RNA Tertiary Structure Research Articles

RNA tertiary structure and conformational dynamics revealed by BASH MaP.

The functional effects of an RNA can arise from complex three-dimensional folds known as tertiary structures. However, predicting the tertiary structure of an RNA and whether an RNA adopts distinct tertiary conformations remains challenging. To address this, we developed BASH MaP, a single-molecule dimethyl sulfate (DMS) footprinting method and DAGGER, a computational pipeline, to identify alternative tertiary structures adopted by different molecules of RNA. BASH MaP utilizes potassium borohydride to reveal the chemical accessibility of the N7 position of guanosine, a key mediator of tertiary structures. We used BASH MaP to identify diverse conformational states and dynamics of RNA G-quadruplexes, an important RNA tertiary motif, in vitro and in cells. BASH MaP and DAGGER analysis of the fluorogenic aptamer Spinach reveals that it adopts alternative tertiary conformations which determine its fluorescence states. BASH MaP thus provides an approach for structural analysis of RNA by revealing previously undetectable tertiary structures.

RNA tertiary structure and conformational dynamics revealed by BASH MaP.

The functional effects of an RNA can arise from complex three-dimensional folds known as tertiary structures. However, predicting the tertiary structure of an RNA and whether an RNA adopts distinct tertiary conformations remains challenging. To address this, we developed BASH MaP, a single-molecule dimethyl sulfate (DMS) footprinting method and DAGGER, a computational pipeline, to identify alternative tertiary structures adopted by different molecules of RNA. BASH MaP utilizes potassium borohydride to reveal the chemical accessibility of the N7 position of guanosine, a key mediator of tertiary structures. We used BASH MaP to identify diverse conformational states and dynamics of RNA G-quadruplexes, an important RNA tertiary motif, in vitro and in cells. BASH MaP and DAGGER analysis of the fluorogenic aptamer Spinach reveals that it adopts alternative tertiary conformations which determine its fluorescence states. BASH MaP thus provides an approach for structural analysis of RNA by revealing previously undetectable tertiary structures.

The dual role of a highly structured RNA (the S fragment) in the replication of foot-and-mouth disease virus.

Secondary and tertiary RNA structures play key roles in genome replication of single-stranded positive sense RNA viruses. Complex, functional structures are particularly abundant in the untranslated regions of picornaviruses, where they are involved in initiation of translation, priming of new strand synthesis and genome circularization. The 5' UTR of foot-and-mouth disease virus (FMDV) is predicted to include a c. 360 nucleotide-long stem-loop, termed the short (S) fragment. This structure is highly conserved and essential for viral replication, but the precise function(s) are unclear. Here, we used selective 2' hydroxyl acetylation analyzed by primer extension (SHAPE) to experimentally determine aspects of the structure, alongside comparative genomic analyses to confirm structure conservation from a wide range of field isolates. To examine its role in virus replication in cell culture, we introduced a series of deletions to the distal and proximal regions of the stem-loop. These truncations affected genome replication in a size-dependent and, in some cases, host cell-dependent manner. Furthermore, during the passage of viruses incorporating the largest tolerated deletion from the proximal region of the S fragment stem-loop, an additional mutation was selected in the viral RNA-dependent RNA polymerase, 3Dpol. These data suggest that the S fragment and 3Dpol interact in the formation of the FMDV replication complex.

CNRBind: Small Molecule-RNA Binding Sites Recognition via Site Significant from Nucleotide and Complex Network Information

Background: Small molecule-RNA binding sites play a significant role in developing drugs for disease treatment. However, it is a challenge to propose accurate computational tools for identifying these binding sites. Method: In this study, an accurate prediction model named CNRBind was constructed by extracting site significant information from nucleotide and complex networks. We designed complex networks and calculated three topological structural parameters according to RNA tertiary structure. Acknowledging nucleotide interdependence, a sliding window was selected to integrate the influence of adjacent sites. Finally, the model was constructed using a random forest classifier. Results: Compared to the other computational tools, CNRBind was competitive and had excellent discriminative ability for metal ion-binding site prediction. Furthermore, statistic analysis revealed significant differences between CNRBind and existing methods. Additionally, CNRBind is a promising predictor in cases where experimental tertiary structure is unavailable. Conclusion: These results show that CNRBind is effective because of the proposed site significant information encoding strategy. The approach provides a reasonable supplement for biology researches. The dataset and resource codes can be accessed at: https://github.com/Kangxiaoneuq/CNRBind.

Ribonanza: deep learning of RNA structure through dual crowdsourcing.

Prediction of RNA structure from sequence remains an unsolved problem, and progress has been slowed by a paucity of experimental data. Here, we present Ribonanza, a dataset of chemical mapping measurements on two million diverse RNA sequences collected through Eterna and other crowdsourced initiatives. Ribonanza measurements enabled solicitation, training, and prospective evaluation of diverse deep neural networks through a Kaggle challenge, followed by distillation into a single, self-contained model called RibonanzaNet. When fine tuned on auxiliary datasets, RibonanzaNet achieves state-of-the-art performance in modeling experimental sequence dropout, RNA hydrolytic degradation, and RNA secondary structure, with implications for modeling RNA tertiary structure.

RNA secondary structure prediction using transformer-based deep learning models

The Human Genome Project has led to an exponential increase in data related to the sequence, structure, and function of biomolecules. Bioinformatics is an interdisciplinary research field that primarily uses computational methods to analyze large amounts of biological macromolecule data. Its goal is to discover hidden biological patterns and related information. Furthermore, analysing additional relevant information can enhance the study of biological operating mechanisms. This paper discusses the fundamental concepts of RNA, RNA secondary structure, and its prediction.Subsequently, the application of machine learning technologies in predicting the structure of biological macromolecules is explored. This chapter describes the relevant knowledge of algorithms and computational complexity and presents a RNA tertiary structure prediction algorithm based on ResNet. To address the issue of the current scoring function's unsuitability for long RNA, a scoring model based on ResNet is proposed, and a structure prediction algorithm is designed. The chapter concludes by presenting some open and interesting challenges in the field of RNA tertiary structure prediction.

RNAscape: geometric mapping and customizable visualization of RNA structure.

Analyzing and visualizing the tertiary structure and complex interactions of RNA is essential for being able to mechanistically decipher their molecular functions in vivo. Secondary structure visualization software can portray many aspects of RNA; however, these layouts are often unable to preserve topological correspondence since they do not consider tertiary interactions between different regions of an RNA molecule. Likewise, quaternary interactions between two or more interacting RNA molecules are not considered in secondary structure visualization tools. The RNAscape webserver produces visualizations that can preserve topological correspondence while remaining both visually intuitive and structurally insightful. RNAscape achieves this by designing a mathematical structural mapping algorithm which prioritizes the helical segments, reflecting their tertiary organization. Non-helical segments are mapped in a way that minimizes structural clutter. RNAscape runs a plotting script that is designed to generate publication-quality images. RNAscape natively supports non-standard nucleotides, multiple base-pairing annotation stylesand requires no programming experience. RNAscape can also be used to analyze RNA/DNA hybrid structures and DNA topologies, including G-quadruplexes. Users can upload their own three-dimensional structures or enter a Protein Data Bank (PDB) ID of an existing structure. The RNAscape webserver allows users to customize visualizations through various settings as desired. URL: https://rnascape.usc.edu/.

High-resolution RNA tertiary structures in Zika virus stem-loop A for the development of inhibitory small molecules.

Flaviviruses such as Zika (ZIKV) and dengue virus (DENV) are positive-sense RNA viruses belonging to Flaviviridae The flavivirus genome contains a 5' end stem-loop promoter sequence known as stem-loop A (SLA) that is recognized by the flavivirus polymerase NS5 during viral RNA synthesis and 5' guanosine cap methylation. The crystal structures of ZIKV and DENV SLAs show a well-defined fold, consisting of a bottom stem, side loop, and top stem-loop, providing unique interaction sites for small molecule inhibitors to disrupt the promoter function. To facilitate the identification of small molecule binding sites in flavivirus SLA, we determined high-resolution structures of the bottom and top stems of ZIKV SLA, which contain a single U- or G-bulge, respectively. Both bulge nucleotides exhibit multiple orientations, from folded back on the adjacent nucleotide to flipped out of the helix, and are stabilized by stacking or base triple interactions. These structures suggest that even a single unpaired nucleotide can provide flexibility to RNA structures, and its conformation is mainly determined by the stabilizing chemical environment. To facilitate discovery of small molecule inhibitors that interfere with the functions of ZIKV SLA, we screened and identified compounds that bind to the bottom and top stems of ZIKV SLA.

Monitoring Real-Time Temperature Dynamics of a Short RNA Hairpin Using Förster Resonance Energy Transfer and Circular Dichroism.

RNA molecules play crucial roles in gene expression regulation and cellular signaling, and these functions are governed by the formation of RNA secondary and tertiary structures. These structures are highly dynamic and subject to rapid changes in response to environmental cues, temperature in particular. Thermosensitive RNA secondary structures have been harnessed by multiple organisms to survey their temperature environment and to adjust gene expression accordingly. It is thus highly desirable to observe RNA structural changes in real time over a range of temperatures. Multiple approaches have been developed to study structural dynamics, but many of these require extensive processing of the RNA, large amounts of RNA input, and/or cannot be applied under physiological conditions. Here, we describe the use of a dually fluorescently labeled RNA oligonucleotide (containing a predicted hairpin structure) to monitor subtle RNA structural dynamics in vitro by Förster resonance energy transfer (FRET) and circular dichroism (CD) spectroscopy. These approaches can be employed under physiologically relevant conditions over a range of temperatures and with RNA concentrations as low as 200nM; they enable us to observe RNA structural dynamics in real time and to correlate these dynamics with changes in biological processes such as translation.

Efficient Prediction Model of mRNA End-to-End Distance and Conformation: Three-Dimensional RNA Illustration Program (TRIP).

The secondary and tertiary structures of RNA play a vital role in the regulation of biological reactions. These structures have been experimentally studied through in vivo and in vitro analyses, and in silico models have become increasingly accurate in predicting them. Recent technologies have diversified RNA structure predictions, from the earliest thermodynamic and molecular dynamic-based RNA structure predictions to deep learning-based conformation predictions in the past decade. While most research on RNA structure prediction has focused on short non-coding RNAs, there has been limited research on predicting the conformation of longer mRNAs. Our study introduces a computer simulation model called the Three-dimensional RNA Illustration Program (TRIP). TRIP is based on single-chain models and angle restriction of each bead component from previously reported single-molecule fluorescence in situ hybridization (smFISH) experiments. TRIP is a fast and efficient application that only requires up to three inputs to acquire outputs. It can also provide a rough visualization of the 3D conformation of RNA, making it a valuable tool for predicting RNA end-to-end distance.

Simultaneous Localization of Two High Affinity Divalent Metal Ion Binding Sites in the Tetracycline RNA Aptamer with Mn2+-Based Pulsed Dipolar EPR Spectroscopy.

Mg2+ ions play an essential part in stabilizing the tertiary structure of nucleic acids. While the importance of these ions is well documented, their localization and elucidation of their role in the structure and dynamics of nucleic acids are often challenging. In this work, pulsed electron-electron double resonance spectroscopy (PELDOR, also known as DEER) was used to localize two high affinity divalent metal ion binding sites in the tetracycline RNA aptamer with high accuracy. For this purpose, the aptamer was labeled at different positions with a semirigid nitroxide spin label and diamagnetic Mg2+ was replaced with paramagnetic Mn2+, which did not alter the folding process or ligand binding. Out of the several divalent metal ion binding sites that are known from the crystal structure, two binding sites with high affinity were detected: one that is located at the ligand binding center and another at the J1/2 junction of the RNA.

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.

Integrating end-to-end learning with deep geometrical potentials for ab initio RNA structure prediction

RNAs are fundamental in living cells and perform critical functions determined by their tertiary architectures. However, accurate modeling of 3D RNA structure remains a challenging problem. We present a novel method, DRfold, to predict RNA tertiary structures by simultaneous learning of local frame rotations and geometric restraints from experimentally solved RNA structures, where the learned knowledge is converted into a hybrid energy potential to guide RNA structure assembly. The method significantly outperforms previous approaches by >73.3% in TM-score on a sequence-nonredundant dataset containing recently released structures. Detailed analyses showed that the major contribution to the improvements arise from the deep end-to-end learning supervised with the atom coordinates and the composite energy function integrating complementary information from geometry restraints and end-to-end learning models. The open-source DRfold program with fast training protocol allows large-scale application of high-resolution RNA structure modeling and can be further improved with future expansion of RNA structure databases.

RNA tertiary structure modeling with BRiQ potential in CASP15.

We describe the modeling method for RNA tertiary structures employed by team AIchemy_RNA2 in the 15th Critical Assessment of Structure Prediction (CASP15). The method consists of the following steps. Firstly, secondary structure information was derived from various manually-verified sources. With this information, the full length RNA was fragmented into structural modules. The structures of each module were predicted and then assembled into the full structure. To reduce the searching conformational space, an RNA structure was organized into an optimal base folding tree. And to further improve the sampling efficiency, the energy surface was smoothed at high temperatures during the Monte Carlo sampling to make it easier to move across the energy barrier. The statistical potential energy function BRiQ was employed during Monte Carlo energy optimization.

Magnesium Ion-Driven Folding and Conformational Switching Kinetics of Tetracycline Binding Aptamer: Implications for in vivo Riboswitch Engineering

Engineering in vitro selected RNA aptamers into in vivo functional riboswitches represents a long-standing challenge in molecular biology. The highly specific aptamer domain of the riboswitch undergoes a conformational adjustment in response to ligand sensing, which in turn exerts the regulatory function. Besides essential factors like structural complexity and ligand binding kinetics, the active role of magnesium ions in stabilizing RNA tertiary structures and assisting in ligand binding can be a vital criterion. We present spectroscopic studies on the magnesium ion-driven folding of the Tetracycline binding aptamer. Using fluorescent labels, the aptamer pre-folding and subsequent ligand binding is monitored by magnesium titration experiments and time-resolved stopped-flow measurements. A minimum concentration of 0.5 mM magnesium is required to fold into a magnesium ion-stabilized binding-competent state with a preformed binding pocket. Tetracycline binding causes a pronounced conformational change that results in the establishment of the triple helix core motif, and that further propagates towards the closing stem. By a dynamic acquisition of magnesium ions, a kink motif is formed at the intersection of the triple helix and closing stem regions. This ultimately entails a stabilization of the closing stem which is discussed as a key element in the regulatory function of the Tetracycline aptamer.

Photoswitchable molecular glue for RNA: reversible photocontrol of structure and function of the ribozyme.

Single-stranded RNA folds into a variety of secondary and higher-order structures. Distributions and dynamics of multiple RNA conformations are responsible for the biological function of RNA. We here developed a photoswitchable molecular glue for RNA, which could reversibly control the association of two unpaired RNA regions in response to light stimuli. The photoswitchable molecular glue, NCTA, is an RNA-binding ligand possessing a photoisomerizable azobenzene moiety. Z-NCTA is an active ligand for the target RNA containing 5'-WGG-3'/5'-WGG-3' (W=U or A) site and stabilizes its hybridized state, while its isomer E-NCTA is not. Photoreversible isomerization of NCTA enabled control of the secondary and tertiary structure of the target RNA. The RNA-cleaving activity of hammerhead ribozyme, where appropriate RNA folding is necessary, could be reversibly regulated by photoirradiation in cells treated with NCTA, demonstrating precise photocontrol of RNA structure and function by the photoswitchable molecular glue.

RNA tertiary structure prediction using RNAComposer in CASP15.

As CASP15 participants, in the new category of 3D RNA structure prediction, we applied expert modeling with the support of our proprietary system RNAComposer. Although RNAComposer is primarily known as an automated web server, its features allow it to be used interactively, for example, for homology-based modeling or assembling models from user-provided structural elements. In the paper, we present various scenarios of applying the system to predict the 3D RNA structures that we employed. Their combination with expert input, comparative analysis of models, and routines to select representative resultant structures form a ready-for-reuse workflow. With selected examples, we demonstrate its application for the in silico modeling of natural and synthetic RNA molecules targeted in CASP15.

An Encodable Scaffold for Sequence-Specific Recognition of Duplex RNA.

RNA, unlike DNA, folds into a multitude of secondary and tertiary structures. This structural diversity has impeded the development of ligands that can sequence-specifically target this biomolecule. We sought to develop ligands for double-stranded RNA (dsRNA) segments, which are ubiquitous in RNA tertiary structure. The major groove of double-stranded DNA is sequence-specifically recognized by a range of dimeric helical transcription factors, including the basic leucine zippers (bZIP) and basic helix-loop-helix (bHLH) proteins; however, such simple structural motifs are not prevalent in RNA-binding proteins. We interrogated the high-resolution structures of DNA and RNA to identify requirements for a helix fork motif to occupy dsRNA major grooves akin to dsDNA. Our analysis suggested that the rigidity and angle of approach of dimeric helices in bZIP/bHLH motifs are not ideal for the binding of dsRNA major grooves. This investigation revealed that the replacement of the leucine zipper motifs in bHLH proteins with synthetic crosslinkers would allow recognition of dsRNA. We show that a model bHLH DNA-binding motif does not bind dsRNA but can be reengineered as an RNA ligand. Based on this hypothesis, we rationally designed a miniature synthetic crosslinked helix fork (CHF) as a generalizable proteomimetic scaffold for targeting dsRNA. We evaluated several CHF constructs against a set of RNA and DNA hairpins to probe the specificity of the designed construct. Our studies reveal a new class of proteomimetics as an encodable platform for sequence-specific recognition of dsRNA.

An Encodable Scaffold for Sequence‐Specific Recognition of Duplex RNA

AbstractRNA, unlike DNA, folds into a multitude of secondary and tertiary structures. This structural diversity has impeded the development of ligands that can sequence‐specifically target this biomolecule. We sought to develop ligands for double‐stranded RNA (dsRNA) segments, which are ubiquitous in RNA tertiary structure. The major groove of double‐stranded DNA is sequence‐specifically recognized by a range of dimeric helical transcription factors, including the basic leucine zippers (bZIP) and basic helix‐loop‐helix (bHLH) proteins; however, such simple structural motifs are not prevalent in RNA‐binding proteins. We interrogated the high‐resolution structures of DNA and RNA to identify requirements for a helix fork motif to occupy dsRNA major grooves akin to dsDNA. Our analysis suggested that the rigidity and angle of approach of dimeric helices in bZIP/bHLH motifs are not ideal for the binding of dsRNA major grooves. This investigation revealed that the replacement of the leucine zipper motifs in bHLH proteins with synthetic crosslinkers would allow recognition of dsRNA. We show that a model bHLH DNA‐binding motif does not bind dsRNA but can be reengineered as an RNA ligand. Based on this hypothesis, we rationally designed a miniature synthetic crosslinked helix fork (CHF) as a generalizable proteomimetic scaffold for targeting dsRNA. We evaluated several CHF constructs against a set of RNA and DNA hairpins to probe the specificity of the designed construct. Our studies reveal a new class of proteomimetics as an encodable platform for sequence‐specific recognition of dsRNA.

Arena: Rapid and Accurate Reconstruction of Full Atomic RNA Structures From Coarse-grained Models

RNA tertiary structures from experiments or computational predictions often contain missing atoms, which prevent analyses requiring full atomic structures. Current programs for RNA reconstruction can be slow, inaccurate, and/or require specific atoms to be present in the input. We present Arena (Atomic Reconstruction of RNA), which reconstructs a full atomic RNA structure from residues that can have as few as one atom. Arena first fills in missing atoms and then iteratively refines their placement to reduce nonideal geometries. We benchmarked Arena on a dataset of 361 RNA structures, where Arena achieves high accuracy and speed compared to other structure reconstruction programs. For example, Arena was used to reconstruct full atomic structures from a single phosphorus atom per nucleotide to, on average, within 3.63 Å RMSD of the experimental structure, while virtually removing all clashes and running in <3 s, which is 353× and 46× faster than state-of-the-art programs PDBFixer and C2A, respectively. The Arena source code is available at https://github.com/pylelab/Arena and the webserver at https://zhanggroup.org/Arena/.