Allostery pp 385-398 | Cite as

A Critical Evaluation of Correlated Mutation Algorithms and Coevolution Within Allosteric Mechanisms

  • Dennis R. Livesay
  • Kyle E. Kreth
  • Anthony A. Fodor
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 796)

Abstract

The notion of using the evolutionary history encoded within multiple sequence alignments to predict allosteric mechanisms is appealing. In this approach, correlated mutations are expected to reflect coordinated changes that maintain intramolecular coupling between residue pairs. Despite much early fanfare, the general suitability of correlated mutations to predict allosteric couplings has not yet been established. Lack of progress along these lines has been hindered by several algorithmic limitations including phylogenetic artifacts within alignments masking true covariance and the computational intractability of consideration of more than two correlated residues at a time. Recent progress in algorithm development, however, has been substantial with a new generation of correlated mutation algorithms that have made fundamental progress toward solving these difficult problems. Despite these encouraging results, there remains little evidence to suggest that the evolutionary constraints acting on allosteric couplings are sufficient to be recovered from multiple sequence alignments. In this review, we argue that due to the exquisite sensitivity of protein dynamics, and hence that of allosteric mechanisms, the latter vary widely within protein families. If it turns out to be generally true that even very similar homologs display a wide divergence of allosteric mechanisms, then even a perfect correlated mutation algorithm could not be reliably used as a general mechanism for discovery of allosteric pathways.

Key words

Allostery Thermodynamic coupling Correlated mutation Covariance Coevolution Mutual information 

Notes

Acknowledgments

The authors would like to thank Richard W. Aldrich and Gregory B. Gloor for helpful comments on the manuscript, and Donald J. Jacobs for numerous insightful discussions related to the correlated mutation algorithms, allostery, and the relationships therein.

References

  1. 1.
    Horovitz, A., Bochkareva, E. S., Yifrach, O., and Girshovich, A. S. (1994). Prediction of an inter-residue interaction in the chaperonin GroEL from multiple sequence alignment is confirmed by double-mutant cycle analysis. J Mol Biol 238, 133–8.PubMedCrossRefGoogle Scholar
  2. 2.
    Lockless, S. W., and Ranganathan, R. (1999). Evolutionarily conserved pathways of energetic connectivity in protein families. Science 286, 295–9.PubMedCrossRefGoogle Scholar
  3. 3.
    Fodor, A. A., and Aldrich, R. W. (2004). On evolutionary conservation of thermodynamic coupling in proteins. J Biol Chem 279, 19046–50.PubMedCrossRefGoogle Scholar
  4. 4.
    Chi, C. N., Elfstrom, L., Shi, Y., Snall, T., Engstrom, A., and Jemth, P. (2008). Reassessing a sparse energetic network within a single protein domain. Proc Natl Acad Sci U S A 105, 4679–84.PubMedCrossRefGoogle Scholar
  5. 5.
    Liu, Z., Chen, J., and Thirumalai, D. (2009). On the accuracy of inferring energetic coupling between distant sites in protein families from evolutionary imprints: illustrations using lattice model. Proteins 77, 823–31.PubMedCrossRefGoogle Scholar
  6. 6.
    Jensen, R. A., and Stenmark, S. L. (1970). Comparative allostery of 3-deoxy-D-arabino-heptulosonate-7-phosphate synthetase as a molecular basis for classification. J Bacteriol 101, 763–9.PubMedGoogle Scholar
  7. 7.
    Jensen, A. A., and Spalding, T. A. (2004). Allosteric modulation of G-protein coupled receptors. Eur J Pharm Sci 21, 407–20.PubMedCrossRefGoogle Scholar
  8. 8.
    May, L. T., Avlani, V. A., Sexton, P. M., and Christopoulos, A. (2004). Allosteric modulation of G protein-coupled receptors. Curr Pharm Des 10, 2003–13.PubMedCrossRefGoogle Scholar
  9. 9.
    Hudson, J. W., Golding, G. B., and Crerar, M. M. (1993). Evolution of allosteric control in glycogen phosphorylase. J Mol Biol 234, 700–21.PubMedCrossRefGoogle Scholar
  10. 10.
    Royer, W. E., Jr., Knapp, J. E., Strand, K., and Heaslet, H. A. (2001). Cooperative hemoglobins: conserved fold, diverse quaternary assemblies and allosteric mechanisms. Trends Biochem Sci 26, 297–304.PubMedCrossRefGoogle Scholar
  11. 11.
    Royer, W. E., Jr., Zhu, H., Gorr, T. A., Flores, J. F., and Knapp, J. E. (2005). Allosteric hemoglobin assembly: diversity and similarity. J Biol Chem 280, 27477–80.PubMedCrossRefGoogle Scholar
  12. 12.
    Chakrabarti, S., and Panchenko, A. R. (2009). Coevolution in defining the functional specificity. Proteins 75, 231–40.PubMedCrossRefGoogle Scholar
  13. 13.
    del Sol, A., Tsai, C. J., Ma, B., and Nussinov, R. (2009). The origin of allosteric functional modulation: multiple pre-existing pathways. Structure 17, 1042–50.PubMedCrossRefGoogle Scholar
  14. 14.
    Cui, Q., and Karplus, M. (2008). Allostery and cooperativity revisited. Protein Sci 17, 1295–307.PubMedCrossRefGoogle Scholar
  15. 15.
    Formaneck, M. S., Ma, L., and Cui, Q. (2006). Reconciling the “old” and “new” views of protein allostery: a molecular simulation study of chemotaxis Y protein (CheY). Proteins 63, 846–67.PubMedCrossRefGoogle Scholar
  16. 16.
    Ashkenazy, H., and Kliger, Y. Reducing phylogenetic bias in correlated mutation analysis. Protein Eng Des Sel 23, 321–6.Google Scholar
  17. 17.
    Fodor, A. A., and Aldrich, R. W. (2004). Influence of conservation on calculations of amino acid covariance in multiple sequence alignments. Proteins 56, 211–21.PubMedCrossRefGoogle Scholar
  18. 18.
    Wollenberg, K. R., and Atchley, W. R. (2000). Separation of phylogenetic and functional associations in biological sequences by using the parametric bootstrap. Proc Natl Acad Sci U S A 97, 3288–91.PubMedCrossRefGoogle Scholar
  19. 19.
    Noivirt, O., Eisenstein, M., and Horovitz, A. (2005). Detection and reduction of evolutionary noise in correlated mutation analysis. Protein Eng Des Sel 18, 247–53.PubMedCrossRefGoogle Scholar
  20. 20.
    Dimmic, M. W., Hubisz, M. J., Bustamante, C. D., and Nielsen, R. (2005). Detecting coevolving amino acid sites using Bayesian mutational mapping. Bioinformatics 21 Suppl 1, i126-35.PubMedCrossRefGoogle Scholar
  21. 21.
    Dutheil, J., Pupko, T., Jean-Marie, A., and Galtier, N. (2005). A model-based approach for detecting coevolving positions in a molecule. Mol Biol Evol 22, 1919–28.PubMedCrossRefGoogle Scholar
  22. 22.
    Ashkenazy, H., Unger, R., and Kliger, Y. (2009). Optimal data collection for correlated mutation analysis. Proteins 74, 545–55.PubMedCrossRefGoogle Scholar
  23. 23.
    Vicatos, S., Reddy, B. V., and Kaznessis, Y. (2005). Prediction of distant residue contacts with the use of evolutionary information. Proteins 58, 935–49.PubMedCrossRefGoogle Scholar
  24. 24.
    Kundrotas, P. J., and Alexov, E. G. (2006). Predicting residue contacts using pragmatic correlated mutations method: reducing the false positives. BMC Bioinformatics 7, 503.PubMedCrossRefGoogle Scholar
  25. 25.
    Dunn, S. D., Wahl, L. M., and Gloor, G. B. (2008). Mutual information without the influence of phylogeny or entropy dramatically improves residue contact prediction. Bioinformatics 24, 333–40.PubMedCrossRefGoogle Scholar
  26. 26.
    Dickson, R. J., Wahl, L. M., Fernandes, A. D., and Gloor, G. B. (2010). Identifying and Seeing beyond Multiple Sequence Alignment Errors Using Intra-Molecular Protein Covariation. PLoS One 5, e11082.PubMedCrossRefGoogle Scholar
  27. 27.
    Little, D. Y., and Chen, L. (2009). Identification of coevolving residues and coevolution potentials emphasizing structure, bond formation and catalytic coordination in protein evolution. PLoS One 4, e4762.PubMedCrossRefGoogle Scholar
  28. 28.
    Edgar, R. C., and Batzoglou, S. (2006). Multiple sequence alignment. Curr Opin Struct Biol 16, 368–73.PubMedCrossRefGoogle Scholar
  29. 29.
    Martin, L. C., Gloor, G. B., Dunn, S. D., and Wahl, L. M. (2005). Using information theory to search for co-evolving residues in proteins. Bioinformatics 21, 4116–24.PubMedCrossRefGoogle Scholar
  30. 30.
    Weil, P., Hoffgaard, F., and Hamacher, K. (2009). Estimating sufficient statistics in co-evolutionary analysis by mutual information. Comput Biol Chem 33, 440–4.PubMedCrossRefGoogle Scholar
  31. 31.
    Buslje, C. M., Santos, J., Delfino, J. M., and Nielsen, M. (2009). Correction for phylogeny, small number of observations and data redundancy improves the identification of coevolving amino acid pairs using mutual information. Bioinformatics 25, 1125–31.PubMedCrossRefGoogle Scholar
  32. 32.
    Fernandes, A. D., and Gloor, G. B. Mutual information is critically dependent on prior assumptions: would the correct estimate of mutual information please identify itself? Bioinformatics 26, 1135–9.Google Scholar
  33. 33.
    Brown, C. A., and Brown, K. S. Validation of coevolving residue algorithms via pipeline sensitivity analysis: ELSC and OMES and ZNMI, oh my! PLoS One 5, e10779.Google Scholar
  34. 34.
    Burger, L., and van Nimwegen, E. Disentangling direct from indirect co-evolution of residues in protein alignments. PLoS Comput Biol 6, e1000633.Google Scholar
  35. 35.
    Weigt, M., White, R. A., Szurmant, H., Hoch, J. A., and Hwa, T. (2009). Identification of direct residue contacts in protein-protein interaction by message passing. Proc Natl Acad Sci U S A 106, 67–72.PubMedCrossRefGoogle Scholar
  36. 36.
    Gobel, U., Sander, C., Schneider, R., and Valencia, A. (1994). Correlated mutations and residue contacts in proteins. Proteins 18, 309–17.PubMedCrossRefGoogle Scholar
  37. 37.
    Clarke, N. D. (1995). Covariation of residues in the homeodomain sequence family. Protein Sci 4, 2269–78.PubMedCrossRefGoogle Scholar
  38. 38.
    Mildvan, A. S., Weber, D. J., and Kuliopulos, A. (1992). Quantitative interpretations of double mutations of enzymes. Arch Biochem Biophys 294, 327–40.PubMedCrossRefGoogle Scholar
  39. 39.
    Gloor, G. B., Martin, L. C., Wahl, L. M., and Dunn, S. D. (2005). Mutual information in protein multiple sequence alignments reveals two classes of coevolving positions. Biochemistry 44, 7156–65.PubMedCrossRefGoogle Scholar
  40. 40.
    Istomin, A. Y., Gromiha, M. M., Vorov, O. K., Jacobs, D. J., and Livesay, D. R. (2008). New insight into long-range nonadditivity within protein double-mutant cycles. Proteins 70, 915–24.PubMedCrossRefGoogle Scholar
  41. 41.
    Suel, G. M., Lockless, S. W., Wall, M. A., and Ranganathan, R. (2003). Evolutionarily conserved networks of residues mediate allosteric communication in proteins. Nat Struct Biol 10, 59–69.PubMedCrossRefGoogle Scholar
  42. 42.
    Halabi, N., Rivoire, O., Leibler, S., and Ranganathan, R. (2009). Protein sectors: evolutionary units of three-dimensional structure. Cell 138, 774–86.PubMedCrossRefGoogle Scholar
  43. 43.
    Kuriyan, J., and Eisenberg, D. (2007). The origin of protein interactions and allostery in colocalization. Nature 450, 983–90.PubMedCrossRefGoogle Scholar
  44. 44.
    Fenton, A. W. (2008). Allostery: an illustrated definition for the ‘second secret of life’. Trends Biochem Sci 33, 420–5.PubMedCrossRefGoogle Scholar
  45. 45.
    Koshland, D. E. (1958). Application of a Theory of Enzyme Specificity to Protein Synthesis. Proc Natl Acad Sci U S A 44, 98–104.PubMedCrossRefGoogle Scholar
  46. 46.
    Yu, E. W., and Koshland, D. E., Jr. (2001). Propagating conformational changes over long (and short) distances in proteins. Proc Natl Acad Sci U S A 98, 9517–20.PubMedCrossRefGoogle Scholar
  47. 47.
    Ottemann, K. M., Xiao, W., Shin, Y. K., and Koshland, D. E., Jr. (1999). A piston model for transmembrane signaling of the aspartate receptor. Science 285, 1751–4.PubMedCrossRefGoogle Scholar
  48. 48.
    Swain, J. F., and Gierasch, L. M. (2006). The changing landscape of protein allostery. Curr Opin Struct Biol 16, 102–8.PubMedCrossRefGoogle Scholar
  49. 49.
    Kumar, S., Ma, B., Tsai, C. J., Sinha, N., and Nussinov, R. (2000). Folding and binding cascades: dynamic landscapes and population shifts. Protein Sci 9, 10–9.PubMedCrossRefGoogle Scholar
  50. 50.
    Monod, J., Wyman, J., and Changeux, J. P. (1965). On the Nature of Allosteric Transitions: a Plausible Model. J Mol Biol 12, 88–118.PubMedCrossRefGoogle Scholar
  51. 51.
    Gunasekaran, K., Ma, B., and Nussinov, R. (2004). Is allostery an intrinsic property of all dynamic proteins? Proteins 57, 433–43.PubMedCrossRefGoogle Scholar
  52. 52.
    Bruschweiler, S., Schanda, P., Kloiber, K., Brutscher, B., Kontaxis, G., Konrat, R., and Tollinger, M. (2009). Direct observation of the dynamic process underlying allosteric signal transmission. J Am Chem Soc 131, 3063–8.PubMedCrossRefGoogle Scholar
  53. 53.
    Schlegel, J., Armstrong, G. S., Redzic, J. S., Zhang, F., and Eisenmesser, E. Z. (2009). Characterizing and controlling the inherent dynamics of cyclophilin-A. Protein Sci 18, 811–24.PubMedGoogle Scholar
  54. 54.
    Lee, A. L., Kinnear, S. A., and Wand, A. J. (2000). Redistribution and loss of side chain entropy upon formation of a calmodulin-peptide complex. Nat Struct Biol 7, 72–7.PubMedCrossRefGoogle Scholar
  55. 55.
    Mau, T., Baleja, J. D., and Wagner, G. (1992). Effects of DNA binding and metal substitution on the dynamics of the GAL4 DNA-binding domain as studied by amide proton exchange. Protein Sci 1, 1403–12.PubMedCrossRefGoogle Scholar
  56. 56.
    Forman, B. M., Umesono, K., Chen, J., and Evans, R. M. (1995). Unique response pathways are established by allosteric interactions among nuclear hormone receptors. Cell 81, 541–50.PubMedCrossRefGoogle Scholar
  57. 57.
    Conigrave, A. D., and Franks, A. H. (2003). Allosteric activation of plasma membrane receptors--physiological implications and structural origins. Prog Biophys Mol Biol 81, 219–40.PubMedCrossRefGoogle Scholar
  58. 58.
    Hardy, J. A., and Wells, J. A. (2004). Searching for new allosteric sites in enzymes. Curr Opin Struct Biol 14, 706–15.PubMedCrossRefGoogle Scholar
  59. 59.
    Pendergrass, D. C., Williams, R., Blair, J. B., and Fenton, A. W. (2006). Mining for allosteric information: natural mutations and positional sequence conservation in pyruvate kinase. IUBMB Life 58, 31–8.PubMedCrossRefGoogle Scholar
  60. 60.
    Fodor, A. A., Black, K. D., and Zagotta, W. N. (1997). Tetracaine reports a conformational change in the pore of cyclic nucleotide-gated channels. J Gen Physiol 110, 591–600.PubMedCrossRefGoogle Scholar
  61. 61.
    Mottonen, J.M., Jacobs, D. J., and Livesay, D. R. (2010). Allosteric response is both conserved and variable across three CheY orthologs. Biophys J 99, 2245–2254.PubMedCrossRefGoogle Scholar
  62. 62.
    Whitaker, R. J., Byng, G. S., Gherna, R. L., and Jensen, R. A. (1981). Comparative allostery of 3-deoxy-D-arabino-heptulosonate 7-phosphate synthetase as an indicator of taxonomic relatedness in pseudomonad genera. J Bacteriol 145, 752–9.PubMedGoogle Scholar
  63. 63.
    Jensen, R. A., and Twarog, R. (1972). Allostery of 3-deoxy-D-arabino-heptulosonate 7-phosphate synthetase in Clostridium: another conserved generic characteristic. J Bacteriol 111, 641–8.PubMedGoogle Scholar
  64. 64.
    Halperin, I., Wolfson, H., and Nussinov, R. (2006). Correlated mutations: advances and limitations. A study on fusion proteins and on the Cohesin-Dockerin families. Proteins 63, 832–45.PubMedCrossRefGoogle Scholar
  65. 65.
    McLachlan, A. D. (1971). Tests for comparing related amino-acid sequences. Cytochrome c and cytochrome c 551. J Mol Biol 61, 409–24.PubMedCrossRefGoogle Scholar
  66. 66.
    Atchley, W. R., Wollenberg, K. R., Fitch, W. M., Terhalle, W., and Dress, A. W. (2000). Correlations among amino acid sites in bHLH protein domains: an information theoretic analysis. Mol Biol Evol 17, 164–78.PubMedGoogle Scholar
  67. 67.
    Hatley, M. E., Lockless, S. W., Gibson, S. K., Gilman, A. G., and Ranganathan, R. (2003). Allosteric determinants in guanine nucleotide-binding proteins. Proc Natl Acad Sci U S A 100, 14445–50.PubMedCrossRefGoogle Scholar
  68. 68.
    Kass, I., and Horovitz, A. (2002). Mapping pathways of allosteric communication in GroEL by analysis of correlated mutations. Proteins 48, 611–7.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Dennis R. Livesay
    • 1
  • Kyle E. Kreth
    • 1
  • Anthony A. Fodor
    • 1
  1. 1.Department of Bioinformatics and GenomicsUniversity of North Carolina at CharlotteCharlotteUSA

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