Conformational changes in nucleic acids play a key role in the way genetic information is stored, transferred, and processed in living cells. Here, we describe new approaches that employ a broad range of experimental data, including NMR-derived chemical shifts and residual dipolar couplings, small-angle X-ray scattering, and computational approaches such as molecular dynamics simulations to determine ensembles of DNA and RNA at atomic resolution. We review the complementary information that can be obtained from diverse sets of data and the various methods that have been developed to combine these data with computational methods to construct ensembles and assess their uncertainty. We conclude by surveying RNA and DNA ensembles determined using these methods, highlighting the unique physical and functional insights obtained so far.

Keyword(s): Au-SAXSchemical shiftsDNANMRRDCRNASAXS

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Literature Cited

  1. Dethoff EA, Chugh J, Mustoe AM, Al-Hashimi HM. 1.  2012. Functional complexity and regulation through RNA dynamics. Nature 482:322–30 [Google Scholar]
  2. Cruz JA, Westhof E. 2.  2009. The dynamic landscapes of RNA architecture. Cell 136:604–9 [Google Scholar]
  3. Fuxreiter M, Simon I, Bondos S. 3.  2011. Dynamic protein-DNA recognition: beyond what can be seen. Trends Biochem. Sci. 36:415–23 [Google Scholar]
  4. Perez A, Luque FJ, Orozco M. 4.  2012. Frontiers in molecular dynamics simulations of DNA. Acc. Chem. Res. 45:196–205 [Google Scholar]
  5. Woodson SA. 5.  2008. RNA folding and ribosome assembly. Curr. Opin. Chem. Biol. 12:667–73 [Google Scholar]
  6. Cooper TA, Wan L, Dreyfuss G. 6.  2009. RNA and disease. Cell 136:777–93 [Google Scholar]
  7. Hermann T. 7.  2002. Rational ligand design for RNA: the role of static structure and conformational flexibility in target recognition. Biochimie 84:869–75 [Google Scholar]
  8. Chang AL, Wolf JJ, Smolke CD. 8.  2012. Synthetic RNA switches as a tool for temporal and spatial control over gene expression. Curr. Opin. Biotechnol. 23:679–88 [Google Scholar]
  9. Frauenfelder H, Sligar SG, Wolynes PG. 9.  1991. The energy landscapes and motions of proteins. Science 254:1598–603 [Google Scholar]
  10. Rambo RP, Tainer JA. 10.  2010. Bridging the solution divide: comprehensive structural analyses of dynamic RNA, DNA, and protein assemblies by small-angle X-ray scattering. Curr. Opin. Struct. Biol. 20:128–37 [Google Scholar]
  11. Koch MHJ, Vachette P, Svergun DI. 11.  2003. Small-angle scattering: a view on the properties, structures and structural changes of biological macromolecules in solution. Q. Rev. Biophys. 36:147–227 [Google Scholar]
  12. Putnam CD, Hammel M, Hura GL, Tainer JA. 12.  2007. X-ray solution scattering (SAXS) combined with crystallography and computation: defining accurate macromolecular structures, conformations and assemblies in solution. Q. Rev. Biophys. 40:191–285 [Google Scholar]
  13. Fang X, Littrell K, Yang XJ, Henderson SJ, Siefert S. 13.  et al. 2000. Mg2+-dependent compaction and folding of yeast tRNAPhe and the catalytic domain of the B. subtilis RNase P RNA determined by small-angle X-ray scattering. Biochemistry 39:11107–13 [Google Scholar]
  14. Stovgaard K, Andreetta C, Ferkinghoff-Borg J, Hamelryck T. 14.  2010. Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models. BMC Bioinforma. 11:429 [Google Scholar]
  15. Schwieters CD, Clore GM. 15.  2007. A physical picture of atomic motions within the Dickerson DNA dodecamer in solution derived from joint ensemble refinement against NMR and large-angle X-ray scattering data. Biochemistry 46:1152–66 [Google Scholar]
  16. Svergun D, Barberato C, Koch MHJ. 16.  1995. CRYSOL: a program to evaluate X-ray solution scattering of biological macromolecules from atomic coordinates. J. Appl. Crystallogr. 28:768–73 [Google Scholar]
  17. Yang S, Blachowicz L, Makowski L, Roux B. 17.  2010. Multidomain assembled states of Hck tyrosine kinase in solution. Proc. Natl. Acad. Sci. USA 107:15757–62 [Google Scholar]
  18. Wang YX, Zuo X, Wang J, Yu P, Butcher SE. 18.  2010. Rapid global structure determination of large RNA and RNA complexes using NMR and small-angle X-ray scattering. Methods 52:180–91 [Google Scholar]
  19. Burke JE, Butcher SE. 19.  2012. Nucleic acid structure characterization by small angle X-ray scattering (SAXS). Curr. Protoc. Nucleic Acid Chem. 2012:7.18 [Google Scholar]
  20. Grishaev A, Ying J, Canny MD, Pardi A, Bax A. 20.  2008. Solution structure of tRNAVal from refinement of homology model against residual dipolar coupling and SAXS data. J. Biomol. NMR 42:99–109 [Google Scholar]
  21. Mathew-Fenn RS, Das R, Silverman JA, Walker PA, Harbury PA. 21.  2008. A molecular ruler for measuring quantitative distance distributions. PLoS One 3:e3229 [Google Scholar]
  22. Mathew-Fenn RS, Das R, Harbury PA. 22.  2008. Remeasuring the double helix. Science 322:446–49 [Google Scholar]
  23. Shi X, Herschlag D, Harbury PA. 23.  2013. Structural ensemble and microscopic elasticity of freely diffusing DNA by direct measurement of fluctuations. Proc. Natl. Acad. Sci. USA 110:E1444–51 [Google Scholar]
  24. Mastroianni AJ, Sivak DA, Geissler PL, Alivisatos AP. 24.  2009. Probing the conformational distributions of subpersistence length DNA. Biophys. J. 97:1408–17 [Google Scholar]
  25. Bernado P, Mylonas E, Petoukhov MV, Blackledge M, Svergun DI. 25.  2007. Structural characterization of flexible proteins using small-angle X-ray scattering. J. Am. Chem. Soc. 129:5656–64 [Google Scholar]
  26. Sosnick TR, Woodson SA. 26.  2011. New era of molecular structure and dynamics from solution scattering experiments. Biopolymers 95:503–4 [Google Scholar]
  27. Lu Y, Jeffries CM, Trewhella J. 27.  2011. Invited review: probing the structures of muscle regulatory proteins using small-angle solution scattering. Biopolymers 95:505–16 [Google Scholar]
  28. Caliskan G, Briber RM, Thirumalai D, Garcia-Sakai V, Woodson SA, Sokolov AP. 28.  2006. Dynamic transition in tRNA is solvent induced. J. Am. Chem. Soc. 128:32–33 [Google Scholar]
  29. Roh JH, Tyagi M, Briber RM, Woodson SA, Sokolov AP. 29.  2011. The dynamics of unfolded versus folded tRNA: the role of electrostatic interactions. J. Am. Chem. Soc. 133:16406–9 [Google Scholar]
  30. Lam SL, Chi LM. 30.  2010. Use of chemical shifts for structural studies of nucleic acids. Prog. Nucl. Magn. Reson. Spectrosc. 56:289–310 [Google Scholar]
  31. Jensen MR, Salmon L, Nodet G, Blackledge M. 31.  2010. Defining conformational ensembles of intrinsically disordered and partially folded proteins directly from chemical shifts. J. Am. Chem. Soc. 132:1270–72 [Google Scholar]
  32. Robustelli P, Kohlhoff K, Cavalli A, Vendruscolo M. 32.  2010. Using NMR chemical shifts as structural restraints in molecular dynamics simulations of proteins. Structure 18:923–33 [Google Scholar]
  33. Cromsigt J, van Buuren B, Schleucher J, Wijmenga S. 33.  2001. Resonance assignment and structure determination for RNA. Methods Enzymol. 338:371–99 [Google Scholar]
  34. Wijmenga SS, Kruithof M, Hilbers CW. 34.  1997. Analysis of 1H chemical shifts in DNA: assessment of the reliability of 1H chemical shift calculations for use in structure refinement. J. Biomol. NMR 10:337–50 [Google Scholar]
  35. Barton S, Heng X, Johnson BA, Summers MF. 35.  2013. Database proton NMR chemical shifts for RNA signal assignment and validation. J. Biomol. NMR 55:33–46 [Google Scholar]
  36. Frank AT, Horowitz S, Andricioaei I, Al-Hashimi HM. 36.  2013. Utility of 1H NMR chemical shifts in determining RNA structure and dynamics. J. Phys. Chem. B 117:2045–52 [Google Scholar]
  37. Sitkoff D, Case DA. 37.  1998. Theories of chemical shift anisotropies in proteins and nucleic acids. Prog. Nucl. Magn. Reson. Spectrosc. 32:165–90 [Google Scholar]
  38. Suardiaz R, Sahakyan AB, Vendruscolo M. 38.  2013. A geometrical parametrization of C1′-C5′ RNA ribose chemical shifts calculated by density functional theory. J. Chem. Phys. 139:034101 [Google Scholar]
  39. Tolman JR, Flanagan JM, Kennedy MA, Prestegard JH. 39.  1995. Nuclear magnetic dipole interactions in field-oriented proteins: information for structure determination in solution. Proc. Natl. Acad. Sci. USA 92:9279–83 [Google Scholar]
  40. Tolman JR, Flanagan JM, Kennedy MA, Prestegard JH. 40.  1997. NMR evidence for slow collective motions in cyanometmyoglobin. Nat. Struct. Biol. 4:292–97 [Google Scholar]
  41. Hansen MR, Mueller L, Pardi A. 41.  1998. Tunable alignment of macromolecules by filamentous phage yields dipolar coupling interactions. Nat. Struct. Biol. 5:1065–74 [Google Scholar]
  42. Clore GM, Starich MR, Gronenborn AM. 42.  1998. Measurement of residual dipolar couplings of macromolecules aligned in the nematic phase of a colloidal suspension of rod-shaped viruses. J. Am. Chem. Soc. 120:10571–72 [Google Scholar]
  43. Tjandra N, Bax A. 43.  1997. Direct measurement of distances and angles in biomolecules by NMR in a dilute liquid crystalline medium. Science 278:1111–14 [Google Scholar]
  44. Blackledge M. 44.  2005. Recent progress in the study of biomolecular structure and dynamics in solution from residual dipolar couplings. Prog. Nucl. Magn. Res. Spectrosc. 46:23–61 [Google Scholar]
  45. Tolman JR, Ruan K. 45.  2006. NMR residual dipolar couplings as probes of biomolecular dynamics. Chem. Rev. 106:1720–36 [Google Scholar]
  46. Getz M, Sun X, Casiano-Negroni A, Zhang Q, Al-Hashimi HM. 46.  2007. Review NMR studies of RNA dynamics and structural plasticity using NMR residual dipolar couplings. Biopolymers 86:384–402 [Google Scholar]
  47. Bothe JR, Nikolova EN, Eichhorn CD, Chugh J, Hansen AL, Al-Hashimi HM. 47.  2011. Characterizing RNA dynamics at atomic resolution using solution-state NMR spectroscopy. Nat. Methods 8:919–31 [Google Scholar]
  48. Zweckstetter M, Bax A. 48.  2000. Predicition of sterically induced alignment in a dilute liquid crystalline phase: aid to protein structure determination by NMR. J. Am. Chem. Soc. 122:3791–92 [Google Scholar]
  49. Zhang Q, Stelzer AC, Fisher CK, Al-Hashimi HM. 49.  2007. Visualizing spatially correlated dynamics that directs RNA conformational transitions. Nature 450:1263–67 [Google Scholar]
  50. Zhang Q, Sun X, Watt ED, Al-Hashimi HM. 50.  2006. Resolving the motional modes that code for RNA adaptation. Science 311:653–56 [Google Scholar]
  51. Musselman C, Pitt SW, Gulati K, Foster LL, Andricioaei I, Al-Hashimi HM. 51.  2006. Impact of static and dynamic A-form heterogeneity on the determination of RNA global structural dynamics using NMR residual dipolar couplings. J. Biomol. NMR 36:235–49 [Google Scholar]
  52. Ramirez BE, Bax A. 52.  1998. Modulation of the alignment tensor of macromolecules dissolved in a dilute liquid crystalline medium. J. Am. Chem. Soc. 120:9106–7 [Google Scholar]
  53. Peti W, Meiler J, Bruschweiler R, Griesinger C. 53.  2002. Model-free analysis of protein backbone motion from residual dipolar couplings. J. Am. Chem. Soc. 124:5822–33 [Google Scholar]
  54. Al-Hashimi HM, Majumdar A, Gorin A, Kettani A, Skripkin E, Patel DJ. 54.  2001. Field- and phage-induced dipolar couplings in a homodimeric DNA quadruplex, relative orientation of G·(C-A) triad and G-tetrad motifs and direct determination of C2 symmetry axis orientation. J. Am. Chem. Soc. 123:633–40 [Google Scholar]
  55. Latham MP, Hanson P, Brown DJ, Pardi A. 55.  2008. Comparison of alignment tensors generated for native tRNAVal using magnetic fields and liquid crystalline media. J. Biomol. NMR 40:83–94 [Google Scholar]
  56. Dethoff EA, Hansen AL, Zhang Q, Al-Hashimi HM. 56.  2010. Variable helix elongation as a tool to modulate RNA alignment and motional couplings. J. Magn. Reson. 202:117–21 [Google Scholar]
  57. Bardaro MF Jr, Varani G. 57.  2012. Independent alignment of RNA for dynamic studies using residual dipolar couplings. J. Biomol. NMR 54:69–80 [Google Scholar]
  58. Ottiger M, Tjandra N, Bax A. 58.  1997. Magnetic field dependent amide 15N chemical shifts in a protein-DNA complex resulting from magnetic ordering in solution. J. Am. Chem. Soc. 119:9825–30 [Google Scholar]
  59. Cornilescu G, Bax A. 59.  2000. Measurement of proton, nitrogen, and carbonyl chemical shielding anisotropies in a protein dissolved in a dilute liquid crystalline phase. J. Am. Chem. Soc. 122:10143–54 [Google Scholar]
  60. Wu ZR, Tjandra N, Bax A. 60.  2001. 31P chemical shift anisotropy as an aid in determining nucleic acid structure in liquid crystals. J. Am. Chem. Soc. 123:3617–18 [Google Scholar]
  61. Hansen AL, Al-Hashimi HM. 61.  2006. Insight into the CSA tensors of nucleobase carbons in RNA polynucleotides from solution measurements of residual CSA: towards new long-range orientational constraints. J. Magn. Reson. 179:299–307 [Google Scholar]
  62. Ying J, Grishaev A, Bryce DL, Bax A. 62.  2006. Chemical shift tensors of protonated base carbons in helical RNA and DNA from NMR relaxation and liquid crystal measurements. J. Am. Chem. Soc. 128:11443–54 [Google Scholar]
  63. Wijmenga SS, van Buuren BNM. 63.  1998. The use of NMR methods for conformational studies of nucleic acids. Prog. Nucl. Magn. Reson. Spectrosc. 32:287–387 [Google Scholar]
  64. Furtig B, Richter C, Wohnert J, Schwalbe H. 64.  2003. NMR spectroscopy of RNA. Chembiochem 4:936–62 [Google Scholar]
  65. Lindorff-Larsen K, Best RB, DePristo MA, Dobson CM, Vendruscolo M. 65.  2005. Simultaneous determination of protein structure and dynamics. Nature 433:128–32 [Google Scholar]
  66. Iwahara J, Clore GM. 66.  2006. Detecting transient intermediates in macromolecular binding by paramagnetic NMR. Nature 440:1227–30 [Google Scholar]
  67. Salmon L, Nodet G, Ozenne V, Yin G, Jensen MR. 67.  et al. 2010. NMR characterization of long-range order in intrinsically disordered proteins. J. Am. Chem. Soc. 132:8407–18 [Google Scholar]
  68. Blackledge MJ, Bruschweiler R, Griesinger C, Schmidt JM, Xu P, Ernst RR. 68.  1993. Conformational backbone dynamics of the cyclic decapeptide antamanide: application of a new multiconformational search algorithm based on NMR data. Biochemistry 32:10960–74 [Google Scholar]
  69. Vögeli B, Kazemi S, Güntert P, Riek R. 69.  2012. Spatial elucidation of motion in proteins by ensemble-based structure calculation using exact NOEs. Nat. Struct. Mol. Biol. 19:1053–57 [Google Scholar]
  70. Palmer AG 3rd, Massi F. 70.  2006. Characterization of the dynamics of biomacromolecules using rotating-frame spin relaxation NMR spectroscopy. Chem. Rev. 106:1700–19 [Google Scholar]
  71. Sekhar A, Kay LE. 71.  2013. NMR paves the way for atomic level descriptions of sparsely populated, transiently formed biomolecular conformers. Proc. Natl. Acad. Sci. USA 110:12867–74 [Google Scholar]
  72. Nikolova EN, Kim E, Wise AA, O'Brien PJ, Andricioaei I, Al-Hashimi HM. 72.  2011. Transient Hoogsteen base pairs in canonical duplex DNA. Nature 470:498–502 [Google Scholar]
  73. Dethoff EA, Petzold K, Chugh J, Casiano-Negroni A, Al-Hashimi HM. 73.  2012. Visualizing transient low-populated structures of RNA. Nature 491:724–28 [Google Scholar]
  74. Al-Hashimi HM, Walter NG. 74.  2008. RNA dynamics: It is about time. Curr. Opin. Struct. Biol. 18:321–29 [Google Scholar]
  75. Walter NG, Harris DA, Pereira MJ, Rueda D. 75.  2001. In the fluorescent spotlight: global and local conformational changes of small catalytic RNAs. Biopolymers 61:224–42 [Google Scholar]
  76. Qin PZ, Dieckmann T. 76.  2004. Application of NMR and EPR methods to the study of RNA. Curr. Opin. Struct. Biol. 14:350–59 [Google Scholar]
  77. Krstic I, Endeward B, Margraf D, Marko A, Prisner TF. 77.  2012. Structure and dynamics of nucleic acids. Top. Curr. Chem. 321:159–98 [Google Scholar]
  78. Bokinsky G, Zhuang X. 78.  2005. Single-molecule RNA folding. Acc. Chem. Res. 38:566–73 [Google Scholar]
  79. Zhuang X. 79.  2005. Single-molecule RNA science. Annu. Rev. Biophys. Biomol. Struct. 34:399–414 [Google Scholar]
  80. Schiemann O, Piton N, Mu Y, Stock G, Engels JW, Prisner TF. 80.  2004. A PELDOR-based nanometer distance ruler for oligonucleotides. J. Am. Chem. Soc. 126:5722–29 [Google Scholar]
  81. Schiemann O, Weber A, Edwards TE, Prisner TF, Sigurdsson ST. 81.  2003. Nanometer distance measurements on RNA using PELDOR. J. Am. Chem. Soc. 125:3434–35 [Google Scholar]
  82. Weber A, Schiemann O, Bode B, Prisner TF. 82.  2002. PELDOR at S- and X-band frequencies and the separation of exchange coupling from dipolar coupling. J. Magn. Reson. 157:277–85 [Google Scholar]
  83. Solomatin SV, Greenfeld M, Chu S, Herschlag D. 83.  2010. Multiple native states reveal persistent ruggedness of an RNA folding landscape. Nature 463:681–84 [Google Scholar]
  84. Weeks KM. 84.  2010. Advances in RNA structure analysis by chemical probing. Curr. Opin. Struct. Biol. 20:295–304 [Google Scholar]
  85. Kladwang W, VanLang CC, Cordero P, Das R. 85.  2011. A two-dimensional mutate-and-map strategy for non-coding RNA structure. Nat. Chem. 3:954–62 [Google Scholar]
  86. Showalter SA, Bruschweiler R. 86.  2007. Quantitative molecular ensemble interpretation of NMR dipolar couplings without restraints. J. Am. Chem. Soc. 129:4158–59 [Google Scholar]
  87. Li D-W, Bruschweiler R. 87.  2010. NMR-based protein potentials. Angew. Chem. Int. Ed. Engl. 49:6778–80 [Google Scholar]
  88. Chen AA, Pappu RV. 88.  2007. Parameters of monovalent ions in the AMBER-99 forcefield: assessment of inaccuracies and proposed improvements. J. Phys. Chem. B 111:11884–87 [Google Scholar]
  89. Sim AY, Minary P, Levitt M. 89.  2012. Modeling nucleic acids. Curr. Opin. Struct. Biol. 22:273–78 [Google Scholar]
  90. Chu VB, Bai Y, Lipfert J, Herschlag D, Doniach S. 90.  2008. A repulsive field: advances in the electrostatics of the ion atmosphere. Curr. Opin. Chem. Biol. 12:619–25 [Google Scholar]
  91. Torda AE, Scheek RM, van Gunsteren WF. 91.  1989. Time-dependent distance restraints in molecular-dynamics simulations. Chem. Phys. Lett. 157:289–94 [Google Scholar]
  92. Nilges M, Gronenborn AM, Brunger AT, Clore GM. 92.  1988. Determination of three-dimensional structures of proteins by simulated annealing with interproton distance restraints: application to crambin, potato carboxypeptidase inhibitor and barley serine proteinase inhibitor 2. Protein Eng. 2:27–38 [Google Scholar]
  93. Bewley CA, Gustafson KR, Boyd MR, Covell DG, Bax A. 93.  et al. 1998. Solution structure of cyanovirin-N, a potent HIV-inactivating protein. Nat. Struct. Biol. 5:571–78 [Google Scholar]
  94. Clore GM, Gronenborn AM. 94.  1998. New methods of structure refinement for macromolecular structure determination by NMR. Proc. Natl. Acad. Sci. USA 95:5891–98 [Google Scholar]
  95. Lange OF, Lakomek NA, Fares C, Schroder GF, Walter KF. 95.  et al. 2008. Recognition dynamics up to microseconds revealed from an RDC-derived ubiquitin ensemble in solution. Science 320:1471–75 [Google Scholar]
  96. Allison JR, Varnai P, Dobson CM, Vendruscolo M. 96.  2009. Determination of the free energy landscape of α-synuclein using spin label nuclear magnetic resonance measurements. J. Am. Chem. Soc. 131:18314–26 [Google Scholar]
  97. Roux B, Islam SM. 97.  2013. Restrained-ensemble molecular dynamics simulations based on distance histograms from double electron-electron resonance spectroscopy. J. Phys. Chem. B 117:4733–39 [Google Scholar]
  98. Borkar AN, De Simone A, Montalvao RW, Vendruscolo M. 98.  2013. A method of determining RNA conformational ensembles using structure-based calculations of residual dipolar couplings. J. Chem. Phys. 138:215103 [Google Scholar]
  99. Markwick PRL, Nilges M. 99.  2012. Computational approaches to the interpretation of NMR data for studying protein dynamics. Chem. Phys. 396:124–34 [Google Scholar]
  100. Chen Y, Campbell SL, Dokholyan NV. 100.  2007. Deciphering protein dynamics from NMR data using explicit structure sampling and selection. Biophys. J. 93:2300–6 [Google Scholar]
  101. Salmon L, Bascom G, Andricioaei I, Al-Hashimi HM. 101.  2013. A general method for constructing atomic-resolution RNA ensembles using NMR residual dipolar couplings: the basis for interhelical motions revealed. J. Am. Chem. Soc. 135:5457–66 [Google Scholar]
  102. Frank AT, Stelzer AC, Al-Hashimi HM, Andricioaei I. 102.  2009. Constructing RNA dynamical ensembles by combining MD and motionally decoupled NMR RDCs: new insights into RNA dynamics and adaptive ligand recognition. Nucleic Acids Res. 37:3670–79 [Google Scholar]
  103. Eichhorn CD, Feng J, Suddala KC, Walter NG, Brooks CL 3rd, Al-Hashimi HM. 103.  2012. Unraveling the structural complexity in a single-stranded RNA tail: implications for efficient ligand binding in the prequeuosine riboswitch. Nucleic Acids Res. 40:1345–55 [Google Scholar]
  104. Bai Y, Chu VB, Lipfert J, Pande VS, Herschlag D, Doniach S. 104.  2008. Critical assessment of nucleic acid electrostatics via experimental and computational investigation of an unfolded state ensemble. J. Am. Chem. Soc. 130:12334–41 [Google Scholar]
  105. Guerry P, Salmon L, Mollica L, Ortega-Roldan J-L, Markwick P. 105.  et al. 2013. Mapping the population of protein conformational energy sub-states from NMR dipolar couplings. Angew. Chem. Int. Ed. Engl. 52:3181–85 [Google Scholar]
  106. Nodet G, Salmon L, Ozenne V, Meier S, Jensen MR, Blackledge M. 106.  2009. Quantitative description of backbone conformational sampling of unfolded proteins at amino acid resolution from NMR residual dipolar couplings. J. Am. Chem. Soc. 131:17908–18 [Google Scholar]
  107. Markwick PRL, Bouvignies G, Salmon L, McCammon JA, Nilges M, Blackledge M. 107.  2009. Toward a unified representation of protein structural dynamics in solution. J. Am. Chem. Soc. 131:16968–75 [Google Scholar]
  108. Salmon L, Pierce L, Grimm A, Ortega-Roldan J-L, Mollica L. 108.  et al. 2012. Multi-timescale conformational dynamics of the SH3 domain of CD2-associated protein using NMR spectroscopy and accelerated molecular dynamics. Angew. Chem. Int. Ed. Engl. 51:6103–6 [Google Scholar]
  109. Guerry P, Mollica L, Blackledge M. 109.  2013. Mapping protein conformational energy landscapes using NMR and molecular simulation. Chemphyschem 14:3046–58 [Google Scholar]
  110. Granata D, Camilloni C, Vendruscolo M, Laio A. 110.  2013. Characterization of the free-energy landscapes of proteins by NMR-guided metadynamics. Proc. Natl. Acad. Sci. USA 110:6817–22 [Google Scholar]
  111. Shan Y, Salmon L, Hashimi HM. 111.  2013. Measuring similarity between dynamic ensembles of biomolecules. Submitted manuscript
  112. Stelzer AC, Frank AT, Bailor MH, Andricioaei I, Al-Hashimi HM. 112.  2009. Constructing atomic-resolution RNA structural ensembles using MD and motionally decoupled NMR RDCs. Methods 49:167–73 [Google Scholar]
  113. Bertini I, Giachetti A, Luchinat C, Parigi G, Petoukhov MV. 113.  et al. 2010. Conformational space of flexible biological macromolecules from average data. J. Am. Chem. Soc. 132:13553–58 [Google Scholar]
  114. Fisher CK, Huang A, Stultz CM. 114.  2010. Modeling intrinsically disordered proteins with Bayesian statistics. J. Am. Chem. Soc. 132:14919–27 [Google Scholar]
  115. Clore GM, Garrett DS. 115.  1999. R-factor, free R, and complete cross-validation for dipolar coupling refinement of NMR structures. J. Am. Chem. Soc. 121:9008–12 [Google Scholar]
  116. Best RB, Vendruscolo M. 116.  2004. Determination of protein structures consistent with NMR order parameters. J. Am. Chem. Soc. 126:8090–91 [Google Scholar]
  117. Simone A, Richter B, Salvatella X, Vendruscolo M. 117.  De 2009. Toward an accurate determination of free energy landscapes in solution states of proteins. J. Am. Chem. Soc. 131:3810–11 [Google Scholar]
  118. Richter B, Gsponer J, Várnai P, Salvatella X, Vendruscolo M. 118.  2007. The MUMO (minimal under-restraining minimal over-restraining) method for the determination of native state ensembles of proteins. J. Biomol. NMR 37:117–35 [Google Scholar]
  119. Zhou SK, Chellappa R. 119.  2006. From sample similarity to ensemble similarity: probabilistic distance measures in reproducing kernel Hilbert space. IEEE Trans. Pattern Anal. Mach. Intell. 28:917–29 [Google Scholar]
  120. Tucker BJ, Breaker RR. 120.  2005. Riboswitches as versatile gene control elements. Curr. Opin. Struct. Biol. 15:342–48 [Google Scholar]
  121. Stoddard CD, Montange RK, Hennelly SP, Rambo RP, Sanbonmatsu KY, Batey RT. 121.  2010. Free state conformational sampling of the SAM-I riboswitch aptamer domain. Structure 18:787–97 [Google Scholar]
  122. Brunger AT, Adams PD, Clore GM, DeLano WL, Gros P. 122.  et al. 1998. Crystallography & NMR system: a new software suite for macromolecular structure determination. Acta Crystallogr. D 54:905–21 [Google Scholar]
  123. Bailor MH, Sun X, Al-Hashimi HM. 123.  2010. Topology links RNA secondary structure with global conformation, dynamics, and adaptation. Science 327:202–6 [Google Scholar]
  124. Chu VB, Lipfert J, Bai Y, Pande VS, Doniach S, Herschlag D. 124.  2009. Do conformational biases of simple helical junctions influence RNA folding stability and specificity?. RNA 15:2195–205 [Google Scholar]
  125. Mustoe AM, Bailor MH, Teixeira RM, Brooks CL 3rd, Al-Hashimi HM. 125.  2012. New insights into the fundamental role of topological constraints as a determinant of two-way junction conformation. Nucleic Acids Res. 40:892–904 [Google Scholar]
  126. Bailor MH, Mustoe AM, Brooks CL 3rd, Al-Hashimi HM. 126.  2011. Topological constraints: using RNA secondary structure to model 3D conformation, folding pathways, and dynamic adaptation. Curr. Opin. Struct. Biol. 21:296–305 [Google Scholar]
  127. MacKerell AD, Banavali N, Foloppe N. 127.  2000. Development and current status of the CHARMM force field for nucleic acids. Biopolymers 56:257–65 [Google Scholar]
  128. Stelzer AC, Frank AT, Kratz JD, Swanson MD, Gonzalez-Hernandez MJ. 128.  et al. 2011. Discovery of selective bioactive small molecules by targeting an RNA dynamic ensemble. Nat. Chem. Biol. 7:553–59 [Google Scholar]
  129. Shaw DE, Deneroff MM, Dror RO, Kuskin JS, Larson RH. 129.  et al. 2008. Anton, a special-purpose machine for molecular dynamics simulation. Commun. ACM 51:91–97 [Google Scholar]
  130. Denning EJ, Priyakumar UD, Nilsson L, Mackerell AD Jr. 130.  2011. Impact of 2′-hydroxyl sampling on the conformational properties of RNA: update of the CHARMM all-atom additive force field for RNA. J. Comput. Chem. 32:1929–43 [Google Scholar]
  131. Foloppe N, MacKerell AD Jr. 131.  2000. All-atom empirical force field for nucleic acids: I. Parameter optimization based on small molecule and condensed phase macromolecular target data. J. Comput. Chem. 21:86–104 [Google Scholar]
  132. Bailor MH, Mustoe AM, Brooks CL 3rd, Al-Hashimi HM. 132.  2011. 3D maps of RNA interhelical junctions. Nat. Protoc. 6:1536–45 [Google Scholar]

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