Quantitative Understanding of SHAPE Mechanism from RNA Structure and Dynamics Analysis

Integrating experimental data with molecular simulations to investigate RNA structural dynamics

Conformational dynamics is crucial for ribonucleic acid (RNA) function. Techniques such as nuclear magnetic resonance, cryo-electron microscopy, small- and wide-angle X-ray scattering, chemical probing, single-molecule Förster resonance energy transfer, or even thermal or mechanical denaturation experiments probe RNA dynamics at different time and space resolutions. Their combination with accurate atomistic molecular dynamics (MD) simulations paves the way for quantitative and detailed studies of RNA dynamics. First, experiments provide a quantitative validation tool for MD simulations. Second, available data can be used to refine simulated structural ensembles to match experiments. Finally, comparison with experiments allows for improving MD force fields that are transferable to new systems for which data is not available. Here we review the recent literature and provide our perspective on this field.

Biomotors, viral assembly, and RNA nanobiotechnology: Current achievements and future directions

The International Society of RNA Nanotechnology and Nanomedicine (ISRNN) serves to further the development of a wide variety of functional nucleic acids and other related nanotechnology platforms. To aid in the dissemination of the most recent advancements, a biennial discussion focused on biomotors, viral assembly, and RNA nanobiotechnology has been established where international experts in interdisciplinary fields such as structural biology, biophysical chemistry, nanotechnology, cell and cancer biology, and pharmacology share their latest accomplishments and future perspectives. The results summarized here highlight advancements in our understanding of viral biology and the structure-function relationship of frame-shifting elements in genomic viral RNA, improvements in the predictions of SHAPE analysis of 3D RNA structures, and the understanding of dynamic RNA structures through a variety of experimental and computational means. Additionally, recent advances in the drug delivery, vaccine design, nanopore technologies, biomotor and biomachine development, DNA packaging, RNA nanotechnology, and drug delivery are included in this critical review. We emphasize some of the novel accomplishments, major discussion topics, and present current challenges and perspectives of these emerging fields.

An overview of structural approaches to study therapeutic RNAs

RNAs provide considerable opportunities as therapeutic agent to expand the plethora of classical therapeutic targets, from extracellular and surface proteins to intracellular nucleic acids and its regulators, in a wide range of diseases. RNA versatility can be exploited to recognize cell types, perform cell therapy, and develop new vaccine classes. Therapeutic RNAs (aptamers, antisense nucleotides, siRNA, miRNA, mRNA and CRISPR-Cas9) can modulate or induce protein expression, inhibit molecular interactions, achieve genome editing as well as exon-skipping. A common RNA thread, which makes it very promising for therapeutic applications, is its structure, flexibility, and binding specificity. Moreover, RNA displays peculiar structural plasticity compared to proteins as well as to DNA. Here we summarize the recent advances and applications of therapeutic RNAs, and the experimental and computational methods to analyze their structure, by biophysical techniques (liquid-state NMR, scattering, reactivity, and computational simulations), with a focus on dynamic and flexibility aspects and to binding analysis. This will provide insights on the currently available RNA therapeutic applications and on the best techniques to evaluate its dynamics and reactivity.

Riboswitch-mediated regulation of riboflavin biosynthesis genes in prokaryotes

Prokaryotic organisms frequently use riboswitches to quantify intracellular metabolite concentration via high-affinity metabolite receptors. Riboswitches possess a metabolite-sensing system that controls gene regulation in a cis-acting fashion at the initiation of transcriptional/translational level by binding with a specific metabolite and controlling various biochemical pathways. Riboswitch binds with flavin mononucleotide (FMN), a phosphorylated form of riboflavin and controls gene expression involved in riboflavin biosynthesis and transport pathway. The first step of the riboflavin biosynthesis pathway is initiated by the conversion of guanine nucleotide triphosphate (GTP), which is an intermediate of the purine biosynthesis pathway. An alternative pentose phosphate pathway of riboflavin biosynthesis includes the enzymatic conversion of ribulose-5-phosphate into 3, 4 dihydroxy-2-butanone-4-phosphates by DHBP synthase. The product of ribAB interferes with both GTP cyclohydrolase II as well as DHBP synthase activities, which catalyze the cleavage of GTP and converts DHBP Ribu5P in the initial steps of both riboflavin biosynthesis branches. Riboswitches are located in the 5' untranslated region (5' UTR) of messenger RNAs and contain an aptamer domain (highly conserved in sequence) where metabolite binding leads to a conformational change in an aptamer domain, which modulate the regulation of gene expression located on bacterial mRNA. In this review, we focus on how riboswitch regulates the riboflavin biosynthesis pathway in Bacillus subtilis and Lactobacillus plantarum.

Insights into the secondary and tertiary structure of the Bovine Viral Diarrhea Virus Internal Ribosome Entry Site

The internal ribosome entry site (IRES) RNA of bovine viral diarrhoea virus (BVDV), an economically significant Pestivirus, is required for the cap-independent translation of viral genomic RNA. Thus, it is essential for viral replication and pathogenesis. We applied a combination of high-throughput biochemical RNA structure probing (SHAPE-MaP) and in silico modelling approaches to gain insight into the secondary and tertiary structures of BVDV IRES RNA. Our study demonstrated that BVDV IRES RNA in solution forms a modular architecture composed of three distinct structural domains (I-III). Two regions within domain III are represented in tertiary interactions to form an H-type pseudoknot. Computational modelling of the pseudoknot motif provided a fine-grained picture of the tertiary structure and local arrangement of helices in the BVDV IRES. Furthermore, comparative genomics and consensus structure predictions revealed that the pseudoknot is evolutionarily conserved among many Pestivirus species. These studies provide detailed insight into the structural arrangement of BVDV IRES RNA H-type pseudoknot and encompassing motifs that likely contribute to the optimal functionality of viral cap-independent translation element.

The International Society of RNA Nanotechnology and Nanomedicine (ISRNN): The Present and Future of the Burgeoning Field

The International Society of RNA Nanotechnology and Nanomedicine (ISRNN) hosts an annual meeting series focused on presenting the latest research achievements involving RNA-based therapeutics and strategies, aiming to expand their current biomedical applications while overcoming the remaining challenges of the burgeoning field of RNA nanotechnology. The most recent online meeting hosted a series of engaging talks and discussions from an international cohort of leading nanotechnologists that focused on RNA modifications and modulation, dynamic RNA structures, overcoming delivery limitations using a variety of innovative platforms and approaches, and addressing the newly explored potential for immunomodulation with programmable nucleic acid nanoparticles. In this Nano Focus, we summarize the main discussion points, conclusions, and future directions identified during this two-day webinar as well as more recent advances to highlight and to accelerate this exciting field.

SHAPER: A Web Server for Fast and Accurate SHAPE Reactivity Prediction

Selective 2′-hydroxyl acylation analyzed by primer extension (SHAPE) chemical probing serves as a convenient and efficient experiment technique for providing information about RNA local flexibility. The local structural information contained in SHAPE reactivity data can be used as constraints in 2D/3D structure predictions. Here, we present SHAPE predictoR (SHAPER), a web server for fast and accurate SHAPE reactivity prediction. The main purpose of the SHAPER web server is to provide a portal that uses experimental SHAPE data to refine 2D/3D RNA structure selection. Input structures for the SHAPER server can be obtained through experimental or computational modeling. The SHAPER server can accept RNA structures with single or multiple conformations, and the predicted SHAPE profile and correlation with experimental SHAPE data (if provided) for each conformation can be freely downloaded through the web portal. The SHAPER web server is available at http://rna.physics.missouri.edu/shaper/.

IsRNA1: De Novo Prediction and Blind Screening of RNA 3D Structures

Modeling structures and functions of large ribonucleic acid (RNAs) especially with complicated topologies is highly challenging due to the inefficiency of large conformational sampling and the presence of complicated tertiary interactions. To address this problem, one highly promising approach is coarse-grained modeling. Here, following an iterative simulated reference state approach to decipher the correlations between different structural parameters, we developed a potent coarse-grained RNA model named as IsRNA1 for RNA studies. Molecular dynamics simulations in the IsRNA1 can predict the native structures of small RNAs from a sequence and fold medium-sized RNAs into near-native tertiary structures with the assistance of secondary structure constraints. A large-scale benchmark test on RNA 3D structure prediction shows that IsRNA1 exhibits improved performance for relatively large RNAs of complicated topologies, such as large stem-loop structures and structures containing long-range tertiary interactions. The advantages of IsRNA1 include the consideration of the correlations between the different structural variables, the appropriate characterization of canonical base-pairing and base-stacking interactions, and the better sampling for the backbone conformations. Moreover, a blind screening protocol was developed based on IsRNA1 to identify good structural models from a pool of candidates without prior knowledge of the native structures.

Sieving RNA 3D Structures with SHAPE and Evaluating Mechanisms Driving Sequence-Dependent Reactivity Bias

Selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) chemical probing provides local RNA flexibility information at single-nucleotide resolution. In general, SHAPE is thought of as a secondary structure (2D) technology, but we find evidence that robust tertiary structure (3D) information is contained in SHAPE data. Here, we report a new model that achieves a higher correlation between SHAPE data and native RNA 3D structures than the previous 3D structure-SHAPE relationship model. Furthermore, we demonstrate that the new model improves our ability to discern between SHAPE-compatible and -incompatible structures on model decoys. After identifying sequence-dependent bias in SHAPE experiments, we propose a mechanism driving sequence-dependent bias in SHAPE experiments, using replica-exchange umbrella sampling simulations to confirm that the SHAPE sequence bias is largely explained by the stability of the unreacted SHAPE reagent in the binding pocket. Taken together, this work represents multiple practical advances in our mechanistic and predictive understanding of SHAPE technology.

A Bayes-inspired theory for optimally building an efficient coarse-grained folding force field

Because of their potential utility in predicting conformational changes and assessing folding dynamics, coarse-grained (CG) RNA folding models are appealing for rapid characterization of RNA molecules. Previously, we reported the iterative simulated RNA reference state (IsRNA) method for parameterizing a CG force field for RNA folding, which consecutively updates the simulation force field to reflect marginal distributions of folding coordinates in the structure database and extract various energy terms. While the IsRNA model was validated by showing close agreement between the IsRNA-simulated and experimentally observed distributions, here, we expand our theoretical understanding of the model and, in doing so, improve the parameterization process to optimize the subset of included folding coordinates, which leads to accelerated simulations. Using statistical mechanical theory, we analyze the underlying, Bayesian concept that drives parameterization of the energy function, providing a general method for developing predictive, knowledge-based, polymer force fields on the basis of limited data. Furthermore, we propose an optimal parameterization procedure, based on the principal of maximum entropy.

Advances in the Bioinformatics Knowledge of mRNA Polyadenylation in Baculovirus Genes

Baculoviruses are a group of insect viruses with large circular dsDNA genomes exploited in numerous biotechnological applications, such as the biological control of agricultural pests, the expression of recombinant proteins or the gene delivery of therapeutic sequences in mammals, among others. Their genomes encode between 80 and 200 proteins, of which 38 are shared by all reported species. Thanks to multi-omic studies, there is remarkable information about the baculoviral proteome and the temporality in the virus gene expression. This allows some functional elements of the genome to be very well described, such as promoters and open reading frames. However, less information is available about the transcription termination signals and, consequently, there are still imprecisions about what are the limits of the transcriptional units present in the baculovirus genomes and how is the processing of the 3′ end of viral mRNA. Regarding to this, in this review we provide an update about the characteristics of DNA signals involved in this process and we contribute to their correct prediction through an exhaustive analysis that involves bibliography information, data mining, RNA structure and a comprehensive study of the core gene 3′ ends from 180 baculovirus genomes.

Quantitative comparison between sub-millisecond time resolution single-molecule FRET measurements and 10-second molecular simulations of a biosensor protein

Molecular Dynamics (MD) simulations seek to provide atomic-level insights into conformationally dynamic biological systems at experimentally relevant time resolutions, such as those afforded by single-molecule fluorescence measurements. However, limitations in the time scales of MD simulations and the time resolution of single-molecule measurements have challenged efforts to obtain overlapping temporal regimes required for close quantitative comparisons. Achieving such overlap has the potential to provide novel theories, hypotheses, and interpretations that can inform idealized experimental designs that maximize the detection of the desired reaction coordinate. Here, we report MD simulations at time scales overlapping with in vitro single-molecule Förster (fluorescence) resonance energy transfer (smFRET) measurements of the amino acid binding protein LIV-BP^SS at sub-millisecond resolution. Computationally efficient all-atom structure-based simulations, calibrated against explicit solvent simulations, were employed for sampling multiple cycles of LIV-BP^SS clamshell-like conformational changes on the time scale of seconds, examining the relationship between these events and those observed by smFRET. The MD simulations agree with the smFRET measurements and provide valuable information on local dynamics of fluorophores at their sites of attachment on LIV-BP^SS and the correlations between fluorophore motions and large-scale conformational changes between LIV-BP^SS domains. We further utilize the MD simulations to inform the interpretation of smFRET data, including Förster radius (R₀) and fluorophore orientation factor (κ²) determinations. The approach we describe can be readily extended to distinct biochemical systems, allowing for the interpretation of any FRET system conjugated to protein or ribonucleoprotein complexes, including those with more conformational processes, as well as those implementing multi-color smFRET.

Förster (fluorescence) resonance energy transfer (FRET) has been used extensively by biophysicists as a molecular-scale ruler that yields fundamental structural and kinetic insights into transient processes including complex formation and conformational rearrangements required for biological function. FRET techniques require the identification of informative fluorophore labeling sites, spaced at defined distances to inform on a reaction coordinate of interest and consideration of noise sources that have the potential to obscure quantitative interpretations. Here, we describe an approach to leverage advancements in computationally efficient all-atom structure-based molecular dynamics simulations in which structural dynamics observed via FRET can be interpreted in full atomistic detail on commensurate time scales. We demonstrate the potential of this approach using a model FRET system, the amino acid binding protein LIV-BP^SS conjugated to self-healing organic fluorophores. LIV-BP^SS exhibits large scale, sub-millisecond clamshell-like conformational changes between open and closed conformations associated with ligand unbinding and binding, respectively. Our findings inform on the molecular basis of the dynamics observed by smFRET and on strategies to optimize fluorophore labeling sites, the manner of fluorophore attachment, and fluorophore composition.

IPANEMAP: integrative probing analysis of nucleic acids empowered by multiple accessibility profiles

The manual production of reliable RNA structure models from chemical probing experiments benefits from the integration of information derived from multiple protocols and reagents. However, the interpretation of multiple probing profiles remains a complex task, hindering the quality and reproducibility of modeling efforts. We introduce IPANEMAP, the first automated method for the modeling of RNA structure from multiple probing reactivity profiles. Input profiles can result from experiments based on diverse protocols, reagents, or collection of variants, and are jointly analyzed to predict the dominant conformations of an RNA. IPANEMAP combines sampling, clustering and multi-optimization, to produce secondary structure models that are both stable and well-supported by experimental evidences. The analysis of multiple reactivity profiles, both publicly available and produced in our study, demonstrates the good performances of IPANEMAP, even in a mono probing setting. It confirms the potential of integrating multiple sources of probing data, informing the design of informative probing assays.

Structural Flexibility of DNA-RNA Hybrid Duplex: Stretching and Twist-Stretch Coupling

DNA-RNA hybrid (DRH) duplexes play essential roles during the replication of DNA and the reverse transcription of RNA viruses, and their flexibility is important for their biological functions. Recent experiments indicated that A-form RNA and B-form DNA have a strikingly different flexibility in stretching and twist-stretch coupling, and the structural flexibility of DRH duplex is of great interest, especially in stretching and twist-stretch coupling. In this work, we performed microsecond all-atom molecular dynamics simulations with new AMBER force fields to characterize the structural flexibility of DRH duplex in stretching and twist-stretch coupling. We have calculated all the helical parameters, stretch modulus, and twist-stretch coupling parameters for the DRH duplex. First, our analyses on structure suggest that the DRH duplex exhibits an intermediate conformation between A- and B-forms and closer to A-form, which can be attributed to the stronger rigidity of the RNA strand than the DNA strand. Second, our calculations show that the DRH duplex has the stretch modulus of 834 ± 34 pN and a very weak twist-stretch coupling. Our quantitative analyses indicate that, compared with DNA and RNA duplexes, the different flexibility of the DRH duplex in stretching and twist-stretch coupling is mainly attributed to its apparently different basepair inclination in the helical structure.

The interplay between molecular flexibility and RNA chemical probing reactivities analyzed at the nucleotide level via an extensive molecular dynamics study

Determination of the tridimensional structure of ribonucleic acid molecules is fundamental for understanding their function in the cell. A common method to investigate RNA structures of large molecules is the use of chemical probes such as SHAPE (2^'-hydroxyl acylation analyzed by primer extension) reagents, DMS (dimethyl sulfate) and CMCT (1-cyclohexyl-3-(2-morpholinoethyl) carbodiimide metho-p-toluene sulfate), the reaction of which is dependent on the local structural properties of each nucleotide. In order to understand the interplay between local flexibility, sugar pucker, canonical pairing and chemical reactivity of the probes, we performed all-atom molecular dynamics simulations on a set of RNA molecules for which both tridimensional structure and chemical probing data are available and we analyzed the correlations between geometrical parameters and the chemical reactivity. Our study confirms that SHAPE reactivity is guided by the local flexibility of the different chemical moieties but suggests that a combination of multiple parameters is needed to better understand the implications of the reactivity at the molecular level. This is also the case for DMS and CMCT for which the reactivity appears to be more complex than commonly accepted.

Extracting information from RNA SHAPE data: Kalman filtering approach

RNA SHAPE experiments have become important and successful sources of information for RNA structure prediction. In such experiments, chemical reagents are used to probe RNA backbone flexibility at the nucleotide level, which in turn provides information on base pairing and therefore secondary structure. Little is known, however, about the statistics of such SHAPE data. In this work, we explore different representations of noise in SHAPE data and propose a statistically sound framework for extracting reliable reactivity information from multiple SHAPE replicates. Our analyses of RNA SHAPE experiments underscore that a normal noise model is not adequate to represent their data. We propose instead a log-normal representation of noise and discuss its relevance. Under this assumption, we observe that processing simulated SHAPE data by directly averaging different replicates leads to bias. Such bias can be reduced by analyzing the data following a log transformation, either by log-averaging or Kalman filtering. Application of Kalman filtering has the additional advantage that a prior on the nucleotide reactivities can be introduced. We show that the performance of Kalman filtering is then directly dependent on the quality of that prior. We conclude the paper with guidelines on signal processing of RNA SHAPE data.