Abstract
No existing algorithm can start with arbitrary RNA sequences and return the precise three-dimensional structures that ensure their biological function. This chapter outlines current algorithms for automated RNA structure prediction (including our own FARNA–FARFAR), highlights their successes, and dissects their limitations, using a tetraloop and the sarcin/ricin motif as examples. The barriers to future advances are considered in light of three particular challenges: improving computational sampling, reducing reliance on experimentally solved structures, and avoiding coarse-grained representations of atomic-level interactions. To help meet these challenges and better understand the current state of the field, we propose an ongoing community-wide CASP-style experiment for evaluating the performance of current structure prediction algorithms.
Sripakdeevong and Beauchamp are equally contributing authors.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Adams P et al (2004) Crystal structure of a self-splicing group I intron with both exons. Nature 430(6995):45–50
Antao VP, Tinoco I Jr (1992) Thermodynamic parameters for loop formation in RNA and DNA hairpin tetraloops. Nucleic Acids Res 20(4):819
Ban N et al (2000) The complete atomic structure of the large ribosomal subunit at 2.4 A resolution. Science 289(5481):905–920
Batey R et al (2004) Structure of a natural guanine-responsive riboswitch complexed with the metabolite hypoxanthine. Nature 432(7015):411–415
Birney E et al (2007) Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 447(7146):799–816
Bowman GR et al (2008) Structural insight into RNA hairpin folding intermediates. J Am Chem Soc 130(30):9676–9678
Cate JH et al (1996) Crystal structure of a group I ribozyme domain: principles of RNA packing. Science 273(5282):1678–1685
Correll CC et al (2003) The common and the distinctive features of the bulged-G motif based on a 1.04 A resolution RNA structure. Nucleic Acids Res 31(23):6806–6818
Costa M, Michel F (1997) Rules for RNA recognition of GNRA tetraloops deduced by in vitro selection: comparison with in vivo evolution. EMBO J 16(11):3289–3302
Cruz JA et al (2012) RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction. RNA 23:23
Das R, Baker D (2007) Automated de novo prediction of native-like RNA tertiary structures. Proc Natl Acad Sci USA 104(37):14664–14669
Das R et al (2008) Structural inference of native and partially folded RNA by high-throughput contact mapping. Proc Natl Acad Sci USA 105(11):4144–4149
Das R et al (2009) Simultaneous prediction of protein folding and docking at high resolution. Proc Natl Acad Sci USA 106(45):18978–18983
Das R et al (2010) Atomic accuracy in predicting and designing noncanonical RNA structure. Nat Methods 7(4):291–294
Ding F et al (2008) Ab initio RNA folding by discrete molecular dynamics: from structure prediction to folding mechanisms. RNA 14(6):1164–1173
Ditzler MA et al (2010) Molecular dynamics and quantum mechanics of RNA: conformational and chemical change we can believe in. Acc Chem Res 43(1):40–47
Endo Y et al (1991) Ribosomal RNA identity elements for ricin A-chain recognition and catalysis. J Mol Biol 221(1):193
Fadrná E et al (2009) Single stranded loops of quadruplex DNA as key benchmark for testing nucleic acids force fields. J Chem Theory Comput 5(9):2514–2530
Ferre-D’amare AR, Rupert PB (2002) The hairpin ribozyme: from crystal structure to function. Biochem Soc Trans 30(Pt 6):1105–1109
Fleishman SJ et al (2010) Rosetta in CAPRI rounds 13-19. Proteins 78(15):3212–3218
Foloppe N, MacKerell AD Jr (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(2):86–104
Garcia AE, Paschek D (2008) Simulation of the pressure and temperature folding/unfolding equilibrium of a small RNA hairpin. J Am Chem Soc 130(3):815–817
Geary C et al (2007) Comprehensive features of natural and in vitro selected GNRA tetraloop-binding receptors. Nucleic Acids Res 36(4):1138–1152
Gherghe CM et al (2009) Native-like RNA tertiary structures using a sequence-encoded cleavage agent and refinement by discrete molecular dynamics. J Am Chem Soc 131(7):2541–2546
Golden B et al (1998) A preorganized active site in the crystal structure of the Tetrahymena ribozyme. Science 282(5387):259
Golden B et al (2004) Crystal structure of a phage Twort group I ribozyme? product complex. Nat Struct Mol Biol 12(1):82–89
Hainzl T et al (2005) Structural insights into SRP RNA: an induced fit mechanism for SRP assembly. RNA 11(7):1043–1050
Harms J et al (2001) High resolution structure of the large ribosomal subunit from a mesophilic eubacterium. Cell 107(5):679–688
Holley RW et al (1965) Nucleotide sequences in the yeast alanine transfer ribonucleic acid. J Biol Chem 240(5):2122
Jaeger L, Chworos A (2006) The architectonics of programmable RNA and DNA nanostructures. Curr Opin Struct Biol 16(4):531–543
Jonikas M et al (2009a) Coarse-grained modeling of large RNA molecules with knowledge-based potentials and structural filters. RNA 15(2):189–199
Jonikas MA et al (2009b) Knowledge-based instantiation of full atomic detail into coarse grain RNA 3D structural models. Bioinformatics 25(24):3259–3266
Jucker FM, Pardi A (1995) Solution structure of the CUUG hairpin loop: a novel RNA tetraloop motif. Biochemistry 34(44):14416–14427
Jucker FM et al (1996) A network of heterogeneous hydrogen bonds in GNRA tetraloops. J Mol Biol 264(5):968–980
Kim SH et al (1974) Three-dimensional tertiary structure of yeast phenylalanine transfer RNA. Science 185(149):435–440
Kim DE et al (2009) Sampling bottlenecks in de novo protein structure prediction. J Mol Biol 393(1):249–260
Kortemme T et al (2003) An orientation-dependent hydrogen bonding potential improves prediction of specificity and structure for proteins and protein-protein complexes. J Mol Biol 326(4):1239–1259
Lehnert V et al (1996) New loop-loop tertiary interactions in self-splicing introns of subgroup IC and ID: a complete 3D model of the Tetrahymena thermophila ribozyme. Chem Biol 3:993–1009
Leontis NB, Westhof E (2001) Geometric nomenclature and classification of RNA base pairs. RNA 7(04):499–512
Levinthal C (1968) Are there pathways for protein folding. J Chim Phys 65(1):44–45
Levitt M (1969) Detailed molecular model for transfer ribonucleic acid. Nature 224(5221):759–763
Majerfeld I, Yarus M (2005) A diminutive and specific RNA binding site for L-tryptophan. Nucleic Acids Res 33(17):5482
Major F et al (1991) The combination of symbolic and numerical computation for three-dimensional modeling of RNA. Science 253(5025):1255
Mandal M, Breaker RR (2004) Gene regulation by riboswitches. Nat Rev Mol Cell Biol 5(6):451–463
Martinez HM et al (2008) RNA2D3D: a program for generating, viewing, and comparing 3-dimensional models of RNA. J Biomol Struct Dyn 25(6):669
Mashima T et al (2009) Unique quadruplex structure and interaction of an RNA aptamer against bovine prion protein. Nucleic Acids Res 37(18):6249–6258
Massire C, Westhof E (1998) MANIP: an interactive tool for modelling RNA. J Mol Graph Model 16(4–6):197–205, 255-257
McGraw AP et al (2009) Molecular basis of TRAP–5 SL RNA interaction in the Bacillus subtilis trp operon transcription attenuation mechanism. RNA 15(1):55
Molinaro M, Tinoco I Jr (1995) Use of ultra stable UNCG tetraloop hairpins to fold RNA structures: thermodynamic and spectroscopic applications. Nucleic Acids Res 23(15):3056
Mueller F, Brimacombe R (1997) A new model for the three-dimensional folding of Escherichia coli 16 S ribosomal RNA. I. Fitting the RNA to a 3D electron microscopic map at 20 Å. J Mol Biol 271(4):524–544
Nimjee SM et al (2004) Aptamers: an emerging class of therapeutics. Annu Rev Med 56:555–583
Nissen P et al (2000) The structural basis of ribosome activity in peptide bond synthesis. Science 289(5481):920–930
Nussinov R, Jacobson AB (1980) Fast algorithm for predicting the secondary structure of single-stranded RNA. Proc Natl Acad Sci USA 77(11):6309
Parisien M, Major F (2008) The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data. Nature 452(7183):51–55
Penny GD et al (1996) Requirement for Xist in X chromosome inactivation. Nature 379(6561):131
Pérez A et al (2007) Refinement of the AMBER force field for nucleic acids: improving the description of [alpha]/[gamma] conformers. Biophys J 92(11):3817–3829
Pley HW et al (1994) Model for an RNA tertiary interaction from the structure of an intermolecular complex between a GAAA tetraloop and an RNA helix. Nature 372(6501):111–113
Raman S et al (2009) Structure prediction for CASP8 with all-atom refinement using Rosetta. Proteins 77(Suppl 9):89–99
Rich A, RajBhandary UL (1976) Transfer RNA: molecular structure, sequence, and properties. Annu Rev Biochem 45(1):805–860
Richardson JS et al (2008) RNA backbone: consensus all-angle conformers and modular string nomenclature (an RNA Ontology Consortium contribution). RNA 14(3):465
Rohl CA et al (2004) Protein structure prediction using Rosetta. Methods Enzymol 383:66–93
Sarver M et al (2008) FR3D: finding local and composite recurrent structural motifs in RNA 3D structures. J Math Biol 56(1–2):215–252
Seggerson K, Moore PB (1998) Structure and stability of variants of the sarcin-ricin loop of 28 S rRNA: NMR studies of the prokaryotic SRL and a functional mutant. RNA 4(10):1203–1215
Serganov A et al (2004) Structural basis for discriminative regulation of gene expression by adenine-and guanine-sensing mRNAs. Chem Biol 11(12):1729–1741
Sharma S et al (2008) iFoldRNA: three-dimensional RNA structure prediction and folding. Bioinformatics 24(17):1951
Shulman RG et al (1973) Determination of secondary and tertiary structural features of transfer RNA molecules in solution by nuclear magnetic resonance. Proc Natl Acad Sci USA 70(7):2042
Simons KT et al (1997) Assembly of protein tertiary structures from fragments with similar local sequences using simulated annealing and Bayesian scoring functions. J Mol Biol 268(1):209–225
Sorin EJ et al (2002) RNA simulations: probing hairpin unfolding and the dynamics of a GNRA tetraloop. J Mol Biol 317(4):493–506
Spackova N, Sponer J (2006) Molecular dynamics simulations of sarcin-ricin rRNA motif. Nucleic Acids Res 34(2):697
Sripakdeevong P et al (2011) An enumerative stepwise ansatz enables atomic-accuracy RNA loop modeling. Proc Natl Acad Sci USA 108(51):20573–20578
Staehelin M et al (1968) Structure of a mammalian serine tRNA. Nature 219(5161):1363–1365
Stojanovic MN, Stefanovic D (2003) A deoxyribozyme-based molecular automaton. Nat Biotechnol 21(9):1069–1074
Sykes MT, Levitt M (2005) Describing RNA structure by libraries of clustered nucleotide doublets. J Mol Biol 351(1):26–38
Varani G (1995) Exceptionally stable nucleic acid hairpins. Annu Rev Biophys Biomol Struct 24(1):379–404
Watts JM et al (2009) Architecture and secondary structure of an entire HIV-1 RNA genome. Nature 460(7256):711–716
Wimberly BT et al (2000) Structure of the 30 S ribosomal subunit. Nature 407(6802):327–339
Win MN et al (2009) Frameworks for programming biological function through RNA parts and devices. Chem Biol 16(3):298–310
Xia T et al (1998) Thermodynamic parameters for an expanded nearest-neighbor model for formation of RNA duplexes with Watson-Crick base pairs. Biochemistry 37(42):14719–14735
Yang H et al (2003) Tools for the automatic identification and classification of RNA base pairs. Nucleic Acids Res 31(13):3450
Ye JD et al (2008) Synthetic antibodies for specific recognition and crystallization of structured RNA. Proc Natl Acad Sci USA 105(1):82
Yusupov MM et al (2001) Crystal structure of the ribosome at 5.5 A resolution. Science 292(5518):883–896
Zirbel CL et al (2009) Classification and energetics of the base-phosphate interactions in RNA. Nucleic Acids Res 37(15):4898–4918
Zuker M, Stiegler P (1981) Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Res 9(1):133
Note added in proof
Since the time of writing (2010), we have described a method called stepwise assembly that appears to resolve the conformational sampling bottleneck for small RNA loops (Sripakdeevong et al. 2011). Further, we and others have initiated RNA-Puzzles, a series of community-wide blind trials for RNA structure prediction (Cruz et al. 2012).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Sripakdeevong, P., Beauchamp, K., Das, R. (2012). Why Can’t We Predict RNA Structure At Atomic Resolution?. In: Leontis, N., Westhof, E. (eds) RNA 3D Structure Analysis and Prediction. Nucleic Acids and Molecular Biology, vol 27. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25740-7_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-25740-7_4
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25739-1
Online ISBN: 978-3-642-25740-7
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)