Abstract
RNA encompasses an essential part of all known forms of life. The functions of many RNA molecules are dependent on their ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that either utilize information derived from known structures of other RNA molecules (by way of template-based modeling) or attempt to simulate the physical process of RNA structure formation (by way of template-free modeling). All computational methods suffer from various limitations that make theoretical models less reliable than high-resolution experimentally determined structures. This chapter provides a protocol for computational modeling of RNA 3D structure that overcomes major limitations by combining two complementary approaches: template-based modeling that is capable of predicting global architectures based on similarity to other molecules but often fails to predict local unique features, and template-free modeling that can predict the local folding, but is limited to modeling the structure of relatively small molecules. Here, we combine the use of a template-based method ModeRNA with a template-free method SimRNA. ModeRNA requires a sequence alignment of the target RNA sequence to be modeled with a template of the known structure; it generates a model that predicts the structure of a conserved core and provides a starting point for modeling of variable regions. SimRNA can be used to fold small RNAs (<80 nt) without any additional structural information, and to refold parts of models for larger RNAs that have a correctly modeled core. ModeRNA can be either downloaded, compiled and run locally or run through a web interface at http://genesilico.pl/modernaserver/. SimRNA is currently available to download for local use as a precompiled software package at http://genesilico.pl/software/stand-alone/simrna and as a web server at http://genesilico.pl/SimRNAweb. For model optimization we use QRNAS, available at http://genesilico.pl/qrnas.
The authors wish it to be known that the three first authors (P.P., J.M.K., and D.K.) should be regarded as joint first authors.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Doudna JA (2000) Structural genomics of RNA. Nat Struct Biol 7(Suppl):954–956
Rother K et al (2011) RNA and protein 3D structure modeling: similarities and differences. J Mol Model 17(9):2325–2336
Magnus M et al (2014) Computational modeling of RNA 3D structures, with the aid of experimental restraints. RNA Biol 11(5):522–536
Rother M et al (2011) ModeRNA server: an online tool for modeling RNA 3D structures. Bioinformatics 27(17):2441–2442
Rother M et al (2011) ModeRNA: a tool for comparative modeling of RNA 3D structure. Nucleic Acids Res 39(10):4007–4022
Tozzini V (2009) Multiscale modeling of proteins. Acc Chem Res 43(2):220–230
Kolinski A (2004) Protein modeling and structure prediction with a reduced representation. Acta Biochim Pol 51(2):349–371
Boniecki M et al (2003) Protein fragment reconstruction using various modeling techniques. J Comput Aided Mol Des 17(11):725–738
Kolinski A, Bujnicki JM (2005) Generalized protein structure prediction based on combination of fold-recognition with de novo folding and evaluation of models. Proteins 61(Suppl 7):84–90
Magnus M, Boniecki MJ, Dawson W, Bujnicki JM (2016) SimRNAweb: a web server for RNA 3D structure modeling with optional restraints. Nucleic Acids Res 44(W1):W315–319. doi:10.1093/nar/gkw279
Altschul SF et al (1990) Basic local alignment search tool. J Mol Biol 215(3):403–410
Nawrocki EP et al (2015) Rfam 12.0: updates to the RNA families database. Nucleic Acids Res 43(Database issue):D130–D137
Nawrocki EP, Eddy SR (2013) Infernal 1.1: 100-fold faster RNA homology searches. Bioinformatics 29(22):2933–2935
Zhou Y et al (2008) GISSD: group I intron sequence and structure database. Nucleic Acids Res 36(Database issue):D31–D37
Wilm A, Higgins DG, Notredame C (2008) R-Coffee: a method for multiple alignment of non-coding RNA. Nucleic Acids Res 36(9):e52
Cruz JA et al (2012) RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction. RNA 14(4):610–625
Chen VB et al (2010) MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr D Biol Crystallogr 66(Pt 1):12–21
Hajdin CE et al (2010) On the significance of an RNA tertiary structure prediction. RNA 16(7):1340–1349
Acknowledgements
We would like to thank Wayne Dawson for critical reading of the manuscript and valuable comments and suggestions. This work was supported mainly by the National Science Centre (NCN) [2012/04/A/NZ2/00455 to J.M.B.]. D.K. was supported by the Foundation for Polish Science (FNP) [grant MPD/2010/3 to Prof. Artur Jarmolowski, project cofinanced by the European Union Regional Development Fund]. M.M. was supported by the National Science Centre (NCN)[2014/12/T/NZ2/00501]. J.M.B. and J.M.K. were also supported by the European Research Council [ERC, StG grant RNA + P = 123D to J.M.B.] and J.M.B. was supported by the “Ideas for Poland” fellowship from the FNP.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media New York
About this protocol
Cite this protocol
Piatkowski, P., Kasprzak, J.M., Kumar, D., Magnus, M., Chojnowski, G., Bujnicki, J.M. (2016). RNA 3D Structure Modeling by Combination of Template-Based Method ModeRNA, Template-Free Folding with SimRNA, and Refinement with QRNAS. In: Turner, D., Mathews, D. (eds) RNA Structure Determination. Methods in Molecular Biology, vol 1490. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6433-8_14
Download citation
DOI: https://doi.org/10.1007/978-1-4939-6433-8_14
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-6431-4
Online ISBN: 978-1-4939-6433-8
eBook Packages: Springer Protocols