RNA Tertiary Structure Research Articles

Small aminoacyl transfer centers at GU within a larger RNA

Separate aminoacyl transfer centers related to the small …GUNNN..: NNNU ribozyme seem possible at the frequent GU sequences dispersed throughout an RNA tertiary structure. In fact, such activity is easily detected and varies more than 2 orders in rate, probabably being faster at sites with less structural constraint. Analysis of a particular constrained active site in an rRNA transcript suggests that its difficulty lies not in substrate strand association, but in binding and/or group transfer from the aminoacyl precursor. Efficient aminoacyl transfer requires accurate complementarity between large or small ribozymes and oligoribonucleotide substrates, even when only three or four base pairs link the two. Thus, multi-site active ribozymal superstructures might have coordinated an RNA metabolism, including aiding an early translation apparatus.

Fingerprinting Noncanonical and Tertiary RNA Structures by Differential SHAPE Reactivity

Fingerprinting Noncanonical and Tertiary RNA Structures by Differential SHAPE Reactivity

Single-Molecule Optical Trap Study of Human CCR5 mRNA Structure

Tertiary structure of mRNA can regulate translation by the ribosome. Specifically, potential pseudoknot structures are found in many genes which may stimulate programmed −1 ribosomal frame shifting. We conducted single-molecule optical trapping experiments on CCR5 mRNA, which encodes the co-receptor for HIV-1. We found that individual molecules of CCR5 mRNA will randomly fold into several unique conformations when stretched repeatedly, one of these being consistent with a proposed pseudoknot structure. Other conformations have higher energies than would be expected for duplex RNA and may be explained by tertiary RNA structure. A new analysis technique was applied, where we consider the change in energy per distance (dE/dx) of the molecule. This method of analysis provides a useful means to classify the many conformations the mRNA adopts as well as providing unique insights into the structure of CCR5 mRNA.

RNA Folding in Crowded Solutions

Many non-coding RNAs fold into specific three-dimensional structures in order to act as catalysts or regulatory elements. Folded RNA structures are stabilized by K+ and Mg2+ ions that neutralize the phosphate negative charge and bind to specific RNA motifs. In the cell, however, the stability of the folded RNA depends on its interactions with many other solutes. Using small angle X-ray scattering to measure the folding of a bacterial group I ribozyme, we showed that molecular crowding equivalent to what is present in real cells stabilizes RNA tertiary structures by several kcal/mol. We used polyethylene glycol (PEG) with different molecular weights as a crowding agent, as it does not appreciably interact with the RNA. Stabilization of the native RNA in MgCl2 or NaCl is most likely due to the excluded volume effect, and as our results were not explained by changes to water or ion activity. Crowder molecules favor more compact structures of the unfolded and native RNAs. Furthermore, compression of the native state ensemble correlates with an increase in ribozyme catalytic activity. Consequently, the ribozyme reaches its catalytically active structure at much lower Mg2+ concentrations in a crowded milieu than in a dilute solution. Thus, our results partly explain why many ribozymes are more active in the crowded environment of the cell than in the test tube.

Statistical mechanical modeling of RNA folding: from free energy landscape to tertiary structural prediction.

In spite of the success of computational methods for predicting RNA secondary structure, the problem of predicting RNA tertiary structure folding remains. Low-resolution structural models show promise as they allow for rigorous statistical mechanical computation for the conformational entropies, free energies, and the coarse-grained structures of tertiary folds. Molecular dynamics refinement of coarse-grained structures leads to all-atom 3D structures. Modeling based on statistical mechanics principles also has the unique advantage of predicting the full free energy landscape, including local minima and the global free energy minimum. The energy landscapes combined with the 3D structures form the basis for quantitative predictions of RNA functions. In this chapter, we present an overview of statistical mechanical models for RNA folding and then focus on a recently developed RNA statistical mechanical model -- the Vfold model. The main emphasis is placed on the physics underpinning the models, the computational strategies, and the connections to RNA biology.

On the page number of RNA secondary structures with pseudoknots

Let S denote the set of (possibly noncanonical) base pairs {i, j } of an RNA tertiary structure; i.e. {i, j} ∈ S if there is a hydrogen bond between the ith and jth nucleotide. The page number of S, denoted π(S), is the minimum number k such that Scan be decomposed into a disjoint union of k secondary structures. Here, we show that computing the page number is NP-complete; we describe an exact computation of page number, using constraint programming, and determine the page number of a collection of RNA tertiary structures, for which the topological genus is known. We describe an approximation algorithm from which it follows that ω(S) ≤ π(S) ≤ ω(S) ・log n,where the clique number of S, ω(S), denotes the maximum number of base pairs that pairwise cross each other.

RNA CoSSMos: Characterization of Secondary Structure Motifs--a searchable database of secondary structure motifs in RNA three-dimensional structures

RNA secondary structure is important for designing therapeutics, understanding protein–RNA binding and predicting tertiary structure of RNA. Several databases and downloadable programs exist that specialize in the three-dimensional (3D) structure of RNA, but none focus specifically on secondary structural motifs such as internal, bulge and hairpin loops. The RNA Characterization of Secondary Structure Motifs (RNA CoSSMos) database is a freely accessible and searchable online database and website of 3D characteristics of secondary structure motifs. To create the RNA CoSSMos database, 2156 Protein Data Bank (PDB) files were searched for internal, bulge and hairpin loops, and each loop's structural information, including sugar pucker, glycosidic linkage, hydrogen bonding patterns and stacking interactions, was included in the database. False positives were defined, identified and reclassified or omitted from the database to ensure the most accurate results possible. Users can search via general PDB information, experimental parameters, sequence and specific motif and by specific structural parameters in the subquery page after the initial search. Returned results for each search can be viewed individually or a complete set can be downloaded into a spreadsheet to allow for easy comparison. The RNA CoSSMos database is automatically updated weekly and is available at http://cossmos.slu.edu.

The size of RNA as an ideal branched polymer

Because of the branching arising from partial self-complementarity, long single-stranded (ss) RNA molecules are significantly more compact than linear arrangements (e.g., denatured states) of the same sequence of monomers. To elucidate the dependence of compactness on the nature and extent of branching, we represent ssRNA secondary structures as tree graphs which we treat as ideal branched polymers, and use a theorem of Kramers for evaluating their root-mean-square radius of gyration, ̂R(g)=√<linear span>R(g)(2)<linear span>. We consider two sets of sequences--random and viral--with nucleotide sequence lengths (N) ranging from 100 to 10,000. The RNAs of icosahedral viruses are shown to be more compact (i.e., to have smaller ̂R(g)) than the random RNAs. For the random sequences we find that ̂R(g) varies as N(1/3). These results are contrasted with the scaling of ̂R(g) for ideal randomly branched polymers (N(1/4)), and with that from recent modeling of (relatively short, N ≤ 161) RNA tertiary structures (N(2/5)).

Rational Truncation of an RNA Aptamer to Prostate-Specific Membrane Antigen Using Computational Structural Modeling

RNA aptamers represent an emerging class of pharmaceuticals with great potential for targeted cancer diagnostics and therapy. Several RNA aptamers that bind cancer cell-surface antigens with high affinity and specificity have been described. However, their clinical potential has yet to be realized. A significant obstacle to the clinical adoption of RNA aptamers is the high cost of manufacturing long RNA sequences through chemical synthesis. Therapeutic aptamers are often truncated postselection by using a trial-and-error process, which is time consuming and inefficient. Here, we used a "rational truncation" approach guided by RNA structural prediction and protein/RNA docking algorithms that enabled us to substantially truncateA9, an RNA aptamer to prostate-specific membrane antigen (PSMA),with great potential for targeted therapeutics. This truncated PSMA aptamer (A9L; 41mer) retains binding activity, functionality, and is amenable to large-scale chemical synthesis for future clinical applications. In addition, the modeled RNA tertiary structure and protein/RNA docking predictions revealed key nucleotides within the aptamer critical for binding to PSMA and inhibiting its enzymatic activity. Finally, this work highlights the utility of existing RNA structural prediction and protein docking techniques that may be generally applicable to developing RNA aptamers optimized for therapeutic use.

Functional RNA Elements in the Dengue Virus Genome

Dengue virus (DENV) genome amplification is a process that involves the viral RNA, cellular and viral proteins, and a complex architecture of cellular membranes. The viral RNA is not a passive template during this process; it plays an active role providing RNA signals that act as promoters, enhancers and/or silencers of the replication process. RNA elements that modulate RNA replication were found at the 5′ and 3′ UTRs and within the viral coding sequence. The promoter for DENV RNA synthesis is a large stem loop structure located at the 5′ end of the genome. This structure specifically interacts with the viral polymerase NS5 and promotes RNA synthesis at the 3′ end of a circularized genome. The circular conformation of the viral genome is mediated by long range RNA-RNA interactions that span thousands of nucleotides. Recent studies have provided new information about the requirement of alternative, mutually exclusive, structures in the viral RNA, highlighting the idea that the viral genome is flexible and exists in different conformations. In this article, we describe elements in the promoter SLA and other RNA signals involved in NS5 polymerase binding and activity, and provide new ideas of how dynamic secondary and tertiary structures of the viral RNA participate in the viral life cycle.

A Powerful Approach for the Selection of 2-Aminopurine Substitution Sites to Investigate RNA Folding

A precise tertiary structure must be adopted to allow the function of many RNAs in cells. Accordingly, increasing resources have been devoted to the elucidation of RNA structures and the folding of RNAs. 2-Aminopurine (2AP), a fluorescent nucleobase analogue, can be substituted in strategic positions of DNA or RNA molecules to act as site-specific probe to monitor folding and folding dynamics of nucleic acids. Recent studies further demonstrated the potential of 2AP modifications in the assessment of folding kinetics during ligand-induced secondary and tertiary RNA structure rearrangements. However, an efficient way to unambiguously identify reliable positions for 2AP sensors is as yet unavailable and would represent a major asset, especially in the absence of crystallographic or NMR structural data for a target molecule. We report evidence of a novel and direct correlation between the 2'-OH flexibility of nucleotides, observed by selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) probing and the fluorescence response following nucleotide substitutions by 2AP. This correlation leads to a straightforward method, using SHAPE probing with benzoyl cyanide, to select appropriate nucleotide sites for 2AP substitution. This clear correlation is presented for three model RNAs of biological significance: the SAM-II, adenine (addA), and preQ(1) class II (preQ(1)cII) riboswitches.

The Molecular Interactions That Stabilize RNA Tertiary Structure: RNA Motifs, Patterns, and Networks

RNA molecules adopt specific three-dimensional structures critical to their function. Many essential metabolic processes, including protein synthesis and RNA splicing, are carried out by RNA molecules with elaborate tertiary structures (e.g. 3QIQ, right). Indeed, the ribosome and self-splicing introns are complex RNA machines. But even the coding regions in messenger RNAs and viral RNAs are flanked by highly structured untranslated regions, which provide regulatory information necessary for gene expression. RNA tertiary structure is defined as the three-dimensional arrangement of RNA building blocks, which include helical duplexes, triple-stranded structures, and other components that are held together through connections collectively termed RNA tertiary interactions. The structural diversity of these interactions is now a subject of intense investigation, involving the techniques of NMR, X-ray crystallography, chemical genetics, and phylogenetic analysis. At the same time, many investigators are using biophysical techniques to elucidate the driving forces for tertiary structure formation and the mechanisms for its stabilization. RNA tertiary folding is promoted by maximization of base stacking, much like the hydrophobic effect that drives protein folding. RNA folding also requires electrostatic stabilization, both through charge screening and site binding of metals, and it is enhanced by desolvation of the phosphate backbone. In this Account, we provide an overview of the features that specify and stabilize RNA tertiary structure. A major determinant for overall tertiary RNA architecture is local conformation in secondary-structure junctions, which are regions from which two or more duplexes project. At junctions and other structures, such as pseudoknots and kissing loops, adjacent helices stack on one another, and these coaxial stacks play a major role in dictating the overall architectural form of an RNA molecule. In addition to RNA junction topology, a second determinant for RNA tertiary structure is the formation of sequence-specific interactions. Networks of triple helices, tetraloop-receptor interactions, and other sequence-specific contacts establish the framework for the overall tertiary fold. The third determinant of tertiary structure is the formation of stabilizing stacking and backbone interactions, and many are not sequence specific. For example, ribose zippers allow 2'-hydroxyl groups on different RNA strands to form networks of interdigitated hydrogen bonds, serving to seal strands together and thereby stabilize adjacent substructures. These motifs often require monovalent and divalent cations, which can interact diffusely or through chelation to specific RNA functional groups. As we learn more about the components of RNA tertiary structure, we will be able to predict the structures of RNA molecules from their sequences, thereby obtaining key information about biological function. Understanding and predicting RNA structure is particularly important given the recent discovery that although most of our genome is transcribed into RNA molecules, few of them have a known function. The prevalence of RNA viruses and pathogens with RNA genomes makes RNA drug discovery an active area of research. Finally, knowledge of RNA structure will facilitate the engineering of supramolecular RNA structures, which can be used as nanomechanical components for new materials. But all of this promise depends on a better understanding of the RNA parts list, and how the pieces fit together.

RNA tertiary structure prediction with ModeRNA

Noncoding RNAs perform important roles in the cell. As their function is tightly connected with structure, and as experimental methods are time-consuming and expensive, the field of RNA structure prediction is developing rapidly. Here, we present a detailed study on using the ModeRNA software. The tool uses the comparative modeling approach and can be applied when a structural template is available and an alignment of reasonable quality can be performed. We guide the reader through the entire process of modeling Escherichia coli tRNA(Thr) in a conformation corresponding to the complex with an aminoacyl-tRNA synthetase (aaRS). We describe the choice of a template structure, preparation of input files, and explore three possible modeling strategies. In the end, we evaluate the resulting models using six alternative benchmarks. The ModeRNA software can be freely downloaded from http://iimcb.genesilico.pl/moderna/ under the conditions of the General Public License. It runs under LINUX, Windows and Mac OS. It is also available as a server at http://iimcb.genesilico.pl/modernaserver/. The models and the script to reproduce the study from this article are available at http://www.genesilico.pl/moderna/examples/.

Feature-based 3D motif filtering for ribosomal RNA

RNA 3D motifs are recurrent substructures in an RNA subunit and are building blocks of the RNA architecture. They play an important role in binding proteins and consolidating RNA tertiary structures. RNA 3D motif searching consists of two steps: candidate generation and candidate filtering. We proposed a novel method, known as Feature-based RNA Motif Filtering (FRMF), for identifying motifs based on a set of moment invariants and the Earth Mover's Distance in the second step. A positive set of RNA motifs belonging to six characteristic types, with eight subtypes occurring in HM 50S, is compiled by us. The proposed method is validated on this representative set. FRMF successfully finds most of the positive fragments. Besides the proposed new method and the compiled positive set, we also recognize some new motifs, in particular a π-turn and some non-standard A-minor motifs are found. These newly discovered motifs provide more information about RNA structure conformation. Matlab code can be downloaded from www.cs.cityu.edu.hk/~yingshen/FRMF.html cshswong@cityu.edu.hk Supplementary data are available at Bioinformatics online.

Evidence for a Thermodynamically Distinct Mg2+ Ion Associated with Formation of an RNA Tertiary Structure

A folding strategy adopted by some RNAs is to chelate cations in pockets or cavities, where the ions neutralize charge from solvent-inaccessible phosphate. Although such buried Mg(2+)-RNA chelates could be responsible for a significant fraction of the Mg(2+)-dependent stabilization free energy of some RNA tertiary structures, direct measurements have not been feasible because of the difficulty of finding conditions under which the free energy of Mg(2+) chelation is uncoupled from RNA folding and from unfavorable interactions with Mg(2+) ions in other environments. In a 58mer rRNA fragment, we have used a high-affinity thermophilic ribosomal protein to trap the RNA in a structure nearly identical to native; Mg(2+)- and protein-stabilized structures differ in the solvent exposure of a single nucleotide located at the chelation site. Under these conditions, titration of a high affinity chelation site takes place in a micromolar range of Mg(2+) concentration, and is partially resolved from the accumulation of Mg(2+) in the ion atmosphere. From these experiments, we estimate the total and site-specific Mg(2+)-RNA interaction free energies over the range of accessed Mg(2+) concentrations. At 0.1 mM Mg(2+) and 60 mM K(+), specific site binding contributes ∼-3 kcal/mol of the total Mg(2+) interaction free energy of ∼-13 kcal/mol from all sources; at higher Mg(2+) concentrations the site-binding contribution becomes a smaller proportion of the total (-4.5 vs -33 kcal/mol). Under approximately physiological ionic conditions, the specific binding site will be saturated but will provide only a fraction of the total free energy of Mg(2+)-RNA interactions.

Salt Contribution to RNA Tertiary Structure Folding Stability

Accurate quantification of the ionic contribution to RNA folding stability could greatly enhance our ability to understand and predict RNA functions. Recently, motivated by the potential importance of ion correlation and fluctuation in RNA folding, we developed the tightly bound ion (TBI) model. Extensive experimental tests showed that the TBI model can lead to better treatment of multivalent ions than the Poisson-Boltzmann equation. In this study, we use the model to quantify the contribution of salt (Na+ and Mg2+) to the RNA tertiary structure folding free energy. Folding of the RNA tertiary structure often involves intermediates. We focus on the folding transition from an intermediate state to the native state, and compute the electrostatic folding free energy of the RNA. Based on systematic calculations for a variety of RNA molecules, we derive a set of formulas for the electrostatic free energy for tertiary structural folding as a function of the sequence length and compactness of the RNA and the Na+ and Mg2+ concentrations. Extensive comparisons with experimental data suggest that our model and the extracted empirical formulas are quite reliable.

Thermodynamics and Kinetics of the Hairpin Ribozyme from Atomistic Folding/Unfolding Simulations

We report a set of atomistic folding/unfolding simulations for the hairpin ribozyme using a Monte Carlo algorithm. The hairpin ribozyme folds in solution and catalyzes self-cleavage or ligation via a specific two-domain structure. The minimal active ribozyme has been studied extensively, showing stabilization of the active structure by cations and dynamic motion of the active structure. Here, we introduce a simple model of tertiary-structure formation that leads to a phase diagram for the RNA as a function of temperature and tertiary-structure strength. We then employ this model to capture many folding/unfolding events and to examine the transition-state ensemble (TSE) of the RNA during folding to its active “docked” conformation. The TSE is compact but with few tertiary interactions formed, in agreement with single-molecule dynamics experiments. To compare with experimental kinetic parameters, we introduce a novel method to benchmark Monte Carlo kinetic parameters to docking/undocking rates collected over many single molecular trajectories. We find that topology alone, as encoded in a biased potential that discriminates between secondary and tertiary interactions, is sufficient to predict the thermodynamic behavior and kinetic folding pathway of the hairpin ribozyme. This method should be useful in predicting folding transition states for many natural or man-made RNA tertiary structures.

RNA Folding Pathways and the Self-Assembly of Ribosomes

Many RNAs do not directly code proteins but are nonetheless indispensable to cellular function. These strands fold into intricate three-dimensional shapes that are essential structures in protein synthesis, splicing, and many other processes of gene regulation and expression. A variety of biophysical and biochemical methods are now showing, in real time, how ribosomal subunits and other ribonucleoprotein complexes assemble from their molecular components. Footprinting methods are particularly useful for studying the folding of long RNAs: they provide quantitative information about the conformational state of each residue and require little material. Data from footprinting complement the global information available from small-angle X-ray scattering or cryo-electron microscopy, as well as the dynamic information derived from single-molecule Förster resonance energy transfer (FRET) and NMR methods. In this Account, I discuss how we have used hydroxyl radical footprinting and other experimental methods to study pathways of RNA folding and 30S ribosome assembly. Hydroxyl radical footprinting probes the solvent accessibility of the RNA backbone at each residue in as little as 10 ms, providing detailed views of RNA folding pathways in real time. In conjunction with other methods such as solution scattering and single-molecule FRET, time-resolved footprinting of ribozymes showed that stable domains of RNA tertiary structure fold in less than 1 s. However, the free energy landscapes for RNA folding are rugged, and individual molecules kinetically partition into folding pathways that lead through metastable intermediates, stalling the folding or assembly process. Time-resolved footprinting was used to follow the formation of tertiary structure and protein interactions in the 16S ribosomal RNA (rRNA) during the assembly of 30S ribosomes. As previously observed in much simpler ribozymes, assembly occurs in stages, with individual molecules taking different routes to the final complex. Interactions occur concurrently in all domains of the 16S rRNA, and multistage protection of binding sites of individual proteins suggests that initial encounter complexes between the rRNA and ribosomal proteins are remodeled during assembly. Equilibrium footprinting experiments showed that one primary binding protein was sufficient to stabilize the tertiary structure of the entire 16S 5'-domain. The rich detail available from the footprinting data showed that the secondary assembly protein S16 suppresses non-native structures in the 16S 5'-domain. In doing so, S16 enables a conformational switch distant from its own binding site, which may play a role in establishing interactions with other domains of the 30S subunit. Together, the footprinting results show how protein-induced changes in RNA structure are communicated over long distances, ensuring cooperative assembly of even very large RNA-protein complexes such as the ribosome.

A conditional random fields method for RNA sequence–structure relationship modeling and conformation sampling

Accurate tertiary structures are very important for the functional study of non-coding RNA molecules. However, predicting RNA tertiary structures is extremely challenging, because of a large conformation space to be explored and lack of an accurate scoring function differentiating the native structure from decoys. The fragment-based conformation sampling method (e.g. FARNA) bears shortcomings that the limited size of a fragment library makes it infeasible to represent all possible conformations well. A recent dynamic Bayesian network method, BARNACLE, overcomes the issue of fragment assembly. In addition, neither of these methods makes use of sequence information in sampling conformations. Here, we present a new probabilistic graphical model, conditional random fields (CRFs), to model RNA sequence–structure relationship, which enables us to accurately estimate the probability of an RNA conformation from sequence. Coupled with a novel tree-guided sampling scheme, our CRF model is then applied to RNA conformation sampling. Experimental results show that our CRF method can model RNA sequence–structure relationship well and sequence information is important for conformation sampling. Our method, named as TreeFolder, generates a much higher percentage of native-like decoys than FARNA and BARNACLE, although we use the same simple energy function as BARNACLE.Contact: zywang@ttic.edu; j3xu@ttic.eduSupplementary Information: Supplementary data are available at Bioinformatics online.

Modeling and automation of sequencing-based characterization of RNA structure

Sequence census methods reduce molecular measurements such as transcript abundance and protein-nucleic acid interactions to counting problems via DNA sequencing. We focus on a novel assay utilizing this approach, called selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq), that can be used to characterize RNA secondary and tertiary structure. We describe a fully automated data analysis pipeline for SHAPE-Seq analysis that includes read processing, mapping, and structural inference based on a model of the experiment. Our methods rely on the solution of a series of convex optimization problems for which we develop efficient and effective numerical algorithms. Our results can be easily extended to other chemical probes of RNA structure, and also generalized to modeling polymerase drop-off in other sequence census-based experiments.