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PubMed2001

Computational methods for RNA structure determination.

During the past year, major improvements have been made in methods used to solve RNA structures from crystals, find RNA patterns in sequence data and determine RNA secondary structure. Computational methods for assisting an interactive computer graphics human modeler, searching the conformational space of RNA tertiary structure, studying the dynamics of complexes involving RNA and simulating RNA catalytic activities have also been advanced.

Base Sequence↗
PubMed2005

Predicting RNA structure using mutual information.

BACKGROUND: With the ever-increasing number of sequenced RNAs and the establishment of new RNA databases, such as the Comparative RNA Web Site and Rfam, there is a growing need for accurately and automatically predicting RNA structures from multiple alignments. Since RNA secondary structure is often conserved in evolution, the well known, but underused, mutual information measure for identifying covarying sites in an alignment can be useful for identifying structural elements. This article presents MIfold, a MATLAB toolbox that employs mutual information, or a related covariation measure, to display and predict conserved RNA secondary structure (including pseudoknots) from an alignment. RESULTS: We show that MIfold can be used to predict simple pseudoknots, and that the performance can be adjusted to make it either more sensitive or more selective. We also demonstrate that the overall performance of MIfold improves with the number of aligned sequences for certain types of RNA sequences. In addition, we show that, for these sequences, MIfold is more sensitive but less selective than the related RNAalifold structure prediction program and is comparable with the COVE structure prediction package. CONCLUSION: MIfold provides a useful supplementary tool to programs such as RNA Structure Logo, RNAalifold and COVE, and should be useful for automatically generating structural predictions for databases such as Rfam.

Algorithms↗
PubMed1987

Improved parameters for prediction of RNA structure.

Thermodynamic studies of oligoribonucleotides are providing parameters and insights for the fundamental interactions that determine RNA structure. These results can be used to predict the secondary structure of RNA from its sequence. Comparisons of predicted structures with those deduced from phylogenetic data indicate a modest success rate that is improving as more parameters are determined experimentally. Two major fundamental interactions in RNA are stacking and hydrogen bonding. Both contribute similar increments to free-energy changes for associations of oligoribonucleotides. Thus, parameters for stacking and hydrogen bonding will likely be important for predicting the three-dimensional structures of RNAs and for interpreting RNA-RNA associations. Both applications should be important for providing a full understanding of catalysis by RNA.

Animals↗
PubMed1994

Stabilization of RNA structure by Mg ions. Specific and non-specific effects.

The stabilities of three different RNA fragments have been measured as a function of Mg2+ concentrations, and are interpreted in terms of two different models of Mg(2+)-RNA interaction. The models presume either tight binding of ions to specific site(s) in a folded RNA, or non-specific, electrostatic binding to both folded and unfolded forms; qualitatively different predictions are made for the melting temperature dependence on ion concentration. Three different modes of Mg2+ interactions with RNA structures are distinguished. Hairpins are stabilized by completely non-specific binding, with affinities the same as or weaker than those for single strand and duplex homopolymers binding Mg2+. In contrast, a ribosomal RNA tertiary structure is stabilized by specific binding of a single ion; since no other di- or trivalent ion is as effective as Mg2+, direct coordination of Mg2+ to the RNA structure is probably taking place. A third class of sites is best analyzed by the site-specific model, but any di- or trivalent ion is as effective as Mg2+; the ion(s) are probably localized in a region of unusually high charge density. The magnitude of a Mg(2+)-induced shift in RNAtm is itself not diagnostic of specific site binding or RNA tertiary structure, since large shifts can be observed for all three interaction modes.

Binding Sites↗
PubMed1998

Stepping through an RNA structure: A novel approach to conformational analysis.

Drawing from the growing database of complex three-dimensional RNA structures, a systematic method has been developed for classifying and analyzing the variety of conformations adopted by nucleic acids. This method is based on the development of a reduced representation for nucleic acid backbone conformation, simplifying the formidable eight-dimensional problem that has long complicated nucleic acid conformational analysis. Two pseudotorsion angles (eta and theta) have been defined, based on the selection of two appropriate pivot points along the RNA backbone, P and C4'. These pseudotorsions, together with a complete library of conventional torsion angles, can be calculated for any RNA structure or all-atom model using a new program called AMIGOS. Having computed eta and theta pseudotorsions for each position on an RNA molecule, they can be represented on a two-dimensional plot similar to the phi-phi plots that have traditionally been used for protein conformational analysis. Like a Ramachandran plot, clusters of residues appear at discrete regions on an eta-theta plot. Nucleotides within these clusters share conformational properties, often belonging to the same type of structural motif such as A-platforms, sheared tandem purine-purine pairs and GNRA tetraloops. An eta-theta plot provides a two-dimensional representation of the conformational properties of an entire RNA molecule, facilitating rapid analysis of structural features. In addition to the utility of eta-theta plots for intuitive visualization of conformational space, the pseudotorsional convention described here should significantly simplify approaches to macromolecular modeling of RNA structure.

Algorithms↗
PubMed1997

RNA structures and folding: from conventional to new issues in structure predictions.

Prediction and modeling of RNA structures has become an indispensable tool of biological research disciplines. Currently, reliable predictions require massive input of experimental data. Structure-forming elements are conventional base pairs, as well as a rapidly increasing repertoire of novel structural motifs. New developments extend structural analysis beyond the one-sequence/one-structure paradigm and allow questions that are relevant to molecular evolution to be answered.

Algorithms↗
PubMed2005

Tree decomposition based fast search of RNA structures including pseudoknots in genomes.

Searching genomes for RNA secondary structure with computational methods has become an important approach to the annotation of non-coding RNAs. However, due to the lack of efficient algorithms for accurate RNA structure-sequence alignment, computer programs capable of fast and effectively searching genomes for RNA secondary structures have not been available. In this paper, a novel RNA structure profiling model is introduced based on the notion of a conformational graph to specify the consensus structure of an RNA family. Tree decomposition yields a small tree width t for such conformation graphs (e.g., t = 2 for stem loops and only a slight increase for pseudo-knots). Within this modelling framework, the optimal alignment of a sequence to the structure model corresponds to finding a maximum valued isomorphic subgraph and consequently can be accomplished through dynamic programming on the tree decomposition of the conformational graph in time O(k(t)N(2)), where k is a small parameter; and N is the size of the projiled RNA structure. Experiments show that the application of the alignment algorithm to search in genomes yields the same search accuracy as methods based on a Covariance model with a significant reduction in computation time. In particular; very accurate searches of tmRNAs in bacteria genomes and of telomerase RNAs in yeast genomes can be accomplished in days, as opposed to months required by other methods. The tree decomposition based searching tool is free upon request and can be downloaded at our site h t t p ://w.uga.edu/RNA-informatics/software/index.php.

Algorithms↗
PubMed2004

A protein-dependent riboswitch controlling ptsGHI operon expression in Bacillus subtilis: RNA structure rather than sequence provides interaction specificity.

The Gram-positive soil bacterium Bacillus subtilis transports glucose by the phosphotransferase system. The genes for this system are encoded in the ptsGHI operon. The expression of this operon is controlled at the level of transcript elongation by a protein-dependent riboswitch. In the absence of glucose a transcriptional terminator prevents elongation into the structural genes. In the presence of glucose, the GlcT protein is activated and binds and stabilizes an alternative RNA structure that overlaps the terminator and prevents termination. In this work, we have studied the structural and sequence requirements for the two mutually exclusive RNA structures, the terminator and the RNA antiterminator (the RAT sequence). In both cases, the structure seems to be more important than the actual sequence. The number of paired and unpaired bases in the RAT sequence is essential for recognition by the antiterminator protein GlcT. In contrast, mutations of individual bases are well tolerated as long as the general structure of the RAT is not impaired. The introduction of one additional base in the RAT changed its structure and resulted in complete loss of interaction with GlcT. In contrast, this mutant RAT was efficiently recognized by a different B.subtilis antitermination protein, LicT.

Bacillus subtilis↗
PubMed2002

A general edit distance between RNA structures.

Arc-annotated sequences are useful in representing the structural information of RNA sequences. In general, RNA secondary and tertiary structures can be represented as a set of nested arcs and a set of crossing arcs, respectively. Since RNA functions are largely determined by molecular confirmation and therefore secondary and tertiary structures, the comparison between RNA secondary and tertiary structures has received much attention recently. In this paper, we propose the notion of edit distance to measure the similarity between two RNA secondary and tertiary structures, by incorporating various edit operations performed on both bases and arcs (i.e., base-pairs). Several algorithms are presented to compute the edit distance between two RNA sequences with various arc structures and under various score schemes, either exactly or approximately, with provably good performance. Preliminary experimental tests confirm that our definition of edit distance and the computation model are among the most reasonable ones ever studied in the literature.

Algorithms↗
PubMed2001

A mini-greedy algorithm for faster structural RNA stem-loop search.

When a set of coregulated genes share a common structural RNA motif, e.g. a hairpin, most motif search approaches fail to locate the covarying but structurally conserved motif. There do exist methods that can locate structural RNA motifs, like FOLDALIGN, but the main problem with these methods is that they are computationally expensive. In FOLDALIGN, a major contribution to this is the use of a greedy algorithm to construct the multiple alignment. To ensure good quality many redundant computations must be made. However, by applying the greedy algorithm on a carefully selected subset of sequences, near full greedy quality can be obtained. The basic idea is to estimate the order in which the sequences entered a good greedy alignment. If such a ranking, found from all pairwise alignments, is in good agreement with the order of appearance in the multiple alignment, the core structural motif can be found by performing the greedy algorithm on just the top sequences in the ranking. The ranking used in this mini-greedy algorithm is found by using two complementing approaches: 1) When interpreting the FOLDALIGN score as an inner product (kernel), the sequences can be ranked according to their distance to their center of mass; 2) We construct an algorithm that attempts to find the K closest sequences in the vector space associated with the inner product, and the remaining sequences can be ranked by their minimum distance to any of the sequences, or to the center of mass in this set. The two approaches arecompared and merged, and the results discussed. We also show that structural alignments of near full greedy quality can found in significantly reduced time, using these methods. The algorithm is being included in the SLASH (Stem-Loop Align SearcH) server available at http://www.bioinf.au.dk/slash.

Algorithms↗
PubMed1999

Multiple functions of Saccharomyces cerevisiae splicing protein Prp24 in U6 RNA structural rearrangements.

U6 spliceosomal RNA has a complex secondary structure that includes a highly conserved stemloop near the 3' end. The 3' stem is unwound when U6 RNA base-pairs with U4 RNA during spliceosome assembly, but likely reforms when U4 RNA leaves the spliceosome prior to the catalysis of splicing. A mutation in yeast U6 RNA that hyperstabilizes the 3' stem confers cold sensitivity and inhibits U4/U6 assembly as well as a later step in splicing. Here we show that extragenic suppressors of the 3' stem mutation map to the gene coding for splicing factor Prp24. The suppressor mutations are located in the second and third of three RNA-recognition motifs (RRMs) in Prp24 and are predicted to disrupt RNA binding. Mutations in U6 RNA predicted to destabilize a novel helix adjacent to the 3' stem also suppress the 3' stem mutation and enhance the growth defect of a suppressor mutation in RRM2 of Prp24. Both phenotypes are reverted by a compensatory mutation that restores pairing in the novel helix. These results are best explained by a model in which RRMs 2 and 3 of Prp24 stabilize an extended intramolecular structure in U6 RNA that competes with the U4/U6 RNA interaction, and thus influence both association and dissociation of U4 and U6 RNAs during the splicing cycle.

Amino Acid Sequence↗
PubMed1985

Secondary structure of the circular form of the Tetrahymena rRNA intervening sequence: a technique for RNA structure analysis using chemical probes and reverse transcriptase.

The structure of the intervening sequence (IVS) of the Tetrahymena rRNA precursor mediates cleavage-ligation reactions that result in pre-rRNA splicing and IVS cyclization. We have developed a method for RNA structure analysis and applied it to the circular form of the IVS RNA. The native RNA was treated with dimethyl sulfate or diethyl pyrocarbonate to modify bases not involved in secondary or tertiary interactions. The RNA was then used as a template for reverse transcription. Elongation of synthetic oligodeoxynucleotide primers was found to stop (or pause) one nucleotide prior to 1-methyladenosine, 3-methylcytidine, and 7-ethoxycarbonyladenosine residues. The detection of 1-methyladenosine is particularly useful for locating single-stranded regions. After chemical cleavage of the RNA, 7-methylguanosine also could be detected. In general, the sites of modification were consistent with a previous model of the secondary structure of the linear form of the IVS RNA, a model based on enzymatic cleavage data, free energy calculations, and phylogenetic comparison. Thus, IVS RNA autocyclization does not involve major rearrangements of the secondary structure, although there is evidence for a conformational change in one region of the molecule. The methods described here should be of general use for obtaining information about structure far from the ends of RNA molecules.

Animals↗
PubMed2001

Modular construction of a tertiary RNA structure: the specificity domain of the Bacillus subtilis RNase P RNA.

The structure of the specificity domain (S-domain) of the Bacillus subtilis RNase P RNA has been proposed to be composed of a core and a buttress module, analogous to the bipartite structure of the P4-P6 domain of the Tetrahymena group I ribozyme. The core module is the functional unit of the S-domain and contains the binding site for the T stem-loop of a tRNA. The buttress module provides structural stability to the core module and consists of a GA3 tetraloop and its receptor. To explicitly test the hypothesis that modular construction can describe the structure of the S-domain and is a useful RNA design strategy, we analyzed the equilibrium folding and substrate binding of three classes of S-domain mutants. Addition or deletion of a base pair in the helical linker region between the modules only modestly destabilizes the tertiary structure. tRNA binding selectivity is affected in one but not in two other mutants of this class. Elimination of the GA3 tetraloop-receptor interactions significantly destabilizes the core module and results in the loss of tRNA binding selectivity. Replacing the buttress module with that of a homologous RNase P RNA maintains the tRNA binding selectivity. Overall, we have observed that the linker regions between the two modules can tolerate moderate structural changes and that the buttress modules can be shuffled between homologous S-domains. These results suggest that it is feasible to design an RNA using a buttress module to stabilize a functional module.

Bacillus subtilis↗
PubMed2006

MeRNA: a database of metal ion binding sites in RNA structures.

Metal ions are essential for the folding of RNA into stable tertiary structures and for the catalytic activity of some RNA enzymes. To aid in the study of the roles of metal ions in RNA structural biology, we have created MeRNA (Metals in RNA), a comprehensive compilation of all metal binding sites identified in RNA 3D structures available from the PDB and Nucleic Acid Database. Currently, our database contains information relating to binding of 9764 metal ions corresponding to 23 distinct elements, in 256 RNA structures. The metal ion locations were confirmed and ligands characterized using original literature references. MeRNA includes eight manually identified metal-ion binding motifs, which are described in the literature. MeRNA is searchable by PDB identifier, metal ion, method of structure determination, resolution and R-values for X-ray structure and distance from metal to any RNA atom or to water. New structures with their respective binding motifs will be added to the database as they become available. The MeRNA database will further our understanding of the roles of metal ions in RNA folding and catalysis and have applications in structural and functional analysis, RNA design and engineering. The MeRNA database is accessible at http://merna.lbl.gov.

Binding Sites↗
PubMed2001

An efficient method for solving RNA structures: MAD phasing by replacing magnesium with zinc.

The structure of a 46-nucleotide RNA complex has been successfully solved using multi-wavelength anomalous dispersion (MAD) at the zinc K edge. Taking advantage of the eight magnesium-binding sites, it has been shown that for five of them magnesium could be replaced by zinc. This resulted in an excellent 2.0 A MAD electron-density map. Zinc, in common with some other transition metals, is able to replace magnesium in RNA structures, but zinc has the advantage of its K edge being ideally located at 1.284 A. As most RNA molecules contain magnesium-binding sites, it is suggested that this method could be a valuable alternative to the use of bromo derivatives of bases, which is limited to chemically synthesizable and thus rather short RNA sequences.

Crystallography, X-Ray↗
PubMed2003

The lonepair triloop: a new motif in RNA structure.

The lonepair triloop (LPTL) is an RNA structural motif that contains a single ("lone") base-pair capped by a hairpin loop containing three nucleotides. The two nucleotides immediately outside of this motif (5' and 3' to the lonepair) are not base-paired to one another, restricting the length of this helix to a single base-pair. Four examples of this motif, along with three tentative examples, were initially identified in the 16S and 23S rRNAs with covariation analysis. An evaluation of the recently determined crystal structures of the Thermus thermophilus 30S and Haloarcula marismortui 50S ribosomal subunits revealed the authenticity for all of these proposed interactions and identified 16 more LPTLs in the 5S, 16S and 23S rRNAs. This motif is found in the T loop in the tRNA crystal structures. The lonepairs are positioned, in nearly all examples, immediately 3' to a regular secondary structure helix and are stabilized by coaxial stacking onto this flanking helix. In all but two cases, the nucleotides in the triloop are involved in a tertiary interaction with another section of the rRNA, establishing an overall three-dimensional function for this motif. Of these 24 examples, 14 occur in multi-stem loops, seven in hairpin loops and three in internal loops. While the most common lonepair, U:A, occurs in ten of the 24 LPTLs, the remaining 14 LPTLs contain seven different base-pair types. Only a few of these lonepairs adopt the standard Watson-Crick base-pair conformations, while the majority of the base-pairs have non-standard conformations. While the general three-dimensional conformation is similar for all examples of this motif, characteristic differences lead to several subtypes present in different structural environments. At least one triloop nucleotide in 22 of the 24 LPTLs in the rRNAs and tRNAs forms a tertiary interaction with another part of the RNA. When a LPTL containing the GNR or UYR triloop sequence forms a tertiary interaction with the first (and second) triloop nucleotide, it recruits a fourth nucleotide to mediate stacking and mimic the tetraloop conformation. Approximately half of the LPTL motifs are in close association with proteins. The majority of these LPTLs are positioned at sites in rRNAs that are conserved in the three phylogenetic domains; a few of these occur in regions of the rRNA associated with ribosomal function, including the presumed site of peptidyl transferase activity in the 23S rRNA.

Base Pairing↗
PubMed2002

Classification of RNA structures based on hydrogen bond and base-base stacking patterns: application for NMR structures.

A computational system, CSNA, for classifying RNA structures according to structural characters was developed. CSNA lists up all the hydrogen bonds and base-base stackings in the structures, and classifies the structures into sub-groups based on their patterns as the first step grouping. The frequency of each hydrogen bond or base-base stacking is calculated, the frequency score being defined as the sum of the frequency of existing hydrogen bonds or base-base stackings for each sub-group. Finally, the sub-groups are further classified into groups based on the frequency score defined in this study and the difference between the patterns. According to the frequency score, CSNA suggests a group that shares most frequently appearing hydrogen bonds and base-base stackings. CSNA was applied to the classification of the results of two individual simulated annealing calculations based on NMR information. It was found that CSNA could extract structures with lower energy without checking any energy term and could provide well converged groups as the lowest energy structures. Thus, CSNA could be a new tool for structural determination of nucleic acids.

Algorithms↗
PubMed2002

IRES elements: features of the RNA structure contributing to their activity.

The activity of internal ribosome entry site (IRES) elements depends on their structural organization. We have addressed here the study of conserved structural motifs in the foot-and-mouth disease virus (FMDV) IRES as an example to understand the relationship between RNA structure and function. The features of the RNA structure known to be functionally relevant are discussed in regards to the capacity to modulate interaction of translation initiation factors with the FMDV IRES element. Additionally, the contribution of non-canonical RNA-binding proteins to FMDV IRES organization as well as stimulation of its activity by other mRNA regions is discussed.

Base Sequence↗