No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
A coarse-grained model with implicit salt for RNAs: Predicting 3D structure, stability and salt effect
13. D. E. Draper, “Folding of RNA tertiary structure: Linkages between backbone phosphates, ions, and water,” Biopolymers 99, 1105–1113 (2013).
16. A. Kundagrami, and M. Muthukumar, “Theory of competitive counterion adsorption on flexible polyelectrolytes: Divalent salts,” J. Chem. Phys. 128, 244901 (2008).
17. M. Muthukumar, “Theory of counter-ion condensation on flexible polyelectrolytes: Adsorption mechanism,” J. Chem. Phys. 120, 9343 (2004).
18. S. A. Pabit, J. L. Sutton, H. Chen, and L. Pollack, “Role of ion valence in the submillisecond collapse and folding of a small RNA domain,” Biochemistry 52, 1539–1546 (2013).
19. Z. J. Tan, and S. J. Chen, “Electrostatic correlations and fluctuations for ion binding to a finite length polyelectrolyte,” J. Chem. Phys. 122, 044903 (2005).
24. F. Michel and E. Westhof, “Modelling of the three-dimensional architecture of group I catalytic introns based on comparative sequence analysis,” J. Mol. Biol. 216, 585–610 (1990).
25. M. E. Harris, J. M. Nolan, A. Malhotra, J. W. Brown, S. C. Harvey, and N. R. Pace, “Use of photoaffinity crosslinking and molecular modeling to analyze the global architecture of ribonuclease P RNA,” Embo. J. 13, 3953–3963 (1994).
28. K. Rother, M. Rother, M. Boniecki, T. Puton, and J. M. Bujnicki, “RNA and protein 3D structure modeling: Similarities and differences,” J. Mol. Model 17, 2325–2336 (2011).
31. J. A. Cruz, M. F. Blanchet, M. Boniecki, J. M. Bujnicki, S. J. Chen, S. Cao, R. Das, F. Ding, N. V. Dokholyan, S. C. Flores, L. Huang, C. A. Lavender, V. Lisi, F. Major, K. Mikolajczak, D. J. Patel, A. Philips, T. Puton, J. Santalucia, F. Sijenyi, T. Hermann, K. Rother, M. Rother, A. Serganov, M. Skorupski, T. Soltysinski, P. Sripakdeevong, I. Tuszynska, K. M. Weeks, C. Waldsich, M. Wildauer, N. B. Leontis, and E. Westhof, “RNA-Puzzles: A CASP-like evalution of RNA three-dimensional structure prediction,” RNA 18, 610–625 (2012).
32. C. E. Hajdin, F. Ding, N. V. Dokholyan, and K. M. Weeks, “On the significance of an RNA tertiary structure prediction,” RNA 16, 1340–1349 (2010).
37. F. Jossinet, T. E. Ludwig, and E. Westhof, “Assemble: An interactive graphical tool to analyze and build RNA architectures at 2D and 3D levels,” Bioinformatics 26, 2057–2059 (2010).
38. H. M. Martinez, J. V. Maizel Jr., and B. A. Shapiro, “RNA 2D3D: A program for generating, viewing, and comparing 3-dimensional models of RNA,” J. Biomol. Struct. Dyn. 25, 669–683 (2008).
39. C. Zwieb and F. Muller, “Three-dimensional comparative modeling of RNA,” Nucleic Acids Symp. Ser. 36, 69–71 (1997).
40. T. J. Macke and D. A. Case, “Modeling unusual nucleic acid structures,” in Molecular Modeling of Nucleic Acids, ACS Symposium Series Vol. 682 (American Chemical Society, 1998), pp. 379–393.
41. M. Rother, K. Rother, T. Puton, and J. M. Bujnicki, “ModeRNA: A tool for comparative modeling of RNA 3D structure,” Nucleic Acids Res. 39, 4007–4022 (2011).
43. F. Sijenyi, P. Saro, Z. Ouyang, K. Damm-Ganamet, M. Wood, J. Jiang, and J. SantaLucia Jr., “The RNA dolding problems: Different levels of RNA structure prediction,” in RNA 3D Structure Analysis and Prediction, Nucleic Acids and Molecular Biology Series, edited by N. Leontis and E. Westhof (Springer, 2011).
44. M. Popenda, M. Szachniuk, M. Antczak, K. J. Purzycka, P. Lukasiak, N. Bartol, J. Blazewicz, and R. W. Adamiak, “Automated 3D structure composition for large RNAs,” Nucleic Acids Res. 40, e112 (2012).
47. R. Das, J. Karanicolas, and D. Baker, “Atomic accuracy in predicting and designing noncanonical RNA structure,” Nat. Methods 7, 291–294 (2010).
51. Y. Zhao, Y. Huang, Z. Gong, Y. Wang, J. Man, and Y. Xiao, “Automated and fast building of three-dimensional RNA structures,” Sci. Rep. 2, 734 (2012).
54. Y. Huang, S. Liu, D. Guo, L. Li, and Y. Xiao,“A novel protocol for three-dimensional structure prediction of RNA-protein complexes,” Sci. Rep. 3, 1887 (2013).
55. R. K. Z. Tan, A. S. Petrov, and S. C. Harvey, “YUP: A molecular simulation program for coarse-grained and multiscaled models,” J. Chem. Theory Comput. 2, 529–540 (2006).
56. M. A. Jonikas, R. J. Radmer, A. Laederach, R. Das, S. Pearlman, D. Herschlag, and R. B. Altman, “Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters,” RNA 15,189–199 (2009).
57. O. Taxilaga-Zetina, P. Pliego-Pastrana, and M. D. Carbajal-Tinoco, “Three-dimensional structures of RNA obtained by means of knowledge-based interaction potentials,” Phys. Rev. E 81, 041914 (2010).
58. F. Ding, S. Sharma, P. Chalasani, V. V. Demidov, N. E. Broude, and N. V. Dokholyan, “Ab initio RNA folding by discrete molecular dynamics: From structure prediction to folding mechanisms,” RNA 14, 1164–1173 (2008).
62. S. Pasquali and P. Derreumaux, “HiRE: A high resolution coarse-grained energy model for RNA,” J. Phys. Chem. B 114, 11957–11966 (2010).
63. T. Cragnolini, P. Derreumaux, and S. Pasquali,“Coarse-grained simulations of RNA and DNA duplexes,” J. Phys. Chem. B 117, 8047–8060 (2013).
64. Z. Xia, D. P. Gardner, R. R. Gutell, and P. Ren, “Coarse-grained model for simulation RNA three-dimensional structures,” J. Phys. Chem. B 114, 13497–13506 (2010).
65. Z. Xia, D. R. Bell, Y. Shi, and P. Ren, “RNA 3D structure prediction by using a coarse-grained model and experimental data,” J. Phys. Chem. B 117, 3135–3144 (2013).
66. P. Sulc, F. Romano, T. E. Ouldridge, J. P. K. Doye, and A. A. Louis, “A nucleotide-level coarse-grained model of RNA,” J. Chem. Phys. 140, 235102 (2014).
67. N. Hori and S. Takada, “Coarse-grained structure-based model for RNA-protein complexes developed by fluctuation matching,” J. Chem. Theory Comput. 8, 3384–3394 (2012).
70. N. E. Buchete, J. E. Straub, and D. Thirumalai, “Anisotropic coarse-grained statistical potentials improve the ability to identify nativelike protein structures,” J. Chem. Phys. 118, 7658 (2003).
71. A. E. Giessen and J. E. Straub, “Coarse-grained model of coil-to-helix kinetics demonstrates the importance of multiple nucleation sites in helix folding,” J. Chem. Theory Comput. 2, 674–684 (2006).
75. N. Denesyuk and D. Thirumalai, “Coarse-grained model for predicting RNA folding thermodynamics,” J. Phys. Chem. B 117, 4901–4911 (2013).
78. F. H. Wang, Y. Y. Wu, and Z. J. Tan, “Salt contribution to the flexibility of single-stranded nucleic acid of finite length,” Biopolymers 99, 370–381 (2013).
See supplementary material at http://dx.doi.org/10.1063/1.4894752
for the detailed description of energy functions and corresponding parameters of the model, the melting curves of three RNAs (RH23, RH24, and RH30) at different [Na+
]'s and the description of the 46 RNAs used in this work and predicted results. [Supplementary Material]
81. G. S. Manning, “The molecular theory of polyelectrolyte solutions with applications to the electrostatic properties of polynucleotides,” Q. Rev. Biophys. 11, 179–246 (1978).
82. C. M. Gherghe, C. W. Leonard, F. Ding, N. V. Dokholyan, and K. M. Week, “Native-like RNA tertiary structures using a sequence-encoded cleavage agent and refinement by discrete molecular dynamics,” J. Am. Chem. Soc. 131, 2541–2546 (2009).
83. T. Xia, J. SantaLucia Jr., M. E. Burkand, R. Kierzek, S. J. Schroeder, X. Jiao, C. Cox, and D. H. Turner, “Thermodynamic parameters for an expanded nearest-neighbor model for formation of RNA duplexes with Watson-Crick base pairs,” Biochemistry 37, 14719–14735 (1998).
84. D. H. Mathews, J. Sabina, M. Zuker, and D. H. Turner, “Expended sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure,” J. Mol. Biol. 288, 911–940 (1999).
85. F. Leonarski, F. Trovato, V. Tozzini, A. Les, and J. Trylska, “Evolutionary algorithm in the optimization of a coarse-grained force field,” J. Chem. Theory Comput. 9, 4874–4889 (2013).
86. J. Berrauer, X. Huang, A. Y. Sim, and M. Levitt, “Fully differentiable coarse-grained and all-atom knowledge-based potentials for RNA structure evaluation,” RNA 17, 1066–1075 (2011).
89. N. Madras and A. D. Sokal, “The pivot algorithm: A highly efficient Monte Carlo method for the self-avoiding walk,” J. Stat. Phys. 50, 109–186 (1988).
90. M. Parisien, J. A. Cruz, E. Westhof, and F. Major, “New metrics for comparing and assessing discrepancies between RNA 3D structures and models,” RNA 15, 1875–1885 (2009).
94. S. Chauhan and S. A. Woodson,“Tertiary interactions determine the accuracy of RNA folding,” J. Am. Chem. Soc. 130, 1296–1303 (2008).
95. J. Zhang, J. Dundas, M. Lin, M. Chen, W. Wang, and J. Liang, “Prediction of geometrically feasible three-dimensional structures of pseudoknotted RNA through free energy estimation,” RNA 15, 2248–2263 (2009).
97. X. Xu and S. J. Chen, “Kinetic mechanism of conformational switch between bistable RNA hairpins,” J. Am. Chem. Soc. 134, 12499–12507 (2012).
98. M. J. Serra, M. H. Lyttle, T. J. Axenson, C. A. Schadt, and D. H. Turner, “RNA hairpin loop stability depends on closing base pair,” Nucleic Acids Res. 21, 3845–3849 (1993).
99. M. J. Serra, W. T. Barnes, K. Betschart, M. J. Gutierrez, K. J. Sprouse, C. K. Riley, L. Stewart, and R. E. Temel, “Improved parameters for the prediction of RNA hairpin stability,” Biochemistry 36, 4844–4851 (1997).
101. C. J. Vecenie, C. V. Morrow, A. Zyra, and M. J. Serra, “Sequence dependence of the stability of RNA hairpin molecules with six nucleotide loops,” Biochemistry 45, 1400–1407 (2006).
103. D. J. Williams and K. B. Hall, “Thermodynamic comparison of salt dependence of natural RNA hairpins and RNA hairpins with non-nucleotide spacers,” Biochemistry 35, 14665–14670 (1996).
105. A. M. Soto, V. Misra, and D. E. Draper, “Tertiary structure of an RNA pseudoknot is stabilized by “diffuse” Mg2+ ions,” Biochemistry 46, 2973–2983 (2007).
106. P. L. Nixon and D. P. Giedroc, “Energetics of a strongly pH dependent RNA tertiary structure in a frameshifting pseudoknot,” J. Mol. Biol. 296, 659–671 (2000).
109. A. Casiano-Negroni, X. Sun, and H. M. Al-Hashimi, “Probing Na+-induced changes in the HIV-1 TAR conformational dynamics using NMR residual dipolar couplings: New insights into the role of counterions and electrostatic interactions in adaptive recognition,” Biochemistry 46, 6525–6535 (2007).
110. R. Lavery, M. Moakher, J. H. Maddocks, D. Petkeviciute, and K. Zakrzewska, “Conformational analysis of nucleic acids revisited: Curves+,” Nucleic Acids Res. 37, 5917–5929 (2009).
111. W. Stephenson, S. Keller, R. Santiago, J. E. Albrecht, P. N. Asare-Okai, S. A. Tenenbaum, M. Zuker, and P. T. X. Li, “Combining temperature and force to study folding of an RNA hairpin,” Phys. Chem. Chem. Phys. 16, 906–917 (2014).
112. S. Biyun, S. S. Cho, and D. Thirumalai, “Folding of human telomerase RNA pseudoknot using ion-jump and temperature-quench simulations,” J. Am. Chem. Soc. 133, 20634–20643 (2011).
115. R. Das, M. Kudaravalli, M. Jonikas, A. Laederach, R. Fong, J. P. Schwans, D. Baker, J. A. Piccirilli, R. B. Altman, and D. Herschlag, “Structural inference of native and partially folded RNA by high-throughput contact mapping,” Proc. Natl. Acad. Sci. U.S.A. 105, 4144–4149 (2008).
116. S. E. Butcher and A. M. Pyle, “The molecular interactions that stabilize RNA tertiary structure: RNA motifs, patterns, and networks,” Acc. Chem. Res. 44, 1302–1311 (2011).
117. M. H. Bailor, A. M. Mustoe, C. L. Brooks, and H. M. Al-Hashimi, “Topological constraints: Using RNA secondary structure to model 3D conformation, folding pathways, and dynamic adaptation,” Curr. Opin. Struct. Biol. 21, 296–305 (2011).
118. M. J. Seetin and D. H. Mathews, “Automated RNA tertiary structure prediction from secondary structure and low-resolution restraints,” J. Comput. Chem. 32, 2232–2244 (2011).
119. K. A. Wilkinson, E. J. Merino, and K. M. Weeks, “Selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE): Quantitative RNA structure analysis at single nucleotide resolution,” Nat. Protoc. 1, 1610–1616 (2006).
121. F. Ding, C. A. Lavender, K. M. Weeks, and N. V. Dokholyan, “Three-dimensional RNA structure refinement by hydroxyl radical probing,” Nat. Methods 9, 603–608 (2012).
123. M. A. Jonikas, R. J. Radmer, and R. B. Altman, “Knowledge-based instantiation of full atomic detail into coarse-grain RNA 3D structural models,” Bioinformatics 25, 3259–3266 (2009).
Article metrics loading...
To bridge the gap between the sequences and 3-dimensional (3D) structures of RNAs, some computational models have been proposed for predicting RNA 3D structures. However, the existed models seldom consider the conditions departing from the room/body temperature and high salt (1M NaCl), and thus generally hardly predict the thermodynamics and salt effect. In this study, we propose a coarse-grained model with implicit salt for RNAs to predict 3D structures, stability, and salt effect. Combined with Monte Carlo simulated annealing algorithm and a coarse-grained force field, the model folds 46 tested RNAs (≤45 nt) including pseudoknots into their native-like structures from their sequences, with an overall mean RMSD of 3.5 Å and an overall minimum RMSD of 1.9 Å from the experimental structures. For 30 RNA hairpins, the present model also gives the reliable predictions for the stability and salt effect with the mean deviation ∼ 1.0 °C of melting temperatures, as compared with the extensive experimental data. In addition, the model could provide the ensemble of possible 3D structures for a short RNA at a given temperature/salt condition.
Full text loading...
Most read this month