Topological constraints are major determinants of tRNA tertiary structure and dynamics and provide basis for tertiary folding cooperativity

Impact of Ion-Mixing Entropy on Orientational Preferences of DNA Helices: FRET Measurements and Computer Simulations

Biological processes require DNA and RNA helices to pack together in specific interhelical orientations. While electrostatic repulsion between backbone charges is expected to be maximized when helices are in parallel alignment, such orientations are commonplace in nature. To better understand how the repulsion is overcome, we used experimental and computational approaches to investigate how the orientational preferences of DNA helices depend on the concentration and valence of mobile cations. We used Förster resonance energy transfer (FRET) to probe the relative orientations of two 24-bp helices held together via a freely rotating PEG linker. At low cation concentrations, the helices preferred more "cross"-like orientations over those closer to parallel, and this preference was reduced with increasing salt concentrations. The results were in good quantitative agreement with Poisson-Boltzmann (PB) calculations for monovalent salt (Na+). However, PB underestimated the ability of mixtures of monovalent and divalent ions (Mg2+) to reduce the conformational preference. As a complementary approach, we performed all-atom molecular dynamics (MD) simulations and found better agreement with the experimental results. While MD and PB predict similar electrostatic forces, MD predicts a greater accumulation of Mg2+ in the ion atmosphere surrounding the DNA. Mg2+ occupancy is predicted to be greater in conformations close to the parallel orientation than in conformations close to the crossed orientation, enabling a greater release of Na+ ions and providing an entropic gain (one bound ion for two released). MD predicts an entropy gain larger than that of PB because of the increased Mg2+ occupancy. The entropy changes have a negligible effect at low Mg2+ concentrations because the free energies are dominated by electrostatic repulsion. However, as the Mg2+ concentration increases, charge screening is more effective and the mixing entropy produces readily detectable changes in packing preferences. Our results underline the importance of mixing entropy of counterions in nucleic acid interactions and provide a new understanding on the impact of a mixed ion atmosphere on the packing of DNA helices.

Pressure pushes tRNALys3 into excited conformational states

Conformational dynamics play essential roles in RNA function. However, detailed structural characterization of excited states of RNA remains challenging. Here, we apply high hydrostatic pressure (HP) to populate excited conformational states of tRNALys3, and structurally characterize them using a combination of HP 2D-NMR, HP-SAXS (HP-small-angle X-ray scattering), and computational modeling. HP-NMR revealed that pressure disrupts the interactions of the imino protons of the uridine and guanosine U-A and G-C base pairs of tRNALys3. HP-SAXS profiles showed a change in shape, but no change in overall extension of the transfer RNA (tRNA) at HP. Configurations extracted from computational ensemble modeling of HP-SAXS profiles were consistent with the NMR results, exhibiting significant disruptions to the acceptor stem, the anticodon stem, and the D-stem regions at HP. We propose that initiation of reverse transcription of HIV RNA could make use of one or more of these excited states.

The roles of structural dynamics in the cellular functions of RNAs

RNAs fold into 3D structures that range from simple helical elements to complex tertiary structures and quaternary ribonucleoprotein assemblies. The functions of many regulatory RNAs depend on how their 3D structure changes in response to a diverse array of cellular conditions. In this Review, we examine how the structural characterization of RNA as dynamic ensembles of conformations, which form with different probabilities and at different timescales, is improving our understanding of RNA function in cells. We discuss the mechanisms of gene regulation by microRNAs, riboswitches, ribozymes, post-transcriptional RNA modifications and RNA-binding proteins, and how the cellular environment and processes such as liquid-liquid phase separation may affect RNA folding and activity. The emerging RNA-ensemble-function paradigm is changing our perspective and understanding of RNA regulation, from in vitro to in vivo and from descriptive to predictive.

Structure-Based Model of RNA Pseudoknot Captures Magnesium-Dependent Folding Thermodynamics

We develop a simple, coarse-grained approach for simulating the folding of the Beet Western Yellow Virus (BWYV) pseudoknot toward the goal of creating a transferable model that can be used to study other small RNA molecules. This approach combines a structure-based model (SBM) of RNA with an electrostatic scheme that has previously been shown to correctly reproduce ionic condensation in the native basin. Mg²⁺ ions are represented explicitly, directly incorporating ion-ion correlations into the system, and K⁺ is represented implicitly, through the mean-field generalized Manning counterion condensation theory. Combining the electrostatic scheme with a SBM enables the electrostatic scheme to be tested beyond the native basin. We calibrate the SBM to reproduce experimental BWYV unfolding data by eliminating overstabilizing backbone interactions from the molecular contact map and by strengthening base pairing and stacking contacts relative to other native contacts, consistent with the experimental observation that relative helical stabilities are central determinants of the RNA unfolding sequence. We find that this approach quantitatively captures the Mg²⁺ dependence of the folding temperature and generates intermediate states that better approximate those revealed by experiment. Finally, we examine how our model captures Mg²⁺ condensation about the BWYV pseudoknot and a U-tail variant, for which the nine 3' end nucleotides are replaced with uracils, and find our results to be consistent with experimental condensation measurements. This approach can be easily transferred to other RNA molecules by eliminating and strengthening the same classes of contacts in the SBM and including generalized Manning counterion condensation.

RNA Structural Differentiation: Opportunities with Pattern Recognition

Our awareness and appreciation of the many regulatory roles of RNA have dramatically increased in the past decade. This understanding, in addition to the impact of RNA in many disease states, has renewed interest in developing selective RNA-targeted small molecule probes. However, the fundamental guiding principles in RNA molecular recognition that could accelerate these efforts remain elusive. While high-resolution structural characterization can provide invaluable insight, examples of well-characterized RNA structures, not to mention small molecule:RNA complexes, remain limited. This Perspective provides an overview of the current techniques used to understand RNA molecular recognition when high-resolution structural information is unavailable. We will place particular emphasis on a new method, pattern recognition of RNA with small molecules (PRRSM), that provides rapid insight into critical components of RNA recognition and differentiation by small molecules as well as into RNA structural features.

High-Throughput Investigation of Diverse Junction Elements in RNA Tertiary Folding

RNAs fold into defined tertiary structures to function in critical biological processes. While quantitative models can predict RNA secondary structure stability, we are still unable to predict the thermodynamic stability of RNA tertiary structure. Here, we probe conformational preferences of diverse RNA two-way junctions to develop a predictive model for the formation of RNA tertiary structure. We quantitatively measured tertiary assembly energetics of >1,000 of RNA junctions inserted in multiple structural scaffolds to generate a "thermodynamic fingerprint" for each junction. Thermodynamic fingerprints enabled comparison of junction conformational preferences, revealing principles for how sequence influences 3-dimensional conformations. Utilizing fingerprints of junctions with known crystal structures, we generated ensembles for related junctions that predicted their thermodynamic effects on assembly formation. This work reveals sequence-structure-energetic relationships in RNA, demonstrates the capacity for diverse compensation strategies within tertiary structures, and provides a path to quantitative modeling of RNA folding energetics based on "ensemble modularity."

Tuning RNA folding and function through rational design of junction topology

Structured RNAs such as ribozymes must fold into specific 3D structures to carry out their biological functions. While it is well-known that architectural features such as flexible junctions between helices help guide RNA tertiary folding, the mechanisms through which junctions influence folding remain poorly understood. We combine computational modeling with single molecule Förster resonance energy transfer (smFRET) and catalytic activity measurements to investigate the influence of junction design on the folding and function of the hairpin ribozyme. Coarse-grained simulations of a wide range of junction topologies indicate that differences in sterics and connectivity, independent of stacking, significantly affect tertiary folding and appear to largely explain previously observed variations in hairpin ribozyme stability. We further use our simulations to identify stabilizing modifications of non-optimal junction topologies, and experimentally validate that a three-way junction variant of the hairpin ribozyme can be stabilized by specific insertion of a short single-stranded linker. Combined, our multi-disciplinary study further reinforces that junction sterics and connectivity are important determinants of RNA folding, and demonstrates the potential of coarse-grained simulations as a tool for rationally tuning and optimizing RNA folding and function.

Capturing RNA Folding Free Energy with Coarse-Grained Molecular Dynamics Simulations

We introduce a coarse-grained RNA model for molecular dynamics simulations, RACER (RnA CoarsE-gRained). RACER achieves accurate native structure prediction for a number of RNAs (average RMSD of 2.93 Å) and the sequence-specific variation of free energy is in excellent agreement with experimentally measured stabilities (R2 = 0.93). Using RACER, we identified hydrogen-bonding (or base pairing), base stacking, and electrostatic interactions as essential driving forces for RNA folding. Also, we found that separating pairing vs. stacking interactions allowed RACER to distinguish folded vs. unfolded states. In RACER, base pairing and stacking interactions each provide an approximate stability of 3-4 kcal/mol for an A-form helix. RACER was developed based on PDB structural statistics and experimental thermodynamic data. In contrast with previous work, RACER implements a novel effective vdW potential energy function, which led us to re-parameterize hydrogen bond and electrostatic potential energy functions. Further, RACER is validated and optimized using a simulated annealing protocol to generate potential energy vs. RMSD landscapes. Finally, RACER is tested using extensive equilibrium pulling simulations (0.86 ms total) on eleven RNA sequences (hairpins and duplexes).

Small Molecule-Based Pattern Recognition To Classify RNA Structure

Three-dimensional RNA structures are notoriously difficult to determine, and the link between secondary structure and RNA conformation is only beginning to be understood. These challenges have hindered the identification of guiding principles for small molecule:RNA recognition. We herein demonstrate that the strong and differential binding ability of aminoglycosides to RNA structures can be used to classify five canonical RNA secondary structure motifs through principal component analysis (PCA). In these analyses, the aminoglycosides act as receptors, while RNA structures labeled with a benzofuranyluridine fluorophore act as analytes. Complete (100%) predictive ability for this RNA training set was achieved by incorporating two exhaustively guanidinylated aminoglycosides into the receptor library. The PCA was then externally validated using biologically relevant RNA constructs. In bulge-stem-loop constructs of HIV-1 transactivation response element (TAR) RNA, we achieved nucleotide-specific classification of two independent secondary structure motifs. Furthermore, examination of cheminformatic parameters and PCA loading factors revealed trends in aminoglycoside:RNA recognition, including the importance of shape-based discrimination, and suggested the potential for size and sequence discrimination within RNA structural motifs. These studies present a new approach to classifying RNA structure and provide direct evidence that RNA topology, in addition to sequence, is critical for the molecular recognition of RNA.

Principles and Overview of Sampling Methods for Modeling Macromolecular Structure and Dynamics

Investigation of macromolecular structure and dynamics is fundamental to understanding how macromolecules carry out their functions in the cell. Significant advances have been made toward this end in silico, with a growing number of computational methods proposed yearly to study and simulate various aspects of macromolecular structure and dynamics. This review aims to provide an overview of recent advances, focusing primarily on methods proposed for exploring the structure space of macromolecules in isolation and in assemblies for the purpose of characterizing equilibrium structure and dynamics. In addition to surveying recent applications that showcase current capabilities of computational methods, this review highlights state-of-the-art algorithmic techniques proposed to overcome challenges posed in silico by the disparate spatial and time scales accessed by dynamic macromolecules. This review is not meant to be exhaustive, as such an endeavor is impossible, but rather aims to balance breadth and depth of strategies for modeling macromolecular structure and dynamics for a broad audience of novices and experts.

Structural Analysis of Multi-Helical RNAs by NMR-SAXS/WAXS: Application to the U4/U6 di-snRNA

NMR and SAXS (small-angle X-ray scattering)/WAXS (wide-angle X-ray scattering) are highly complementary approaches for the analysis of RNA structure in solution. Here we describe an efficient NMR-SAXS/WAXS approach for structural investigation of multi-helical RNAs. We illustrate this approach by determining the overall fold of a 92-nt 3-helix junction from the U4/U6 di-snRNA. The U4/U6 di-snRNA is conserved in eukaryotes and is part of the U4/U6.U5 tri-snRNP, a large ribonucleoprotein complex that comprises a major subunit of the assembled spliceosome. Helical orientations can be determined by X-ray scattering data alone, but the addition of NMR RDC (residual dipolar coupling) restraints improves the structure models. RDCs were measured in two different external alignment media and also by magnetic susceptibility anisotropy. The resulting alignment tensors are collinear, which is a previously noted problem for nucleic acids. Including WAXS data in the calculations produces models with significantly better fits to the scattering data. In solution, the U4/U6 di-snRNA forms a 3-helix junction with a planar Y-shaped structure and has no detectable tertiary interactions. Single-molecule Förster resonance energy transfer data support the observed topology. A comparison with the recently determined cryo-electron microscopy structure of the U4/U6.U5 tri-snRNP illustrates how proteins scaffold the RNA and dramatically alter the geometry of the U4/U6 3-helix junction.

Biochemical Methods To Investigate lncRNA and the Influence of lncRNA:Protein Complexes on Chromatin

Long noncoding RNAs (lncRNAs), defined as nontranslated transcripts greater than 200 nucleotides in length, are often differentially expressed throughout developmental stages, tissue types, and disease states. The identification, visualization, and suppression/overexpression of these sequences have revealed impacts on a wide range of biological processes, including epigenetic regulation. Biochemical investigations on select systems have revealed striking insight into the biological roles of lncRNAs and lncRNA:protein complexes, which in turn prompt even more unanswered questions. To begin, multiple protein- and RNA-centric technologies have been employed to isolate lncRNA:protein and lncRNA:chromatin complexes. LncRNA interactions with the multi-subunit protein complex PRC2, which acts as a transcriptional silencer, represent some of the few cases where the binding affinity, selectivity, and activity of a lncRNA:protein complex have been investigated. At the same time, recent reports of full-length lncRNA secondary structures suggest the formation of complex structures with multiple independent folding domains and pave the way for more detailed structural investigations and predictions of lncRNA three-dimensional structure. This review will provide an overview of the methods and progress made to date as well as highlight new methods that promise to further inform the molecular recognition, specificity, and function of lncRNAs.

Structural and Dynamic Basis for Low-Affinity, High-Selectivity Binding of L-Glutamine by the Glutamine Riboswitch

Naturally occurring L-glutamine riboswitches occur in cyanobacteria and marine metagenomes, where they reside upstream of genes involved in nitrogen metabolism. By combining X-ray, NMR, and MD, we characterized an L-glutamine-dependent conformational transition in the Synechococcus elongatus glutamine riboswitch from tuning fork to L-shaped alignment of stem segments. This transition generates an open ligand-binding pocket with L-glutamine selectivity enforced by Mg(2+)-mediated intermolecular interactions. The transition also stabilizes the P1 helix through a long-range "linchpin" Watson-Crick G-C pair-capping interaction, while melting a short helix below P1 potentially capable of modulating downstream readout. NMR data establish that the ligand-free glutamine riboswitch in Mg(2+) solution exists in a slow equilibrium between flexible tuning fork and a minor conformation, similar, but not identical, to the L-shaped bound conformation. We propose that an open ligand-binding pocket combined with a high conformational penalty for forming the ligand-bound state provide mechanisms for reducing binding affinity while retaining high selectivity.

Secondary structure encodes a cooperative tertiary folding funnel in the Azoarcus ribozyme

A requirement for specific RNA folding is that the free-energy landscape discriminate against non-native folds. While tertiary interactions are critical for stabilizing the native fold, they are relatively non-specific, suggesting additional mechanisms contribute to tertiary folding specificity. In this study, we use coarse-grained molecular dynamics simulations to explore how secondary structure shapes the tertiary free-energy landscape of the Azoarcus ribozyme. We show that steric and connectivity constraints posed by secondary structure strongly limit the accessible conformational space of the ribozyme, and that these so-called topological constraints in turn pose strong free-energy penalties on forming different tertiary contacts. Notably, native A-minor and base-triple interactions form with low conformational free energy, while non-native tetraloop/tetraloop–receptor interactions are penalized by high conformational free energies. Topological constraints also give rise to strong cooperativity between distal tertiary interactions, quantitatively matching prior experimental measurements. The specificity of the folding landscape is further enhanced as tertiary contacts place additional constraints on the conformational space, progressively funneling the molecule to the native state. These results indicate that secondary structure assists the ribozyme in navigating the otherwise rugged tertiary folding landscape, and further emphasize topological constraints as a key force in RNA folding.

Modulating RNA Alignment Using Directional Dynamic Kinks: Application in Determining an Atomic-Resolution Ensemble for a Hairpin using NMR Residual Dipolar Couplings

Approaches that combine experimental data and computational molecular dynamics (MD) to determine atomic resolution ensembles of biomolecules require the measurement of abundant experimental data. NMR residual dipolar couplings (RDCs) carry rich dynamics information, however, difficulties in modulating overall alignment of nucleic acids have limited the ability to fully extract this information. We present a strategy for modulating RNA alignment that is based on introducing variable dynamic kinks in terminal helices. With this strategy, we measured seven sets of RDCs in a cUUCGg apical loop and used this rich data set to test the accuracy of an 0.8 μs MD simulation computed using the Amber ff10 force field as well as to determine an atomic resolution ensemble. The MD-generated ensemble quantitatively reproduces the measured RDCs, but selection of a sub-ensemble was required to satisfy the RDCs within error. The largest discrepancies between the RDC-selected and MD-generated ensembles are observed for the most flexible loop residues and backbone angles connecting the loop to the helix, with the RDC-selected ensemble resulting in more uniform dynamics. Comparison of the RDC-selected ensemble with NMR spin relaxation data suggests that the dynamics occurs on the ps-ns time scales as verified by measurements of R(1ρ) relaxation-dispersion data. The RDC-satisfying ensemble samples many conformations adopted by the hairpin in crystal structures indicating that intrinsic plasticity may play important roles in conformational adaptation. The approach presented here can be applied to test nucleic acid force fields and to characterize dynamics in diverse RNA motifs at atomic resolution.

MD Simulations of tRNA and Aminoacyl-tRNA Synthetases: Dynamics, Folding, Binding, and Allostery

While tRNA and aminoacyl-tRNA synthetases are classes of biomolecules that have been extensively studied for decades, the finer details of how they carry out their fundamental biological functions in protein synthesis remain a challenge. Recent molecular dynamics (MD) simulations are verifying experimental observations and providing new insight that cannot be addressed from experiments alone. Throughout the review, we briefly discuss important historical events to provide a context for how far the field has progressed over the past few decades. We then review the background of tRNA molecules, aminoacyl-tRNA synthetases, and current state of the art MD simulation techniques for those who may be unfamiliar with any of those fields. Recent MD simulations of tRNA dynamics and folding and of aminoacyl-tRNA synthetase dynamics and mechanistic characterizations are discussed. We highlight the recent successes and discuss how important questions can be addressed using current MD simulations techniques. We also outline several natural next steps for computational studies of AARS:tRNA complexes.

Noncanonical secondary structure stabilizes mitochondrial tRNA(Ser(UCN)) by reducing the entropic cost of tertiary folding

Mammalian mitochondrial tRNA(Ser(UCN)) (mt-tRNA(Ser)) and pyrrolysine tRNA (tRNA(Pyl)) fold to near-canonical three-dimensional structures despite having noncanonical secondary structures with shortened interhelical loops that disrupt the conserved tRNA tertiary interaction network. How these noncanonical tRNAs compensate for their loss of tertiary interactions remains unclear. Furthermore, in human mt-tRNA(Ser), lengthening the variable loop by the 7472insC mutation reduces mt-tRNA(Ser) concentration in vivo through poorly understood mechanisms and is strongly associated with diseases such as deafness and epilepsy. Using simulations of the TOPRNA coarse-grained model, we show that increased topological constraints encoded by the unique secondary structure of wild-type mt-tRNA(Ser) decrease the entropic cost of folding by ∼2.5 kcal/mol compared to canonical tRNA, offsetting its loss of tertiary interactions. Further simulations show that the pathogenic 7472insC mutation disrupts topological constraints and hence destabilizes the mutant mt-tRNA(Ser) by ∼0.6 kcal/mol relative to wild-type. UV melting experiments confirm that insertion mutations lower mt-tRNA(Ser) melting temperature by 6-9 °C and increase the folding free energy by 0.8-1.7 kcal/mol in a largely sequence- and salt-independent manner, in quantitative agreement with our simulation predictions. Our results show that topological constraints provide a quantitative framework for describing key aspects of RNA folding behavior and also provide the first evidence of a pathogenic mutation that is due to disruption of topological constraints.

Hierarchy of RNA functional dynamics

RNA dynamics play a fundamental role in many cellular functions. However, there is no general framework to describe these complex processes, which typically consist of many structural maneuvers that occur over timescales ranging from picoseconds to seconds. Here, we classify RNA dynamics into distinct modes representing transitions between basins on a hierarchical free-energy landscape. These transitions include large-scale secondary-structural transitions at >0.1-s timescales, base-pair/tertiary dynamics at microsecond-to-millisecond timescales, stacking dynamics at timescales ranging from nanoseconds to microseconds, and other "jittering" motions at timescales ranging from picoseconds to nanoseconds. We review various modes within these three different tiers, the different mechanisms by which they are used to regulate function, and how they can be coupled together to achieve greater functional complexity.