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Automated Modeling of RNA 3D Structure

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RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1097))

Abstract

This chapter gives an overview over the current methods for automated modeling of RNA structures, with emphasis on template-based methods. The currently used approaches to RNA modeling are presented with a side view on the protein world, where many similar ideas have been used. Two main programs for automated template-based modeling are presented: ModeRNA assembling structures from fragments and MacroMoleculeBuilder performing a simulation to satisfy spatial restraints. Both approaches have in common that they require an alignment of the target sequence to a known RNA structure that is used as a modeling template. As a way to find promising template structures and to align the target and template sequences, we propose a pipeline combining the ParAlign and Infernal programs on RNA family data from Rfam. We also briefly summarize template-free methods for RNA 3D structure prediction. Typically, RNA structures generated by automated modeling methods require local or global optimization. Thus, we also discuss methods that can be used for local or global refinement of RNA structures.

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References

  1. Parisien M, Major F (2008) The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data. Nature 452:51–55

    Article  CAS  PubMed  Google Scholar 

  2. Das R, Karanicolas J, Baker D (2010) Atomic accuracy in predicting and designing noncanonical RNA structure. Nat Methods 7: 291–294

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  3. Armache JP, Jarasch A, Anger AM et al (2010) Cryo-EM structure and rRNA model of a translating eukaryotic 80S ribosome at 5.5-A resolution. Proc Natl Acad Sci USA 107:19748–19753

    Google Scholar 

  4. Wallner B, Elofsson A (2003) Can correct protein models be identified? Protein Sci 12: 1073–1086

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Pawlowski M, Gajda MJ, Matlak R, Bujnicki JM (2008) MetaMQAP: a meta-server for the quality assessment of protein models. BMC Bioinforma 9:403

    Article  Google Scholar 

  6. Noivirt-Brik O, Prilusky J, Sussman JL (2009) Assessment of disorder predictions in CASP8. Proteins 77(Suppl 9):210–216

    Article  CAS  PubMed  Google Scholar 

  7. CASP-1 (1995) Special issue. Proteins 23

    Google Scholar 

  8. Bujnicki JM, Elofsson A, Fischer D, Rychlewski L (2001) LiveBench-1: continuous benchmarking of protein structure prediction servers. Protein Sci 10:352–361

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  9. Pieper U, Webb BM, Barkan DT et al (2011) ModBase, a database of annotated comparative protein structure models, and associated resources. Nucleic Acids Res 39:D465–D474

    Google Scholar 

  10. Motono C, Nakata J, Koike R et al (2011) SAHG, a comprehensive database of predicted structures of all human proteins. Nucleic Acids Res 39:D487–D493

    Google Scholar 

  11. Eswar N, Eramian D, Webb B, Shen MY, Sali A (2008) Protein structure modeling with MODELLER. Methods Mol Biol 426:145–159

    Google Scholar 

  12. Capriotti E, Norambuena T, Marti-Renom MA, Melo F (2011) All-atom knowledge-based potential for RNA structure prediction and assessment. Bioinformatics 27:1086–1093

    Google Scholar 

  13. Sarver M, Zirbel CL, Stombaugh J, Mokdad A, Leontis NB (2008) FR3D: finding local and composite recurrent structural motifs in RNA 3D structures. J Math Biol 56:215–252

    Article  PubMed Central  PubMed  Google Scholar 

  14. Rother K, Rother M, Boniecki M, Puton T, Bujnicki JM (2011) RNA and protein 3D structure modeling: similarities and differences. J Mol Model 17(9):2325– 2336

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  15. Guex N, Peitsch MC (1997) SWISS-MODEL and the Swiss-PdbViewer: an environment for comparative protein modeling. Electrophoresis 18:2714–2723

    Article  CAS  PubMed  Google Scholar 

  16. Sali A, Blundell TL (1993) Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol 234:779–815

    Article  CAS  PubMed  Google Scholar 

  17. Rother M, Rother K, Puton T, Bujnicki JM (2011) ModeRNA: a tool for comparative modeling of RNA 3D structure. Nucleic Acids Res 39:4007–4022

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  18. Flores SC, Altman RB (2010) Turning limited experimental information into 3D models of RNA. Rna 16:1769–1778

    Google Scholar 

  19. Krieger E, Nabuurs SB, Vriend G (2003) Homology modeling. Methods Biochem Anal 44:509–523

    CAS  PubMed  Google Scholar 

  20. Bordoli L, Kiefer F, Arnold K, Benkert P, Battey J, Schwede T (2009) Protein structure homology modeling using SWISS-MODEL workspace. Nat Protoc 4:1–13

    Google Scholar 

  21. Parisien M, Cruz JA, Westhof E, Major F (2009) New metrics for comparing and assessing discrepancies between RNA 3D structures and models. RNA 15:1875–1885

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  22. Wadley LM, Keating KS, Duarte CM, Pyle AM (2007) Evaluating and learning from RNA pseudotorsional space: quantitative validation of a reduced representation for RNA structure. J Mol Biol 372:942–957

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  23. Richardson JS, Schneider B, Murray LW et al (2008) RNA backbone: consensus all-angle conformers and modular string nomenclature (an RNA Ontology Consortium contribution). RNA 14:465–481

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  24. Sykes MT, Levitt M (2005) Describing RNA structure by libraries of clustered nucleotide doublets. J Mol Biol 351:26–38

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  25. Flores SC, Wan Y, Russell R, Altman RB (2010) Predicting RNA structure by multiple template homology modeling. Pac Symp Biocomput:216–227

    Google Scholar 

  26. Schmidt JP, Delp SL, Sherman MA, Taylor CA, Pande VS, Altman RB (2008) The Simbios National Center: Systems Biology in Motion. Proc IEEE Inst Electr Electron Eng 96:1266–1280

    Google Scholar 

  27. Gardner PP, Daub J, Tate JG et al (2009) Rfam: updates to the RNA families database. Nucleic Acids Res 37:D136–D140

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  28. Saebo PE, Andersen SM, Myrseth J, Laerdahl JK, Rognes T (2005) PARALIGN: rapid and sensitive sequence similarity searches powered by parallel computing technology. Nucleic Acids Res 33:W535–W539

    Google Scholar 

  29. Nawrocki EP, Kolbe DL, Eddy SR (2009) Infernal 1.0: inference of RNA alignments. Bioinformatics 25:1335–1337

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  30. Wilm A, Higgins DG, Notredame C (2008) R-Coffee: a method for multiple alignment of non-coding RNA. Nucleic Acids Res 36:e52

    Article  PubMed Central  PubMed  Google Scholar 

  31. Capriotti E, Marti-Renom MA (2010) Quantifying the relationship between sequence and three-dimensional structure conservation in RNA. BMC Bioinformatics 11:322

    Google Scholar 

  32. DeLano WL (2002) The PyMOL Molecular Graphics System, Version 1.5.0.4 Schrdinger, LLC

    Google Scholar 

  33. Pettersen EF, Goddard TD, Huang CC et al (2004) UCSF Chimera–a visualization system for exploratory research and analysis. J Comput Chem 25:1605–1612

    Article  CAS  PubMed  Google Scholar 

  34. Emsley P, Cowtan K (2004) Coot: model-building tools for molecular graphics. Acta Crystallogr D Biol Crystallogr 60:2126–2132

    Article  PubMed  Google Scholar 

  35. Popenda M, Szachniuk M, Blazewicz M et al (2010) RNA FRABASE 2.0: an advanced web-accessible database with the capacity to search the three-dimensional fragments within RNA structures. BMC Bioinformatics 11:231

    Google Scholar 

  36. Bindewald E, Hayes R, Yingling YG, Kasprzak W, Shapiro BA (2008) RNAJunction: a database of RNA junctions and kissing loops for three-dimensional structural analysis and nanodesign. Nucleic Acids Res 36:D392–D397

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  37. Tamura M, Hendrix DK, Klosterman PS, Schimmelman NR, Brenner SE, Holbrook SR (2004) SCOR: structural classification of RNA, version 2.0. Nucleic Acids Res 32:D182–D184

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  38. Das R, Baker D (2007) Automated de novo prediction of native-like RNA tertiary structures. Proc Natl Acad Sci U S A 104: 14664–14669

    Google Scholar 

  39. Leontis NB, Stombaugh J, Westhof E (2002) The non-Watson-Crick base pairs and their associated isostericity matrices. Nucleic Acids Res 30:3497–3531

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  40. Lescoute A, Leontis NB, Massire C, Westhof E (2005) Recurrent structural RNA motifs, Isostericity Matrices and sequence alignments. Nucleic Acids Res 33:2395–2409

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  41. Stombaugh J, Zirbel CL, Westhof E, Leontis NB (2009) Frequency and isostericity of RNA base pairs. Nucleic Acids Res 37:2294–2312

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  42. Anfinsen CB (1973) Principles that govern the folding of protein chains. Science 181:223–230

    Article  CAS  PubMed  Google Scholar 

  43. Hardin C, Pogorelov TV, Luthey-Schulten Z (2002) Ab initio protein structure prediction. Curr Opin Struct Biol 12:176–181

    Article  CAS  PubMed  Google Scholar 

  44. Scheraga HA (1996) Recent developments in the theory of protein folding: searching for the global energy minimum. Biophys Chem 59:329–339

    Article  CAS  PubMed  Google Scholar 

  45. Zuo G, Li W, Zhang J, Wang J, Wang W (2010) Folding of a small RNA hairpin based on simulation with replica exchange molecular dynamics. J Phys Chem B 114:5835–5839

    Article  CAS  PubMed  Google Scholar 

  46. Deng NJ, Cieplak P (2010) Free energy profile of RNA hairpins: a molecular dynamics simulation study. Biophys J 98:627–636

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  47. Sarzynska J, Reblova K, Sponer J, Kulinski T (2008) Conformational transitions of flanking purines in HIV-1 RNA dimerization initiation site kissing complexes studied by CHARMM explicit solvent molecular dynamics. Biopolymers 89:732–746

    Article  CAS  PubMed  Google Scholar 

  48. Sanbonmatsu KY, Tung CS (2007) High performance computing in biology: multimillion atom simulations of nanoscale systems. J Struct Biol 157:470–480

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  49. Tozzini V (2010) Multiscale modeling of proteins. Acc Chem Res 43:220–230

    Google Scholar 

  50. Tan RKZ, Petrov AS, Harvey SC (2006) YUP: a molecular simulation program for coarse-grained and multiscale models. J Chem Theory Comput 2:529–540

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  51. Jonikas MA, Radmer RJ, Laederach A et al (2009) Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters. RNA 15:189–199

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  52. Cao S, Chen SJ (2009) A new computational approach for mechanical folding kinetics of RNA hairpins. Biophys J 96:4024–4034

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  53. Ding F, Sharma S, Chalasani P, Demidov VV, Broude NE, Dokholyan NV (2008) Ab initio RNA folding by discrete molecular dynamics: from structure prediction to folding mechanisms. RNA 14:1164–1173

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  54. Rother K, Rother M, Boniecki M et al (2012) Template-based and template-free modeling of RNA 3D structure: inspirations from protein structure modeling. In: Leontis NB, Westhof E (eds) RNA 3D structure analysis and prediction. Springer, Berlin

    Google Scholar 

  55. Xia Z, Gardner DP, Gutell RR, Ren P (2010) Coarse-grained model for simulation of RNA three-dimensional structures. J Phys Chem B 114:13497–13506

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  56. Pasquali S, Derreumaux P (2010) HiRE-RNA: a high resolution coarse-grained energy model for RNA. J Phys Chem B 114:11957–11966

    Article  CAS  PubMed  Google Scholar 

  57. Canutescu AA, Dunbrack RL Jr (2003) Cyclic coordinate descent: a robotics algorithm for protein loop closure. Protein Sci 12: 963–972

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  58. Boomsma W, Hamelryck T (2005) Full cyclic coordinate descent: solving the protein loop closure problem in Calpha space. BMC Bioinforma 6:159

    Article  Google Scholar 

  59. Bernauer J, Huang X, Sim AY, Levitt M (2011) Fully differentiable coarse-grained and all-atom knowledge-based potentials for RNA structure evaluation. RNA 17:1066–1075

    Google Scholar 

  60. Christen M, Hunenberger PH, Bakowies D et al (2005) The GROMOS software for biomolecular simulation: GROMOS05. J Comput Chem 26:1719–1751

    Article  CAS  PubMed  Google Scholar 

  61. Case DA, Cheatham TE 3rd, Darden T et al (2005) The Amber biomolecular simulation programs. J Comput Chem 26:1668–1688

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  62. Foloppe N (2000) D. MA. 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 

  63. Sefcikova J, Krasovska MV, Spackova N, Sponer J, Walter NG (2007) Impact of an extruded nucleotide on cleavage activity and dynamic catalytic core conformation of the hepatitis delta virus ribozyme. Biopolymers 85:392–406

    Google Scholar 

  64. Sefcikova J, Krasovska MV, Sponer J, Walter NG (2007) The genomic HDV ribozyme utilizes a previously unnoticed U-turn motif to accomplish fast site-specific catalysis. Nucleic Acids Res 35:1933–1946

    Google Scholar 

  65. Ditzler MA, Otyepka M, Sponer J, Walter NG (2010) Molecular dynamics and quantum mechanics of RNA: conformational and chemical change we can believe in. Acc Chem Res 43:40–47

    Google Scholar 

  66. Fadrna E, Spackova N, Stefl R, Koca J, Cheatham TE, 3rd, Sponer J (2004) Molecular dynamics simulations of Guanine quadruplex loops: advances and force field limitations. Biophys J 87:227–242

    Google Scholar 

  67. Ditzler MA, Sponer J, Walter NG (2009) Molecular dynamics suggest multifunctionality of an adenine imino group in acid-base catalysis of the hairpin ribozyme. Rna 15:560–575

    Google Scholar 

  68. Soares TA, Hunenberger PH, Kastenholz MA et al (2005) An improved nucleic acid parameter set for the GROMOS force field. J Comput Chem 26:725–737

    Google Scholar 

  69. Eastman P, Pande V (2010) OpenMM: A Hardware-Independent Framework for Molecular Simulations. Computing in Science & Engineering 12:34–39

    Google Scholar 

  70. Draper DE, Grilley D, Soto AM (2005) Ions and RNA folding. Annu Rev Biophys Biomol Struct 34:221–243

    Article  CAS  PubMed  Google Scholar 

  71. Draper DE (2008) RNA folding: thermodynamic and molecular descriptions of the roles of ions. Biophys J 95:5489–5495

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  72. Reblova K, Fadrna E, Sarzynska J et al (2007) Conformations of flanking bases in HIV-1 RNA DIS kissing complexes studied by molecular dynamics. Biophys J 93:3932– 3949

    Google Scholar 

  73. Aduri R, Psciuk BT, Saro P, Taniga H, Schlegel HB, SantaLucia J (2007) AMBER Force Field Parameters for the Naturally Occurring Modified Nucleosides in RNA. J Chem Theory Comput 3:1464–1475

    Google Scholar 

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Authors and Affiliations

  1. Laboratory of Bioinformatics and Protein Engineering, International Institute of Molecular and Cell Biology, Warsaw, Poland

    Kristian Rother

  2. Laboratory of Bioinformatics, Faculty of Biology, Institute of Molecular Biology and Biotechnology, Adam Mickiewicz University, Poznan, Poland

    Magdalena Rother, Pawel Skiba & Janusz M. Bujnicki

Authors
  1. Kristian Rother
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  2. Magdalena Rother
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  3. Pawel Skiba
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  4. Janusz M. Bujnicki
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Corresponding author

Correspondence to Kristian Rother .

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Editors and Affiliations

  1. Center for non-coding RNA in Technology and Health, IKVH University of Copenhagen, Frederiksberg, Denmark

    Jan Gorodkin

  2. University of Washington Dept. Computer Science & Engineering, Seattle, Washington, USA

    Walter L. Ruzzo

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Rother, K., Rother, M., Skiba, P., Bujnicki, J.M. (2014). Automated Modeling of RNA 3D Structure. In: Gorodkin, J., Ruzzo, W. (eds) RNA Sequence, Structure, and Function: Computational and Bioinformatic Methods. Methods in Molecular Biology, vol 1097. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-709-9_18

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  • DOI: https://doi.org/10.1007/978-1-62703-709-9_18

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-708-2

  • Online ISBN: 978-1-62703-709-9

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