797. 10.1093/nar/gkh340, 390337, 15034147.
38. Katoh K, Misawa K, Kuma K-I, Miyata T. MAFFT: a novel method for rapid multiple sequence alignment based on fast fourier transform. Nucl Acids Res 2002, 30(14):3059-3066. 10.1093/nar/gkf436, 135756, 12136088.
39. Hsieh C-J, Sustik MA, Dhillon IS, Ravikumar P. Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation. Proceedings of the conference 'Advances in Neural Information Processing Systems 24 (NIPS 2011). Advances in Neural Information Processing Systems, vol. 24 Granada, Spain: Neural Information Processing Systems Foundation, Shawe-Taylor J, Zemel RS, Bartlett P, Pereira F, Weinberger KQ, http://papers.nips.cc/paper/4266-sparse-inverse-covariance-matrix-estimation-using-quadratic-approximation.