Structured RNAs and RNA-protein complexes (RNPs) are involved in many essential biological processes and the specific conformations of these RNAs are crucial to their various functions. However, in vitro studies have found that RNA has propensity for misfolding into inactive species that often consist of extensive secondary and tertiary interactions, which can be locally and globally stabilizing, resulting in long-lived non-native conformers. DEAD-box helicases are one class of proteins that have been found to accelerate folding and rearrangements of highly structured RNAs. While these proteins have been shown to use ATP to unwind short RNA helices, it is not known how they disrupt the tertiary interactions that often stabilize both native and misfolded RNA conformations. We used single molecule fluorescence to probe the mechanism by which DEAD-box proteins facilitate global unfolding of a structured RNA. DEAD-box protein CYT-19, a mitochondrial protein from Neurospora crassa, was found to destabilize a specific tertiary interaction with the Tetrahymena group I intron ribozyme using a helix capture mechanism. The protein molecule binds to a helix within the structured RNA only after the helix spontaneously loses its tertiary contacts, and then uses ATP to unwind the helix, liberating the product strands. Ded1, a multi-functional DEAD-box protein found in Saccharomyces cerevisiae, 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 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. / text

RNA and protein molecules undergo a dynamic folding process that is important to their function. Computational methods are critical for studying this folding pro- cess because it is difficult to observe experimentally. In this work, we introduce new computational techniques to study RNA and protein energy landscapes, includ- ing a method to approximate an RNA energy landscape with a coarse graph (map) and new tools for analyzing graph-based approximations of RNA and protein energy landscapes. These analysis techniques can be used to study RNA and protein fold- ing kinetics such as population kinetics, folding rates, and the folding of particular subsequences. In particular, a map-based Master Equation (MME) method can be used to analyze the population kinetics of the maps, while another map analysis tool, map-based Monte Carlo (MMC) simulation, can extract stochastic folding pathways from the map. To validate the results, I compared our methods with other computational meth- ods and with experimental studies of RNA and protein. I first compared our MMC and MME methods for RNA with other computational methods working on the com- plete energy landscape and show that the approximate map captures the major fea- tures of a much larger (e.g., by orders of magnitude) complete energy landscape. Moreover, I show that the methods scale well to large molecules, e.g., RNA with 200+ nucleotides. Then, I correlate the computational results with experimental findings. I present comparisons with two experimental cases to show how I can pre- dict kinetics-based functional rates of ColE1 RNAII and MS2 phage RNA and their mutants using our MME and MMC tools respectively. I also show that the MME and MMC tools can be applied to map-based approximations of protein energy energy landscapes and present kinetics analysis results for several proteins.

At first glance, robots and proteins have little in common. Robots are commonly thought of as tools that perform tasks such as vacuuming the floor, while proteins play essential roles in many biochemical processes. However, the functionality of both robots and proteins is highly dependent on their motions. In order to study motions in these two divergent domains, the same underlying algorithmic framework can be applied. This method is derived from probabilistic roadmap methods (PRMs) originally developed for robotic motion planning. It builds a graph, or roadmap, where configurations are represented as vertices and transitions between configurations are edges. The contribution of this work is a set of intelligent methods applied to PRMs. These methods facilitate both the modeling and analysis of motions, and have enabled the study of complex and high-dimensional problems in both robotic and molecular domains. In order to efficiently study biologically relevant molecular folding behaviors we have developed new techniques based on Monte Carlo solution, master equation calculation, and non-linear dimensionality reduction to run simulations and analysis on the roadmap. The first method, Map-based master equation calculation (MME), extracts global properties of the folding landscape such as global folding rates. On the other hand, another method, Map-based Monte Carlo solution (MMC), can be used to extract microscopic features of the folding process. Also, the application of dimensionality reduction returns a lower-dimensional representation that still retains the principal features while facilitating both modeling and analysis of motion landscapes. A key contribution of our methods is the flexibility to study larger and more complex structures, e.g., 372 residue Alpha-1 antitrypsin and 200 nucleotide ColE1 RNAII. We also applied intelligent roadmap-based techniques to the area of robotic motion. These methods take advantage of unsupervised learning methods at all stages of the planning process and produces solutions in complex spaces with little cost and less manual intervention compared to other adaptive methods. Our results show that our methods have low overhead and that they out-perform two existing adaptive methods in all complex cases studied.

The accurate prediction of an RNA secondary structure from its sequence will enhance the experimental design and interpretation for the increasing number of scientists that study RNA. While the computer programs that make these predictions have improved, additional improvements are necessary, in particular for larger RNAs. The first major section of this dissertation is concerned with improving the prediction accuracy of RNA secondary structures by generating new energetic parameters and evaluating a new RNA folding model. Statistical potentials for hairpin and internal loops produce significantly higher prediction accuracy when compared with nine other folding programs. While more improvements can be made to the energetic parameters used by secondary structure folding programs, I believe that a new approach is also necessary. I describe a RNA folding model that is predicated on a large body of computational and experimental work. This model includes energetics, contact distance, competition and a folding pathway. Each component of this folding model is evaluated and substantiated for its validity. The statistical potentials were created with comparative analysis. Comparative analysis requires the creation of highly accurate multiple RNA sequence alignments. The second major section of this dissertation is focused on my template-based sequence aligner, CRWAlign. Multiple sequence aligners generally run into problems when the pairwise sequence identity drops too low. By utilizing multiple dimensions of data to establish a profile for each position in a template alignment, CRWAlign is able to align new sequences with high accuracy even for pairs of sequence with low identity. / text

Numerous essential cellular processes, such as gene regulation and tRNA processing, are carried out by structured RNAs. While in vitro most RNAs become kinetically trapped in non-functional misfolded states that render them inactive on a biologically-relevant time scale, RNAs folding in vivo do not share this same outcome. RNAs do indeed misfold in the cell; however, chaperone proteins promote escape from these non-native states and foster folding to functional conformations. DEAD-box proteins are ATP-dependent RNA chaperone proteins that function by disrupting structure, which can facilitate structural conversions. Here, studies with both local and global focuses are used to uncover mechanistic features of DEAD-box proteins CYT-19 and Mss116p. Both of these proteins are general RNA chaperones as they each have the ability to facilitate proper folding of multiple structured RNAs. The first study probes how DEAD-box proteins interact with a simple duplex substrate. Separating the strands of a duplex is an ATP-dependent process and is central to structural disruption by DEAD-box proteins. Here, how ATP is utilized during duplex separation is monitored by comparing ATP hydrolysis rates with strand separation rates. Results indicate that one ATP molecule is sufficient for complete separation of a 6-11 base pair RNA duplex. Under some conditions, ATP binding in the absence of hydrolysis is sufficient for duplex separation. Next, focus is shifted to a more global perspective as the function of Mss116p is probed in the folding of a cognate group II intron substrate, aI5[gamma], under near-physiological conditions. Three catalytically-active constructs of aI5[gamma] are used and catalysis serves as a proxy for folding. Folding of all constructs is promoted by the presence of Mss116p and ATP. In vitro and in vivo results indicate that a local unfolding event is promoted by Mss116p, stimulating formation of the native state. Lastly, orthogonal methods that probe physical features of RNA are used to provide insight into the structural intermediates with which Mss116p acts. / text

Structured RNAs are pervasive in biology, spanning a functional repertoire that includes messengers, regulators of gene expression and catalysts of translation and splicing. From the relatively simple tRNAs and riboswitches to the highly structured ribosomal RNAs, the ability of RNAs to function is dependent on well-defined secondary and tertiary structures. However, studies of RNA folding in vitro have revealed an extreme propensity to form alternative structures, which can be long-lived and interfere with function. In the cell, a diverse array of RNA binding proteins and RNA chaperones guide RNAs towards the correct structure and disrupt misfolded intermediates. Among these proteins, DEAD-box protein family stands out as one of the largest groups, with its members ubiquitously involved in RNA metabolism across all domains of life. DEAD-box proteins can function as both specific and general RNA chaperones by disrupting RNA structures in an ATP-dependent manner. Here I describe my work studying the general RNA chaperone mechanism of the Neurospora crassa protein CYT-19, a model DEAD-box protein and a biological RNA chaperone that is required for efficient folding of self-splicing group I intron RNAs in vivo. After an introduction to DEAD-box proteins and their mechanisms as RNA remodelers (Chapter 1), I will first describe studies of group I intron unfolding by CYT-19, focusing on the effects of RNA tertiary structure stability on CYT-19 activity and targeting to RNA substrates (Chapter 2). I will then describe the characterization of ATP-dependent mechanisms during CYT-19-mediated refolding of the misfolded group I intron (Chapter 3). In Chapter 4, I will present small-angle X-ray scattering (SAXS) studies of structural features of DEAD-box proteins that allow them to efficiently interact with large structured RNA substrates. Finally, I will turn to studies of DEAD-box protein involvement during early steps of RNA compaction and folding, using SAXS and activity-based approaches (Chapter 5). I will conclude with a general discussion of superfamily 2 RNA helicases, which include DEAD-box and related proteins, and their functions and mechanisms as remodelers of structured RNAs and RNPs. / text

The secondary structure for nucleic acids provides a level of description that is both abstract enough to allow for efficient algorithms and realistic enough to provide a good approximate to the thermodynamic and kinetics properties of RNA structure formation. The secondary structure model has furthermore been successful in explaining salient features of RNA evolution in nature and in the test tube. In this contribution we review the computational chemistry of RNA secondary structures using a simplified algorithmic approach for explanation.

The functions of many cellular RNAs require that they fold into specific three-dimensional native structures, which typically involves arranging secondary structure elements and stabilizing the folded structure with tertiary contacts. However, RNA folding is inherently complex, as most RNAs fold along pathways containing multiple intermediates, including some misfolded intermediates that can accumulate and persist. Our understanding of the origins and structures of misfolded forms and the resolution of misfolding remains limited. Here, we investigate folding of the Tetrahymena intron, an extensively studied RNA folding model system since its initial discovery decades ago. The ribozyme variant predominantly misfolds, and slow refolding to the native state requires extensive structural disruption. Paradoxically, the misfolded conformation contains extensive native structure and lacks incorrect secondary and tertiary contacts despite requiring displacement of a native helix, termed P3, with incorrect secondary structure to misfold. We propose a model for a new origin of RNA misfolding to resolve this paradox, wherein misfolded ribozyme contains within its core incorrect arrangement of two single-stranded segments, i.e. altered topology. This model predicts a requirement for P3 disruption to exchange the misfolded and native topologies. We mutated P3 to modulate its stability and used the ribozyme's catalytic activity to show that P3 is disrupted during the refolding transition. Furthermore, we demonstrate that unfolding of the peripheral tertiary contacts precedes disruption of P3 to allow the necessary structural transitions. We then explored the influence of topology on the pathways leading to the misfolded and native states. Our results suggest that P3 exists in an earlier pathway intermediate that resembles the misfolded conformation, and that P3 unfolds to allow a small yet significant fraction of ribozyme to avoid misfolding. Despite being on a path to misfolding, the decision to misfold depends upon the probability of disrupting P3 and exchanging topology at this intermediate. Additionally, we show that having a stable P3 in the unfolded ribozyme allows almost complete avoidance of misfolding. Together, these studies lead to a physical model for folding and misfolding of a large RNA that is unprecedented in its scope and detail. / text

Many functional RNAs are required to fold into specific three-dimensional structures. A fundamental property of RNA is that its secondary structure and even some tertiary contacts are highly stable, which gives rise to independent modular RNA motifs and makes RNAs prone to adopting misfolded intermediates. Consequently, in addition to stabilizing the native structure relative to the unfolded species (defined here as stability), RNAs are faced with the challenge of stabilizing the native structure relative to alternative structures (defined as structural specificity). How RNAs have evolved to overcome these challenges is incompletely understood. Self-splicing group I introns have been used to study RNA structure and folding for decades. Among them, the Tetrahymena intron was the first discovered and has been studied extensively. In this work, we found that a version of the intron that was generated by in vitro selection for enhanced stability also displayed enhanced specificity against a stable misfolded structure that is globally similar to the native state, despite the absence of selective pressure to increase the energy gap between these structures. Further dissection suggests that the increased specificity against misfolding arises from two point mutations, which strengthen a local tertiary contact network that apparently cannot form in the misfolded conformation. Our results suggest that the structural rigidity and intricate networks of contacts inherent to structured RNAs can allow them to evolve exquisite structural specificity without explicit negative selection, even against closely-related alternative structures. To explore further how RNAs gain stability from intricate architectures, we examined a novel group I intron from red algae (Bangia). Biochemical methods and computational modeling suggest that this intron possesses general motifs of group IC1 introns but also forms an atypical tertiary contact, which has been reported previously in other subgroups and helps position the reactive helix at the active site. In the Bangia intron, the partners have been swapped relative to known group I RNAs that include this contact. This result underscores the modular nature of RNA motifs and provides insight into how structured RNAs can arrange helices and contacts in multiple ways to achieve and stabilize functional structures. / text

Group I introns are structured RNAs that have been used extensively as model systems for RNA folding because they are experimentally tractable, yet complex enough to have folding challenges associated with larger RNAs. The Tetrahymena group I intron consists of a set of conserved core helices and a set of peripheral elements. Peripheral elements surround the core helices and form long range tertiary contacts between each other and to the core. Interestingly, a long-lived misfolded state is populated that has the same long range tertiary contacts as the native state but differs locally within the core. Our lab showed that the intact periphery is necessary to specify the correct core structure, as mutating tertiary contacts or removing the P5abc peripheral element dramatically destabilized the native ribozyme relative to the misfolded form. However, we also showed that the thermodynamic benefit peripheral structure provided is accompanied by kinetic liability in folding, apparently because native tertiary contacts formed by peripheral elements around the misfolded core must come apart to allow refolding of the misfolded RNA to the native state. In addition to peripheral elements, proteins also play a role in stabilizing the native structures of many group I introns. The CYT-18 protein, which occupies the same binding site as P5abc, stabilizes the functional structures of certain group I introns by using a set of insertions that are absent in other related bacterial and mitochondrial aminoacyl tRNA synthetases. Using the P5abc deletion variant of the Tetrahymena ribozyme, I sought to further define CYT-18 roles in RNA folding by probing its thermodynamic and kinetic effects on the native state formation relative to the misfolded state. I demonstrated that CYT-18, like P5abc, provided thermodynamic stability to the native state. However, unlike P5abc, CYT-18 had no apparent effect on the refolding kinetics, suggesting that a protein co-factor can stabilize the functional structure without acquiring the associated costs in RNA folding kinetics. Furthermore, I found that the mechanism of CYT-18 action appears to be distinct from P5abc. Disruption of the long-range contact P14, which is formed between P5c and L2 and is part of the network of peripheral contacts, dramatically weakened P5abc binding to the native ribozyme core by ~10⁸ fold. Interestingly, CYT-18 maintained specific and tight binding to these mutants, which suggests that CYT-18 does not rely on a circular network of contacts to specifically stabilize the native state. Instead, the specificity may arise from a more direct and intimate contact of CYT-18 with the ribozyme core. This study gives insight into an evolutionary advantage of protein co-factors in RNA folding; proteins may offer thermodynamic assistance without inhibiting folding kinetics. / text