Principles for targeting RNA with drug-like small molecules

The multifaceted roles of mass spectrometric analysis in nucleic acids drug discovery and development

The deceptively simple concepts of mass determination and fragment analysis are the basis for the application of mass spectrometry (MS) to a boundless range of analytes, including fundamental components and polymeric forms of nucleic acids (NAs). This platform affords the intrinsic ability to observe first-hand the effects of NA-active drugs on the chemical structure, composition, and conformation of their targets, which might affect their ability to interact with cognate NAs, proteins, and other biomolecules present in a natural environment. The possibility of interfacing with high-performance separation techniques represents a multiplying factor that extends these capabilities to cover complex sample mixtures obtained from organisms that were exposed to NA-active drugs. This report provides a brief overview of these capabilities in the context of the analysis of the products of NA-drug activity and NA therapeutics. The selected examples offer proof-of-principle of the applicability of this platform to all phases of the journey undertaken by any successful NA drug from laboratory to bedside, and provide the rationale for its rapid expansion outside traditional laboratory settings in support to ever growing manufacturing operations.

In Silico Selection and Validation of High-Affinity ssDNA Aptamers Targeting Paromomycin

Glycans are promising for disease diagnosis since glycan biosynthesis is significantly affected by disease states, and glycosylation changes are probably more pronounced than protein expression during the transformation to the diseased condition. Glycan-specific aptamers can be developed for challenging applications such as cancer targeting; however, the high flexibility of glycosidic bonds and scarcity of studies on glycan-aptamer binding mechanisms increased the difficulty of screening. In this work, the model of interactions between glycans and ssDNA aptamers synthesized based on the sequence of rRNA genes was developed. Our simulation-based approach revealed that paromomycin as a representative example of glycans is preferred to bind base-restricted stem structures of aptamers because they are more critical in stabilizing the flexible structures of glycans. Combined experiments and simulations have identified two optimal mutant aptamers. Our work would provide a potential strategy that the glycan-binding rRNA genes could act as the initial aptamer pools to accelerate aptamer screening. In addition, this in silico workflow would be potentially applied in the more extensive in vitro development and application of RNA-templated ssDNA aptamers targeting glycans.

Conformational dynamics of RNA G4C2 and G2C4 repeat expansions causing ALS/FTD using NMR and molecular dynamics studies

G4C2 and G2C4 repeat expansions in chromosome 9 open reading frame 72 (C9orf72) are the most common cause of genetically defined amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), or c9ALS/FTD. The gene is bidirectionally transcribed, producing G4C2 repeats [r(G4C2)exp] and G2C4 repeats [r(G2C4)exp]. The c9ALS/FTD repeat expansions are highly structured, and structural studies showed that r(G4C2)exp predominantly folds into a hairpin with a periodic array of 1 × 1 G/G internal loops and a G-quadruplex. A small molecule probe revealed that r(G4C2)exp also adopts a hairpin structure with 2 × 2 GG/GG internal loops. We studied the conformational dynamics adopted by 2 × 2 GG/GG loops using temperature replica exchange molecular dynamics (T-REMD) and further characterized the structure and underlying dynamics using traditional 2D NMR techniques. These studies showed that the loop's closing base pairs influence both structure and dynamics, particularly the configuration adopted around the glycosidic bond. Interestingly, r(G2C4) repeats, which fold into an array of 2 × 2 CC/CC internal loops, are not as dynamic. Collectively, these studies emphasize the unique sensitivity of r(G4C2)exp to small changes in stacking interactions, which is not observed in r(G2C4)exp, providing important considerations for further principles in structure-based drug design.

The lncRNA HOTAIR: a pleiotropic regulator of epithelial cell plasticity

The epithelial-to-mesenchymal transition (EMT) is a trans-differentiation process that endows epithelial cells with mesenchymal properties, including motility and invasion capacity; therefore, its aberrant reactivation in cancerous cells represents a critical step to gain a metastatic phenotype. The EMT is a dynamic program of cell plasticity; many partial EMT states can be, indeed, encountered and the full inverse mesenchymal-to-epithelial transition (MET) appears fundamental to colonize distant secondary sites. The EMT/MET dynamics is granted by a fine modulation of gene expression in response to intrinsic and extrinsic signals. In this complex scenario, long non-coding RNAs (lncRNAs) emerged as critical players. This review specifically focuses on the lncRNA HOTAIR, as a master regulator of epithelial cell plasticity and EMT in tumors. Molecular mechanisms controlling its expression in differentiated as well as trans-differentiated epithelial cells are highlighted here. Moreover, current knowledge about HOTAIR pleiotropic functions in regulation of both gene expression and protein activities are described. Furthermore, the relevance of the specific HOTAIR targeting and the current challenges of exploiting this lncRNA for therapeutic approaches to counteract the EMT are discussed.

Real-time label-free detection of dynamic aptamer-small molecule interactions using a nanopore nucleic acid conformational sensor

Nucleic acids can undergo conformational changes upon binding small molecules. These conformational changes can be exploited to develop new therapeutic strategies through control of gene expression or triggering of cellular responses and can also be used to develop sensors for small molecules such as neurotransmitters. Many analytical approaches can detect dynamic conformational change of nucleic acids, but they need labeling, are expensive, and have limited time resolution. The nanopore approach can provide a conformational snapshot for each nucleic acid molecule detected, but has not been reported to detect dynamic nucleic acid conformational change in response to small -molecule binding. Here we demonstrate a modular, label-free, nucleic acid-docked nanopore capable of revealing time-resolved, small molecule-induced, single nucleic acid molecule conformational transitions with millisecond resolution. By using the dopamine-, serotonin-, and theophylline-binding aptamers as testbeds, we found that these nucleic acids scaffolds can be noncovalently docked inside the MspA protein pore by a cluster of site-specific charged residues. This docking mechanism enables the ion current through the pore to characteristically vary as the aptamer undergoes conformational changes, resulting in a sequence of current fluctuations that report binding and release of single ligand molecules from the aptamer. This nanopore tool can quantify specific ligands such as neurotransmitters, elucidate nucleic acid-ligand interactions, and pinpoint the nucleic acid motifs for ligand binding, showing the potential for small molecule biosensing, drug discovery assayed via RNA and DNA conformational changes, and the design of artificial riboswitch effectors in synthetic biology.

Splicing activates transcription from weak promoters upstream of alternative exons

Transcription and splicing are intrinsically coupled. Alternative splicing of internal exons can fine-tune gene expression through a recently described phenomenon called exon-mediated activation of transcription starts (EMATS). However, the association of this phenomenon with human diseases remains unknown. Here, we develop a strategy to activate gene expression through EMATS and demonstrate its potential for treatment of genetic diseases caused by loss of expression of essential genes. We first identified a catalog of human EMATS genes and provide a list of their pathological variants. To test if EMATS can be used to activate gene expression, we constructed stable cell lines expressing a splicing reporter based on the alternative splicing of motor neuron 2 (SMN2) gene. Using small molecules and antisense oligonucleotides (ASOs) currently used for treatment of spinal muscular atrophy, we demonstrated that increase of inclusion of alternative exons can trigger an activation of gene expression up to 45-fold by enhancing transcription in EMATS-like genes. We observed the strongest effects in genes under the regulation of weak human promoters located proximal to highly included skipped exons.

Targeting long non-coding RNA NUDT6 enhances smooth muscle cell survival and limits vascular disease progression

Long non-coding RNAs (lncRNAs) orchestrate various biological processes and regulate the development of cardiovascular diseases. Their potential therapeutic benefit to tackle disease progression has recently been extensively explored. Our study investigates the role of lncRNA Nudix Hydrolase 6 (NUDT6) and its antisense target fibroblast growth factor 2 (FGF2) in two vascular pathologies: abdominal aortic aneurysms (AAA) and carotid artery disease. Using tissue samples from both diseases, we detected a substantial increase of NUDT6, whereas FGF2 was downregulated. Targeting Nudt6 in vivo with antisense oligonucleotides in three murine and one porcine animal model of carotid artery disease and AAA limited disease progression. Restoration of FGF2 upon Nudt6 knockdown improved vessel wall morphology and fibrous cap stability. Overexpression of NUDT6 in vitro impaired smooth muscle cell (SMC) migration, while limiting their proliferation and augmenting apoptosis. By employing RNA pulldown followed by mass spectrometry as well as RNA immunoprecipitation, we identified Cysteine and Glycine Rich Protein 1 (CSRP1) as another direct NUDT6 interaction partner, regulating cell motility and SMC differentiation. Overall, the present study identifies NUDT6 as a well-conserved antisense transcript of FGF2. NUDT6 silencing triggers SMC survival and migration and could serve as a novel RNA-based therapeutic strategy in vascular diseases.

A functional group-guided approach to aptamers for small molecules

Aptameric receptors are important biosensor components, yet our ability to identify them depends on the target structures. We analyzed the contributions of individual functional groups on small molecules to binding within 27 target-aptamer pairs, identifying potential hindrances to receptor isolation-for example, negative cooperativity between sterically hindered functional groups. To increase the probability of aptamer isolation for important targets, such as leucine and voriconazole, for which multiple previous selection attempts failed, we designed tailored strategies focused on overcoming individual structural barriers to successful selections. This approach enables us to move beyond standardized protocols into functional group-guided searches, relying on sequences common to receptors for targets and their analogs to serve as anchors in regions of vast oligonucleotide spaces wherein useful reagents are likely to be found.

Structural basis for water modulating RNA duplex formation in the CUG repeats of myotonic dystrophy type 1

Secondary structures formed by expanded CUG RNA are involved in the pathobiology of myotonic dystrophy type 1. Understanding the molecular basis of toxic RNA structures can provide insights into the mechanism of disease pathogenesis and accelerate the drug discovery process. Here, we report the crystal structure of CUG repeat RNA containing three U-U mismatches between C-G and G-C base pairs. The CUG RNA crystallizes as an A-form duplex, with the first and third U-U mismatches adopting a water-mediated asymmetric mirror isoform geometry. We found for the first time that a symmetric, water-bridged U-H₂O-U mismatch is well tolerated within the CUG RNA duplex, which was previously suspected but not observed. The new water-bridged U-U mismatch resulted in high base-pair opening and single-sided cross-strand stacking interactions, which in turn dominate the CUG RNA structure. Furthermore, we performed molecular dynamics (MD) simulations that complemented the structural findings and proposed that the first and third U-U mismatches are interchangeable conformations, while the central water-bridged U-U mismatch represents an intermediate state that modulates the RNA duplex conformation. Collectively, the new structural features provided in this work are important for understanding the recognition of U-U mismatches in CUG repeats by external ligands such as proteins or small molecules.

A hybrid structure determination approach to investigate the druggability of the nucleocapsid protein of SARS-CoV-2

The pandemic caused by SARS-CoV-2 has called for concerted efforts to generate new insights into the biology of betacoronaviruses to inform drug screening and development. Here, we establish a workflow to determine the RNA recognition and druggability of the nucleocapsid N-protein of SARS-CoV-2, a highly abundant protein crucial for the viral life cycle. We use a synergistic method that combines NMR spectroscopy and protein-RNA cross-linking coupled to mass spectrometry to quickly determine the RNA binding of two RNA recognition domains of the N-protein. Finally, we explore the druggability of these domains by performing an NMR fragment screening. This workflow identified small molecule chemotypes that bind to RNA binding interfaces and that have promising properties for further fragment expansion and drug development.

Targeting Riboswitches with Beta-Axial-Substituted Cobalamins

RNA-targeting small-molecule therapeutics is an emerging field hindered by an incomplete understanding of the basic principles governing RNA-ligand interactions. One way to advance our knowledge in this area is to study model systems where these interactions are better understood, such as riboswitches. Riboswitches bind a wide array of small molecules with high affinity and selectivity, providing a wealth of information on how RNA recognizes ligands through diverse structures. The cobalamin-sensing riboswitch is a particularly useful model system, as similar sequences show highly specialized binding preferences for different biological forms of cobalamin. This riboswitch is also widely dispersed across bacteria and therefore holds strong potential as an antibiotic target. Many synthetic cobalamin forms have been developed for various purposes including therapeutics, but their interaction with cobalamin riboswitches is yet to be explored. In this study, we characterize the interactions of 11 cobalamin derivatives with three representative cobalamin riboswitches using in vitro binding experiments (both chemical footprinting and a fluorescence-based assay) and a cell-based reporter assay. The derivatives show productive interactions with two of the three riboswitches, demonstrating simultaneous plasticity and selectivity within these RNAs. The observed plasticity is partially achieved through a novel structural rearrangement within the ligand binding pocket, providing insight into how similar RNA structures can be targeted. As the derivatives also show in vivo functionality, they serve as several potential lead compounds for further drug development.

Triplex-Forming Peptide Nucleic Acid Controls Dynamic Conformations of RNA Bulges

RNA folding is driven by the formation of double-helical segments interspaced by loops of unpaired nucleotides. Among the latter, bulges formed by one or several unpaired nucleotides are one of the most common structural motifs that play an important role in stabilizing RNA-RNA, RNA-protein, and RNA-small molecule interactions. Single-nucleotide bulges can fold in alternative structures where the unpaired nucleobase is either looped-out (flexible) in a solvent or stacked-in (intercalated) between the base pairs. In the present study, we discovered that triplex-forming peptide nucleic acids (PNAs) had unusually high affinity for single-purine-nucleotide bulges in double-helical RNA. Depending on the PNA's sequence, the triplex formation shifted the equilibrium between looped-out and stacked-in conformations. The ability to control the dynamic equilibria of RNA's structure will be an important tool for studying structure-function relationships in RNA biology and may have potential in novel therapeutic approaches targeting disease-related RNAs.

Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications

Small molecules have been providing medical breakthroughs for human diseases for more than a century. Recently, identifying small molecule inhibitors that target microRNAs (miRNAs) has gained importance, despite the challenges posed by labour-intensive screening experiments and the significant efforts required for medicinal chemistry optimization. Numerous experimentally-verified cases have demonstrated the potential of miRNA-targeted small molecule inhibitors for disease treatment. This new approach is grounded in their posttranscriptional regulation of the expression of disease-associated genes. Reversing dysregulated gene expression using this mechanism may help control dysfunctional pathways. Furthermore, the ongoing improvement of algorithms has allowed for the integration of computational strategies built on top of laboratory-based data, facilitating a more precise and rational design and discovery of lead compounds. To complement the use of extensive pharmacogenomics data in prioritising potential drugs, our previous work introduced a computational approach based on only molecular sequences. Moreover, various computational tools for predicting molecular interactions in biological networks using similarity-based inference techniques have been accumulated in established studies. However, there are a limited number of comprehensive reviews covering both computational and experimental drug discovery processes. In this review, we outline a cohesive overview of both biological and computational applications in miRNA-targeted drug discovery, along with their disease implications and clinical significance. Finally, utilizing drug-target interaction (DTIs) data from DrugBank, we showcase the effectiveness of deep learning for obtaining the physicochemical characterization of DTIs.

Transporter proteins knowledge graph construction and its application in drug development

Transporters are the main determinant for pharmacokinetics characteristics of drugs, such as absorption, distribution, and excretion of drugs in humans. However, it is difficult to perform drug transporter validation and structure analysis of membrane transporter proteins by experimental methods. Many studies have demonstrated that knowledge graphs (KG) could effectively excavate potential association information between different entities. To improve the effectiveness of drug discovery, a transporter-related KG was constructed in this study. Meanwhile, a predictive frame (AutoInt_KG) and a generative frame (MolGPT_KG) were established based on the heterogeneity information obtained from the transporter-related KG by the RESCAL model. Natural product Luteolin with known transporters was selected to verify the reliability of the AutoInt_KG frame, its ROC-AUC (1:1), ROC-AUC (1:10), PR-AUC (1:1), PR-AUC (1:10) are 0.91, 0.94, 0.91 and 0.78, respectively. Subsequently, the MolGPT_KG frame was constructed to implement efficient drug design based on transporter structure. The evaluation results showed that the MolGPT_KG could generate novel and valid molecules and that these molecules were further confirmed by molecular docking analysis. The docking results showed that they could bind to important amino acids at the active site of the target transporter. Our findings will provide rich information resources and guidance for the further development of the transporter-related drugs.

Investigation of Sequence-Penetration Relationships of Antisense Oligonucleotides

A major limitation for the development of more effective oligonucleotide therapeutics has been a lack of understanding of their penetration into the cytosol. While prior work has shown how backbone modifications affect cytosolic penetration, it is unclear how cytosolic penetration is affected by other features including base composition, base sequence, length, and degree of secondary structure. We have applied the chloroalkane penetration assay, which exclusively reports on material that reaches the cytosol, to investigate the effects of these characteristics on the cytosolic uptake of druglike oligonucleotides. We found that base composition and base sequence had moderate effects, while length did not correlate directly with the degree of cytosolic penetration. Investigating further, we found that the degree of secondary structure had the largest and most predictable correlations with cytosolic penetration. These methods and observations add a layer of design for maximizing the efficacy of new oligonucleotide therapeutics.

The emerging roles of long non-coding RNA in host immune response and intracellular bacterial infections

The long non-coding RNAs (lncRNAs) are evolutionarily conserved classes of non-coding regulatory transcripts of > 200 nucleotides in length. They modulate several transcriptional and post-transcriptional events in the organism. Depending on their cellular localization and interactions, they regulate chromatin function and assembly; and alter the stability and translation of cytoplasmic mRNAs. Although their proposed range of functionality remains controversial, there is increasing research evidence that lncRNAs play a regulatory role in the activation, differentiation and development of immune signaling cascades; microbiome development; and in diseases such as neuronal and cardiovascular disorders; cancer; and pathogenic infections. This review discusses the functional roles of different lncRNAs in regulation of host immune responses, signaling pathways during host-microbe interaction and infection caused by obligate intracellular bacterial pathogens. The study of lncRNAs is assuming significance as it could be exploited for development of alternative therapeutic strategies for the treatment of severe and chronic pathogenic infections caused by Mycobacterium, Chlamydia and Rickettsia infections, as well as commensal colonization. Finally, this review summarizes the translational potential of lncRNA research in development of diagnostic and prognostic tools for human diseases.

Recognizing the power of machine learning and other computational methods to accelerate progress in small molecule targeting of RNA

RNA structures regulate a wide range of processes in biology and disease, yet small molecule chemical probes or drugs that can modulate these functions are rare. Machine learning and other computational methods are well poised to fill gaps in knowledge and overcome the inherent challenges in RNA targeting, such as the dynamic nature of RNA and the difficulty of obtaining RNA high-resolution structures. Successful tools to date include principal component analysis, linear discriminate analysis, k-nearest neighbor, artificial neural networks, multiple linear regression, and many others. Employment of these tools has revealed critical factors for selective recognition in RNA:small molecule complexes, predictable differences in RNA- and protein-binding ligands, and quantitative structure activity relationships that allow the rational design of small molecules for a given RNA target. Herein we present our perspective on the value of using machine learning and other computation methods to advance RNA:small molecule targeting, including select examples and their validation as well as necessary and promising future directions that will be key to accelerate discoveries in this important field.

Targeting RNA with small molecules: lessons learned from Xist RNA

Although more than 98% of the human genome is noncoding, nearly all drugs on the market target one of about 700 disease-related proteins. However, an increasing number of diseases are now being attributed to noncoding RNA and the ability to target them would vastly expand the chemical space for drug development. We recently devised a screening strategy based upon affinity-selection mass spectrometry and succeeded in identifying bioactive compounds for the noncoding RNA prototype, Xist. One such compound, termed X1, has drug-like properties and binds specifically to the RepA motif of Xist in vitro and in vivo. Small-angle X-ray scattering analysis reveals that X1 changes the conformation of RepA in solution, thereby explaining the displacement of cognate interacting protein factors (PRC2 and SPEN) and inhibition of X-chromosome inactivation. In this Perspective, we discuss lessons learned from these proof-of-concept experiments and suggest that RNA can be systematically targeted by drug-like compounds to disrupt RNA structure and function.

Innovations in targeting RNA by fragment-based ligand discovery

A subset of functional regions within large RNAs fold into complex structures able to bind small-molecule ligands with high affinity and specificity. Fragment-based ligand discovery (FBLD) offers notable opportunities for discovery and design of potent small molecules that bind pockets in RNA. Here we share an integrated analysis of recent innovations in FBLD, emphasizing opportunities resulting from fragment elaboration via both linking and growing. Analysis of elaborated fragments emphasizes that high-quality interactions form with complex tertiary structures in RNA. FBLD-inspired small molecules have been shown to modulate RNA functions by competitively inhibiting protein binding and by selectively stabilizing dynamic RNA states. FBLD is creating a foundation to interrogate the relatively unknown structural space for RNA ligands and for discovery of RNA-targeted therapeutics.

How does precursor RNA structure influence RNA processing and gene expression?

RNA is a fundamental biomolecule that has many purposes within cells. Due to its single-stranded and flexible nature, RNA naturally folds into complex and dynamic structures. Recent technological and computational advances have produced an explosion of RNA structural data. Many RNA structures have regulatory and functional properties. Studying the structure of nascent RNAs is particularly challenging due to their low abundance and long length, but their structures are important because they can influence RNA processing. Precursor RNA processing is a nexus of pathways that determines mature isoform composition and that controls gene expression. In this review, we examine what is known about human nascent RNA structure and the influence of RNA structure on processing of precursor RNAs. These known structures provide examples of how other nascent RNAs may be structured and show how novel RNA structures may influence RNA processing including splicing and polyadenylation. RNA structures can be targeted therapeutically to treat disease.

Protein-RNA interactions: from mass spectrometry to drug discovery

Proteins and RNAs are fundamental parts of biological systems, and their interactions affect many essential cellular processes. Therefore, it is crucial to understand at a molecular and at a systems level how proteins and RNAs form complexes and mutually affect their functions. In the present mini-review, we will first provide an overview of different mass spectrometry (MS)-based methods to study the RNA-binding proteome (RBPome), most of which are based on photochemical cross-linking. As we will show, some of these methods are also able to provide higher-resolution information about binding sites, which are important for the structural characterisation of protein-RNA interactions. In addition, classical structural biology techniques such as nuclear magnetic resonance (NMR) spectroscopy and biophysical methods such as electron paramagnetic resonance (EPR) spectroscopy and fluorescence-based methods contribute to a detailed understanding of the interactions between these two classes of biomolecules. We will discuss the relevance of such interactions in the context of the formation of membrane-less organelles (MLOs) by liquid-liquid phase separation (LLPS) processes and their emerging importance as targets for drug discovery.

The era of cryptic exons: implications for ALS-FTD

TDP-43 is an RNA-binding protein with a crucial nuclear role in splicing, and mislocalises from the nucleus to the cytoplasm in a range of neurodegenerative disorders. TDP-43 proteinopathy spans a spectrum of incurable, heterogeneous, and increasingly prevalent neurodegenerative diseases, including the amyotrophic lateral sclerosis and frontotemporal dementia disease spectrum and a significant fraction of Alzheimer's disease. There are currently no directed disease-modifying therapies for TDP-43 proteinopathies, and no way to distinguish who is affected before death. It is now clear that TDP-43 proteinopathy leads to a number of molecular changes, including the de-repression and inclusion of cryptic exons. Importantly, some of these cryptic exons lead to the loss of crucial neuronal proteins and have been shown to be key pathogenic players in disease pathogenesis (e.g., STMN2), as well as being able to modify disease progression (e.g., UNC13A). Thus, these aberrant splicing events make promising novel therapeutic targets to restore functional gene expression. Moreover, presence of these cryptic exons is highly specific to patients and areas of the brain affected by TDP-43 proteinopathy, offering the potential to develop biomarkers for early detection and stratification of patients. In summary, the discovery of cryptic exons gives hope for novel diagnostics and therapeutics on the horizon for TDP-43 proteinopathies.

Interaction between a fluoroquinolone derivative KG022 and RNAs: Effect of base pairs 3′ adjacent to the bulged residues

RNA-targeted small molecules are a promising modality in drug discovery. Recently, we found that a fluoroquinolone derivative, KG022, can bind to RNAs with bulged C or G. To clarify the RNA specificity of KG022, we analyzed the effect of the base pair located at the 3′side of the bulged residue. It was found that KG022 prefers G-C and A-U base pairs at the 3′side. Solution structures of the complexes of KG022 with the four RNA molecules with bulged C or G and G-C or A-U base pairs at the 3′side of the bulged residue were determined to find that the fluoroquinolone moiety is located between two purine bases, and this may be the mechanism of the specificity. This work provides an important example of the specificity of RNA-targeted small molecules.

Small Molecule Regulators of microRNAs Identified by High-Throughput Screen Coupled with High-Throughput Sequencing

MicroRNAs (miRNAs) regulate fundamental biological processes by silencing mRNA targets and are dysregulated in many diseases. Therefore, miRNA replacement or inhibition can be harnessed as potential therapeutics. However, existing strategies for miRNA modulation using oligonucleotides and gene therapies are challenging, especially for neurological diseases, and none have yet gained clinical approval. We explore a different approach by screening a biodiverse library of small molecule compounds for their ability to modulate hundreds of miRNAs in human induced pluripotent stem cell-derived neurons. We demonstrate the utility of the screen by identifying cardiac glycosides as potent inducers of miR-132, a key miRNA downregulated in Alzheimer's disease and other tauopathies. Coordinately, cardiac glycosides downregulate known miR-132 targets, including Tau, and protect rodent and human neurons against various toxic insults. More generally, our dataset of 1370 drug-like compounds and their effects on the miRNome provide a valuable resource for further miRNA-based drug discovery.

RPflex: A Coarse-Grained Network Model for RNA Pocket Flexibility Study

RNA regulates various biological processes, such as gene regulation, RNA splicing, and intracellular signal transduction. RNA’s conformational dynamics play crucial roles in performing its diverse functions. Thus, it is essential to explore the flexibility characteristics of RNA, especially pocket flexibility. Here, we propose a computational approach, RPflex, to analyze pocket flexibility using the coarse-grained network model. We first clustered 3154 pockets into 297 groups by similarity calculation based on the coarse-grained lattice model. Then, we introduced the flexibility score to quantify the flexibility by global pocket features. The results show strong correlations between the flexibility scores and root-mean-square fluctuation (RMSF) values, with Pearson correlation coefficients of 0.60, 0.76, and 0.53 in Testing Sets I–III. Considering both flexibility score and network calculations, the Pearson correlation coefficient was increased to 0.71 in flexible pockets on Testing Set IV. The network calculations reveal that the long-range interaction changes contributed most to flexibility. In addition, the hydrogen bonds in the base–base interactions greatly stabilize the RNA structure, while backbone interactions determine RNA folding. The computational analysis of pocket flexibility could facilitate RNA engineering for biological or medical applications.

RNA demethylase ALKBH5 promotes tumorigenesis of t (8;21) acute myeloid leukemia via ITPA m6A modification

BACKGROUND

Although t (8;21) is in fact considered a good risk acute myeloid leukemia (AML), only 60% of the patients live beyond 5 years after diagnosis. Studies have shown that RNA demethylase ALKBH5 promotes leukemogenesis. However, the molecular mechanism and clinical significance of ALKBH5 in t (8;21) AML have not been elucidated.

METHODS

The expression of ALKBH5 was assessed in t (8;21) AML patients via qRT-PCR and western blot. The proliferative activity of these cells was examined through CCK-8 or colony-forming assays, while flow cytometry approaches were used to examine apoptotic cell rates. The in vivo role of ALKBH5 promoting leukemogenesis was assessed using t (8;21) murine model, CDX, and PDX models. RNA sequencing, m6A RNA methylation assay, RNA immunoprecipitation, and luciferase reporter assay were used to explore the molecular mechanism of ALKBH5 in t (8;21) AML.

RESULTS

ALKBH5 is highly expressed in t (8;21) AML patients. Silencing ALKBH5 suppresses the proliferation and promotes the apoptosis of patient-derived AML cells and Kasumi-1 cells. With integrated transcriptome analysis and wet-lab confirmation, we found that ITPA is a functionally important target of ALKBH5. Mechanistically, ALKBH5 demethylates ITPA mRNA and increases its mRNA stability, leading to enhanced ITPA expression. Furthermore, transcription factor TCF15, specifically expressed in leukemia stem/initiating cells (LSCs/LICs), is responsible for the dysregulated expression of ALKBH5 in t (8;21) AML.

CONCLUSION

Our work uncovers a critical function for the TCF15/ALKBH5/ITPA axis and provides insights into the vital roles of m6A methylation in t (8;21) AML.

Contemporary Progress and Opportunities in RNA-Targeted Drug Discovery

The surprising discovery that RNAs are the predominant gene products to emerge from the human genome catalyzed a renaissance in RNA biology. It is now well-understood that RNAs act as more than just a messenger and comprise a large and diverse family of ribonucleic acids of differing sizes, structures, and functions. RNAs play expansive roles in the cell, contributing to the regulation and fine-tuning of nearly all aspects of gene expression and genome architecture. In line with the significance of these functions, we have witnessed an explosion in discoveries connecting RNAs with a variety of human diseases. Consequently, the targeting of RNAs, and more broadly RNA biology, has emerged as an untapped area of drug discovery, making the search for RNA-targeted therapeutics of great interest. In this Microperspective, I highlight contemporary learnings in the field and present my views on how to catapult us toward the systematic discovery of RNA-targeted medicines.

Machine Learning Informs RNA-Binding Chemical Space

Small molecule targeting of RNA has emerged as a new frontier in medicinal chemistry, but compared to the protein targeting literature our understanding of chemical matter that binds to RNA is limited. In this study, we reported Repository Of BInders to Nucleic acids (ROBIN), a new library of nucleic acid binders identified by small molecule microarray (SMM) screening. The complete results of 36 individual nucleic acid SMM screens against a library of 24 572 small molecules were reported (including a total of 1 627 072 interactions assayed). A set of 2 003 RNA-binding small molecules was identified, representing the largest fully public, experimentally derived library of its kind to date. Machine learning was used to develop highly predictive and interpretable models to characterize RNA-binding molecules. This work demonstrates that machine learning algorithms applied to experimentally derived sets of RNA binders are a powerful method to inform RNA-targeted chemical space.

Chemical RNA Cross-Linking: Mechanisms, Computational Analysis, and Biological Applications

In recent years, RNA has emerged as a multifaceted biomolecule that is involved in virtually every function of the cell and is critical for human health. This has led to a substantial increase in research efforts to uncover the many chemical and biological aspects of RNA and target RNA for therapeutic purposes. In particular, analysis of RNA structures and interactions in cells has been critical for understanding their diverse functions and druggability. In the last 5 years, several chemical methods have been developed to achieve this goal, using chemical cross-linking combined with high-throughput sequencing and computational analysis. Applications of these methods resulted in important new insights into RNA functions in a variety of biological contexts. Given the rapid development of new chemical technologies, a thorough perspective on the past and future of this field is provided. In particular, the various RNA cross-linkers and their mechanisms, the computational analysis and challenges, and illustrative examples from recent literature are discussed.

Peptides Targeting RNA m6 A Methylations Influence the Viability of Cancer Cells

N6-methyladenosine (m6 A) is the most abundant nucleotide modification observed in eukaryotic mRNA. Changes in m6 A levels in transcriptome are tightly correlated to expression levels of m6 A methyltransferases and demethylases. Abnormal expression levels of methyltransferases and demethylases are observed in various diseases and health conditions such as cancer, male infertility, and obesity. This research explores the efficacy of m6 A-modified RNA as an anticancer drug target. We discovered a 12-mer peptide that binds specifically to m6 A-modified RNA using phage display experiments. Our fluorescence-based assays illustrate the selected peptide binds to methylated RNA with lower micromolar affinity and inhibit the binding of protein FTO, a demethylase enzyme specific to m6 A modification. When cancer cell lines were treated with mtp1, it led to an increase in m6 A levels and a decrease in cell viability. Hence our results illustrate the potential of mtp1 to be developed as a drug for cancer.

Inhibiting the growth of ovarian cancer cells in vitro and in vivo by a small molecular inhibitor targeting La-RNA interactions

OBJECTIVE

To identify small molecules blocking La-RNA interactions by using structural dynamics, molecular biology, and in vivo efficacy experiments.

METHODS

A docking virtual assay on the Chemdiv database was used to screen La binders, and their affinity were measured by surface plasmon resonance (SPR). A novel fluorescence polarization (FP) assay referring to the binding of La protein and 3'UUUOH was established to identify the inhibitors. Their activity on ovarian cancer cell proliferation, apoptosis and cell cycle were evaluated using Cell Counting Kit 8 (CCK8) and flow cytometry assay, respectively. Their in vivo efficacy against ovarian cancer growth were evaluated in a cell line-derived xenograft (CDX) model of A2780 cells.

RESULTS

From a total of 20 compounds with high potential binding activity with La protein, two small molecule compounds 4424-1120 and 8017-5932 with relatively stronger inhibition ability on La-RNA interactions were identified. These two compounds shared the same active centers with hydroxyimidazole and hydroxybenzene to interact with La protein through residues ARG57, GLN20 and GLN136. The in vitro assays showed that 4424-1120 and 8017-5932 effectively cause G0/G1 cell cycle arrest, inhibit cell proliferation, reduce cell invasion and promote apoptosis in ovarian cancer cells. In a CDX model on BALB/C Nude mice, we found that the growth rate of the tumor was inhibited by 4424-1120.

CONCLUSION

Our results demonstrated compound 4424-1120 shows good antitumor activity and safety in vitro and in vivo, and it provides a new idea for the discovery of antitumor lead compounds from small drug-like molecules.

Discovery of RNA-targeted small molecules through the merging of experimental and computational technologies

INTRODUCTION

The field of RNA-targeted small molecules is rapidly evolving, owing to the advances in experimental and computational technologies. With the identification of several bioactive small molecules that target RNA, including the FDA-approved risdiplam, the biopharmaceutical industry is gaining confidence in the field. This review, based on the literature obtained from PubMed, aims to disseminate information about the various technologies developed for targeting RNA with small molecules and propose areas for improvement to develop drugs more efficiently, particularly those linked to diseases with unmet medical needs.

AREAS COVERED

The technologies for the identification of RNA targets, screening of chemical libraries against RNA, assessing the bioactivity and target engagement of the hit compounds, structure determination, and hit-to-lead optimization are reviewed. Along with the description of the technologies, their strengths, limitations, and examples of how they can impact drug discovery are provided.

EXPERT OPINION

Many existing technologies employed for protein targets have been repurposed for use in the discovery of RNA-targeted small molecules. In addition, technologies tailored for RNA targets have been developed. Nevertheless, more improvements are necessary, such as artificial intelligence to dissect important RNA structures and RNA-small-molecule interactions and more powerful chemical probing and structure prediction techniques.

Considerations in the Preclinical Assessment of the Safety of Antisense Oligonucleotides

The nucleic acid therapeutics field has made tremendous progress in the past decades. Continuous advances in chemistry and design have led to many successful clinical applications, eliciting even more interest from researchers including both academic groups and drug development companies. Many preclinical studies in the field focus on improving the delivery of antisense oligonucleotide drugs (ONDs) and/or assessing their efficacy in target tissues, often neglecting the evaluation of toxicity, at least in early phases of development. A series of consensus recommendations regarding regulatory considerations and expectations have been generated by the Oligonucleotide Safety Working Group and the Japanese Research Working Group for the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use S6 and Related Issues (WGS6) in several white papers. However, safety aspects should also be kept in sight in earlier phases while screening and designing OND to avoid subsequent failure in the development phase. Experts and members of the network "DARTER," a COST Action funded by the Cooperation in Science and Technology of the EU, have utilized their collective experience working with OND, as well as their insights into OND-mediated toxicities, to generate a series of consensus recommendations to assess OND toxicity in early stages of preclinical research. In the past few years, several publications have described predictive assays, which can be used to assess OND-mediated toxicity in vitro or ex vivo to filter out potential toxic candidates before moving to in vivo phases of preclinical development, that is, animal toxicity studies. These assays also have the potential to provide translational insight since they allow a safety evaluation in human in vitro systems. Yet, small preliminary in vivo studies should also be considered to complement this early assessment. In this study, we summarize the state of the art and provide guidelines and recommendations on the different tests available for these early stage preclinical assessments.

DeepsmirUD: Prediction of Regulatory Effects on microRNA Expression Mediated by Small Molecules Using Deep Learning

Aberrant miRNA expression has been associated with a large number of human diseases. Therefore, targeting miRNAs to regulate their expression levels has become an important therapy against diseases that stem from the dysfunction of pathways regulated by miRNAs. In recent years, small molecules have demonstrated enormous potential as drugs to regulate miRNA expression (i.e., SM-miR). A clear understanding of the mechanism of action of small molecules on the upregulation and downregulation of miRNA expression allows precise diagnosis and treatment of oncogenic pathways. However, outside of a slow and costly process of experimental determination, computational strategies to assist this on an ad hoc basis have yet to be formulated. In this work, we developed, to the best of our knowledge, the first cross-platform prediction tool, DeepsmirUD, to infer small-molecule-mediated regulatory effects on miRNA expression (i.e., upregulation or downregulation). This method is powered by 12 cutting-edge deep-learning frameworks and achieved AUC values of 0.843/0.984 and AUCPR values of 0.866/0.992 on two independent test datasets. With a complementarily constructed network inference approach based on similarity, we report a significantly improved accuracy of 0.813 in determining the regulatory effects of nearly 650 associated SM-miR relations, each formed with either novel small molecule or novel miRNA. By further integrating miRNA-cancer relationships, we established a database of potential pharmaceutical drugs from 1343 small molecules for 107 cancer diseases to understand the drug mechanisms of action and offer novel insight into drug repositioning. Furthermore, we have employed DeepsmirUD to predict the regulatory effects of a large number of high-confidence associated SM-miR relations. Taken together, our method shows promise to accelerate the development of potential miRNA targets and small molecule drugs.

Structural and Functional RNA Motifs of SARS-CoV-2 and Influenza A Virus as a Target of Viral Inhibitors

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the COVID-19 pandemic, whereas the influenza A virus (IAV) causes seasonal epidemics and occasional pandemics. Both viruses lead to widespread infection and death. SARS-CoV-2 and the influenza virus are RNA viruses. The SARS-CoV-2 genome is an approximately 30 kb, positive sense, 5' capped single-stranded RNA molecule. The influenza A virus genome possesses eight single-stranded negative-sense segments. The RNA secondary structure in the untranslated and coding regions is crucial in the viral replication cycle. The secondary structure within the RNA of SARS-CoV-2 and the influenza virus has been intensively studied. Because the whole of the SARS-CoV-2 and influenza virus replication cycles are dependent on RNA with no DNA intermediate, the RNA is a natural and promising target for the development of inhibitors. There are a lot of RNA-targeting strategies for regulating pathogenic RNA, such as small interfering RNA for RNA interference, antisense oligonucleotides, catalytic nucleic acids, and small molecules. In this review, we summarized the knowledge about the inhibition of SARS-CoV-2 and influenza A virus propagation by targeting their RNA secondary structure.

High Throughput FISH Screening Identifies Small Molecules That Modulate Oncogenic lncRNA MALAT1 via GSK3B and hnRNPs

Traditionally, small molecule-based drug discovery has mainly focused on proteins as the drug target. Opening RNA as an additional target space for small molecules offers the possibility to therapeutically modulate disease-driving non-coding RNA targets as well as mRNA of otherwise undruggable protein targets. MALAT1 is a highly conserved long-noncoding RNA whose overexpression correlates with poor overall patient survival in some cancers. We report here a fluorescence in-situ hybridization-based high-content imaging screen to identify small molecules that modulate the oncogenic lncRNA MALAT1 in a cellular setting. From a library of FDA approved drugs and known bioactive molecules, we identified two compounds, including Niclosamide, an FDA-approved drug, that lead to a rapid decrease of MALAT1 nuclear levels with good potency. Mode-of-action studies suggest a novel cellular regulatory pathway that impacts MALAT1 lncRNA nuclear levels by GSK3B activation and the involvement of the RNA modulating family of heterogenous nuclear ribonucleoproteins (hnRNPs). This study is the basis for the identification of novel targets that lead to a reduction of the oncogenic lncRNA MALAT1 in a cancer setting.

RNA-targeting strategies as a platform for ocular gene therapy

Genetic medicine is offering hope as new therapies are emerging for many previously untreatable diseases. The eye is at the forefront of these advances, as exemplified by the approval of Luxturna® by the United States Food and Drug Administration (US FDA) in 2017 for the treatment of one form of Leber Congenital Amaurosis (LCA), an inherited blindness. Luxturna® was also the first in vivo human gene therapy to gain US FDA approval. Numerous gene therapy clinical trials are ongoing for other eye diseases, and novel delivery systems, discovery of new drug targets and emerging technologies are currently driving the field forward. Targeting RNA, in particular, is an attractive therapeutic strategy for genetic disease that may have safety advantages over alternative approaches by avoiding permanent changes in the genome. In this regard, antisense oligonucleotides (ASO) and RNA interference (RNAi) are the currently popular strategies for developing RNA-targeted therapeutics. Enthusiasm has been further fuelled by the emergence of clustered regularly interspersed short palindromic repeats (CRISPR)-CRISPR associated (Cas) systems that allow targeted manipulation of nucleic acids. RNA-targeting CRISPR-Cas systems now provide a novel way to develop RNA-targeted therapeutics and may provide superior efficiency and specificity to existing technologies. In addition, RNA base editing technologies using CRISPR-Cas and other modalities also enable precise alteration of single nucleotides. In this review, we showcase advances made by RNA-targeting systems for ocular disease, discuss applications of ASO and RNAi technologies, highlight emerging CRISPR-Cas systems and consider the implications of RNA-targeting therapeutics in the development of future drugs to treat eye disease.

RNA-targeted small-molecule drug discoveries: a machine-learning perspective

In the past two decades, machine learning (ML) has been extensively adopted in protein-targeted small molecule (SM) discovery. Once trained, ML models could exert their predicting abilities on large volumes of molecules within a short time. However, applying ML approaches to discover RNA-targeted SMs is still in its early stages. This is primarily because of the intrinsic structural instability of RNA molecules that impede the structure-based screening or designing of RNA-targeted SMs. Recently, with more studies revealing RNA structures and a growing number of RNA-targeted ligands being identified, it resulted in an increased interest in the field of drugging RNA. Undeniably, intracellular RNA is much more abundant than protein and, if successfully targeted, will be a major alternative target for therapeutics. Therefore, in this context, as well as under the premise of having RNA-related research data, ML-based methods can get involved in improving the speed of traditional experimental processes. [Figure: see text].

X-Ray Crystallography to Study Conformational Changes in a TPP Riboswitch

Conformational rearrangements are key to the function of riboswitches. These regulatory mRNA regions specifically bind to cellular metabolites using evolutionarily conserved sensing domains and modulate gene expression via adjacent downstream expression platforms, which carry gene expression signals. The regulation is achieved through the ligand-dependent formation of two alternative and mutually exclusive conformations involving the same RNA region. While X-ray crystallography cannot visualize dynamics of such dramatic conformational rearrangements, this method is pivotal to understand RNA-ligand interaction that stabilize the sensing domain and drive folding of the expression platform. X-ray crystallography can reveal local changes in RNA necessary for discriminating cognate and noncognate ligands. This chapter describes preparation of thiamine pyrophosphate riboswitch RNAs and its crystallization with different ligands, resulting in structures with local conformational changes in RNA. These structures can help to derive information on the dynamics of the RNA essential for specific binding to small molecules, with potential for using this information for developing designer riboswitch-ligand systems.

Brief considerations on targeting RNA with small molecules

For more than three decades, RNA has been known to be a relevant and attractive macromolecule to target but figuring out which RNA should be targeted and how remains challenging. Recent years have seen the confluence of approaches for screening, drug optimization, and target validation that have led to the approval of a few RNA-targeting therapeutics for clinical applications. This focused perspective aims to highlight - but not exhaustively review - key factors accounting for these successes while pointing at crucial aspects worth considering for further breakthroughs.

Noncoding RNA therapeutics for substance use disorder

Although noncoding RNAs (ncRNAs) have been shown to regulate maladaptive neuroadaptations that drive compulsive drug use, ncRNA-targeting therapeutics for substance use disorder (SUD) have yet to be clinically tested. Recent advances in RNA-based drugs have improved many therapeutic issues related to immune response, specificity, and delivery, leading to multiple successful clinical trials for other diseases. As the need for safe and effective treatments for SUD continues to grow, novel nucleic acid-based therapeutics represent an appealing approach to target ncRNA mechanisms in SUD. Here, we review ncRNA processes implicated in SUD, discuss recent therapeutic approaches for targeting ncRNAs, and highlight potential opportunities and challenges of ncRNA-targeting therapeutics for SUD.

Inverse In Vitro Selection Enables Comprehensive Analysis of Cross-Chiral L-Aptamer Interactions

Aptamers composed of mirror-image L-(deoxy)ribose nucleic acids, referred to as L-aptamers, are a promising class of RNA-binding reagents. Yet, the selectivity of cross-chiral interactions between L-aptamers and their RNA targets remain poorly characterized, limiting the potential utility of this approach for applications in biological systems. Herein, we carried out the first comprehensive analysis of cross-chiral L-aptamer selectivity using a newly developed "inverse" in vitro selection approach that exploits the genetic nature of the D-RNA ligand. By employing a library of more than a million target-derived sequences, we determined the RNA sequence and structural preference of a model L-aptamer and revealed previously unidentified and potentially broad off-target RNA binding behaviors. These results provide valuable information for assessing the likelihood and consequences of potential off-target interactions and reveal strategies to mitigate these effects. Thus, inverse in vitro selection provides several opportunities to advance L-aptamer technology.

Small molecules in the treatment of COVID-19

The outbreak of COVID-19 has become a global crisis, and brought severe disruptions to societies and economies. Until now, effective therapeutics against COVID-19 are in high demand. Along with our improved understanding of the structure, function, and pathogenic process of SARS-CoV-2, many small molecules with potential anti-COVID-19 effects have been developed. So far, several antiviral strategies were explored. Besides directly inhibition of viral proteins such as RdRp and Mpro, interference of host enzymes including ACE2 and proteases, and blocking relevant immunoregulatory pathways represented by JAK/STAT, BTK, NF-κB, and NLRP3 pathways, are regarded feasible in drug development. The development of small molecules to treat COVID-19 has been achieved by several strategies, including computer-aided lead compound design and screening, natural product discovery, drug repurposing, and combination therapy. Several small molecules representative by remdesivir and paxlovid have been proved or authorized emergency use in many countries. And many candidates have entered clinical-trial stage. Nevertheless, due to the epidemiological features and variability issues of SARS-CoV-2, it is necessary to continue exploring novel strategies against COVID-19. This review discusses the current findings in the development of small molecules for COVID-19 treatment. Moreover, their detailed mechanism of action, chemical structures, and preclinical and clinical efficacies are discussed.

Geneticin shows selective antiviral activity against SARS-CoV-2 by interfering with programmed -1 ribosomal frameshifting

SARS-CoV-2 is currently causing an unprecedented pandemic. While vaccines are massively deployed, we still lack effective large-scale antiviral therapies. In the quest for antivirals targeting conserved structures, we focused on molecules able to bind viral RNA secondary structures. Aminoglycosides are a class of antibiotics known to interact with the ribosomal RNA of both prokaryotes and eukaryotes and have previously been shown to exert antiviral activities by interacting with viral RNA. Here we show that the aminoglycoside geneticin is endowed with antiviral activity against all tested variants of SARS-CoV-2, in different cell lines and in a respiratory tissue model at non-toxic concentrations. The mechanism of action is an early inhibition of RNA replication and protein expression related to a decrease in the efficiency of the -1 programmed ribosomal frameshift (PRF) signal of SARS-CoV-2. Using in silico modeling, we have identified a potential binding site of geneticin in the pseudoknot of frameshift RNA motif. Moreover, we have selected, through virtual screening, additional RNA binding compounds, interacting with the same site with increased potency.

Applying HT-SAXS to chemical ligand screening

Chemical probes are invaluable tools for investigating essential biological processes. Understanding how small-molecule probes engage biomolecular conformations is critical to developing their functional selectivity. High-throughput solution X-ray scattering is well-positioned to profile target-ligand complexes during probe development, bringing conformational insight and selection to traditional ligand binding assays. Access to high-quality synchrotron SAXS datasets and high-throughput data analysis now allows routine academic users to incorporate conformational information into small-molecule development pipelines. Here we describe a general approach for benchmarking and preparing HT-SAXS chemical screens from small fragment libraries. Using the allosteric oxidoreductase Apoptosis-Inducing Factor (AIF) as an exemplary system, we illustrate how HT-SAXS efficiently identifies an allosteric candidate among hits of a microscale thermophoresis ligand screen. We discuss considerations for pursuing HT-SAXS chemical screening with other systems of interest and reflect on advances to extend screening throughput and sensitivity.

SARS-CoV-2 Inhibitors Identified by Phenotypic Analysis of a Collection of Viral RNA-Binding Molecules

Antiviral agents are needed for the treatment of SARS-CoV-2 infections and to control other coronavirus outbreaks that may occur in the future. Here we report the identification and characterization of RNA-binding compounds that inhibit SARS-CoV-2 replication. The compounds were detected by screening a small library of antiviral compounds previously shown to bind HIV-1 or HCV RNA elements with a live-virus cellular assay detecting inhibition of SARS-CoV-2 replication. These experiments allowed detection of eight compounds with promising anti-SARS-CoV-2 activity in the sub-micromolar to micromolar range and wide selectivity indexes. Examination of the mechanism of action of three selected hit compounds excluded action on the entry or egress stages of the virus replication cycle and confirmed recognition by two of the molecules of conserved RNA elements of the SARS-CoV-2 genome, including the highly conserved S2m hairpin located in the 3'-untranslated region of the virus. While further studies are needed to clarify the mechanism of action responsible for antiviral activity, these results facilitate the discovery of RNA-targeted antivirals and provide new chemical scaffolds for developing therapeutic agents against coronaviruses.