Energy barriers, pathways, and dynamics during folding of large, multidomain RNAs

Mass Spectrometry of Nucleic Acid Noncovalent Complexes

Nucleic acids have been among the first targets for antitumor drugs and antibiotics. With the unveiling of new biological roles in regulation of gene expression, specific DNA and RNA structures have become very attractive targets, especially when the corresponding proteins are undruggable. Biophysical assays to assess target structure as well as ligand binding stoichiometry, affinity, specificity, and binding modes are part of the drug development process. Mass spectrometry offers unique advantages as a biophysical method owing to its ability to distinguish each stoichiometry present in a mixture. In addition, advanced mass spectrometry approaches (reactive probing, fragmentation techniques, ion mobility spectrometry, ion spectroscopy) provide more detailed information on the complexes. Here, we review the fundamentals of mass spectrometry and all its particularities when studying noncovalent nucleic acid structures, and then review what has been learned thanks to mass spectrometry on nucleic acid structures, self-assemblies (e.g., duplexes or G-quadruplexes), and their complexes with ligands.

Viroid research and its significance for RNA technology and basic biochemistry

Viroids were described 47 years ago as the smallest RNA molecules capable of infecting plants and autonomously self-replicating without an encoded protein. Work on viroids initiated the development of a number of innovative methods. Novel chromatographic and gelelectrophoretic methods were developed for the purification and characterization of viroids; these methods were later used in molecular biology, gene technology and in prion research. Theoretical and experimental studies of RNA folding demonstrated the general biological importance of metastable structures, and nuclear magnetic resonance spectroscopy of viroid RNA showed the partially covalent nature of hydrogen bonds in biological macromolecules. RNA biochemistry and molecular biology profited from viroid research, such as in the detection of RNA as template of DNA-dependent polymerases and in mechanisms of gene silencing. Viroids, the first circular RNA detected in nature, are important for studies on the much wider spectrum of circular RNAs and other non-coding RNAs.

Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo

When a ribonucleic acid (RNA) molecule folds, it often does not adopt a single, well-defined conformation. The folding energy landscape of an RNA is highly dependent on its nucleotide sequence and molecular environment. Cellular molecules sometimes alter the energy landscape, thereby changing the ensemble of likely low-energy conformations. The effects of these energy landscape changes on the conformational ensemble are particularly challenging to visualize for large RNAs. We have created a robust approach for visualizing the conformational ensemble of RNAs that is well suited for in vitro versus in vivo comparisons. Our method creates a stable map of conformational space for a given RNA sequence. We first identify single point mutations in the RNA that maximally sample suboptimal conformational space based on the ensemble’s partition function. Then, we cluster these diverse ensembles to identify the most diverse partition functions for Boltzmann stochastic sampling. By using, to our knowledge, a novel nestedness distance metric, we iteratively add mutant suboptimal ensembles to converge on a stable 2D map of conformational space. We then compute the selective 2′ hydroxyl acylation by primer extension (SHAPE)-directed ensemble for the RNA folding under different conditions, and we project these ensembles on the map to visualize. To validate our approach, we established a conformational map of the Vibrio vulnificus add adenine riboswitch that reveals five classes of structures. In the presence of adenine, projection of the SHAPE-directed sampling correctly identified the on-conformation; without the ligand, only off-conformations were visualized. We also collected the whole-transcript in vitro and in vivo SHAPE-MaP for human β-actin messenger RNA that revealed similar global folds in both conditions. Nonetheless, a comparison of in vitro and in vivo data revealed that specific regions exhibited significantly different SHAPE-MaP profiles indicative of structural rearrangements, including rearrangement consistent with binding of the zipcode protein in a region distal to the stop codon.

Kinetic and thermodynamic framework for P4-P6 RNA reveals tertiary motif modularity and modulation of the folding preferred pathway

The past decade has seen a wealth of 3D structural information about complex structured RNAs and identification of functional intermediates. Nevertheless, developing a complete and predictive understanding of the folding and function of these RNAs in biology will require connection of individual rate and equilibrium constants to structural changes that occur in individual folding steps and further relating these steps to the properties and behavior of isolated, simplified systems. To accomplish these goals we used the considerable structural knowledge of the folded, unfolded, and intermediate states of P4-P6 RNA. We enumerated structural states and possible folding transitions and determined rate and equilibrium constants for the transitions between these states using single-molecule FRET with a series of mutant P4-P6 variants. Comparisons with simplified constructs containing an isolated tertiary contact suggest that a given tertiary interaction has a stereotyped rate for breaking that may help identify structural transitions within complex RNAs and simplify the prediction of folding kinetics and thermodynamics for structured RNAs from their parts. The preferred folding pathway involves initial formation of the proximal tertiary contact. However, this preference was only ∼10 fold and could be reversed by a single point mutation, indicating that a model akin to a protein-folding contact order model will not suffice to describe RNA folding. Instead, our results suggest a strong analogy with a modified RNA diffusion-collision model in which tertiary elements within preformed secondary structures collide, with the success of these collisions dependent on whether the tertiary elements are in their rare binding-competent conformations.

Coarse-grained modeling of RNA 3D structure

Functional RNA molecules depend on three-dimensional (3D) structures to carry out their tasks within the cell. Understanding how these molecules interact to carry out their biological roles requires a detailed knowledge of RNA 3D structure and dynamics as well as thermodynamics, which strongly governs the folding of RNA and RNA-RNA interactions as well as a host of other interactions within the cellular environment. Experimental determination of these properties is difficult, and various computational methods have been developed to model the folding of RNA 3D structures and their interactions with other molecules. However, computational methods also have their limitations, especially when the biological effects demand computation of the dynamics beyond a few hundred nanoseconds. For the researcher confronted with such challenges, a more amenable approach is to resort to coarse-grained modeling to reduce the number of data points and computational demand to a more tractable size, while sacrificing as little critical information as possible. This review presents an introduction to the topic of coarse-grained modeling of RNA 3D structures and dynamics, covering both high- and low-resolution strategies. We discuss how physics-based approaches compare with knowledge based methods that rely on databases of information. In the course of this review, we discuss important aspects in the reasoning process behind building different models and the goals and pitfalls that can result.

Understanding the kinetic mechanism of RNA single base pair formation

RNA functions are intrinsically tied to folding kinetics. The most elementary step in RNA folding is the closing and opening of a base pair. Understanding this elementary rate process is the basis for RNA folding kinetics studies. Previous studies mostly focused on the unfolding of base pairs. Here, based on a hybrid approach, we investigate the folding process at level of single base pairing/stacking. The study, which integrates molecular dynamics simulation, kinetic Monte Carlo simulation, and master equation methods, uncovers two alternative dominant pathways: Starting from the unfolded state, the nucleotide backbone first folds to the native conformation, followed by subsequent adjustment of the base conformation. During the base conformational rearrangement, the backbone either retains the native conformation or switches to nonnative conformations in order to lower the kinetic barrier for base rearrangement. The method enables quantification of kinetic partitioning among the different pathways. Moreover, the simulation reveals several intriguing ion binding/dissociation signatures for the conformational changes. Our approach may be useful for developing a base pair opening/closing rate model.

An active site rearrangement within the Tetrahymena group I ribozyme releases nonproductive interactions and allows formation of catalytic interactions

Biological catalysis hinges on the precise structural integrity of an active site that binds and transforms its substrates and meeting this requirement presents a unique challenge for RNA enzymes. Functional RNAs, including ribozymes, fold into their active conformations within rugged energy landscapes that often contain misfolded conformers. Here we uncover and characterize one such "off-pathway" species within an active site after overall folding of the ribozyme is complete. The Tetrahymena group I ribozyme (E) catalyzes cleavage of an oligonucleotide substrate (S) by an exogenous guanosine (G) cofactor. We tested whether specific catalytic interactions with G are present in the preceding E•S•G and E•G ground-state complexes. We monitored interactions with G via the effects of 2'- and 3'-deoxy (-H) and -amino (-NH(2)) substitutions on G binding. These and prior results reveal that G is bound in an inactive configuration within E•G, with the nucleophilic 3'-OH making a nonproductive interaction with an active site metal ion termed MA and with the adjacent 2'-OH making no interaction. Upon S binding, a rearrangement occurs that allows both -OH groups to contact a different active site metal ion, termed M(C), to make what are likely to be their catalytic interactions. The reactive phosphoryl group on S promotes this change, presumably by repositioning the metal ions with respect to G. This conformational transition demonstrates local rearrangements within an otherwise folded RNA, underscoring RNA's difficulty in specifying a unique conformation and highlighting Nature's potential to use local transitions of RNA in complex function.

Computational modeling of RNA 3D structures and interactions

RNA molecules have key functions in cellular processes beyond being carriers of protein-coding information. These functions are often dependent on the ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is difficult, which has prompted the development of computational methods for structure prediction from sequence. Recent progress in 3D structure modeling of RNA and emerging approaches for predicting RNA interactions with ions, ligands and proteins have been stimulated by successes in protein 3D structure modeling.

Genome-wide profiling of mouse RNA secondary structures reveals key features of the mammalian transcriptome

Background

The understanding of RNA structure is a key feature toward the comprehension of RNA functions and mechanisms of action. In particular, non-coding RNAs are thought to exert their functions by specific secondary structures, but an efficient annotation on a large scale of these structures is still missing.

Results

By using a novel high-throughput method, named chemical inference of RNA structures, CIRS-seq, that uses dimethyl sulfate, and N-cyclohexyl- N'-(2-morpholinoethyl)carbodiimide metho-p-toluenesulfonate to modify RNA residues in single-stranded conformation within native deproteinized RNA secondary structures, we investigate the structural features of mouse embryonic stem cell transcripts. Our analysis reveals an unexpected higher structuring of the 5′ and 3′ untranslated regions compared to the coding regions, a reduced structuring at the Kozak sequence and stop codon, and a three-nucleotide periodicity across the coding region of messenger RNAs. We also observe that ncRNAs exhibit a higher degree of structuring with respect to protein coding transcripts. Moreover, we find that the Lin28a binding protein binds selectively to RNA motifs with a strong preference toward a single stranded conformation.

Conclusions

This work defines for the first time the complete RNA structurome of mouse embryonic stem cells, revealing an extremely distinct RNA structural landscape. These results demonstrate that CIRS-seq constitutes an important tool for the identification of native deproteinized RNA structures.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0491-2) contains supplementary material, which is available to authorized users.

MEPSA: minimum energy pathway analysis for energy landscapes

From conformational studies to atomistic descriptions of enzymatic reactions, potential and free energy landscapes can be used to describe biomolecular systems in detail. However, extracting the relevant data of complex 3D energy surfaces can sometimes be laborious. In this article, we present MEPSA (Minimum Energy Path Surface Analysis), a cross-platform user friendly tool for the analysis of energy landscapes from a transition state theory perspective. Some of its most relevant features are: identification of all the barriers and minima of the landscape at once, description of maxima edge profiles, detection of the lowest energy path connecting two minima and generation of transition state theory diagrams along these paths. In addition to a built-in plotting system, MEPSA can save most of the generated data into easily parseable text files, allowing more versatile uses of MEPSA's output such as the generation of molecular dynamics restraints from a calculated path.

AVAILABILITY AND IMPLEMENTATION

MEPSA is freely available (under GPLv3 license) at: http://bioweb.cbm.uam.es/software/MEPSA/ CONTACT: pagomez@cbm.csic.es.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Unzippers, resolvers and sensors: a structural and functional biochemistry tale of RNA helicases

The centrality of RNA within the biological world is an irrefutable fact that currently attracts increasing attention from the scientific community. The panoply of functional RNAs requires the existence of specific biological caretakers, RNA helicases, devoted to maintain the proper folding of those molecules, resolving unstable structures. However, evolution has taken advantage of the specific position and characteristics of RNA helicases to develop new functions for these proteins, which are at the interface of the basic processes for transference of information from DNA to proteins. RNA helicases are involved in many biologically relevant processes, not only as RNA chaperones, but also as signal transducers, scaffolds of molecular complexes, and regulatory elements. Structural biology studies during the last decade, founded in X-ray crystallography, have characterized in detail several RNA-helicases. This comprehensive review summarizes the structural knowledge accumulated in the last two decades within this family of proteins, with special emphasis on the structure-function relationships of the most widely-studied families of RNA helicases: the DEAD-box, RIG-I-like and viral NS3 classes.

DEAD-box helicase proteins disrupt RNA tertiary structure through helix capture

Single-molecule fluorescence experiments reveal how DEAD-box proteins unfold structured RNAs to promote conformational transitions and refolding to the native functional state.

DEAD-box helicase proteins accelerate folding and rearrangements of highly structured RNAs and RNA–protein complexes (RNPs) in many essential cellular processes. Although DEAD-box proteins have been shown to use ATP to unwind short RNA helices, it is not known how they disrupt RNA tertiary structure. Here, we use single molecule fluorescence to show that the DEAD-box protein CYT-19 disrupts tertiary structure in a group I intron using a helix capture mechanism. CYT-19 binds to a helix within the structured RNA only after the helix spontaneously loses its tertiary contacts, and then CYT-19 uses ATP to unwind the helix, liberating the product strands. Ded1, a multifunctional yeast DEAD-box protein, gives analogous results with small but reproducible differences that may reflect its in vivo roles. The requirement for spontaneous dynamics likely targets DEAD-box proteins toward less stable RNA structures, which are likely to experience greater dynamic fluctuations, and provides a satisfying explanation for previous correlations between RNA stability and CYT-19 unfolding efficiency. Biologically, the ability to sense RNA stability probably biases DEAD-box proteins to act preferentially on less stable misfolded structures and thereby to promote native folding while minimizing spurious interactions with stable, natively folded RNAs. In addition, this straightforward mechanism for RNA remodeling does not require any specific structural environment of the helicase core and is likely to be relevant for DEAD-box proteins that promote RNA rearrangements of RNP complexes including the spliceosome and ribosome.

In addition to carrying genetic information from DNA to protein, RNAs function in many essential cellular processes. This often requires the RNA to form a specific three-dimensional structure, and some functions require cycling between multiple structures. However, RNAs have a strong propensity to become trapped in nonfunctional, misfolded structures. Due to the intrinsic stability of local structure for RNA, these misfolded species can be long-lived and therefore accumulate. ATP-dependent RNA chaperone proteins called DEAD-box proteins are known to promote native RNA folding by disrupting misfolded structures. Although these proteins can unwind short RNA helices, the mechanism by which they act upon higher order tertiary contacts is unknown. Our current work shows that DEAD-box proteins capture transiently exposed RNA helices, preventing any tertiary contacts from reforming and potentially destabilizing the global RNA architecture. Helix unwinding by the DEAD-box protein then allows the product RNA strands to form new contacts. This helix capture mechanism for manipulation of RNA tertiary structure does not require a specific binding motif or structural environment and may be general for DEAD-box helicase proteins that act on structured RNAs.

Mapping the kinetic barriers of a Large RNA molecule's folding landscape

The folding of linear polymers into discrete three-dimensional structures is often required for biological function. The formation of long-lived intermediates is a hallmark of the folding of large RNA molecules due to the ruggedness of their energy landscapes. The precise thermodynamic nature of the barriers (whether enthalpic or entropic) that leads to intermediate formation is still poorly characterized in large structured RNA molecules. A classic approach to analyzing kinetic barriers are temperature dependent studies analyzed with Eyring's transition state theory. We applied Eyring's theory to time-resolved hydroxyl radical (•OH) footprinting kinetics progress curves collected at eight temperature from 21.5 °C to 51 °C to characterize the thermodynamic nature of folding intermediate formation for the Mg(2+)-mediated folding of the Tetrahymena thermophila group I ribozyme. A common kinetic model configuration describes this RNA folding reaction over the entire temperature range studied consisting of primary (fast) transitions to misfolded intermediates followed by much slower secondary transitions, consistent with previous studies. Eyring analysis reveals that the primary transitions are moderate in magnitude and primarily enthalpic in nature. In contrast, the secondary transitions are daunting in magnitude and entropic in nature. The entropic character of the secondary transitions is consistent with structural rearrangement of the intermediate species to the final folded form. This segregation of kinetic control reveals distinctly different molecular mechanisms during the two stages of RNA folding and documents the importance of entropic barriers to defining rugged RNA folding landscapes.

On the importance of cotranscriptional RNA structure formation

The expression of genes, both coding and noncoding, can be significantly influenced by RNA structural features of their corresponding transcripts. There is by now mounting experimental and some theoretical evidence that structure formation in vivo starts during transcription and that this cotranscriptional folding determines the functional RNA structural features that are being formed. Several decades of research in bioinformatics have resulted in a wide range of computational methods for predicting RNA secondary structures. Almost all state-of-the-art methods in terms of prediction accuracy, however, completely ignore the process of structure formation and focus exclusively on the final RNA structure. This review hopes to bridge this gap. We summarize the existing evidence for cotranscriptional folding and then review the different, currently used strategies for RNA secondary-structure prediction. Finally, we propose a range of ideas on how state-of-the-art methods could be potentially improved by explicitly capturing the process of cotranscriptional structure formation.

Evolutionary evidence for alternative structure in RNA sequence co-variation

Sequence conservation and co-variation of base pairs are hallmarks of structured RNAs. For certain RNAs (e.g. riboswitches), a single sequence must adopt at least two alternative secondary structures to effectively regulate the message. If alternative secondary structures are important to the function of an RNA, we expect to observe evolutionary co-variation supporting multiple conformations. We set out to characterize the evolutionary co-variation supporting alternative conformations in riboswitches to determine the extent to which alternative secondary structures are conserved. We found strong co-variation support for the terminator, P1, and anti-terminator stems in the purine riboswitch by extending alignments to include terminator sequences. When we performed Boltzmann suboptimal sampling on purine riboswitch sequences with terminators we found that these sequences appear to have evolved to favor specific alternative conformations. We extended our analysis of co-variation to classic alignments of group I/II introns, tRNA, and other classes of riboswitches. In a majority of these RNAs, we found evolutionary evidence for alternative conformations that are compatible with the Boltzmann suboptimal ensemble. Our analyses suggest that alternative conformations are selected for and thus likely play functional roles in even the most structured of RNAs.

RNA (Ribonucleic Acid) is a messenger of genetic information, master regulator, and catalyst in the cell. To carry out its function, RNA can fold into complex three-dimensional structures. Certain classes of RNAs, called riboswitches, adopt at least two alternative structures to act as a switch. We set out to detect the evolutionary signal for alternative structures in riboswitches as we hypothesize that these RNA sequences must have evolved to allow both conformations. We find that indeed such signals exist when we compare the sequences of riboswitches from multiple species. When we extend this analysis to other RNA regulators in the cell that are not thought of as switches, we detect equivalent evolutionary support for alternative structures. Viewed through the lens of evolutionary structure conservation RNA sequences appear to have adapted to adopt multiple conformations.

The long-range P3 helix of the Tetrahymena ribozyme is disrupted during folding between the native and misfolded conformations

RNAs are prone to misfolding, but how misfolded structures are formed and resolved remains incompletely understood. The Tetrahymena group I intron ribozyme folds in vitro to a long-lived misfolded conformation (M) that includes extensive native structure but is proposed to differ in topology from the native state (N). A leading model predicts that exchange of the topologies requires unwinding of the long-range, core helix P3, despite the presence of P3 in both conformations. To test this model, we constructed 16 mutations to strengthen or weaken P3. Catalytic activity and in-line probing showed that nearly all of the mutants form the M state before folding to N. The P3-weakening mutations accelerated refolding from M (3- to 30-fold) and the P3-strengthening mutations slowed refolding (6- to 1400-fold), suggesting that P3 indeed unwinds transiently. Upon depletion of Mg(2+), the mutations had analogous effects on unfolding from N to intermediates that subsequently fold to M. The magnitudes for the P3-weakening mutations were larger than in refolding from M, and small-angle X-ray scattering showed that the ribozyme expands rapidly to intermediates from which P3 is disrupted subsequently. These results are consistent with previous results indicating unfolding of native peripheral structure during refolding from M, which probably permits rearrangement of the core. Together, our results demonstrate that exchange of the native and misfolded conformations requires loss of a core helix in addition to peripheral structure. Further, the results strongly suggest that misfolding arises from a topological error within the ribozyme core, and a specific topology is proposed.

Understanding the role of three-dimensional topology in determining the folding intermediates of group I introns

Many RNA molecules exert their biological function only after folding to unique three-dimensional structures. For long, noncoding RNA molecules, the complexity of finding the native topology can be a major impediment to correct folding to the biologically active structure. An RNA molecule may fold to a near-native structure but not be able to continue to the correct structure due to a topological barrier such as crossed strands or incorrectly stacked helices. Achieving the native conformation thus requires unfolding and refolding, resulting in a long-lived intermediate. We investigate the role of topology in the folding of two phylogenetically related catalytic group I introns, the Twort and Azoarcus group I ribozymes. The kinetic models describing the Mg(2+)-mediated folding of these ribozymes were previously determined by time-resolved hydroxyl (∙OH) radical footprinting. Two intermediates formed by parallel intermediates were resolved for each RNA. These data and analytical ultracentrifugation compaction analyses are used herein to constrain coarse-grained models of these folding intermediates as we investigate the role of nonnative topology in dictating the lifetime of the intermediates. Starting from an ensemble of unfolded conformations, we folded the RNA molecules by progressively adding native constraints to subdomains of the RNA defined by the ∙OH time-progress curves to simulate folding through the different kinetic pathways. We find that nonnative topologies (arrangement of helices) occur frequently in the folding simulations despite using only native constraints to drive the reaction, and that the initial conformation, rather than the folding pathway, is the major determinant of whether the RNA adopts nonnative topology during folding. From these analyses we conclude that biases in the initial conformation likely determine the relative flux through parallel RNA folding pathways.

Mss116p: a DEAD-box protein facilitates RNA folding

RNA folding is an essential aspect underlying RNA-mediated cellular processes. Many RNAs, including large, multi-domain ribozymes, are capable of folding to the native, functional state without assistance of a protein cofactor in vitro. In the cell, trans-acting factors, such as proteins, are however known to modulate the structure and thus the fate of an RNA. DEAD-box proteins, including Mss116p, were recently found to assist folding of group I and group II introns in vitro and in vivo. The underlying mechanism(s) have been studied extensively to explore the contribution of ATP hydrolysis and duplex unwinding in helicase-stimulated intron splicing. Here we summarize the ongoing efforts to understand the novel role of DEAD-box proteins in RNA folding.

Toward a molecular understanding of RNA remodeling by DEAD-box proteins

DEAD-box proteins are superfamily 2 helicases that function in all aspects of RNA metabolism. They employ ATP binding and hydrolysis to generate tight, yet regulated RNA binding, which is used to unwind short RNA helices non-processively and promote structural transitions of RNA and RNA-protein substrates. In the last few years, substantial progress has been made toward a detailed, quantitative understanding of the structural and biochemical properties of DEAD-box proteins. Concurrently, progress has been made toward a physical understanding of the RNA rearrangements and folding steps that are accelerated by DEAD-box proteins in model systems. Here, we review the recent progress on both of these fronts, focusing on the mitochondrial DEAD-box proteins Mss116 and CYT-19 and their mechanisms in promoting the splicing of group I and group II introns.

Efficient procedures for the numerical simulation of mid-size RNA kinetics

Motivation

Methods for simulating the kinetic folding of RNAs by numerically solving the chemical master equation have been developed since the late 90's, notably the programs Kinfold and Treekin with Barriers that are available in the Vienna RNA package. Our goal is to formulate extensions to the algorithms used, starting from the Gillespie algorithm, that will allow numerical simulations of mid-size (~ 60–150 nt) RNA kinetics in some practical cases where numerous distributions of folding times are desired. These extensions can contribute to analyses and predictions of RNA folding in biologically significant problems.

Results

By describing in a particular way the reduction of numerical simulations of RNA folding kinetics into the Gillespie stochastic simulation algorithm for chemical reactions, it is possible to formulate extensions to the basic algorithm that will exploit memoization and parallelism for efficient computations. These can be used to advance forward from the small examples demonstrated to larger examples of biological interest.

Software

The implementation that is described and used for the Gillespie algorithm is freely available by contacting the authors, noting that the efficient procedures suggested may also be applicable along with Vienna's Kinfold.

Predicting folding pathways between RNA conformational structures guided by RNA stacks

BACKGROUND

Accurately predicting low energy barrier folding pathways between conformational secondary structures of an RNA molecule can provide valuable information for understanding its catalytic and regulatory functions. Most existing heuristic algorithms guide the construction of folding pathways by free energies of intermediate structures in the next move during the folding. However due to the size and ruggedness of RNA energy landscape, energy-guided search can become trapped in local optima.

RESULTS

In this paper, we propose an algorithm that guides the construction of folding pathways through the formation and destruction of RNA stacks. Guiding the construction of folding pathways by coarse grained movements of RNA stacks can help reduce the search space and make it easier to jump out of local optima. RNAEAPath is able to find lower energy barrier folding pathways between secondary structures of conformational switches and outperforms the existing heuristic algorithms in most test cases.

CONCLUSIONS

RNAEAPath provides an alternate approach for predicting low-barrier folding pathways between RNA conformational secondary structures. The source code of RNAEAPath and the test data sets are available at http://genome.ucf.edu/RNAEAPath.

RNA catalysis as a probe for chaperone activity of DEAD-box helicases

DEAD-box proteins are vitally important to cellular processes and make up the largest class of helicases. Many DEAD-box proteins function as RNA chaperones by accelerating structural transitions of RNA, which can result in the resolution of misfolded conformers or conversion between functional structures. While the biological importance of chaperone proteins is clear, their mechanisms are incompletely understood. Here, we illustrate how the catalytic activity of certain RNAs can be used to measure RNA chaperone activity. By measuring the amount of substrate converted to product, the fraction of catalytically active molecules is measured over time, providing a quantitative measure of the formation or loss of native RNA. The assays are described with references to group I and group II introns and their ribozyme derivatives, and examples are included that illustrate potential complications and indicate how catalytic activity measurements can be combined with physical approaches to gain insights into the mechanisms of DEAD-box proteins as RNA chaperones.

The Azoarcus group I intron ribozyme misfolds and is accelerated for refolding by ATP-dependent RNA chaperone proteins

Structured RNAs traverse complex energy landscapes that include valleys representing misfolded intermediates. In Neurospora crassa and Saccharomyces cerevisiae, efficient splicing of mitochondrial group I and II introns requires the DEAD box proteins CYT-19 and Mss116p, respectively, which promote folding transitions and function as general RNA chaperones. To test the generality of RNA misfolding and the activities of DEAD box proteins in vitro, here we measure native folding of a small group I intron ribozyme from the bacterium Azoarcus by monitoring its catalytic activity. To develop this assay, we first measure cleavage of an oligonucleotide substrate by the prefolded ribozyme. Substrate cleavage is rate-limited by binding and is readily reversible, with an internal equilibrium near unity, such that the amount of product observed is less than the amount of native ribozyme. We use this assay to show that approximately half of the ribozyme folds readily to the native state, whereas the other half forms an intermediate that transitions slowly to the native state. This folding transition is accelerated by urea and increased temperature and slowed by increased Mg(2+) concentration, suggesting that the intermediate is misfolded and must undergo transient unfolding during refolding to the native state. CYT-19 and Mss116p accelerate refolding in an ATP-dependent manner, presumably by disrupting structure in the intermediate. These results highlight the tendency of RNAs to misfold, underscore the roles of CYT-19 and Mss116p as general RNA chaperones, and identify a refolding transition for further dissection of the roles of DEAD box proteins in RNA folding.

Strategies for articulated multibody-based adaptive coarse grain simulation of RNA

Efficient modeling approaches are necessary to accurately predict large-scale structural behavior of biomolecular systems like RNA (ribonucleic acid). Coarse-grained approximations of such complex systems can significantly reduce the computational costs of the simulation while maintaining sufficient fidelity to capture the biologically significant motions. However, given the coupling and nonlinearity of RNA systems (and effectively all biopolymers), it is expected that different parameters such as geometric and dynamic boundary conditions, and applied forces will affect the system's dynamic behavior. Consequently, static coarse-grained models (i.e., models for which the coarse graining is time invariant) are not always able to adequately sample the conformational space of the molecule. We introduce here the concept of adaptive coarse-grained molecular dynamics of RNA, which automatically adjusts the coarseness of the model, in an effort to more optimally increase simulation speed, while maintaining accuracy. Adaptivity requires two basic algorithmic developments: first, a set of integrators that seamlessly allow transitions between higher and lower fidelity models while preserving the laws of motion. Second, we propose and validate metrics for determining when and where more or less fidelity needs to be integrated into the model to allow sufficiently accurate dynamics simulation. Given the central role that multibody dynamics plays in the proposed framework, and the nominally large number of dynamic degrees of freedom being considered in these applications, a computationally efficient multibody method which lends itself well to adaptivity is essential to the success of this effort. A suite of divide-and-conquer algorithm (DCA)-based approaches is employed to this end. These algorithms have been selected and refined for this purpose because they offer a good combination of computational efficiency and modular structure.

RNA folding in living cells

RNA folding is the most essential process underlying RNA function. While significant progress has been made in understanding the forces driving RNA folding in vitro, exploring the rules governing intracellular RNA structure formation is still in its infancy. The cellular environment hosts a great diversity of factors that potentially influence RNA folding in vivo. For example, the nature of transcription and translation is known to shape the folding landscape of RNA molecules. Trans-acting factors such as proteins, RNAs and metabolites, among others, are also able to modulate the structure and thus the fate of an RNA. Here we summarize the ongoing efforts to uncover how RNA folds in living cells.

DEAD-box protein facilitated RNA folding in vivo

In yeast mitochondria the DEAD-box helicase Mss116p is essential for respiratory growth by acting as group I and group II intron splicing factor. Here we provide the first structure-based insights into how Mss116p assists RNA folding in vivo. Employing an in vivo chemical probing technique, we mapped the structure of the ai5γ group II intron in different genetic backgrounds to characterize its intracellular fold. While the intron adopts the native conformation in the wt yeast strain, we found that the intron is able to form most of its secondary structure, but lacks its tertiary fold in the absence of Mss116p. This suggests that ai5γ is largely unfolded in the mss116-knockout strain and requires the protein at an early step of folding. Notably, in this unfolded state misfolded substructures have not been observed. As most of the protein-induced conformational changes are located within domain D1, Mss116p appears to facilitate the formation of this largest domain, which is the scaffold for docking of other intron domains. These findings suggest that Mss116p assists the ordered assembly of the ai5γ intron in vivo.

Roles of DEAD-box proteins in RNA and RNP Folding

RNAs and RNA-protein complexes (RNPs) traverse rugged energy landscapes as they fold to their native structures, and many continue to undergo conformational rearrangements as they function. Due to the inherent stability of local RNA structure, proteins are required to assist with RNA conformational transitions during initial folding and in exchange between functional structures. DEAD-box proteins are superfamily 2 RNA helicases that are ubiquitously involved in RNA-mediated processes. Some of these proteins use an ATP-dependent cycle of conformational changes to disrupt RNA structure nonprocessively, accelerating structural transitions of RNAs and RNPs in a manner that bears a strong resemblance to the activities of certain groups of protein chaperones. This review summarizes recent work using model substrates and tractable self-splicing intron RNAs, which has given new insights into how DEAD-box proteins promote RNA folding steps and conformational transitions, and it summarizes recent progress in identifying sites and mechanisms of DEAD-box protein activity within more complex cellular targets.

Taming free energy landscapes with RNA chaperones

Many non-coding RNAs fold into complex three-dimensional structures, yet the self-assembly of RNA structure is hampered by mispairing, weak tertiary interactions, electrostatic barriers, and the frequent requirement that the 5' and 3' ends of the transcript interact. This rugged free energy landscape for RNA folding means that some RNA molecules in a population rapidly form their native structure, while many others become kinetically trapped in misfolded conformations. Transient binding of RNA chaperone proteins destabilize misfolded intermediates and lower the transition states between conformations, producing a smoother landscape that increases the rate of folding and the probability that a molecule will find the native structure. DEAD-box proteins couple the chemical potential of ATP hydrolysis with repetitive cycles of RNA binding and release, expanding the range of conditions under which they can refold RNA structures.

Inhibition of encephalomyocarditis virus and poliovirus replication by quinacrine: implications for the design and discovery of novel antiviral drugs

The 9-aminoacridine (9AA) derivative quinacrine (QC) has a long history of safe human use as an antiprotozoal and antirheumatic agent. QC intercalates into DNA and RNA and can inhibit DNA replication, RNA transcription, and protein synthesis. The extent of QC intercalation into RNA depends on the complexity of its secondary and tertiary structure. Internal ribosome entry sites (IRESs) that are required for initiation of translation of some viral and cellular mRNAs typically have complex structures. Recent work has shown that some intercalating drugs, including QC, are capable of inhibiting hepatitis C virus IRES-mediated translation in a cell-free system. Here, we show that QC suppresses translation directed by the encephalomyocarditis virus (EMCV) and poliovirus IRESs in a cell-free system and in virus-infected HeLa cells. In contrast, IRESs present in the mammalian p53 transcript that are predicted to have less-complex structures were not sensitive to QC. Inhibition of IRES-mediated translation by QC correlated with the affinity of binding between QC and the particular IRES. Expression of viral capsid proteins, replication of viral RNAs, and production of virus were all strongly inhibited by QC (and 9AA). These results suggest that QC and similar intercalating drugs could potentially be used for treatment of viral infections.

Compact intermediates in RNA folding

Large noncoding RNAs fold into their biologically functional structures via compact yet disordered intermediates, which couple the stable secondary structure of the RNA with the emerging tertiary fold. The specificity of the collapse transition, which coincides with the assembly of helical domains, depends on RNA sequence and counterions. It determines the specificity of the folding pathways and the magnitude of the free energy barriers to the ensuing search for the native conformation. By coupling helix assembly with nascent tertiary interactions, compact folding intermediates in RNA also play a crucial role in ligand binding and RNA-protein recognition.

Structure and dynamics of a processive Brownian motor: the translating ribosome

There is mounting evidence indicating that protein synthesis is driven and regulated by mechanisms that direct stochastic, large-scale conformational fluctuations of the translational apparatus. This mechanistic paradigm implies that a free-energy landscape governs the conformational states that are accessible to and sampled by the translating ribosome. This scenario presents interdependent opportunities and challenges for structural and dynamic studies of protein synthesis. Indeed, the synergism between cryogenic electron microscopic and X-ray crystallographic structural studies, on the one hand, and single-molecule fluorescence resonance energy transfer (smFRET) dynamic studies, on the other, is emerging as a powerful means for investigating the complex free-energy landscape of the translating ribosome and uncovering the mechanisms that direct the stochastic conformational fluctuations of the translational machinery. In this review, we highlight the principal insights obtained from cryogenic electron microscopic, X-ray crystallographic, and smFRET studies of the elongation stage of protein synthesis and outline the emerging themes, questions, and challenges that lie ahead in mechanistic studies of translation.

Evaluation of the information content of RNA structure mapping data for secondary structure prediction

Structure mapping experiments (using probes such as dimethyl sulfate [DMS], kethoxal, and T1 and V1 RNases) are used to determine the secondary structures of RNA molecules. The process is iterative, combining the results of several probes with constrained minimum free-energy calculations to produce a model of the structure. We aim to evaluate whether particular probes provide more structural information, and specifically, how noise in the data affects the predictions. Our approach involves generating "decoy" RNA structures (using the sFold Boltzmann sampling procedure) and evaluating whether we are able to identify the correct structure from this ensemble of structures. We show that with perfect information, we are always able to identify the optimal structure for five RNAs of known structure. We then collected orthogonal structure mapping data (DMS and RNase T1 digest) under several solution conditions using our high-throughput capillary automated footprinting analysis (CAFA) technique on two group I introns of known structure. Analysis of these data reveals the error rates in the data under optimal (low salt) and suboptimal solution conditions (high MgCl(2)). We show that despite these errors, our computational approach is less sensitive to experimental noise than traditional constraint-based structure prediction algorithms. Finally, we propose a novel approach for visualizing the interaction of chemical and enzymatic mapping data with RNA structure. We project the data onto the first two dimensions of a multidimensional scaling of the sFold-generated decoy structures. We are able to directly visualize the structural information content of structure mapping data and reconcile multiple data sets.

RNA editing: a driving force for adaptive evolution?

Genetic variability is considered a key to the evolvability of species. The conversion of an adenosine (A) to inosine (I) in primary RNA transcripts can result in an amino acid change in the encoded protein, a change in secondary structure of the RNA, creation or destruction of a splice consensus site, or otherwise alter RNA fate. Substantial transcriptome and proteome variability is generated by A-to-I RNA editing through site-selective post-transcriptional recoding of single nucleotides. We posit that this epigenetic source of phenotypic variation is an unrecognized mechanism of adaptive evolution. The genetic variation introduced through editing occurs at low evolutionary cost since predominant production of the wild-type protein is retained. This property even allows exploration of sequence space that is inaccessible through mutation, leading to increased phenotypic plasticity and provides an evolutionary advantage for acclimatization as well as long-term adaptation. Furthermore, continuous probing for novel RNA editing sites throughout the transcriptome is an intrinsic property of the editing machinery and represents the molecular basis for increased adaptability. We propose that higher organisms have therefore evolved to systems with increasing RNA editing activity and, as a result, to more complex systems.

Using analytical ultracentrifugation (AUC) to measure global conformational changes accompanying equilibrium tertiary folding of RNA molecules

Analytical ultracentrifugation (AUC) is a powerful technique to determine the global conformational changes in RNA molecules mediated by cations or small molecule ligands. Although most of the developments in the field of AUC have been centered on studies involving protein molecules, the experimental methods as well as the analytical approaches have been successfully adapted and applied to the study of a variety of RNA molecules ranging from small riboswitches to large ribozymes. Most often AUC studies are performed in conjunction with other structural probing techniques that provide complementary information on local changes in the solvent accessibilities at specific regions within RNA molecules. This chapter provides a brief theoretical background, working knowledge of instrumentation, practical considerations for experimental setup, and guidelines for data analysis procedures to enable the design, execution, and interpretation of sedimentation velocity experiments that detect changes in the global dimensions of an RNA molecule during its equilibrium folding.

Complementing global measures of RNA folding with local reports of backbone solvent accessibility by time resolved hydroxyl radical footprinting

A variety of analytical techniques are used to probe the mechanisms by which RNA molecules fold to discrete three dimensional structures. Methods such as small angle X-ray scattering (SAXS) report global properties like overall size and shape of the RNA. Other methods such as chemical or enzymatic mapping (footprinting) report properties with resolution as fine as single nucleotide. The hydroxyl radical (*OH) is a footprinting probe which cleaves the oligonucleotide backbone independently of sequence and thus is a valuable reporter of backbone solvent accessibility. Combinations of global and local measures of folding reactions are uniquely able to distinguish specific from nonspecific processes. This article highlights the application of *OH footprinting as a complement to SAXS for kinetics analysis of RNA folding. We illustrate this combination of techniques using a study of the role played by the stiffness of a hinge in determining the rate limiting step of a Mg(2+)-mediated RNA folding reaction.