Abstract
RNAs adopt specific structures to perform their activities and these are critical to virtually all RNA-mediated processes. Because of difficulties in experimentally assessing structures of large RNAs using NMR, X-ray crystallography, or cryo-microscopy, there is currently great demand for new high-resolution 3D structure prediction methods. Recently we reported on RNAComposer, a knowledge-based method for the fully automated RNA 3D structure prediction from a user-defined secondary structure. RNAComposer method is especially suited for structural biology users. Since our initial report in 2012, both servers, freely available at http://rnacomposer.ibch.poznan.pl and http://rnacomposer.cs.put.poznan.pl have been often visited. Therefore this chapter provides guidance for using RNAComposer and discusses points that should be considered when predicting 3D RNA structure. An application example presents current scope and limitations of RNAComposer.
*These authors contributed equally to this work.
Dedication: This work is dedicated to Professor David Shugar, one of the pioneers in the field of molecular biophysics, on the occasion of his 100th birthday anniversary.
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Spitale RC, Flynn RA, Torre EA, Kool ET, Chang HY (2014) RNA structural analysis by evolving SHAPE chemistry. Wiley Interdiscip Rev RNA 5(6):867–881. doi:10.1002/wrna.1253
Tian S, Cordero P, Kladwang W, Das R (2014) High-throughput mutate-map-rescue evaluates SHAPE-directed RNA structure and uncovers excited states. RNA 20(11):1815–1826. doi:10.1261/rna.044321.114
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(6):1164–1173. doi:10.1261/rna.894608
Jonikas MA, Radmer RJ, Laederach A, Das R, Pearlman S, Herschlag D, Altman RB (2009) Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters. RNA 15(2):189–199. doi:10.1261/rna.1270809
Rother M, Rother K, Puton T, Bujnicki JM (2011) ModeRNA: a tool for comparative modeling of RNA 3D structure. Nucleic Acids Res 39(10):4007–4022. doi:10.1093/nar/gkq1320
Das R, Baker D (2007) Automated de novo prediction of native-like RNA tertiary structures. Proc Natl Acad Sci U S A 104(37):14664–14669. doi:10.1073/pnas.0703836104
Parisien M, Major F (2008) The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data. Nature 452(7183):51–55. doi:10.1038/nature06684
Cao S, Chen SJ (2011) Physics-based de novo prediction of RNA 3D structures. J Phys Chem B 115(14):4216–4226. doi:10.1021/jp112059y
Sharma S, Ding F, Dokholyan NV (2008) iFoldRNA: three-dimensional RNA structure prediction and folding. Bioinformatics 24(17):1951–1952. doi:10.1093/bioinformatics/btn328
Zhao Y, Huang Y, Gong Z, Wang Y, Man J, Xiao Y (2012) Automated and fast building of three-dimensional RNA structures. Sci Rep 2:734. doi:10.1038/srep00734
Popenda M, Szachniuk M, Antczak M, Purzycka KJ, Lukasiak P, Bartol N, Blazewicz J, Adamiak RW (2012) Automated 3D structure composition for large RNAs. Nucleic Acids Res 40(14):e112. doi:10.1093/nar/gks339
Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28(1):235–242
Popenda M, Blazewicz M, Szachniuk M, Adamiak RW (2008) RNA FRABASE version 1.0: an engine with a database to search for the three-dimensional fragments within RNA structures. Nucleic Acids Res 36(Database issue):D386–D391. doi:10.1093/nar/gkm786
Popenda M, Szachniuk M, Blazewicz M, Wasik S, Burke EK, Blazewicz J, Adamiak RW (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. doi:10.1186/1471-2105-11-231
Gan HH, Pasquali S, Schlick T (2003) Exploring the repertoire of RNA secondary motifs using graph theory; implications for RNA design. Nucleic Acids Res 31(11):2926–2943
Schwieters CD, Kuszewski JJ, Tjandra N, Clore GM (2003) The Xplor-NIH NMR molecular structure determination package. J Magn Reson 160(1):65–73
Herraez A (2006) Biomolecules in the computer: Jmol to the rescue. Biochem Mol Biol Educ 34(4):255–261. doi:10.1002/bmb.2006.494034042644
Childs-Disney JL, Yildirim I, Park H, Lohman JR, Guan L, Tran T, Sarkar P, Schatz GC, Disney MD (2014) Structure of the myotonic dystrophy type 2 RNA and designed small molecules that reduce toxicity. ACS Chem Biol 9(2):538–550. doi:10.1021/cb4007387
Mathews DH (2014) RNA secondary structure analysis using RNAstructure. Curr Protoc Bioinformatics 46:12.16.11–12.16.25. doi:10.1002/0471250953.bi1206s46
Do CB, Woods DA, Batzoglou S (2006) CONTRAfold: RNA secondary structure prediction without physics-based models. Bioinformatics 22(14):e90–e98. doi:10.1093/bioinformatics/btl246
Hofacker IL, Fontana W, Stadler PF, Bonhoeffer LS, Tacker M, Schuster P (1994) Fast folding and comparison of RNA secondary structures. Monatshefte Fur Chem 125(2):167–188. doi:10.1007/Bf00818163
Sergiev PV, Dontsova OA, Bogdanov AA (2001) Chemical methods for the structural study of the ribosome: judgment day. Mol Biol 35(4):472–495. doi:10.1023/A:1010506522897
Furtig B, Richter C, Wohnert J, Schwalbe H (2003) NMR spectroscopy of RNA. Chembiochem 4(10):936–962. doi:10.1002/cbic.200300700
Wozniak AK, Nottrott S, Kuhn-Holsken E, Schroder GF, Grubmuller H, Luhrmann R, Seidel CA, Oesterhelt F (2005) Detecting protein-induced folding of the U4 snRNA kink-turn by single-molecule multiparameter FRET measurements. RNA 11(10):1545–1554. doi:10.1261/rna.2950605
Frolow O, Endeward B, Schiemann O, Prisner TF, Engels JW (2008) Nitroxide spin labeled RNA for long range distance measurements by EPR-PELDOR. Nucleic Acids Symp Ser (Oxf) 52:153–154. doi:10.1093/nass/nrn078
Huang LL, Serganov A, Patel DJ (2010) Structural insights into ligand recognition by a sensing domain of the cooperative glycine riboswitch. Mol Cell 40(5):774–786. doi:10.1016/j.molcel.2010.11.026
Grundy FJ, Lehman SC, Henkin TM (2003) The L box regulon: lysine sensing by leader RNAs of bacterial lysine biosynthesis genes. Proc Natl Acad Sci U S A 100(21):12057–12062. doi:10.1073/pnas.2133705100
Serganov A, Huang L, Patel DJ (2008) Structural insights into amino acid binding and gene control by a lysine riboswitch. Nature 455(7217):1263–1267. doi:10.1038/nature07326
Blouin S, Lafontaine DA (2007) A loop-loop interaction and a K-turn motif located in the lysine aptamer domain are important for the riboswitch gene regulation control. RNA 13(8):1256–1267. doi:10.1261/Rna.560307
Xayaphoummine A, Bucher T, Isambert H (2005) Kinefold web server for RNA/DNA folding path and structure prediction including pseudoknots and knots. Nucleic Acids Res 33(Web Server issue):W605–W610. doi:10.1093/nar/gki447
Matthews BW (1975) Comparison of the predicted and observed secondary structure of T4 phage lysozyme. Biochim Biophys Acta 405(2):442–451
Spitale RC, Crisalli P, Flynn RA, Torre EA, Kool ET, Chang HY (2013) RNA SHAPE analysis in living cells. Nat Chem Biol 9(1):18–20. doi:10.1038/nchembio.1131
Purzycka KJ, Pachulska-Wieczorek K, Adamiak RW (2011) The in vitro loose dimer structure and rearrangements of the HIV-2 leader RNA. Nucleic Acids Res 39(16):7234–7248. doi:10.1093/nar/gkr385
Legiewicz M, Zolotukhin AS, Pilkington GR, Purzycka KJ, Mitchell M, Uranishi H, Bear J, Pavlakis GN, Le Grice SF, Felber BK (2010) The RNA transport element of the murine musD retrotransposon requires long-range intramolecular interactions for function. J Biol Chem 285(53):42097–42104. doi:10.1074/jbc.M110.182840
Purzycka KJ, Legiewicz M, Matsuda E, Eizentstat LD, Lusvarghi S, Saha A, Le Grice SF, Garfinkel DJ (2013) Exploring Ty1 retrotransposon RNA structure within virus-like particles. Nucleic Acids Res 41(1):463–473. doi:10.1093/nar/gks983
Huang Q, Purzycka KJ, Lusvarghi S, Li D, Legrice SF, Boeke JD (2013) Retrotransposon Ty1 RNA contains a 5′-terminal long-range pseudoknot required for efficient reverse transcription. RNA 19(3):320–332. doi:10.1261/rna.035535.112
Lusvarghi S, Sztuba-Solinska J, Purzycka KJ, Pauly GT, Rausch JW, Grice SF (2013) The HIV-2 Rev-response element: determining secondary structure and defining folding intermediates. Nucleic Acids Res 41(13):6637–6649. doi:10.1093/nar/gkt353
Krahenbuhl B, Lukavsky P, Wider G (2014) Strategy for automated NMR resonance assignment of RNA: application to 48-nucleotide K10. J Biomol NMR 59(4):231–240. doi:10.1007/s10858-014-9841-3
Acknowledgments
This work was supported by the National Science Center Poland [MAESTRO 2012/06/A/ST6/00384 (to R.W.A)] and Ministry of Science and Higher Education [0492/IP1/2013/72 (to K.J.P.)].
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Biesiada, M., Purzycka, K.J., Szachniuk, M., Blazewicz, J., Adamiak, R.W. (2016). Automated RNA 3D Structure Prediction with RNAComposer. 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_13
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DOI: https://doi.org/10.1007/978-1-4939-6433-8_13
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