Sequence-dependent RNA helix conformational preferences predictably impact tertiary structure formation

Systematic analysis of cotranscriptional RNA folding using transcription elongation complex display

RNA can fold into structures that mediate diverse cellular functions. Understanding how RNA primary sequence directs the formation of functional structures requires methods that can comprehensively assess how changes in an RNA sequence affect its structure and function. Here we have developed a platform for performing high-throughput cotranscriptional RNA biochemical assays, called Transcription Elongation Complex display (TECdisplay). TECdisplay measures RNA function by fractionating a TEC library based on the activity of cotranscriptionally displayed nascent RNA. In this way, RNA function is measured as the distribution of template DNA molecules between fractions of the transcription reaction. This approach circumvents typical RNA sequencing library preparation steps that can cause technical bias. We used TECdisplay to characterize the transcription antitermination activity of >1 million variants of the Clostridium beijerinckii pfl ZTP riboswitch designed to perturb steps within its cotranscriptional folding pathway. Our findings establish TECdisplay as an accessible platform for high-throughput RNA biochemical assays.

Conformational penalties: New insights into nucleic acid recognition

The energy cost accompanying changes in the structures of nucleic acids when they bind partner molecules is a significant but underappreciated thermodynamic contribution to binding affinity and specificity. This review highlights recent advances in measuring conformational penalties and determining their contribution to the recognition, folding, and regulatory activities of nucleic acids. Notable progress includes methods for measuring and structurally characterizing lowly populated conformational states, obtaining ensemble information in high throughput, for large macromolecular assemblies, and in complex cellular environments. Additionally, quantitative and predictive thermodynamic models have been developed that relate conformational penalties to nucleic acid-protein association and cellular activity. These studies underscore the crucial role of conformational penalties in nucleic acid recognition.

Exploring the energetic and conformational properties of the sequence space connecting naturally occurring RNA tetraloop receptor motifs

Folded RNAs contain tertiary contact motifs whose structures and energetics are conserved across different RNAs. The transferable properties of RNA motifs simplify the RNA folding problem, but measuring energetic and conformational properties of many motifs remains a challenge. Here, we use a high-throughput thermodynamic approach to investigate how sequence changes alter the binding properties of naturally occurring motifs, the GAAA tetraloop • tetraloop receptor (TLR) interactions. We measured the binding energies and conformational preferences of TLR sequences that span mutational pathways from the canonical 11ntR to two other natural TLRs, the IC3R and Vc2R. While the IC3R and Vc2R share highly similar energetic and conformational properties, the landscapes that map the sequence changes for their conversion from the 11ntR to changes in these properties differ dramatically. Differences in the energetic landscapes stem from the mutations needed to convert the 11ntR to the IC3R and Vc2R rather than a difference in the intrinsic energetic architectures of these TLRs. The conformational landscapes feature several nonnative TLR variants with conformational preferences that differ from both the initial and final TLRs; these species represent potential branching points along the multidimensional sequence space to sequences with greater fitness in other RNA contexts with alternative conformational preferences. Our high-throughput, quantitative approach reveals the complex nature of sequence-fitness landscapes and leads to models for their molecular origins. Systematic and quantitative molecular approaches provide critical insights into understanding the evolution of natural RNAs as they traverse complex landscapes in response to selective pressures.

Accurately Modeling RNA Stem-Loops in an Implicit Solvent Environment

Ribonucleic acid (RNA) molecules can adopt a variety of secondary and tertiary structures in solution, with stem-loops being one of the more common motifs. Here, we present a systematic analysis of 15 RNA stem-loop sequences simulated with molecular dynamics simulations in an implicit solvent environment. Analysis of RNA cluster ensembles showed that the stem-loop structures can generally adopt the A-form RNA in the stem region. Loop structures are more sensitive, and experimental structures could only be reproduced with modification of CH···O interactions in the force field, combined with an implicit solvent nonpolar correction to better model base stacking interactions. Accurately modeling RNA with current atomistic physics-based models remains challenging, but the RNA systems studied herein may provide a useful benchmark set for testing other RNA modeling methods in the future.

Structural Landscape of nsp Coding Genomic Regions of SARS-CoV-2-ssRNA Genome: A Structural Genomics Approach Toward Identification of Druggable Genome, Ligand-Binding Pockets, and Structure-Based Druggability

SARS-CoV-2 has a single-stranded RNA genome (+ssRNA), and synthesizes structural and non-structural proteins (nsps). All 16 nsp are synthesized from the ORF1a, and ORF1b regions associated with different life cycle preprocesses, including replication. The regions of ORF1a synthesizes nsp1 to 11, and ORF1b synthesizes nsp12 to 16. In this paper, we have predicted the secondary structure conformations, entropy & mountain plots, RNA secondary structure in a linear fashion, and 3D structure of nsp coding genes of the SARS-CoV-2 genome. We have also analyzed the A, T, G, C, A+T, and G+C contents, GC-profiling of these genes, showing the range of the GC content from 34.23 to 48.52%. We have observed that the GC-profile value of the nsp coding genomic regions was less (about 0.375) compared to the whole genome (about 0.38). Additionally, druggable pockets were identified from the secondary structure-guided 3D structural conformations. For secondary structure generation of all the nsp coding genes (nsp 1-16), we used a recent algorithm-based tool (deep learning-based) along with the conventional algorithms (centroid and MFE-based) to develop secondary structural conformations, and we found stem-loop, multi-branch loop, pseudoknot, and the bulge structural components, etc. The 3D model shows bound and unbound forms, branched structures, duplex structures, three-way junctions, four-way junctions, etc. Finally, we identified binding pockets of nsp coding genes which will help as a fundamental resource for future researchers to develop RNA-targeted therapeutics using the druggable genome.

Systematic analysis of cotranscriptional RNA folding using transcription elongation complex display

RNA can fold into structures that mediate diverse cellular functions. Understanding how RNA primary sequence directs the formation of functional structures requires methods that can comprehensively assess how changes in an RNA sequence affect its structure and function. Here we have developed a platform for performing high-throughput cotranscriptional RNA biochemical assays, called Transcription Elongation Complex display (TECdisplay). TECdisplay measures RNA function by fractionating a TEC library based on the activity of cotranscriptionally displayed nascent RNA. In this way, RNA function is measured as the distribution of template DNA molecules between fractions of the transcription reaction. This approach circumvents typical RNA sequencing library preparation steps that can cause technical bias. We used TECdisplay to characterize the transcription antitermination activity of 32,768 variants of the Clostridium beijerinckii pfl ZTP riboswitch designed to perturb steps within its cotranscriptional folding pathway. Our findings establish TECdisplay as an accessible platform for high-throughput RNA biochemical assays.

RNA structures and dynamics with Å resolution revealed by x-ray free-electron lasers

RNA macromolecules, like proteins, fold to assume shapes that are intimately connected to their broadly recognized biological functions; however, because of their high charge and dynamic nature, RNA structures are far more challenging to determine. We introduce an approach that exploits the high brilliance of x-ray free-electron laser sources to reveal the formation and ready identification of angstrom-scale features in structured and unstructured RNAs. Previously unrecognized structural signatures of RNA secondary and tertiary structures are identified through wide-angle solution scattering experiments. With millisecond time resolution, we observe an RNA fold from a dynamically varying single strand through a base-paired intermediate to assume a triple-helix conformation. While the backbone orchestrates the folding, the final structure is locked in by base stacking. This method may help to rapidly characterize and identify structural elements in nucleic acids in both equilibrium and time-resolved experiments.

The structure and mechanism of action of a distinct class of dicistrovirus intergenic region IRESs

Internal ribosomal entry sites (IRESs) engage with the eukaryotic translation apparatus to promote end-independent initiation. We identified a conserved class of ∼150 nt long intergenic region (IGR) IRESs in dicistrovirus genomes derived from members of the phyla Arthropoda, Bryozoa, Cnidaria, Echinodermata, Entoprocta, Mollusca and Porifera. These IRESs, exemplified by Wenling picorna-like virus 2, resemble the canonical cricket paralysis virus (CrPV) IGR IRES in comprising two nested pseudoknots (PKII/PKIII) and a 3'-terminal pseudoknot (PKI) that mimics a tRNA anticodon stem-loop base-paired to mRNA. However, they are ∼50 nt shorter than CrPV-like IRESs, and PKIII is an H-type pseudoknot that lacks the SLIV and SLV stem-loops that are primarily responsible for the affinity of CrPV-like IRESs for the 40S ribosomal subunit and that restrict initial binding of PKI to its aminoacyl (A) site. Wenling-class IRESs bound strongly to 80S ribosomes but only weakly to 40S subunits. Whereas CrPV-like IRESs must be translocated from the A site to the peptidyl (P) site by elongation factor 2 for elongation to commence, Wenling-class IRESs bound directly to the P site of 80S ribosomes, and decoding begins without a prior translocation step. A chimeric CrPV clone containing a Wenling-class IRES was infectious, confirming that the IRES functioned in cells.

DoubleHelix: nucleic acid sequence identification, assignment and validation tool for cryo-EM and crystal structure models

Sequence assignment is a key step of the model building process in both cryogenic electron microscopy (cryo-EM) and macromolecular crystallography (MX). If the assignment fails, it can result in difficult to identify errors affecting the interpretation of a model. There are many model validation strategies that help experimentalists in this step of protein model building, but they are virtually non-existent for nucleic acids. Here, I present doubleHelix-a comprehensive method for assignment, identification, and validation of nucleic acid sequences in structures determined using cryo-EM and MX. The method combines a neural network classifier of nucleobase identities and a sequence-independent secondary structure assignment approach. I show that the presented method can successfully assist sequence-assignment step in nucleic-acid model building at lower resolutions, where visual map interpretation is very difficult. Moreover, I present examples of sequence assignment errors detected using doubleHelix in cryo-EM and MX structures of ribosomes deposited in the Protein Data Bank, which escaped the scrutiny of available model-validation approaches. The doubleHelix program source code is available under BSD-3 license at https://gitlab.com/gchojnowski/doublehelix.

Initiation of translation on nedicistrovirus and related intergenic region IRESs by their factor-independent binding to the P site of 80S ribosomes

Initiation of translation on many viral mRNAs occurs by noncanonical mechanisms that involve 5' end-independent binding of ribosomes to an internal ribosome entry site (IRES). The ∼190-nt-long intergenic region (IGR) IRES of dicistroviruses such as cricket paralysis virus (CrPV) initiates translation without Met-tRNAi Met or initiation factors. Advances in metagenomics have revealed numerous dicistrovirus-like genomes with shorter, structurally distinct IGRs, such as nedicistrovirus (NediV) and Antarctic picorna-like virus 1 (APLV1). Like canonical IGR IRESs, the ∼165-nt-long NediV-like IGRs comprise three domains, but they lack key canonical motifs, including L1.1a/L1.1b loops (which bind to the L1 stalk of the ribosomal 60S subunit) and the apex of stem-loop V (SLV) (which binds to the head of the 40S subunit). Domain 2 consists of a compact, highly conserved pseudoknot (PKIII) that contains a UACUA loop motif and a protruding CrPV-like stem--loop SLIV. In vitro reconstitution experiments showed that NediV-like IRESs initiate translation from a non-AUG codon and form elongation-competent 80S ribosomal complexes in the absence of initiation factors and Met-tRNAi Met Unlike canonical IGR IRESs, NediV-like IRESs bind directly to the peptidyl (P) site of ribosomes leaving the aminoacyl (A) site accessible for decoding. The related structures of NediV-like IRESs and their common mechanism of action indicate that they exemplify a distinct class of IGR IRES.

RNA structures and dynamics with Å resolution revealed by x-ray free electron lasers

RNA macromolecules, like proteins, fold to assume shapes that are intimately connected to their broadly recognized biological functions; however, because of their high charge and dynamic nature, RNA structures are far more challenging to determine. We introduce an approach that exploits the high brilliance of x-ray free electron laser sources to reveal the formation and ready identification of Å scale features in structured and unstructured RNAs. New structural signatures of RNA secondary and tertiary structures are identified through wide angle solution scattering experiments. With millisecond time resolution, we observe an RNA fold from a dynamically varying single strand through a base paired intermediate to assume a triple helix conformation. While the backbone orchestrates the folding, the final structure is locked in by base stacking. In addition to understanding how RNA triplexes form and thereby function as dynamic signaling elements, this new method can vastly increase the rate of structure determination for these biologically essential, but mostly uncharacterized macromolecules.

Dissecting the energetic architecture within an RNA tertiary structural motif via high-throughput thermodynamic measurements

Structured RNAs and RNA/protein complexes perform critical cellular functions. They often contain structurally conserved tertiary contact "motifs," whose occurrence simplifies the RNA folding landscape. Prior studies have focused on the conformational and energetic modularity of intact motifs. Here, we turn to the dissection of one common motif, the 11nt receptor (11ntR), using quantitative analysis of RNA on a massively parallel array to measure the binding of all single and double 11ntR mutants to GAAA and GUAA tetraloops, thereby probing the energetic architecture of the motif. While the 11ntR behaves as a motif, its cooperativity is not absolute. Instead, we uncovered a gradient from high cooperativity amongst base-paired and neighboring residues to additivity between distant residues. As expected, substitutions at residues in direct contact with the GAAA tetraloop resulted in the largest decreases to binding, and energetic penalties of mutations were substantially smaller for binding to the alternate GUAA tetraloop, which lacks tertiary contacts present with the canonical GAAA tetraloop. However, we found that the energetic consequences of base partner substitutions are not, in general, simply described by base pair type or isostericity. We also found exceptions to the previously established stability-abundance relationship for 11ntR sequence variants. These findings of "exceptions to the rule" highlight the power of systematic high-throughput approaches to uncover novel variants for future study in addition to providing an energetic map of a functional RNA.

cRNAsp12 Web Server for the Prediction of Circular RNA Secondary Structures and Stabilities

Circular RNAs (circRNAs) are a novel class of non-coding RNA that, unlike linear RNAs, form a covalently closed loop without the 5' and 3' ends. Growing evidence shows that circular RNAs play important roles in life processes and have great potential implications in clinical and research fields. The accurate modeling of circRNAs structure and stability has far-reaching impact on our understanding of their functions and our ability to develop RNA-based therapeutics. The cRNAsp12 server offers a user-friendly web interface to predict circular RNA secondary structures and folding stabilities from the sequence. Through the helix-based landscape partitioning strategy, the server generates distinct ensembles of structures and predicts the minimal free energy structures for each ensemble with the recursive partition function calculation and backtracking algorithms. For structure predictions in the limited structural ensemble, the server also provides users with the option to set the structural constraints of forcing the base pairs and/or forcing the unpaired bases, such that only structures that meet the criteria are enumerated recursively.

Automated 3D Design and Evaluation of RNA Nanostructures with RNAMake

Despite growing interest in applying RNA's unique structural characteristics to solve diverse biotechnology and nanotechnology problems, there are few computational tools for targeted tertiary design. As a result, RNA 3D design is traditionally slow, resource-consuming, and dependent on expert modeling. In this chapter, we discuss our recently developed software package: RNAMake, a set of applications capable of designing RNA tertiary structures to solve various relevant nanotechnology problems and provide basic thermodynamic calculations for the generated designs. We provide in-depth examples and instructions for designing example RNA nanostructures such as minimal RNA sequences containing a single tertiary contact, generating RNAs that stabilize small-molecule ligands, and building tethers that link ribosomal subunits together. We also highlight the addition of a new Monte Carlo design algorithm and the ability to estimate the thermodynamic contribution of helical elements in RNA 3D structures.

High-throughput biochemistry in RNA sequence space: predicting structure and function

RNAs are central to fundamental biological processes in all known organisms. The set of possible intramolecular interactions of RNA nucleotides defines the range of alternative structural conformations of a specific RNA that can coexist, and these structures enable functional catalytic properties of RNAs and/or their productive intermolecular interactions with other RNAs or proteins. However, the immense combinatorial space of potential RNA sequences has precluded predictive mapping between RNA sequence and molecular structure and function. Recent advances in high-throughput approaches in vitro have enabled quantitative thermodynamic and kinetic measurements of RNA-RNA and RNA-protein interactions, across hundreds of thousands of sequence variations. In this Review, we explore these techniques, how they can be used to understand RNA function and how they might form the foundations of an accurate model to predict the structure and function of an RNA directly from its nucleotide sequence. The experimental techniques and modelling frameworks discussed here are also highly relevant for the sampling of sequence-structure-function space of DNAs and proteins.

Conformational Heterogeneity of RNA Stem-Loop Hairpins Bound to FUS-RNA Recognition Motif with Disordered RGG Tail Revealed by Unbiased Molecular Dynamics Simulations

RNA-protein complexes use diverse binding strategies, ranging from structurally well-defined interfaces to completely disordered regions. Experimental characterization of flexible segments is challenging and can be aided by atomistic molecular dynamics (MD) simulations. Here, we used an extended set of microsecond-scale MD trajectories (400 μs in total) to study two FUS-RNA constructs previously characterized by nuclear magnetic resonance (NMR) spectroscopy. The FUS protein contains a well-structured RNA recognition motif domain followed by a presumably disordered RGG tail that binds RNA stem-loop hairpins. Our simulations not only provide several suggestions complementing the experiments but also reveal major methodological difficulties in studies of such complex RNA-protein interfaces. Despite efforts to stabilize the binding via system-specific force-field adjustments, we have observed progressive distortions of the RNA-protein interface inconsistent with experimental data. We propose that the dynamics is so rich that its converged description is not achievable even upon stabilizing the system. Still, after careful analysis of the trajectories, we have made several suggestions regarding the binding. We identify substates in the RNA loops, which can explain the NMR data. The RGG tail localized in the minor groove remains disordered, sampling countless transient interactions with the RNA. There are long-range couplings among the different elements contributing to the recognition, which can lead to allosteric communication throughout the system. Overall, the RNA-FUS systems form dynamical ensembles that cannot be fully represented by single static structures. Thus, albeit imperfect, MD simulations represent a viable tool to investigate dynamic RNA-protein complexes.

The promise of cryo-EM to explore RNA structural dynamics

Conformational dynamics are essential to macromolecular function. This is certainly true of RNA, whose ability to undergo programmed conformational dynamics is essential to create and regulate complex biological processes. However, methods to easily and simultaneously interrogate both the structure and conformational dynamics of fully functional RNAs in isolation and in complex with proteins have not historically been available. Due to its ability to image and classify single particles, cryogenic electron microscopy (cryo-EM) has the potential to address this gap and may be particularly amenable to exploring structural dynamics within the three-dimensional folds of biologically active RNAs. We discuss the possibilities and current limitations of applying cryo-EM to simultaneously study RNA structure and conformational dynamics, and present one example that illustrates this (as of yet) not fully realized potential.

Measuring thermodynamic preferences to form non-native conformations in nucleic acids using ultraviolet melting

Thermodynamic preferences to form non-native conformations are crucial for understanding how nucleic acids fold and function. However, they are difficult to measure experimentally because this requires accurately determining the population of minor low-abundance (<10%) conformations in a sea of other conformations. Here, we show that melting experiments enable facile measurements of thermodynamic preferences to adopt nonnative conformations in DNA and RNA. The key to this "delta-melt" approach is to use chemical modifications to render specific minor non-native conformations the major state. The validity and robustness of delta-melt is established for four different non-native conformations under various physiological conditions and sequence contexts through independent measurements of thermodynamic preferences using NMR. Delta-melt is faster relative to NMR, simple, and cost-effective and enables thermodynamic preferences to be measured for exceptionally low-populated conformations. Using delta-melt, we obtained rare insights into conformational cooperativity, obtaining evidence for significant cooperativity (1.0 to 2.5 kcal/mol) when simultaneously forming two adjacent Hoogsteen base pairs. We also measured the thermodynamic preferences to form G-C⁺ and A-T Hoogsteen and A-T base open states for nearly all 16 trinucleotide sequence contexts and found distinct sequence-specific variations on the order of 2 to 3 kcal/mol. This rich landscape of sequence-specific non-native minor conformations in the DNA double helix may help shape the sequence specificity of DNA biochemistry. Thus, melting experiments can now be used to access thermodynamic information regarding regions of the free energy landscape of biomolecules beyond the native folded and unfolded conformations.

Exploring molecular biology in sequence space: The road to next-generation single-molecule biophysics

Next-generation sequencing techniques have led to a new quantitative dimension in the biological sciences. In particular, integrating sequencing techniques with biophysical tools allows sequence-dependent mechanistic studies. Using the millions of DNA clusters that are generated during sequencing to perform high-throughput binding affinity and kinetics measurements enabled the construction of energy landscapes in sequence space, uncovering relationships between sequence, structure, and function. Here, we review the approaches to perform ensemble fluorescence experiments on next-generation sequencing chips for variations of DNA, RNA, and protein sequences. As the next step, we anticipate that these fluorescence experiments will be pushed to the single-molecule level, which can directly uncover kinetics and molecular heterogeneity in an unprecedented high-throughput fashion. Molecular biophysics in sequence space, both at the ensemble and single-molecule level, leads to new mechanistic insights. The wide spectrum of applications in biology and medicine ranges from the fundamental understanding of evolutionary pathways to the development of new therapeutics.

Refining the RNA Force Field with Small-Angle X-ray Scattering of Helix-Junction-Helix RNA

The growing recognition of the functional and therapeutic roles played by RNA and the difficulties in gaining atomic-level insights by experiments are paving the way for all-atom simulations of RNA. One of the main impediments to the use of all-atom simulations is the imbalance between the energy terms of the RNA force fields. Through exhaustive sampling of an RNA helix-junction-helix (HJH) model using enhanced sampling, we critically assessed the select Amber force fields against small-angle X-ray scattering (SAXS) experiments. The tested AMBER99SB, DES-AMBER, and CUFIX force fields show deviations from measured profiles. First, we identified parameters leading to inconsistencies. Then, as a way to balance the forces governing RNA folding, we adopted strategies to refine hydrogen bonding, backbone, and base-stacking parameters. We validated the modified force field (HB-CUFIX) against SAXS data of the HJH model in different ionic strengths. Moreover, we tested a set of independent RNA systems to cross-validate the force field. Overall, HB-CUFIX demonstrates improved performance in studying thermodynamics and structural properties of realistic RNA motifs.

Cooperativity and Interdependency between RNA Structure and RNA-RNA Interactions

Complex RNA–RNA interactions are increasingly known to play key roles in numerous biological processes from gene expression control to ribonucleoprotein granule formation. By contrast, the nature of these interactions and characteristics of their interfaces, especially those that involve partially or wholly structured RNAs, remain elusive. Herein, we discuss different modalities of RNA–RNA interactions with an emphasis on those that depend on secondary, tertiary, or quaternary structure. We dissect recently structurally elucidated RNA–RNA complexes including RNA triplexes, riboswitches, ribozymes, and reverse transcription complexes. These analyses highlight a reciprocal relationship that intimately links RNA structure formation with RNA–RNA interactions. The interactions not only shape and sculpt RNA structures but also are enabled and modulated by the structures they create. Understanding this two-way relationship between RNA structure and interactions provides mechanistic insights into the expanding repertoire of noncoding RNA functions, and may inform the design of novel therapeutics that target RNA structures or interactions.

RNA aptamers for AMPA receptors

RNA aptamers are single-stranded RNA molecules, and they are selected against a target of interest so that they can bind to and modulate the activity of the target, such as inhibiting the target activity, with high potency and selectivity. Antagonists, such as RNA aptamers, acting on AMPA receptors, a major subtype of ionotropic glutamate receptors, are potential drug candidates for treatment of a number of CNS diseases that involve excessive receptor activation and/or elevated receptor expression. Here we review the approach to discover RNA aptamers targeting AMPA receptors from a random sequence library (∼10¹⁴ sequences) through a process called systematic evolution of ligands by exponential enrichment (SELEX). As compared with small-molecule compounds, RNA aptamers are a new class of regulatory agents with interesting and desirable pharmacological properties. Some AMPA receptor aptamers we have developed are presented in this review. The promises and challenges of translating RNA aptamers into potential drugs and treatment options are also discussed. This article is part of the special Issue on 'Glutamate Receptors - AMPA receptors'.

High-throughput dissection of the thermodynamic and conformational properties of a ubiquitous class of RNA tertiary contact motifs

Despite RNA's diverse secondary and tertiary structures and its complex conformational changes, nature utilizes a limited set of structural "motifs"-helices, junctions, and tertiary contact modules-to build diverse functional RNAs. Thus, in-depth descriptions of a relatively small universe of RNA motifs may lead to predictive models of RNA tertiary conformational landscapes. Motifs may have different properties depending on sequence and secondary structure, giving rise to subclasses that expand the universe of RNA building blocks. Yet we know very little about motif subclasses, given the challenges in mapping conformational properties in high throughput. Previously, we used "RNA on a massively parallel array" (RNA-MaP), a quantitative, high-throughput technique, to study thousands of helices and two-way junctions. Here, we adapt RNA-MaP to study the thermodynamic and conformational properties of tetraloop/tetraloop receptor (TL/TLR) tertiary contact motifs, analyzing 1,493 TLR sequences from different classes. Clustering analyses revealed variability in TL specificity, stability, and conformational behavior. Nevertheless, natural GAAA/11ntR TL/TLRs, while varying in tertiary stability by ∼2.5 kcal/mol, exhibited conserved TL specificity and conformational properties. Thus, RNAs may tune stability without altering the overall structure of these TL/TLRs. Furthermore, their stability correlated with natural frequency, suggesting thermodynamics as the dominant selection pressure. In contrast, other TL/TLRs displayed heterogenous conformational behavior and appear to not be under strong thermodynamic selection. Our results build toward a generalizable model of RNA-folding thermodynamics based on the properties of isolated motifs, and our characterized TL/TLR library can be used to engineer RNAs with predictable thermodynamic and conformational behavior.

A molecular view of DNA flexibility

DNA dynamics can only be understood by taking into account its complex mechanical behavior at different length scales. At the micrometer level, the mechanical properties of single DNA molecules have been well-characterized by polymer models and are commonly quantified by a persistence length of 50 nm (~150 bp). However, at the base pair level (~3.4 Å), the dynamics of DNA involves complex molecular mechanisms that are still being deciphered. Here, we review recent single-molecule experiments and molecular dynamics simulations that are providing novel insights into DNA mechanics from such a molecular perspective. We first discuss recent findings on sequence-dependent DNA mechanical properties, including sequences that resist mechanical stress and sequences that can accommodate strong deformations. We then comment on the intricate effects of cytosine methylation and DNA mismatches on DNA mechanics. Finally, we review recently reported differences in the mechanical properties of DNA and double-stranded RNA, the other double-helical carrier of genetic information. A thorough examination of the recent single-molecule literature permits establishing a set of general 'rules' that reasonably explain the mechanics of nucleic acids at the base pair level. These simple rules offer an improved description of certain biological systems and might serve as valuable guidelines for future design of DNA and RNA nanostructures.

Compaction of RNA Duplexes in the Cell*

The structure and flexibility of RNA depends sensitively on the microenvironment. Using pulsed electron-electron double-resonance (PELDOR)/double electron-electron resonance (DEER) spectroscopy combined with advanced labeling techniques, we show that the structure of double-stranded RNA (dsRNA) changes upon internalization into Xenopus laevis oocytes. Compared to dilute solution, the dsRNA A-helix is more compact in cells. We recapitulate this compaction in a densely crowded protein solution. Atomic-resolution molecular dynamics simulations of dsRNA semi-quantitatively capture the compaction, and identify non-specific electrostatic interactions between proteins and dsRNA as a possible driver of this effect.

Modeling Loop Composition and Ion Concentration Effects in RNA Hairpin Folding Stability

The ability to accurately predict RNA hairpin structure and stability for different loop sequences and salt conditions is important for understanding, modeling, and designing larger RNA folds. However, traditional RNA secondary structure models cannot treat loop-sequence and ionic effects on RNA hairpin folding. Here, we describe a general, three-dimensional (3D) conformation-based computational method for modeling salt concentration-dependent conformational distributions and the detailed 3D structures for a set of three RNA hairpins that contain a variable, 15-nucleotide loop sequence. For a given RNA sequence, the new, to our knowledge, method integrates a Vfold2D two-dimensional structure folding model with IsRNA coarse-grained molecular dynamics 3D folding simulations and Monte Carlo tightly bound ion estimations of ion-mediated electrostatic interactions. The model predicts free-energy landscapes for the different RNA hairpin-forming sequences with variable salt conditions. The theoretically predicted results agree with the experimental fluorescence measurements, validating the strategy. Furthermore, the theoretical model goes beyond the experimental results by enabling in-depth 3D structural analysis, revealing energetic mechanisms for the sequence- and salt-dependent folding stability. Although the computational framework presented here is developed for RNA hairpin systems, the general method may be applied to investigate other RNA systems, such as multiway junctions or pseudoknots in mixed metal ion solutions.

How We Think about Targeting RNA with Small Molecules

RNA offers nearly unlimited potential as a target for small molecule chemical probes and lead medicines. Many RNAs fold into structures that can be selectively targeted with small molecules. This Perspective discusses molecular recognition of RNA by small molecules and highlights key enabling technologies and properties of bioactive interactions. Sequence-based design of ligands targeting RNA has established rules for affecting RNA targets and provided a potentially general platform for the discovery of bioactive small molecules. The RNA targets that contain preferred small molecule binding sites can be identified from sequence, allowing identification of off-targets and prediction of bioactive interactions by nature of ligand recognition of functional sites. Small molecule targeted degradation of RNA targets (ribonuclease-targeted chimeras, RIBOTACs) and direct cleavage by small molecules have also been developed. These growing technologies suggest that the time is right to provide small molecule chemical probes to target functionally relevant RNAs throughout the human transcriptome.

Machine learning deciphers structural features of RNA duplexes measured with solution X-ray scattering

Macromolecular structures can be determined from solution X-ray scattering. Small-angle X-ray scattering (SAXS) provides global structural information on length scales of 10s to 100s of Ångstroms, and many algorithms are available to convert SAXS data into low-resolution structural envelopes. Extension of measurements to wider scattering angles (WAXS or wide-angle X-ray scattering) can sharpen the resolution to below 10 Å, filling in structural details that can be critical for biological function. These WAXS profiles are especially challenging to interpret because of the significant contribution of solvent in addition to solute on these smaller length scales. Based on training with molecular dynamics generated models, the application of extreme gradient boosting (XGBoost) is discussed, which is a supervised machine learning (ML) approach to interpret features in solution scattering profiles. These ML methods are applied to predict key structural parameters of double-stranded ribonucleic acid (dsRNA) duplexes. Duplex conformations vary with salt and sequence and directly impact the foldability of functional RNA molecules. The strong structural periodicities in these duplexes yield scattering profiles with rich sets of features at intermediate-to-wide scattering angles. In the ML models, these profiles are treated as 1D images or features. These ML models identify specific scattering angles, or regions of scattering angles, which correspond with and successfully predict distinct structural parameters. Thus, this work demonstrates that ML strategies can integrate theoretical molecular models with experimental solution scattering data, providing a new framework for extracting highly relevant structural information from solution experiments on biological macromolecules.

A unified dinucleotide alphabet describing both RNA and DNA structures

By analyzing almost 120 000 dinucleotides in over 2000 nonredundant nucleic acid crystal structures, we define 96+1 diNucleotide Conformers, NtCs, which describe the geometry of RNA and DNA dinucleotides. NtC classes are grouped into 15 codes of the structural alphabet CANA (Conformational Alphabet of Nucleic Acids) to simplify symbolic annotation of the prominent structural features of NAs and their intuitive graphical display. The search for nontrivial patterns of NtCs resulted in the identification of several types of RNA loops, some of them observed for the first time. Over 30% of the nearly six million dinucleotides in the PDB cannot be assigned to any NtC class but we demonstrate that up to a half of them can be re-refined with the help of proper refinement targets. A statistical analysis of the preferences of NtCs and CANA codes for the 16 dinucleotide sequences showed that neither the NtC class AA00, which forms the scaffold of RNA structures, nor BB00, the DNA most populated class, are sequence neutral but their distributions are significantly biased. The reported automated assignment of the NtC classes and CANA codes available at dnatco.org provides a powerful tool for unbiased analysis of nucleic acid structures by structural and molecular biologists.

Quantifying Protein-Protein Interactions in Molecular Simulations

Interactions among proteins, nucleic acids, and other macromolecules are essential for their biological functions and shape the physicochemcial properties of the crowded environments inside living cells. Binding interactions are commonly quantified by dissociation constants K_d, and both binding and nonbinding interactions are quantified by second osmotic virial coefficients B₂. As a measure of nonspecific binding and stickiness, B₂ is receiving renewed attention in the context of so-called liquid–liquid phase separation in protein and nucleic acid solutions. We show that K_d is fully determined by B₂ and the fraction of the dimer observed in molecular simulations of two proteins in a box. We derive two methods to calculate B₂. From molecular dynamics or Monte Carlo simulations using implicit solvents, we can determine B₂ from insertion and removal energies by applying Bennett’s acceptance ratio (BAR) method or the (binless) weighted histogram analysis method (WHAM). From simulations using implicit or explicit solvents, one can estimate B₂ from the probability that the two molecules are within a volume large enough to cover their range of interactions. We validate these methods for coarse-grained Monte Carlo simulations of three weakly binding proteins. Our estimates for K_d and B₂ allow us to separate out the contributions of nonbinding interactions to B₂. Comparison of calculated and measured values of K_d and B₂ can be used to (re-)parameterize and improve molecular force fields by calibrating specific affinities, overall stickiness, and nonbinding interactions. The accuracy and efficiency of K_d and B₂ calculations make them well suited for high-throughput studies of large interactomes.

Structure-mechanics statistical learning unravels the linkage between local rigidity and global flexibility in nucleic acids

The mechanical properties of nucleic acids underlie biological processes ranging from genome packaging to gene expression, but tracing their molecular origin has been difficult due to the structural and chemical complexity. We posit that concepts from machine learning can help to tackle this long-standing challenge. Here, we demonstrate the feasibility and advantage of this strategy through developing a structure-mechanics statistical learning scheme to elucidate how local rigidity in double-stranded (ds)DNA and dsRNA may lead to their global flexibility in bend, stretch, and twist. Specifically, the mechanical parameters in a heavy-atom elastic network model are computed from the trajectory data of all-atom molecular dynamics simulation. The results show that the inter-atomic springs for backbone and ribose puckering in dsRNA are stronger than those in dsDNA, but are similar in strengths for base-stacking and base-pairing. Our analysis shows that the experimental observation of dsDNA being easier to bend but harder to stretch than dsRNA comes mostly from the respective B- and A-form topologies. The computationally resolved composition of local rigidity indicates that the flexibility of both nucleic acids is mostly due to base-stacking. But for properties like twist-stretch coupling, backbone springs are shown to play a major role instead. The quantitative connection between local rigidity and global flexibility sets foundation for understanding how local binding and chemical modification of genetic materials effectuate longer-ranged regulatory signals.

The mechanical properties of nucleic acids underlie biological processes ranging from genome packaging to gene expression. We devise structural mechanics statistical learning method to reveal their molecular origin in terms of chemical interactions.

Sequence-dependent mechanical properties of double-stranded RNA

The mechanical properties of double-stranded RNA (dsRNA) are involved in many of its biological functions and are relevant for future nanotechnology applications. DsRNA must tightly bend to fit inside viral capsids or deform upon the interaction with proteins that regulate gene silencing or the immune response against viral attacks. However, the question of how the nucleotide sequence affects the global mechanical properties of dsRNA has so far remained largely unexplored. Here, we have employed state-of-the-art atomistic molecular dynamics simulations to unveil the mechanical response of different RNA duplexes to an external force. Our results reveal that, similarly to dsDNA, the mechanical properties of dsRNA are highly sequence-dependent. However, we find that the nucleotide sequence affects in a strikingly different manner the stretching and twisting response of RNA and DNA duplexes under force. We find that the elastic response of dsRNA is dominated by the local high flexibility of pyrimidine-purine steps. Moreover, the flexibility of pyrimidine-purine steps is independent of the sequence context, and the global flexibility of the duplex reasonably scales with the number of this kind of base-pair dinucleotides. We conclude that disparities of the mechanical response of dinucleotides are responsible for the differences observed in the mechanical properties of RNA and DNA duplexes.

Salt Dependence of A-Form RNA Duplexes: Structures and Implications

The biological functions of RNA range from gene regulation through catalysis and depend critically on its structure and flexibility. Conformational variations of flexible, non-base-paired components, including RNA hinges, bulges, or single-stranded tails, are well documented. Recent work has also identified variations in the structure of ubiquitous, base-paired duplexes found in almost all functional RNAs. Duplexes anchor the structures of folded RNAs, and their surface features are recognized by partner molecules. To date, no consistent picture has been obtained that describes the range of conformations assumed by RNA duplexes. Here, we apply wide angle, solution X-ray scattering (WAXS) to quantify these variations, by sampling length scales characteristic of helical geometries under different solution conditions. To identify the radius, helical rise, twist, and length of dsRNA helices, we exploit molecular dynamics generated structures, explicit solvent models, and ensemble optimization methods. Our results quantify the substantial and salt-dependent deviations of double-stranded (ds) RNA duplexes from the assumed canonical A-form conformation. Recent experiments underscore the need to properly describe the structures of RNA duplexes when interpreting the salt dependence of RNA conformations.