Probing the dynamic RNA structurome and its functions

Advancements in chemically inducible modified tRNA sequencing techniques: Elucidating novel insights into tRNA epitranscriptomics

In this review, we examine and expound upon the most recent and groundbreaking advancements in the sequencing of tRNA modifications, focusing specifically on the innovative chemical treatment approaches that have revolutionized this field. By delving into the intricate details of these cutting-edge methodologies, we aim to provide an overview of the current state of the art in tRNA modification sequencing, highlighting their unique strengths, limitations, and potential applications.

Small-molecule RNA ligands: a patent review (2018-2024)

INTRODUCTION

Targeting three-dimensional RNA structures with traditional drug-like small molecules is gaining wide attention in both the academia and the pharmaceutical industries, due to their good oral bioavailability, cheap production cost, and the possibility of fine-tuning ADMET properties, which represent a powerful alternative to the current RNA-targeted therapies, including ASO and siRNA. As RNAs are involved in nearly all the physiological and pathological processes, small molecules RNA ligands can have a plethora of different therapeutic applications, spanning from cancer to infectious and neurological diseases.

AREAS COVERED

This review describes patents concerning small molecules RNA ligands published within January 2018 and October 2024, searched through Espacenet, Patentscope, and Google Patents databases.

EXPERT OPINION

The number of patents that has been released in the last few years demonstrates the relevance of targeting RNA structures for the development of next generation chemotherapeutic agents and antiviral/antibacterial drugs, even though this field is still in its infancy and many issues still need to be resolved, in particular related to selectivity. An emerging approach to considerably limiting side effects is presented by RIBOTAC derivatives, as promoting a selective RNase-L mediated RNA degradation allows to significantly reduce the dose of the compound.

The Druggable Transcriptome Project: From Chemical Probes to Precision Medicines

RNA presents abundant opportunities as a drug target, offering significant potential for small molecule medicine development. The transcriptome, comprising both coding and noncoding RNAs, is a rich area for therapeutic innovation, yet challenges persist in targeting RNA with small molecules. RNA structure can be predicted with or without experimental data, but discrepancies with the actual biological structure can impede progress. Prioritizing RNA targets supported by genetic or evolutionary evidence enhances success. Further, small molecules must demonstrate binding to RNA in cells, not solely in vitro, to validate both the target and compound. Effective small molecule binders modulate functional sites that influence RNA biology, as binding to nonfunctional sites requires recruiting effector mechanisms, for example degradation, to achieve therapeutic outcomes. Addressing these challenges is critical to unlocking RNA's vast potential for small molecule medicines, and a strategic framework is proposed to navigate this promising field, with a focus on targeting human RNAs.

Rapid discovery of functional RNA domains

Many strategies have been implemented to enrich an RNA population for a selectable function, but demarcation of the optimal functional motifs or minimal structures within longer libraries remains a lengthy and tedious process. To overcome this problem, we have developed a technique that isolates minimal active segments from complex heterogeneous pools of RNAs. This method allows for truncations to occur at both 5' and 3' ends of functional domains and introduces independent primer-binding sequences, thereby removing sequence and structure bias introduced by constant-sequence regions. We show examples of minimization for genomic and synthetic aptamers and demonstrate that the method can directly reveal an active RNA assembled from multiple strands, facilitating the development of heterodimeric structures used in cellular sensors. This approach provides a pipeline to experimentally define the boundaries of active domains and accelerate the discovery of functional RNAs.

Relaxation Optimized Heteronuclear Experiments for Extending the Size Limit of RNA Nuclear Magnetic Resonance

The application of NMR to large RNAs has been limited by the inability to perform heteronuclear correlation experiments essential for resolving overlapping 1H NMR signals, determining interproton distance restraints and interhelical orientations for structure calculations, and evaluating conformational dynamics. Approaches exploiting 1H-13C correlations that are routinely applied to proteins and small RNAs of ∼60 nucleotides or fewer are impractical for larger RNAs due to rapid dipolar relaxation of protons by their attached carbons. Here we report a 2H-enhanced, 1H-15N correlation approach that enables atom-specific NMR characterization of much larger RNAs. Purine H8 transverse relaxation rates are reduced ∼20-fold with ribose perdeuteration, enabling efficient magnetization transfer via two-bond 1H-15N couplings. We focus on H8-N9 correlation spectra which benefit from favorable N9 chemical shift anisotropy. Chemical shift assignment is enabled by retention of protons at the C1' position, which allow measurement of two-bond H1'-N9 and through-space H1'-H8 correlations with only a minor effect on H8 relaxation. The approach is demonstrated for the 232 nucleotide HIV-1 Rev response element, where chemical shift assignments, 15N-edited nuclear Overhauser effects, and 1H-15N residual dipolar couplings are readily obtained from sensitive, high-resolution spectra. Heteronuclear correlated NMR methods that have been essential for the study of proteins can now be extended to RNAs of at least 78 kDa.

rCGMM: A Coarse-Grained Force Field Embedding Elastic Network for Studying Small Noncoding RNA Dynamics

Short noncoding RNA molecules play significant roles in catalysis, biological regulation, and disease pathways. Their assessment through sequence-based approaches has been a challenge, compounded by the significant structural flexibility accrued from six free backbone torsions per nucleotide. To efficiently study the structure and dynamics of an extensive repertoire of these molecules in a high throughput mode, we have built a coarse-grained force field using one, two, three, and four pseudoatoms to represent the phosphate, sugar, pyrimidines, and purines, respectively. The Boltzmann inversion method was applied to structures of 5 piRNA, 8 miRNA, and 13 siRNA from the Nucleic Acid Database (NDB) to estimate the initial force field parameters and iteratively optimized through 1 μs molecular dynamics run by comparing against an equivalent all-atom simulation using the CHARMM36 force field. We applied an elastic net to model the hydrogen bond network stabilizing the local structure for double-stranded cases. A spine using pseudoatoms was calculated for the same from the coarse-grain beads, and all beads within a threshold radial distance were constrained using soft distance potentials. Lennard-Jones and Coulomb's potential function modeled the nonbonded interaction. Benchmarks on 26 molecules compared through root-mean-square deviation graphs against all-atom simulation show close concurrence for single- and double-stranded small noncoding RNA molecules. The rCGMM force field is available for download at https://github.com/majumderS/rCGMM.

Rapid folding of nascent RNA regulates eukaryotic RNA biogenesis

RNA's catalytic, regulatory, or coding potential depends on structure formation. Because base pairing occurs during transcription, early structural states can govern RNA processing events and dictate the formation of functional conformations. These co-transcriptional states remain mostly unknown. Here, we develop co-transcriptional structure tracking (CoSTseq), which detects nascent RNA base pairing within and upon exit from RNA polymerases (Pols) transcriptome wide in living yeast cells. Monitoring each nucleotide's base pairing activity during transcription, CoSTseq reveals predominantly rapid pairing-within 25 bp of transcription after addition to the nascent chain. Moreover, ∼23% of rRNA nucleotides attain their final base pairing state near Pol I, while most other nucleotides must undergo changes in pairing status during later steps of ribosome biogenesis. We show that helicases act immediately to remodel structures across the rDNA locus to facilitate ribosome biogenesis. By contrast, nascent pre-mRNAs attain local structures indistinguishable from mature mRNAs, suggesting that refolding behind elongating ribosomes resembles co-transcriptional folding behind Pol II.

Real-Time Monitoring of Higher-Order Structure of RNAs by Temperature-Course Size Exclusion Chromatography and Microfluidic Modulation Spectroscopy

Recently, there has been emerging interest in the characterization of the higher order structure (HOS) of oligonucleotide therapeutics because of its potential impact on the function. However, many existing experimental and computational methods face challenges with respect to throughput, cost, and resolution for large ribonucleic acids (RNAs). In this study, we present the use of two orthogonal analytical methods, size-exclusion chromatography (SEC) and microfluidic modulation spectroscopy (MMS), which are used to investigate conformational changes of two 100 mer single guide RNAs (sgRNAs) with complex HOS and aggregation specie profiles. SEC, coupled with multiangle light scattering (MALS), mass spectrometry (MS), and isothermal MMS revealed various forms of aggregation and potential interactions. We also developed temperature-course SEC and thermal ramping MMS methods to monitor real-time HOS changes from room temperature to the RNA melting point. Through the experiments, we observed two discrete steps of thermally induced dissociation of RNA aggregates, namely higher order aggregates (HOA) dissociation and dimer dissociation. Temperature-course SEC allows for thermodynamic analysis of the enthalpy and entropy of the reaction. We also identified two spectral regions in infrared (IR) spectra with thermal ramping MMS, 1665 cm-1 and between 1700 and 1720 cm-1, which closely correlated to the Watson-Crick base pairing and the related HOS change in RNA. The combination of SEC and MMS offers a comprehensive biophysical characterization toolkit for RNA HOS under native conditions, providing valuable insights for candidate optimization and formulation screening in the development of RNA therapeutics.

A Small-Molecule Approach Enables RNA Aptamers to Function as Sensors for Reactive Inorganic Targets

Fluorescent light-up aptamer (FLAP) systems are promising (bio)sensing platforms that are genetically encodable. However, FLAP-mediated detection of each distinct target necessitates either in vitro selection or engineering of nucleic acid sequences. Furthermore, an aptamer that binds an inorganic target or a chemical species with a short lifetime is challenging to realize. Here, we describe a small-molecule approach that makes it possible for a single FLAP system to detect chemically unique, non-fluorogenic, and reactive inorganics. We developed functionalized pre-ligands of RNA aptamers that bind benzylidene imidazolinones (Baby Spinach, Broccolli, Squash). Reactive inorganics, hydrogen sulfide (H2S/HS-) and hydrogen peroxide (H2O2), can specifically convert these pre-ligands into native ligands that fluoresce with FLAPs. Adaptation of this platform to live cells opened an opportunity for constructing whole-cell sensors: Escherichia coli transformed with a Baby Spinach-encoding plasmid and incubated with pre-ligands generated fluorescence in response to exogenous H2S/HS- or H2O2. Leveraging the functional group reactivity of small molecules eliminates the requirement of in vitro selection of a new aptamer sequence or oligonucleotide scaffold engineering for distinct molecular targets. Our method allows for detecting inorganic, short-lived species, thereby advancing FLAP systems beyond their current capabilities.

Cryo-EM reveals mechanisms of natural RNA multivalency

Homo-oligomerization of biological macromolecules leads to functional assemblies that are critical to understanding various cellular processes. However, RNA quaternary structures have been rarely reported. Comparative genomics analysis has identified RNA families containing hundreds of sequences that adopt conserved secondary structures and likely fold into complex three-dimensional (3D) structures. We use cryo-electron microscopy (cryo-EM) to determine structures from four RNA families, including ARRPOF and OLE forming dimers, and ROOL and GOLLD forming hexameric, octameric and dodecameric nanostructures, at 2.6 to 4.6 Å resolutions. These homo-oligomeric assemblies reveal a plethora of structural motifs that contribute to RNA multivalency, including kissing loop, palindromic base-pairing, A-stacking, metal ion coordination, pseudoknot and minor-groove interactions. These results provide the molecular basis of intermolecular interactions driving RNA multivalency with potential functional relevance.

Chemotranscriptomic profiling with a thiamine monophosphate photoaffinity probe

RNA is a multifaceted biomolecule with numerous biological functions and can interact with small molecule metabolites as exemplified by riboswitches. Here, we profile the Escherichia coli transcriptome on interactions with the metabolite Thiamine Monophosphate (TMP). We designed and synthesized a photoaffinity probe based on the scaffold of TMP and applied it to chemotranscriptomic profiling. Using next-generation RNA sequencing, several potential interactions between bacterial transcripts and the probe were identified. A remarkable interaction between the TMP probe and the well-characterized Flavin Mononucleotide (FMN) riboswitch was validated by RT-qPCR, and further verified with competition assays. Localization of the photocrosslinked nucleotides using reverse transcription and docking predictions of the probe suggested binding to the riboswitch aptamer. After examining binding of unmodified TMP to the riboswitch using SHAPE, we found selective yet moderate binding interactions, potentially mediated by the phosphate group of TMP. Lastly, TMP appeared to enhance gene expression of a reporter gene that is under riboswitch control, while the natural ligand FMN displayed an inhibitory effect, hinting at a potential biological role of TMP. This work showcases the possibility of chemotranscriptomic profiling to identify new RNA-small molecule interactions.

DNA Damaging Agents Induce RNA Structural and Transcriptional Changes for Genes Associated with Redox Homeostasis in Arabidopsis thaliana

Living organisms are constantly exposed to various DNA damaging agents. While the mechanisms of DNA damage and DNA repair are well understood, the impact of these agents on RNA secondary structure and subsequent function remains elusive. In this study, we explore the effects of DNA damaging reagent methyl methanesulfonate (MMS) on arabidopsis gene expression and RNA secondary structure using the dimethyl sulfate (DMS) mutational profiling with sequencing (DMS-MaPseq) method. Our analyses reveal that changes in transcriptional levels and mRNA structure are key factors in response to DNA damaging agents. MMS treatment leads to the up-regulation of arabidopsis RBOHs (respiratory burst oxidase homologues) and alteration in the RNA secondary structure of GSTF9 and GSTF10, thereby enhancing mRNA translation efficiency. Redox homeostasis manipulated by RBOHs and GSTFs plays a crucial role in MMS-induced primary root growth inhibition. In conclusion, our findings shed light on the effects of DNA damaging agents on RNA structure and potential mRNA translation, which provide a new insight to understand the mechanism of DNA damage.

Prebiotic RNA self-assembling and the origin of life: Mechanistic and molecular modeling rationale for explaining the prebiotic origin and replication of RNA

In recent years, a great interest has been focused on the prebiotic origin of nucleic acids and life on Earth. An attractive idea is that life was initially based on an autocatalytic and autoreplicative RNA (the RNA-world). RNA duplexes are right-handed helical chains with antiparallel orientation, but the rationale for these features is not yet known. An antiparallel (inverted) stacking of purine nucleosides was reported in crystallographic studies. Molecular modeling also supports the inverted orientation of nucleosides. This preferential stacking can also appear when nucleosides are included in a montmorillonite clay matrix. Free-energy values and geometrical parameters show that D-ribose chirality is preferred for the formation of right-handed RNA molecules. Thus, a "zipper" model with antiparallel and auto-intercalated nucleosides linked by phosphate groups can be proposed to form single RNA chains. Unstacking with strand separation and base pairing by H-bonding, results in shortening and inclination of ribose-phosphate chains, leading to right-handed helicity and antiparallel duplexes. Incorporation of complementary precursors on the major groove template by a self-assembly mechanism provides a prebiotic (non-enzymatic) "tetris" replication model by formation of a transient RNA tetrad and tetraplex. Original hairpin motifs appear as simple building units that form typical RNA structures such as hammerheads, cloverleaves and dumbbells. They occur today in the circular viroids and virusoids, as well as in highly branched and complex rRNA molecules.

From computational models of the splicing code to regulatory mechanisms and therapeutic implications

Since the discovery of RNA splicing and its role in gene expression, researchers have sought a set of rules, an algorithm or a computational model that could predict the splice isoforms, and their frequencies, produced from any transcribed gene in a specific cellular context. Over the past 30 years, these models have evolved from simple position weight matrices to deep-learning models capable of integrating sequence data across vast genomic distances. Most recently, new model architectures are moving the field closer to context-specific alternative splicing predictions, and advances in sequencing technologies are expanding the type of data that can be used to inform and interpret such models. Together, these developments are driving improved understanding of splicing regulatory mechanisms and emerging applications of the splicing code to the rational design of RNA- and splicing-based therapeutics.

A new level of RNA-based plant protection: dsRNAs designed from functionally characterized siRNAs highly effective against Cucumber mosaic virus

RNA-mediated crop protection increasingly becomes a viable alternative to agrochemicals that threaten biodiversity and human health. Pathogen-derived double-stranded RNAs (dsRNAs) are processed into small interfering RNAs (siRNAs), which can then induce silencing of target RNAs, e.g. viral genomes. However, with currently used dsRNAs, which largely consist of undefined regions of the target RNAs, silencing is often ineffective: processing in the plant generates siRNA pools that contain only a few functionally effective siRNAs (esiRNAs). Using an in vitro screen that reliably identifies esiRNAs from siRNA pools, we identified esiRNAs against Cucumber mosaic virus (CMV), a devastating plant pathogen. Topical application of esiRNAs to plants resulted in highly effective protection against massive CMV infection. However, optimal protection was achieved with newly designed multivalent 'effective dsRNAs' (edsRNAs), which contain the sequences of several esiRNAs and are preferentially processed into these esiRNAs. The esiRNA components can attack one or more target RNAs at different sites, be active in different silencing complexes, and provide cross-protection against different viral variants-important properties for combating rapidly mutating pathogens such as CMV. esiRNAs and edsRNAs have thus been established as a new class of 'RNA actives' that significantly increase the efficacy and specificity of RNA-mediated plant protection.

Characterizing 3D RNA structural features from DMS reactivity

Dimethyl sulfate (DMS) chemical mapping probes RNA structure, where low reactivity is generally interpreted as Watson-Crick (WC) base pairs and high reactivity as unpaired nucleotides. Studies examining DMS reactivity of RNAs with known 3D structures have identified nucleotides that deviate from this interpretation with distinct solvent accessibility and hydrogen bonding patterns. Understanding the frequency of these outliers and their recurring structural 3D features remains incomplete. To address this knowledge gap, we systematically analyzed DMS reactivity patterns across a library of 7,500 RNA constructs containing two-way junctions with known 3D structures. We observe DMS reactivity exists on a continuum over four orders of magnitude with approximately 10% overlap in reactivity between WC and non-WC nucleotides. We find that non-WC bases with WC-like DMS protection exhibit increased hydrogen bonding and decreased solvent accessibility, whereas WC pairs exhibiting greater DMS reactivity tend to flank junctions, correlating with weaker base stacking and greater junction dynamics. Furthermore, we discover that DMS reactivity values in non-canonical pairs correlate with atomic distances and base pair geometry, enabling discrimination between different 3D conformations. These DMS reactivity patterns indicate that DMS reactivity provides atomic-scale information about RNA 3D conformations, which can be used to model RNA structures and dynamics.

Dockground: The resource expands to protein-RNA interactome

RNA is a master regulator of cellular processes and will bind to many different proteins throughout its life cycle. Dysregulation of RNA and RNA-binding proteins can lead to various diseases, including cancer. To better understand molecular mechanisms of the cellular processes, it is important to characterize protein-RNA interactions at the structural level. There is a lack of experimental structures available for protein-RNA complexes due to the RNA inherent flexibility, which complicates the experimental structure determination. The scarcity of structures can be made up for with computational modeling. Dockground is a resource for development and benchmarking of structure-based modeling of protein interactions. It contains datasets focusing on different aspects of protein recognition. The foundation of all the datasets is the database of experimentally determined protein complexes, which previously contained only protein-protein assemblies. To further expand the utility of the Dockground resource, we extended the database to protein-RNA interactions. The new functionalities are available on the Dockground website at https://dockground.compbio.ku.edu/. The database can be searched using a number of criteria, including removal of redundancies at various sequence and structure similarity thresholds. The database updates with new structures from the Protein Data Bank on a weekly basis.

Design and Evaluation of Azaspirocycles as RNA binders

This study presents efficient synthetic pathways for preparing novel azaspirocycles. These methodologies involve functionalizing key bicyclic hydrazines with a substituent on one of their bridgehead carbon atoms. The desired spirocyclic cores were successfully obtained through double reductive amination reactions, intramolecular cyclizations, and cleavages of the N-N bond. The isolated molecules possess unique three-dimensional structures, suggesting potential applications in medicinal chemistry and drug discovery. With the growing interest in targeting nucleic acids as a complementary approach to protein-targeting strategies for developing novel active compounds, we investigated the potential of the synthesized azaspirocycles as RNA binders. As a proof of concept, we highlight the promising activity of some compounds as strong binders of HIV-1 TAR RNA and inhibitors of Tat/TAR interactions.

Sequencing technologies to measure translation in single cells

Translation is one of the most energy-intensive processes in a cell and, accordingly, is tightly regulated. Genome-wide methods to measure translation and the translatome and to study the complex regulation of protein synthesis have enabled unprecedented characterization of this crucial step of gene expression. However, technological limitations have hampered our understanding of translation control in multicellular tissues, rare cell types and dynamic cellular processes. Recent optimizations, adaptations and new techniques have enabled these measurements to be made at single-cell resolution. In this Progress, we discuss single-cell sequencing technologies to measure translation, including ribosome profiling, ribosome affinity purification and spatial translatome methods.

MolluscDB 2.0: a comprehensive functional and evolutionary genomics database for over 1400 molluscan species

Mollusca represents the second-largest animal phylum but remains less explored genomically. The increase in high-quality genomes and diverse functional genomic data holds great promise for advancing our understanding of molluscan biology and evolution. To address the opportunities and challenges facing the molluscan research community in managing vast multi-omics resources, we developed MolluscDB 2.0 (http://mgbase.qnlm.ac), which integrates extensive functional genomic data and offers user-friendly tools for multilevel integrative and comparative analyses. MolluscDB 2.0 covers 1450 species across all eight molluscan classes and compiles ∼4200 datasets, making it the most comprehensive multi-omics resource for molluscs to date. MolluscDB 2.0 expands the layers of multi-omics data, including genomes, bulk transcriptomes, single-cell transcriptomes, proteomes, epigenomes and metagenomes. MolluscDB 2.0 also more than doubles the number of functional modules and analytical tools, updating 14 original modules and introducing 20 new, specialized modules. Overall, MolluscDB 2.0 provides highly valuable, open-access multi-omics platform for the molluscan research community, expediting scientific discoveries and deepening our understanding of molluscan biology and evolution.

RASP v2.0: an updated atlas for RNA structure probing data

RNA molecules function in numerous biological processes by folding into intricate structures. Here we present RASP v2.0, an updated database for RNA structure probing data featuring a substantially expanded collection of datasets along with enhanced online structural analysis functionalities. Compared to the previous version, RASP v2.0 includes the following improvements: (i) the number of RNA structure datasets has increased from 156 to 438, comprising 216 transcriptome-wide RNA structure datasets, 141 target-specific RNA structure datasets, and 81 RNA-RNA interaction datasets, thereby broadening species coverage from 18 to 24, (ii) a deep learning-based model has been implemented to impute missing structural signals for 59 transcriptome-wide RNA structure datasets with low structure score coverage, significantly enhancing data quality, particularly for low-abundance RNAs, (iii) three new online analysis modules have been deployed to assist RNA structure studies, including missing structure score imputation, RNA secondary and tertiary structure prediction, and RNA binding protein (RBP) binding prediction. By providing a resource of much more comprehensive RNA structure data, RASP v2.0 is poised to facilitate the exploration of RNA structure-function relationships across diverse biological processes. RASP v2.0 is freely accessible at http://rasp2.zhanglab.net/.

Spontaneous base flipping helps drive Nsp15's preferences in double stranded RNA substrates

Coronaviruses evade detection by the host immune system with the help of the endoribonuclease Nsp15, which regulates levels of viral double stranded RNA by cleaving 3' of uridine (U). While prior structural data shows that to cleave double stranded RNA, Nsp15's target U must be flipped out of the helix, it is not yet understood whether Nsp15 initiates flipping or captures spontaneously flipped bases. We address this gap by designing fluorinated double stranded RNA substrates that allow us to directly relate a U's sequence context to both its tendency to spontaneously flip and its susceptibility to cleavage by Nsp15. Through a combination of nuclease assays, 19F NMR spectroscopy, mass spectrometry, and single particle cryo-EM, we determine that Nsp15 acts most efficiently on unpaired Us, particularly those that are already flipped. Across sequence contexts, we find Nsp15's cleavage efficiency to be directly related to that U's tendency to spontaneously flip. Overall, our findings unify previous characterizations of Nsp15's cleavage preferences, and suggest that activity of Nsp15 during infection is partially driven by bulged or otherwise relatively accessible Us that appear at strategic positions in the viral RNA.

Structure-Based Prediction of lncRNA-Protein Interactions by Deep Learning

The interactions between long noncoding RNA (lncRNA) and protein play crucial roles in various biological processes. Computational methods are essential for predicting lncRNA-protein interactions and deciphering their mechanisms. In this chapter, we aim to introduce the fundamental framework for predicting lncRNA-protein interactions based on three-dimensional structure information. With the increasing availability of lncRNA and protein molecular tertiary structures, the feasibility of using deep learning methods for automatic representation and learning has become evident. This chapter outlines the key steps in predicting lncRNA-protein interactions using deep learning, including three common non-Euclidean data representations for lncRNA and proteins, as well as neural networks tailored to these specific data characteristics. We also highlight the advantages and challenges of structure-based prediction of lncRNA-protein interactions with geometric deep learning methods.

mRNA vaccine sequence and structure design and optimization: Advances and challenges

Messenger RNA (mRNA) vaccines have emerged as a powerful tool against communicable diseases and cancers, as demonstrated by their huge success during the coronavirus disease 2019 (COVID-19) pandemic. Despite the outstanding achievements, mRNA vaccines still face challenges such as stringent storage requirements, insufficient antigen expression, and unexpected immune responses. Since the intrinsic properties of mRNA molecules significantly impact vaccine performance, optimizing mRNA design is crucial in preclinical development. In this review, we outline four key principles for optimal mRNA sequence design: enhancing ribosome loading and translation efficiency through untranslated region (UTR) optimization, improving translation efficiency via codon optimization, increasing structural stability by refining global RNA sequence and extending in-cell lifetime and expression fidelity by adjusting local RNA structures. We also explore recent advancements in computational models for designing and optimizing mRNA vaccine sequences following these principles. By integrating current mRNA knowledge, addressing challenges, and examining advanced computational methods, this review aims to promote the application of computational approaches in mRNA vaccine development and inspire novel solutions to existing obstacles.

A guide to RNA structure analysis and RNA-targeting methods

RNAs are increasingly recognized as promising therapeutic targets, susceptible to modulation by strategies that include targeting with small molecules, antisense oligonucleotides, deoxyribozymes (DNAzymes), or CRISPR/Cas13. However, while drug development for proteins follows well-established paths for rational design based on the accurate knowledge of their three-dimensional structure, RNA-targeting strategies are challenging since comprehensive RNA structures are yet scarce and challenging to acquire. Numerous methods have been developed to elucidate the secondary and three-dimensional structure of RNAs, including X-ray crystallography, cryo-electron microscopy, nuclear magnetic resonance, SHAPE, DMS, and bioinformatic methods, yet they have often revealed flexible transcripts and co-existing populations rather than single-defined structures. Thus, researchers aiming to target RNAs face a critical decision: whether to acquire the detailed structure of transcripts in advance or to adopt phenotypic screens or sequence-based approaches that are independent of the structure. Still, even in strategies that seem to rely only on the nucleotide sequence (like the design of antisense oligonucleotides), researchers may need information about the accessibility of the compounds to the folded RNA molecule. In this concise guide, we provide an overview for researchers interested in targeting RNAs: We start by revisiting current methodologies for defining secondary or three-dimensional RNA structure and then we explore RNA-targeting strategies that may or may not require an in-depth knowledge of RNA structure. We envision that complementary approaches may expedite the development of RNA-targeting molecules to combat disease.

Bioorthogonal Cyclopropenones for Investigating RNA Structure

RNA sequences encode structures that impact protein production and other cellular processes. Misfolded RNAs can also potentiate disease, but a complete picture is lacking. To establish more comprehensive and accurate RNA structure-function relationships, new methods are needed to interrogate RNA in native environments. Existing tools rely primarily on electrophiles that are constitutively "on" or triggered by UV light, often resulting in high background. Here we describe an alternative, chemically triggered approach to cross-link RNAs using bioorthogonal cyclopropenones (CpOs). These reagents selectively react with phosphines to provide ketenes─electrophiles that can trap neighboring nucleophiles to forge covalent cross-links. As a proof-of-concept, we conjugated a CpO motif to thiazole orange (TO-1). TO-1-CpO bound selectively to a model RNA aptamer (Mango) with nanomolar affinity, as confirmed by fluorescence turn-on. After phosphine administration, covalent cross-links were formed between the CpO and RNA. Cross-linking was both time and dose dependent. We further applied the chemically triggered tools to model RNAs under biologically relevant conditions. Collectively, this work expands the toolkit of probes for studying RNA and its native conformations.

RNA infrastructure profiling illuminates transcriptome structure in crowded spaces

RNAs fold into compact structures and undergo protein interactions in cells. These occluded environments can block reagents that probe the underlying RNAs. Probes that can analyze structure in crowded settings can shed light on RNA biology. Here, we employ 2'-OH-reactive probes that are small enough to access folded RNA structure underlying close molecular contacts within cells, providing considerably broader coverage for intracellular RNA structural analysis. The data are analyzed first with well-characterized human ribosomal RNAs and then applied transcriptome-wide to polyadenylated transcripts. The smallest probe acetylimidazole (AcIm) yields 80% greater structural coverage than larger conventional reagent NAIN3, providing enhanced structural information in hundreds of transcripts. The acetyl probe also provides superior signals for identifying m6A modification sites in transcripts, particularly in sites that are inaccessible to a standard probe. Our strategy enables profiling RNA infrastructure, enhancing analysis of transcriptome structure, modification, and intracellular interactions, especially in spatially crowded settings.

The pseudoknot structure of a viral RNA reveals a conserved mechanism for programmed exoribonuclease resistance

Exoribonuclease-resistant RNAs (xrRNAs) are viral RNA structures that block degradation by cellular 5'-3' exoribonucleases to produce subgenomic viral RNAs during infection. Initially discovered in flaviviruses, xrRNAs have since been identified in wide range of RNA viruses, including those that infect plants. High sequence variability among viral xrRNAs raises questions about the shared molecular features that characterize this functional RNA class. Here, we present the first structure of a plant-virus xrRNA in its active exoribonuclease-resistant conformation. The xrRNA forms a 9 base pair pseudoknot that creates a knot-like topology similar to that of flavivirus xrRNAs, despite lacking sequence similarity. Biophysical assays confirm a compact pseudoknot structure in solution, and functional studies validate its relevance both in vitro and during infection. Our study reveals how viral RNAs achieve a common functional outcome through highly divergent sequences and identifies the knot-like topology as a defining feature of xrRNAs.

Nexus between RNA conformational dynamics and functional versatility

RNA conformational dynamics is pivotal for functional regulations in biology. RNA can function as versatile as protein but adopts multiple distinct structures. In this review, we provide a focused review of the recent advances in studies of RNA conformational dynamics and address some of the misconceptions about RNA structure and its conformational dynamics. We discuss why the traditional methods for structure determination come up short in describing RNA conformational space. The examples discussed provide illustrations of the structure-based mechanisms of RNAs with diverse roles, including viral, long noncoding, and catalytic RNAs, one of which focuses on the debated area of conformational heterogeneity of an RNA structural element in the HIV-1 genome.

The role of RNA structure in 3' end processing in eukaryotes

Maturation of pre-mRNA into fully functional mRNA involves a series of highly coordinated steps that are essential for eukaryotic gene expression. RNA structure has been found to play regulatory roles in many of these steps, including cleavage, polyadenylation, and termination. Recent advances in structure probing techniques have been instrumental in revealing how nascent transcript conformation contributes to these dynamic, co-transcriptional processes. In this review, we present examples where RNA structure affects accessibility and/or function of key processing enzymes, thereby influencing the efficiency and precision of 3' end processing machinery. We also discuss emerging technologies that could further enhance our understanding of RNA structure mediated regulation of 3' end processing.

RNA ensembles from in vitro to in vivo: Toward predictive models of RNA cellular function

Deepening our understanding of RNA biology and accelerating development of RNA-based therapeutics go hand-in-hand-both requiring a transition from qualitative descriptions of RNA structure to quantitative models capable of predicting RNA behaviors, and from a static to an ensemble view. Ensembles are determined from their free energy landscapes, which define the relative populations of conformational states and the energetic barriers separating them. Experimental determination of RNA ensembles over the past decade has led to powerful predictive models of RNA behavior in vitro. It has also been shown during this time that the cellular environment redistributes RNA ensembles, changing the abundances of functionally relevant conformers relative to in vitro contexts with subsequent functional RNA consequences. However, recent studies have demonstrated that testing models built from in vitro ensembles with highly quantitative measurements of RNA cellular function, aided by emerging computational methodologies, enables predictive modelling of cellular activity and biological discovery.

Rapid folding of nascent RNA regulates eukaryotic RNA biogenesis

An RNA's catalytic, regulatory, or coding potential depends on RNA structure formation. Because base pairing occurs during transcription, early structural states can govern RNA processing events and dictate the formation of functional conformations. These co-transcriptional states remain unknown. Here, we develop CoSTseq, which detects nascent RNA base pairing within and upon exit from RNA polymerases (Pols) transcriptome-wide in living yeast cells. By monitoring each nucleotide's base pairing activity during transcription, we identify distinct classes of behaviors. While 47% of rRNA nucleotides remain unpaired, rapid and delayed base pairing - with rates of 48.5 and 13.2 kb -1 of transcribed rDNA, respectively - typically completes when Pol I is only 25 bp downstream. We show that helicases act immediately to remodel structures across the rDNA locus and facilitate ribosome biogenesis. In contrast, nascent pre-mRNAs attain local structures indistinguishable from mature mRNAs, suggesting that refolding behind elongating ribosomes resembles co-transcriptional folding behind Pol II.

Unveiling RNA structure-mediated regulations of RNA stability in wheat

Despite the critical role of mRNA stability in post-transcriptional gene regulation, research on this topic in wheat, a vital agricultural crop, remains unclear. Our study investigated the mRNA decay landscape of durum wheat (Triticum turgidum L. ssp. durum, BBAA), revealing subgenomic asymmetry in mRNA stability and its impact on steady-state mRNA abundance. Our findings indicate that the 3' UTR structure and homoeolog preference for RNA structural motifs can influence mRNA stability, leading to subgenomic RNA decay imbalance. Furthermore, single-nucleotide variations (SNVs) selected for RNA structural motifs during domestication can cause variations in subgenomic mRNA stability and subsequent changes in steady-state expression levels. Our research on the transcriptome stability of polyploid wheat highlights the regulatory role of non-coding region structures in mRNA stability, and how domestication shaped RNA structure, altering subgenomic mRNA stability. These results illustrate the importance of RNA structure-mediated post-transcriptional gene regulation in wheat and pave the way for its potential use in crop improvement.

Analysis of the abundance and diversity of RNA secondary structure elements in RNA viruses using the RNAsselem Python package

Recent advancements in experimental and computational methods for RNA secondary structure detection have revealed the crucial role of RNA structural elements in diverse molecular processes within living cells. It has been demonstrated that the secondary structure of the entire viral genome is often responsible for performing crucial functions in the viral life cycle and also influences virus evolution. To investigate the role of viral RNA secondary structure, alongside experimental techniques, the use of bioinformatics tools is important for analyzing various secondary structure patterns, including hairpin loops, internal loops, multifurcations, external loops, bulges, stems, and pseudoknots. Here, we have introduced a Python package for analyzing RNA secondary structure elements in viral genomes, which includes the recognition of common secondary structure patterns, the generation of descriptive statistics for these structural elements, and the provision of their basic properties. We applied the developed package to analyze the secondary structures of complete viral genomes collected from the literature, aiming to gain insights into viral function and evolution. Both the package and the collection of secondary structures of viral genomes are available at http://github.com/KazanovLab/RNAsselem .

DHX36 binding induces RNA structurome remodeling and regulates RNA abundance via m6A reader YTHDF1

RNA structure constitutes a new layer of gene regulatory mechanisms. RNA binding proteins can modulate RNA secondary structures, thus participating in post-transcriptional regulation. The DEAH-box helicase 36 (DHX36) is known to bind and unwind RNA G-quadruplex (rG4) structure but the transcriptome-wide RNA structure remodeling induced by DHX36 binding and the impact on RNA fate remain poorly understood. Here, we investigate the RNA structurome alteration induced by DHX36 depletion. Our findings reveal that DHX36 binding induces structural remodeling not only at the localized binding sites but also on the entire mRNA transcript most pronounced in 3'UTR regions. DHX36 binding increases structural accessibility at 3'UTRs which is correlated with decreased post-transcriptional mRNA abundance. Further analyses and experiments uncover that DHX36 binding sites are enriched for N6-methyladenosine (m6A) modification and YTHDF1 binding; and DHX36 induced structural changes may facilitate YTHDF1 binding to m6A sites leading to RNA degradation. Altogether, our findings uncover the structural remodeling effect of DHX36 binding and its impact on RNA abundance through regulating m6A dependent YTHDF1 binding.

RNA sample optimization for cryo-EM analysis

RNAs play critical roles in most biological processes. Although the three-dimensional (3D) structures of RNAs primarily determine their functions, it remains challenging to experimentally determine these 3D structures due to their conformational heterogeneity and intrinsic dynamics. Cryogenic electron microscopy (cryo-EM) has recently played an emerging role in resolving dynamic conformational changes and understanding structure-function relationships of RNAs including ribozymes, riboswitches and bacterial and viral noncoding RNAs. A variety of methods and pipelines have been developed to facilitate cryo-EM structure determination of challenging RNA targets with small molecular weights at subnanometer to near-atomic resolutions. While a wide range of conditions have been used to prepare RNAs for cryo-EM analysis, correlations between the variables in these conditions and cryo-EM visualizations and reconstructions remain underexplored, which continue to hinder optimizations of RNA samples for high-resolution cryo-EM structure determination. Here we present a protocol that describes rigorous screenings and iterative optimizations of RNA preparation conditions that facilitate cryo-EM structure determination, supplemented by cryo-EM data processing pipelines that resolve RNA dynamics and conformational changes and RNA modeling algorithms that generate atomic coordinates based on moderate- to high-resolution cryo-EM density maps. The current protocol is designed for users with basic skills and experience in RNA biochemistry, cryo-EM and RNA modeling. The expected time to carry out this protocol may range from 3 days to more than 3 weeks, depending on the many variables described in the protocol. For particularly challenging RNA targets, this protocol could also serve as a starting point for further optimizations.

Phylogenomic instructed target analysis reveals ELAV complex binding to multiple optimally spaced U-rich motifs

ELAV/Hu RNA-binding proteins are gene-specific regulators of alternative pre-mRNA processing. ELAV/Hu family proteins bind to short AU-rich motifs which are abundant in pre-mRNA, making it unclear how they achieve gene specificity. ELAV/Hu proteins multimerize, but how multimerization contributes to decode degenerate sequence environments remains uncertain. Here, we show that ELAV forms a saturable complex on extended RNA. Through phylogenomic instructed target analysis we identify the core binding motif U5N2U3, which is repeated in an extended binding site. Optimally spaced short U5N2U3 binding motifs are key for high-affinity binding in this minimal binding element. Binding strength correlates with ELAV-regulated alternative poly(A) site choice, which is physiologically relevant through regulation of the major ELAV target ewg in determining synapse numbers. We further identify a stem-loop secondary structure in the ewg binding site unwound upon ELAV binding at three distal U motifs. Base-pairing of U motifs prevents ELAV binding, but N6-methyladenosine (m6A) has little effect. Further, stem-loops are enriched in ELAV-regulated poly(A) sites. Additionally, ELAV can nucleate preferentially from 3' to 5'. Hence, we identify a decisive mechanism for ELAV complex formation, addressing a fundamental gap in understanding how ELAV/Hu family proteins decode degenerate sequence spaces for gene-specific mRNA processing.

Advances in the field of RNA 3D structure prediction and modeling, with purely theoretical approaches, and with the use of experimental data

Recent advancements in RNA three-dimensional (3D) structure prediction have provided significant insights into RNA biology, highlighting the essential role of RNA in cellular functions and its therapeutic potential. This review summarizes the latest developments in computational methods, particularly the incorporation of artificial intelligence and machine learning, which have improved the efficiency and accuracy of RNA structure predictions. We also discuss the integration of new experimental data types, including cryoelectron microscopy (cryo-EM) techniques and high-throughput sequencing, which have transformed RNA structure modeling. The combination of experimental advances with computational methods represents a significant leap in RNA structure determination. We review the outcomes of RNA-Puzzles and critical assessment of structure prediction (CASP) challenges, which assess the state of the field and limitations of existing methods. Future perspectives are discussed, focusing on the impact of RNA 3D structure prediction on understanding RNA mechanisms and its implications for drug discovery and RNA-targeted therapies, opening new avenues in molecular biology.

Targeting RNA with small molecules, from RNA structures to precision medicines: IUPHAR review: 40

RNA plays important roles in regulating both health and disease biology in all kingdoms of life. Notably, RNA can form intricate three-dimensional structures, and their biological functions are dependent on these structures. Targeting the structured regions of RNA with small molecules has gained increasing attention over the past decade, because it provides both chemical probes to study fundamental biology processes and lead medicines for diseases with unmet medical needs. Recent advances in RNA structure prediction and determination and RNA biology have accelerated the rational design and development of RNA-targeted small molecules to modulate disease pathology. However, challenges remain in advancing RNA-targeted small molecules towards clinical applications. This review summarizes strategies to study RNA structures, to identify small molecules recognizing these structures, and to augment the functionality of RNA-binding small molecules. We focus on recent advances in developing RNA-targeted small molecules as potential therapeutics in a variety of diseases, encompassing different modes of actions and targeting strategies. Furthermore, we present the current gaps between early-stage discovery of RNA-binding small molecules and their clinical applications, as well as a roadmap to overcome these challenges in the near future.

Viral RNA Interactome: The Ultimate Researcher's Guide to RNA-Protein Interactions

RNA molecules in the cell are bound by a multitude of RNA-binding proteins (RBPs) with a variety of regulatory consequences. Often, interactions with these RNA-binding proteins are facilitated by the complex secondary and tertiary structures of RNA molecules. Viral RNAs especially are known to be heavily structured and interact with many RBPs, with roles including genome packaging, immune evasion, enhancing replication and transcription, and increasing translation efficiency. As such, the RNA-protein interactome represents a critical facet of the viral replication cycle. Characterization of these interactions is necessary for the development of novel therapeutics targeted at the disruption of essential replication cycle events. In this review, we aim to summarize the various roles of RNA structures in shaping the RNA-protein interactome, the regulatory roles of these interactions, as well as up-to-date methods developed for the characterization of the interactome and directions for novel, RNA-directed therapeutics.

Bioorthogonal cyclopropenones for investigating RNA structure

RNA sequences encode secondary and tertiary structures that impact protein production and other cellular processes. Misfolded RNAs can also potentiate disease, but the complete picture is lacking. To establish more comprehensive and accurate RNA structure-function relationships, new methods are needed to interrogate RNA and trap native conformations in cellular environments. Existing tools primarily rely on electrophiles that are constitutively "on" or triggered by UV light, often resulting in high background reactivity. We developed an alternative, chemically triggered approach to crosslink RNAs using bioorthogonal cyclopropenones (CpOs). These reagents selectively react with phosphines to provide ketenes-electrophiles that can trap neighboring nucleophiles to forge covalent crosslinks. As proof-of-concept, we synthesized a panel of CpOs and appended them to thiazole orange (TO-1). The TO-1 conjugates bound selectively to a model RNA aptamer (Mango) with nanomolar affinity, confirmed by fluorescence turn-on. After phosphine administration, covalent crosslinks were formed between the CpO probes and RNA. The degree of crosslinking was both time and dose-dependent. We further applied the chemically triggered tools to model RNAs in biologically relevant conditions. Collectively, this work expands the toolkit of probes for studying RNA and its native conformations.

Cryo-EM: A window into the dynamic world of RNA molecules

RNAs are critical for complex cellular functions, characterized by their structural versatility and ability to undergo conformational transitions in response to cellular cues. The elusive structures of RNAs are being unraveled with unprecedented clarity, thanks to the technological advancements in structural biology, including nuclear magnetic resonance (NMR), X-ray crystallography, cryo-electron microscopy (cryo-EM) etc. This review focuses on examining the revolutionary impact of cryo-EM on our comprehension of RNA structural dynamics, underscoring the technique's contributions to structural biology and envisioning the future trajectory of this rapidly evolving field.

Challenges, advances, and opportunities in RNA structural biology by Cryo-EM

RNAs are remarkably versatile molecules that can fold into intricate three-dimensional (3D) structures to perform diverse cellular and viral functions. Despite their biological importance, relatively few RNA 3D structures have been solved, and our understanding of RNA structure-function relationships remains in its infancy. This limitation partly arises from challenges posed by RNA's complex conformational landscape, characterized by structural flexibility, formation of multiple states, and a propensity to misfold. Recently, cryo-electron microscopy (cryo-EM) has emerged as a powerful tool for the visualization of conformationally dynamic RNA-only 3D structures. However, RNA's characteristics continue to pose challenges. We discuss experimental methods developed to overcome these hurdles, including the engineering of modular modifications that facilitate the visualization of small RNAs, improve particle alignment, and validate structural models.

Identification of RNA structures and their roles in RNA functions

The development of high-throughput RNA structure profiling methods in the past decade has greatly facilitated our ability to map and characterize different aspects of RNA structures transcriptome-wide in cell populations, single cells and single molecules. The resulting high-resolution data have provided insights into the static and dynamic nature of RNA structures, revealing their complexity as they perform their respective functions in the cell. In this Review, we discuss recent technical advances in the determination of RNA structures, and the roles of RNA structures in RNA biogenesis and functions, including in transcription, processing, translation, degradation, localization and RNA structure-dependent condensates. We also discuss the current understanding of how RNA structures could guide drug design for treating genetic diseases and battling pathogenic viruses, and highlight existing challenges and future directions in RNA structure research.

Structural and biophysical dissection of RNA conformational ensembles

RNA's ability to form and interconvert between multiple secondary and tertiary structures is critical to its functional versatility and the traditional view of RNA structures as static entities has shifted towards understanding them as dynamic conformational ensembles. In this review we discuss RNA structural ensembles and their dynamics, highlighting the concept of conformational energy landscapes as a unifying framework for understanding RNA processes such as folding, misfolding, conformational changes, and complex formation. Ongoing advancements in cryo-electron microscopy and chemical probing techniques are significantly enhancing our ability to investigate multiple structures adopted by conformationally dynamic RNAs, while traditional methods such as nuclear magnetic resonance spectroscopy continue to play a crucial role in providing high-resolution, quantitative spatial and temporal information. We discuss how these methods, when used synergistically, can provide a comprehensive understanding of RNA conformational ensembles, offering new insights into their regulatory functions.

Context-dependent structure formation of hairpin motifs in bacteriophage MS2 genomic RNA

Many functions of ribonucleic acid (RNA) rely on its ability to assume specific sequence-structure motifs. Packaging signals found in certain RNA viruses are one such prominent example of functional RNA motifs. These signals are short hairpin loops that interact with coat proteins and drive viral self-assembly. As they are found in different positions along the much longer genomic RNA, the formation of their correct structure occurs as a part of a larger context. Any changes to this context can consequently lead to changes in the structure of the motifs themselves. In fact, previous studies have shown that structure and function of RNA motifs can be highly context sensitive to the flanking sequence surrounding them. However, in what ways different flanking sequences influence the structure of an RNA motif they surround has yet to be studied in detail. We focus on a hairpin-rich region of the RNA genome of bacteriophage MS2-a well-studied RNA virus with a wide potential for use in biotechnology-and systematically examine context-dependent structural stability of 14 previously identified hairpin motifs, which include putative and confirmed packaging signals. Combining secondary and tertiary RNA structure prediction of the hairpin motifs placed in different contexts, ranging from the native genomic sequence to random RNA sequences and unstructured poly-U sequences, we determine different measures of motif structural stability. In this way, we show that while some motif structures can be stable in any context, others require specific context provided by the genome. Our results demonstrate the importance of context in RNA structure formation and how changes in the flanking sequence of an RNA motif sometimes lead to drastic changes in its structure. Structural stability of a motif in different contexts could provide additional insights into its functionality as well as assist in determining whether it remains functional when intentionally placed in other contexts.

The regulatory landscape of interacting RNA and protein pools in cellular homeostasis and cancer

Biological systems encompass intricate networks governed by RNA-protein interactions that play pivotal roles in cellular functions. RNA and proteins constituting 1.1% and 18% of the mammalian cell weight, respectively, orchestrate vital processes from genome organization to translation. To date, disentangling the functional fraction of the human genome has presented a major challenge, particularly for noncoding regions, yet recent discoveries have started to unveil a host of regulatory functions for noncoding RNAs (ncRNAs). While ncRNAs exist at different sizes, structures, degrees of evolutionary conservation and abundances within the cell, they partake in diverse roles either alone or in combination. However, certain ncRNA subtypes, including those that have been described or remain to be discovered, are poorly characterized given their heterogeneous nature. RNA activity is in most cases coordinated through interactions with RNA-binding proteins (RBPs). Extensive efforts are being made to accurately reconstruct RNA-RBP regulatory networks, which have provided unprecedented insight into cellular physiology and human disease. In this review, we provide a comprehensive view of RNAs and RBPs, focusing on how their interactions generate functional signals in living cells, particularly in the context of post-transcriptional regulatory processes and cancer.

RNA-Binding Small Molecules in Drug Discovery and Delivery: An Overview from Fundamentals

RNA molecules, similar to proteins, fold into complex structures to confer diverse functions in cells. The intertwining of functions with RNA structures offers a new therapeutic opportunity for small molecules to bind and manipulate disease-relevant RNA pathways, thus creating a therapeutic realm of RNA-binding small molecules. The ongoing interest in RNA targeting and subsequent screening campaigns have led to the identification of numerous compounds that can regulate RNAs from splicing, degradation to malfunctions, with therapeutic benefits for a variety of diseases. Moreover, along with the rise of RNA-based therapeutics, RNA-binding small molecules have expanded their application to the modification, regulation, and delivery of RNA drugs, leading to the burgeoning interest in this field. This Perspective overviews the emerging roles of RNA-binding small molecules in drug discovery and delivery, covering aspects from their action fundamentals to therapeutic applications, which may inspire researchers to advance the field.

SEISMICgraph: a web-based tool for RNA structure data visualization

In recent years, RNA has been increasingly recognized for its essential roles in biology, functioning not only as a carrier of genetic information but also as a dynamic regulator of gene expression through its interactions with other RNAs, proteins, and itself. Advances in chemical probing techniques have significantly enhanced our ability to identify RNA secondary structures and understand their regulatory roles. These developments, alongside improvements in experimental design and data processing, have greatly increased the resolution and throughput of structural analyses. Here, we introduce SEISMICgraph, a web-based tool designed to support RNA structure research by offering data visualization and analysis capabilities for a variety of chemical probing modalities. SEISMICgraph enables simultaneous comparison of data across different sequences and experimental conditions through a user-friendly interface that requires no programming expertise. We demonstrate its utility by investigating known and putative riboswitches and exploring how RNA modifications influence their structure and binding. SEISMICgraph's ability to rapidly visualize adenine-dependent structural changes and assess the impact of pseudouridylation on these transitions provides novel insights and establishes a roadmap for numerous future applications.