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Annual Review of Biophysics

Volume 49, 2020

The Role of Conformational Dynamics and Allostery in Modulating Protein Evolution

Abstract

Advances in sequencing techniques and statistical methods have made it possible not only to predict sequences of ancestral proteins but also to identify thousands of mutations in the human exome, some of which are disease associated. These developments have motivated numerous theories and raised many questions regarding the fundamental principles behind protein evolution, which have been traditionally investigated horizontally using the tip of the phylogenetic tree through comparative studies of extant proteins within a family. In this article, we review a vertical comparison of the modern and resurrected ancestral proteins. We focus mainly on the dynamical properties responsible for a protein's ability to adapt new functions in response to environmental changes. Using the Dynamic Flexibility Index and the Dynamic Coupling Index to quantify the relative flexibility and dynamic coupling at a site-specific, single-amino-acid level, we provide evidence that the migration of hinges, which are often functionally critical rigid sites, is a mechanism through which proteins can rapidly evolve. Additionally, we show that disease-associated mutations in proteins often result in flexibility changes even at positions distal from mutational sites, particularly in the modulation of active site dynamics.

Keyword(s): allostery, conformational dynamics, molecular dynamics simulation, protein design, protein evolution, protein flexibility
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2020-05-06
2024-04-25
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Literature Cited

  1. 1. 
    Abrusán G, Marsh JA. 2019. Ligand-binding-site structure shapes allosteric signal transduction and the evolution of allostery in protein complexes. Mol. Biol. Evol. 36:81711–27
     [Google Scholar]
  2. 2. 
    Agozzino L, Dill KA. 2018. Protein evolution speed depends on its stability and abundance and on chaperone concentrations. PNAS 115:379092–97
     [Google Scholar]
  3. 3. 
    Alber T. 1989. Mutational effects on protein stability. Annu. Rev. Biochem. 58:765–98
     [Google Scholar]
  4. 4. 
    Atilgan C, Gerek ZN, Ozkan SB, Atilgan AR 2010. Manipulation of conformational change in proteins by single-residue perturbations. Biophys. J. 99:3933–43
     [Google Scholar]
  5. 5. 
    Bahar I, Atilgan AR, Demirel MC, Erman B 1998. Vibrational dynamics of folded proteins: significance of slow and fast motions in relation to function and stability. Phys. Rev. Lett. 80:122733–36
     [Google Scholar]
  6. 6. 
    Bahar I, Cheng MH, Lee JY, Kaya C, Zhang S 2015. Structure-encoded global motions and their role in mediating protein-substrate interactions. Biophys. J. 109:61101–9
     [Google Scholar]
  7. 7. 
    Baier F, Hong N, Yang G, Pabis A, Miton CM et al. 2019. Cryptic genetic variation shapes the adaptive evolutionary potential of enzymes. eLife 8:e40789
     [Google Scholar]
  8. 8. 
    Ben-David M, Huang H, Sun MGF, Corbi-Verge C, Petsalaki E et al. 2019. Allosteric modulation of binding specificity by alternative packing of protein cores. J. Mol. Biol. 431:2336–50
     [Google Scholar]
  9. 9. 
    Bhabha G, Ekiert DC, Jennewein M, Zmasek CM, Tuttle LM et al. 2013. Divergent evolution of protein conformational dynamics in dihydrofolate reductase. Nat. Struct. Mol. Biol. 20:111243–49
     [Google Scholar]
  10. 10. 
    Bloom JD, Labthavikul ST, Otey CR, Arnold FH 2006. Protein stability promotes evolvability. PNAS 103:155869–74
     [Google Scholar]
  11. 11. 
    Bolia A, Gerek ZN, Keskin O, Ozkan SB, Dev KK 2012. The binding affinities of proteins interacting with the PDZ domain of PICK1. Proteins 80:51393–408
     [Google Scholar]
  12. 12. 
    Bolia A, Ozkan SB. 2016. Adaptive BP-Dock: an induced fit docking approach for full receptor flexibility. J. Chem. Inf. Model. 56:4734–46
     [Google Scholar]
  13. 13. 
    Butler BM, Gerek ZN, Kumar S, Ozkan SB 2015. Conformational dynamics of nonsynonymous variants at protein interfaces reveals disease association: the role of dynamics in neutral and damaging nsSNVs. Proteins Struct. Funct. Bioinform. 83:3428–35
     [Google Scholar]
  14. 14. 
    Butler BM, Kazan IC, Kumar A, Ozkan SB 2018. Coevolving residues inform protein dynamics profiles and disease susceptibility of nSNVs. PLOS Comput. Biol. 14:11e1006626
     [Google Scholar]
  15. 15. 
    Campbell E, Kaltenbach M, Correy GJ, Carr PD, Porebski BT et al. 2016. The role of protein dynamics in the evolution of new enzyme function. Nat. Chem. Biol. 12:11944–50
     [Google Scholar]
  16. 16. 
    Cooper A, Dryden DT. 1984. Allostery without conformational change: a plausible model. Eur. Biophys. J. 11:2103–9
     [Google Scholar]
  17. 17. 
    Copp JN, Anderson DW, Akiva E, Babbitt PC, Tokuriki N 2019. Exploring the sequence, function, and evolutionary space of protein superfamilies using sequence similarity networks and phylogenetic reconstructions. Methods Enzymol 620:315–47
     [Google Scholar]
  18. 18. 
    Coyle SM, Flores J, Lim WA 2013. Exploitation of latent allostery enables the evolution of new modes of MAP kinase regulation. Cell 154:4875–87
     [Google Scholar]
  19. 19. 
    Curado‐Carballada C, Feixas F, Osuna S 2019. Molecular dynamics simulations on Aspergillus niger monoamine oxidase: conformational dynamics and inter-monomer communication essential for its efficient catalysis. Adv. Synth. Catal. 361:112718–26
     [Google Scholar]
  20. 20. 
    Finnigan GC, Hanson-Smith V, Stevens TH, Thornton JW 2012. Evolution of increased complexity in a molecular machine. Nature 481:7381360–64
     [Google Scholar]
  21. 21. 
    Fuglebakk E, Echave J, Reuter N 2012. Measuring and comparing structural fluctuation patterns in large protein datasets. Bioinformatics 28:192431–40
     [Google Scholar]
  22. 22. 
    Geng C, Xue LC, Roel‐Touris J, Bonvin AMJJ 2019. Finding the ΔΔG spot: Are predictors of binding affinity changes upon mutations in protein-protein interactions ready for it. Wiley Interdiscip. Rev. Comput. Mol. Sci. 9:5e1410
     [Google Scholar]
  23. 23. 
    Gerek ZN, Kumar S, Ozkan SB 2013. Structural dynamics flexibility informs function and evolution at a proteome scale. Evol. Appl. 6:3423–33
     [Google Scholar]
  24. 24. 
    Gerek ZN, Ozkan SB. 2010. A flexible docking scheme to explore the binding selectivity of PDZ domains. Protein Sci 19:5914–28
     [Google Scholar]
  25. 25. 
    Gerek ZN, Ozkan SB. 2011. Change in allosteric network affects binding affinities of PDZ domains: analysis through perturbation response scanning. PLOS Comput. Biol. 7:10e1002154
     [Google Scholar]
  26. 26. 
    Gobeil SMC, Ebert MCCJC, Park J, Gagné D, Doucet N et al. 2019. The structural dynamics of engineered β-lactamases vary broadly on three timescales yet sustain native function. Sci. Rep. 9:6656
     [Google Scholar]
  27. 27. 
    Guerois R, Nielsen JE, Serrano L 2002. Predicting changes in the stability of proteins and protein complexes: a study of more than 1000 mutations. J. Mol. Biol. 320:2369–87
     [Google Scholar]
  28. 28. 
    Guo J, Zhou H-X. 2016. Protein allostery and conformational dynamics. Chem. Rev. 116:6503–15
     [Google Scholar]
  29. 29. 
    Halabi N, Rivoire O, Leibler S, Ranganathan R 2009. Protein sectors: evolutionary units of three-dimensional structure. Cell 138:4774–86
     [Google Scholar]
  30. 30. 
    Haliloglu T, Bahar I. 2015. Adaptability of protein structures to enable functional interactions and evolutionary implications. Curr. Opin. Struct. Biol. 35:17–23
     [Google Scholar]
  31. 31. 
    Hawkins RJ, McLeish TCB. 2004. Coarse-grained model of entropic allostery. Phys. Rev. Lett. 93:9098104
     [Google Scholar]
  32. 32. 
    Hilser VJ. 2010. Biochemistry: an ensemble view of allostery. Science 327:5966653–54
     [Google Scholar]
  33. 33. 
    Hobbs JK, Shepherd C, Saul DJ, Demetras NJ, Haaning S et al. 2012. On the origin and evolution of thermophily: reconstruction of functional Precambrian enzymes from ancestors of Bacillus. Mol. Biol. Evol. 29:2825–35
     [Google Scholar]
  34. 34. 
    Ingles-Prieto A, Ibarra-Molero B, Delgado-Delgado A, Perez-Jimenez R, Fernandez JM et al. 2013. Conservation of protein structure over four billion years. Structure 21:91690–97
     [Google Scholar]
  35. 35. 
    Jiménez-Osés G, Osuna S, Gao X, Sawaya MR, Gilson L et al. 2014. The role of distant mutations and allosteric regulation on LovD active site dynamics. Nat. Chem. Biol. 10:6431–36
     [Google Scholar]
  36. 36. 
    Kaltenbach M, Jackson CJ, Campbell EC, Hollfelder F, Tokuriki N 2015. Reverse evolution leads to genotypic incompatibility despite functional and active site convergence. eLife 4:e06492
     [Google Scholar]
  37. 37. 
    Keskin O, Bahar I, Jernigan RL, Beutler JA, Shoemaker RH et al. 2000. Characterization of anticancer agents by their growth inhibitory activity and relationships to mechanism of action and structure. Anticancer Drug Des 15:279–98
     [Google Scholar]
  38. 38. 
    Khersonsky O, Roodveldt C, Tawfik DS 2006. Enzyme promiscuity: evolutionary and mechanistic aspects. Curr. Opin. Chem. Biol. 10:5498–508
     [Google Scholar]
  39. 39. 
    Khersonsky O, Röthlisberger D, Dym O, Albeck S, Jackson CJ et al. 2010. Evolutionary optimization of computationally designed enzymes: Kemp eliminases of the KE07 series. J. Mol. Biol. 396:41025–42
     [Google Scholar]
  40. 40. 
    Khersonsky O, Tawfik DS. 2010. Enzyme promiscuity: a mechanistic and evolutionary perspective. Annu. Rev. Biochem. 79:471–505
     [Google Scholar]
  41. 41. 
    Kim H, Zou T, Modi C, Dörner K, Grunkemeyer TJ et al. 2015. A hinge migration mechanism unlocks the evolution of green-to-red photoconversion in GFP-like proteins. Structure 23:134–43
     [Google Scholar]
  42. 42. 
    Kimura M. 1991. The neutral theory of molecular evolution: a review of recent evidence. Idengaku Zasshi 66:4367–86
     [Google Scholar]
  43. 43. 
    Knies JL, Cai F, Weinreich DM 2017. Enzyme efficiency but not thermostability drives cefotaxime resistance evolution in TEM-1 β-lactamase. Mol. Biol. Evol. 34:51040–54
     [Google Scholar]
  44. 44. 
    Knudsen M, Wiuf C. 2010. The CATH database. Hum. Genom. 4:3207–12
     [Google Scholar]
  45. 45. 
    Köhler S, Bauer S, Horn D, Robinson PN 2008. Walking the interactome for prioritization of candidate disease genes. Am. J. Hum. Genet. 82:4949–58
     [Google Scholar]
  46. 46. 
    Kumar A, Butler BM, Kumar S, Ozkan SB 2015. Integration of structural dynamics and molecular evolution via protein interaction networks: a new era in genomic medicine. Curr. Opin. Struct. Biol. 35:135–42
     [Google Scholar]
  47. 47. 
    Kumar A, Glembo TJ, Ozkan SB 2015. The role of conformational dynamics and allostery in the disease development of human ferritin. Biophys. J. 109:61273–81
     [Google Scholar]
  48. 48. 
    Kumar S, Dudley JT, Filipski A, Liu L 2011. Phylomedicine: an evolutionary telescope to explore and diagnose the universe of disease mutations. Trends Genet 27:9377–86
     [Google Scholar]
  49. 49. 
    Kumar S, Suleski MP, Markov GJ, Lawrence S, Marco A, Filipski AJ 2009. Positional conservation and amino acids shape the correct diagnosis and population frequencies of benign and damaging personal amino acid mutations. Genome Res 19:91562–69
     [Google Scholar]
  50. 50. 
    Larrimore KE, Kazan IC, Kannan L, Kendle RP, Jamal T et al. 2017. Plant-expressed cocaine hydrolase variants of butyrylcholinesterase exhibit altered allosteric effects of cholinesterase activity and increased inhibitor sensitivity. Sci. Rep. 7:110419
     [Google Scholar]
  51. 51. 
    Li Z, Bolia A, Maxwell JD, Bobkov AA, Ghirlanda G et al. 2015. A rigid hinge region is necessary for high-affinity binding of dimannose to cyanovirin and associated constructs. Biochemistry 54:466951–60
     [Google Scholar]
  52. 52. 
    Liang Z, Verkhivker GM, Hu G 2019. Integration of network models and evolutionary analysis into high-throughput modeling of protein dynamics and allosteric regulation: theory, tools and applications. Brief. Bioinform. In press
    [Google Scholar]
  53. 53. 
    Liberles DA, Teichmann SA, Bahar I, Bastolla U, Bloom J et al. 2012. The interface of protein structure, protein biophysics, and molecular evolution. Protein Sci 21:6769–85
     [Google Scholar]
  54. 54. 
    Lieberman RL, Wustman BA, Huertas P, Powe AC, Pine CW et al. 2007. Structure of acid β-glucosidase with pharmacological chaperone provides insight into Gaucher disease. Nat. Chem. Biol. 3:2101–7
     [Google Scholar]
  55. 55. 
    Liu X, Golden LC, Lopez JA, Shepherd TR, Yu L, Fuentes EJ 2019. Conformational dynamics and cooperativity drive the specificity of a protein-ligand interaction. Biophys. J. 116:122314–30
     [Google Scholar]
  56. 56. 
    Liu Y, Bahar I. 2012. Sequence evolution correlates with structural dynamics. Mol. Biol. Evol. 29:92253–63
     [Google Scholar]
  57. 57. 
    Liu Y, Gierasch LM, Bahar I 2010. Role of Hsp70 ATPase domain intrinsic dynamics and sequence evolution in enabling its functional interactions with NEFs. PLOS Comput. Biol. 6:9e1000931
     [Google Scholar]
  58. 58. 
    Lynch M, Ackerman MS, Gout J-F, Long H, Sung W et al. 2016. Genetic drift, selection and the evolution of the mutation rate. Nat. Rev. Genet. 17:11704–14
     [Google Scholar]
  59. 59. 
    Maguid S, Fernandez-Alberti S, Echave J 2008. Evolutionary conservation of protein vibrational dynamics. Gene 422:1–27–13
     [Google Scholar]
  60. 60. 
    Maguid S, Fernández-Alberti S, Parisi G, Echave J 2006. Evolutionary conservation of protein backbone flexibility. J. Mol. Evol. 63:4448–57
     [Google Scholar]
  61. 61. 
    McLeish TCB, Rodgers TL, Wilson MR 2013. Allostery without conformation change: modelling protein dynamics at multiple scales. Phys. Biol. 10:5056004
     [Google Scholar]
  62. 62. 
    McLeish TCB, Schaefer C, von der Heydt AC 2018. The ‘allosteron’ model for entropic allostery of self-assembly. Philos. Trans. R. Soc. B 373:174920170186
     [Google Scholar]
  63. 63. 
    Mikulska-Ruminska K, Shrivastava I, Krieger J, Zhang S, Li H et al. 2019. Characterization of differential dynamics, specificity, and allostery of lipoxygenase family members. J. Chem. Inf. Model. 59:52496–508
     [Google Scholar]
  64. 64. 
    Miller M, Bromberg Y, Swint-Kruse L 2017. Computational predictors fail to identify amino acid substitution effects at rheostat positions. Sci. Rep. 7:41329
     [Google Scholar]
  65. 65. 
    Mishra SK, Jernigan RL. 2018. Protein dynamic communities from elastic network models align closely to the communities defined by molecular dynamics. PLOS ONE 13:6e0199225
     [Google Scholar]
  66. 66. 
    Mishra SK, Kandoi G, Jernigan RL 2019. Coupling dynamics and evolutionary information with structure to identify protein regulatory and functional binding sites. Proteins Struct. Funct. Bioinform. 87:10850–68
     [Google Scholar]
  67. 67. 
    Modi T, Huihui J, Ghosh K, Ozkan SB 2018. Ancient thioredoxins evolved to modern-day stability-function requirement by altering native state ensemble. Philos. Trans. R. Soc. B 373:174920170184
     [Google Scholar]
  68. 68. 
    Modi T, Ozkan SB. 2018. Mutations utilize dynamic allostery to confer resistance in TEM-1 β-lactamase. Int. J. Mol. Sci. 19:123808
     [Google Scholar]
  69. 69. 
    Morley KL, Kazlauskas RJ. 2005. Improving enzyme properties: When are closer mutations better. Trends Biotechnol 23:5231–37
     [Google Scholar]
  70. 70. 
    Moult J. 2008. Comparative modeling in structural genomics. Structure 16:114–16
     [Google Scholar]
  71. 71. 
    Navlakha S, Kingsford C. 2010. The power of protein interaction networks for associating genes with diseases. Bioinformatics 26:81057–63
     [Google Scholar]
  72. 72. 
    Nei M, Kumar S. 2000. Molecular Evolution and Phylogenetics Oxford, UK: Oxford Univ. Press
  73. 73. 
    Neuwald AF. 2007. The CHAIN program: forging evolutionary links to underlying mechanisms. Trends Biochem. Sci. 32:11487–93
     [Google Scholar]
  74. 74. 
    Nussinov R, Tsai C-J. 2013. Allostery in disease and in drug discovery. Cell 153:2293–305
     [Google Scholar]
  75. 75. 
    Nussinov R, Tsai C-J, Liu J 2014. Principles of allosteric interactions in cell signaling. J. Am. Chem. Soc. 136:5117692–701
     [Google Scholar]
  76. 76. 
    Otten R, Liu L, Kenner LR, Clarkson MW, Mavor D et al. 2018. Rescue of conformational dynamics in enzyme catalysis by directed evolution. Nat. Commun. 9:1314
     [Google Scholar]
  77. 77. 
    Patel R, Scheinfeldt LB, Sanderford MD, Lanham TR, Tamura K et al. 2018. Adaptive landscape of protein variation in human exomes. Mol. Biol. Evol. 35:82015–25
     [Google Scholar]
  78. 78. 
    Pauling L, Zuckerkandl E, Henriksen T, Lövstad R 1963. Chemical paleogenetics: molecular “restoration studies” of extinct forms of life. Acta Chem. Scand. 17:Suppl.9–16
     [Google Scholar]
  79. 79. 
    Penkler D, Sensoy Ö, Atilgan C, Tastan Bishop Ö 2017. Perturbation-response scanning reveals key residues for allosteric control in Hsp70. J. Chem. Inf. Model. 57:61359–74
     [Google Scholar]
  80. 80. 
    Perez-Jimenez R, Inglés-Prieto A, Zhao Z-M, Sanchez-Romero I, Alegre-Cebollada J et al. 2011. Single-molecule paleoenzymology probes the chemistry of resurrected enzymes. Nat. Struct. Mol. Biol. 18:5592–96
     [Google Scholar]
  81. 81. 
    Ponzoni L, Bahar I. 2018. Structural dynamics is a determinant of the functional significance of missense variants. PNAS 115:164164–69
     [Google Scholar]
  82. 82. 
    Ponzoni L, Zhang S, Cheng MH, Bahar I 2018. Shared dynamics of LeuT superfamily members and allosteric differentiation by structural irregularities and multimerization. Philos. Trans. R. Soc. B 373:174920170177
     [Google Scholar]
  83. 83. 
    Risso VA, Gavira JA, Mejia-Carmona DF, Gaucher EA, Sanchez-Ruiz JM 2013. Hyperstability and substrate promiscuity in laboratory resurrections of Precambrian β-lactamases. J. Am. Chem. Soc. 135:82899–902
     [Google Scholar]
  84. 84. 
    Risso VA, Manssour-Triedo F, Delgado-Delgado A, Arco R, Barroso-delJesus A et al. 2015. Mutational studies on resurrected ancestral proteins reveal conservation of site-specific amino acid preferences throughout evolutionary history. Mol. Biol. Evol. 32:2440–55
     [Google Scholar]
  85. 85. 
    Risso VA, Sanchez-Ruiz JM. 2017. Resurrected ancestral proteins as scaffolds for protein engineering. Directed Enzyme Evolution: Advances and Applications M Alcalde 229–55 Berlin: Springer
     [Google Scholar]
  86. 86. 
    Risso VA, Sanchez-Ruiz JM, Ozkan SB 2018. Biotechnological and protein-engineering implications of ancestral protein resurrection. Curr. Opin. Struct. Biol. 51:106–15
     [Google Scholar]
  87. 87. 
    Rocks JW, Ronellenfitsch H, Liu AJ, Nagel SR, Katifori E 2019. Limits of multifunctionality in tunable networks. PNAS 116:72506–11
     [Google Scholar]
  88. 88. 
    Romero-Romero ML, Risso VA, Martinez-Rodriguez S, Ibarra-Molero B, Sanchez-Ruiz JM 2016. Engineering ancestral protein hyperstability. Biochem. J. 473:203611–20
     [Google Scholar]
  89. 89. 
    Saavedra HG, Wrabl JO, Anderson JA, Li J, Hilser VJ 2018. Dynamic allostery can drive cold adaptation in enzymes. Nature 558:7709324–28
     [Google Scholar]
  90. 90. 
    Sahni N, Yi S, Taipale M, Fuxman Bass JI, Coulombe-Huntington J et al. 2015. Widespread macromolecular interaction perturbations in human genetic disorders. Cell 161:3647–60
     [Google Scholar]
  91. 91. 
    Sethi A, O'Donoghue P, Luthey-Schulten Z 2005. Evolutionary profiles from the QR factorization of multiple sequence alignments. PNAS 102:114045–50
     [Google Scholar]
  92. 92. 
    Socolich M, Lockless SW, Russ WP, Lee H, Gardner KH, Ranganathan R 2005. Evolutionary information for specifying a protein fold. Nature 437:7058512–18
     [Google Scholar]
  93. 93. 
    Subramanian S, Kumar S. 2006. Evolutionary anatomies of positions and types of disease-associated and neutral amino acid mutations in the human genome. BMC Genom 7:306
     [Google Scholar]
  94. 94. 
    Swint-Kruse L. 2016. Using evolution to guide protein engineering: The devil IS in the details. Biophys. J. 111:110–18
     [Google Scholar]
  95. 95. 
    Tan L, Serene S, Chao HX, Gore J 2011. Hidden randomness between fitness landscapes limits reverse evolution. Phys. Rev. Lett. 106:19198102
     [Google Scholar]
  96. 96. 
    Tawfik DS, Tokuriki N. 2009. Protein dynamism and evolvability. Science 324:5924203–7
     [Google Scholar]
  97. 97. 
    Taylor JL, Price JE, Toney MD 2015. Directed evolution of the substrate specificity of dialkylglycine decarboxylase. Biochim. Biophys. Acta Proteins Proteom. 1854:2146–55
     [Google Scholar]
  98. 98. 
    Thirumalai D, Hyeon C, Zhuravlev PI, Lorimer GH 2019. Symmetry, rigidity, and allosteric signaling: from monomeric proteins to molecular machines. Chem. Rev. 119:126788–821
     [Google Scholar]
  99. 99. 
    Tokuriki N, Tawfik DS. 2009. Stability effects of mutations and protein evolvability. Curr. Opin. Struct. Biol. 19:5596–604
     [Google Scholar]
  100. 100. 
    Townsend PD, Rodgers TL, Glover LC, Korhonen HJ, Richards SA et al. 2015. The role of protein-ligand contacts in allosteric regulation of the Escherichia coli catabolite activator protein. J. Biol. Chem. 290:3622225–35
     [Google Scholar]
  101. 101. 
    Tuncbag N, Gursoy A, Keskin O 2009. Identification of computational hot spots in protein interfaces: Combining solvent accessibility and inter-residue potentials improves the accuracy. Bioinformatics 25:121513–20
     [Google Scholar]
  102. 102. 
    Turner JM, Graziano J, Spraggon G, Schultz PG 2006. Structural plasticity of an aminoacyl-tRNA synthetase active site. PNAS 103:176483–88
     [Google Scholar]
  103. 103. 
    Wang S-W, Bitbol A-F, Wingreen NS 2019. Revealing evolutionary constraints on proteins through sequence analysis. PLOS Comput. Biol. 15:4e1007010
     [Google Scholar]
  104. 104. 
    Wang X, Wei X, Thijssen B, Das J, Lipkin SM, Yu H 2012. Three-dimensional reconstruction of protein networks provides insight into human genetic disease. Nat. Biotechnol. 30:2159–64
     [Google Scholar]
  105. 105. 
    Wei G, Xi W, Nussinov R, Ma B 2016. Protein ensembles: How does nature harness thermodynamic fluctuations for life? The diverse functional roles of conformational ensembles in the cell. Chem. Rev. 116:116516–51
     [Google Scholar]
  106. 106. 
    Weinreich DM, Delaney NF, Depristo MA, Hartl DL 2006. Darwinian evolution can follow only very few mutational paths to fitter proteins. Science 312:5770111–14
     [Google Scholar]
  107. 107. 
    Wilding M, Hong N, Spence M, Buckle AM, Jackson CJ 2019. Protein engineering: the potential of remote mutations. Biochem. Soc. Trans. 47:2701–11
     [Google Scholar]
  108. 108. 
    Wodak SJ, Paci E, Dokholyan NV, Berezovsky IN, Horovitz A et al. 2019. Allostery in its many disguises: from theory to applications. Structure 27:4566–78
     [Google Scholar]
  109. 109. 
    Woldeyes RA, Sivak DA, Fraser JS 2014. E pluribus unum, no more: from one crystal, many conformations. Curr. Opin. Struct. Biol. 28:156–62
     [Google Scholar]
  110. 110. 
    Yang G, Hong N, Baier F, Jackson CJ, Tokuriki N 2016. Conformational tinkering drives evolution of a promiscuous activity through indirect mutational effects. Biochemistry 55:324583–93
     [Google Scholar]
  111. 111. 
    Yue P, Li Z, Moult J 2005. Loss of protein structure stability as a major causative factor in monogenic disease. J. Mol. Biol. 353:2459–73
     [Google Scholar]
  112. 112. 
    Zhang S, Li H, Krieger JM, Bahar I 2019. Shared signature dynamics tempered by local fluctuations enables fold adaptability and specificity. Mol. Biol. Evol. 36:92053–68
     [Google Scholar]
  113. 113. 
    Zheng W, Brooks BR, Doniach S, Thirumalai D 2005. Network of dynamically important residues in the open/closed transition in polymerases is strongly conserved. Structure 13:4565–77
     [Google Scholar]
  114. 114. 
    Zheng W, Brooks BR, Thirumalai D 2006. Low-frequency normal modes that describe allosteric transitions in biological nanomachines are robust to sequence variations. PNAS 103:207664–69
     [Google Scholar]
  115. 115. 
    Zou T, Risso VA, Gavira JA, Sanchez-Ruiz JM, Ozkan SB 2015. Evolution of conformational dynamics determines the conversion of a promiscuous generalist into a specialist enzyme. Mol. Biol. Evol. 32:1132–43
     [Google Scholar]
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The Role of Conformational Dynamics and Allostery in Modulating Protein Evolution
Annual Review of Biophysics 49, 267 (2020); https://doi.org/10.1146/annurev-biophys-052118-115517
/content/journals/10.1146/annurev-biophys-052118-115517
/content/journals/10.1146/annurev-biophys-052118-115517
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