Discovery of Key Physicochemical, Structural, and Spatial Properties of RNA-Targeted Bioactive Ligands

Investigating the Intramolecular Competition of Different RNA Binding Motifs for Neomycin B by Native Top-Down Mass Spectrometry

The ongoing search for small molecule drugs that target ribonucleic acids (RNA) is complicated by a limited understanding of the principles that govern RNA-small molecule interactions. Here we have used stoichiometry-resolved native top-down mass spectrometry (MS) to study the binding of neomycin B to small model hairpin RNAs, an unstructured RNA, and a viral RNA construct. For 15-22 nt model RNAs with hairpin structure, we found that neomycin B binding to hairpin loops relies on interactions with both the nucleobases and the 2'-OH groups, and that a simple 5' or 3' overhang can introduce an additional binding motif. For a 47 nt RNA construct derived from stem IA of the human immunodeficiency virus 1 (HIV-1) rev response element (RRE) RNA, native top-down MS identified four different binding motifs, of which the purine-rich internal loop showed the highest affinity for neomycin B. Stoichiometry-resolved binding site mapping by native top-down MS allows for a new perspective on binding specificity, and has the potential to reveal unexpected principles of small molecule binding to RNA.

Resolving the intricate binding of neomycin B to multiple binding motifs of a neomycin-sensing riboswitch aptamer by native top-down mass spectrometry and NMR spectroscopy

Understanding small molecule binding to RNA can be complicated by an intricate interplay between binding stoichiometry, multiple binding motifs, different occupancies of different binding motifs, and changes in the structure of the RNA under study. Here, we use native top-down mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy to experimentally resolve these factors and gain a better understanding of the interactions between neomycin B and the 40 nt aptamer domain of a neomycin-sensing riboswitch engineered in yeast. Data from collisionally activated dissociation of the 1:1, 1:2 and 1:3 RNA-neomycin B complexes identified a third binding motif C of the riboswitch in addition to the two motifs A and B found in our previous study, and provided occupancies of the different binding motifs for each complex stoichiometry. Binding of a fourth neomycin B molecule was unspecific according to both MS and NMR data. Intriguingly, all major changes in the aptamer structure can be induced by the binding of the first neomycin B molecule regardless of whether it binds to motif A or B as evidenced by stoichiometry-resolved MS data together with titration data from 1H NMR spectroscopy in the imino proton region. Specific binding of the second and third neomycin B molecules further stabilizes the riboswitch aptamer, thereby allowing for a gradual response to increasing concentrations of neomycin B, which likely leads to a fine-tuning of the cellular regulatory mechanism.

Recent applications of artificial intelligence in RNA-targeted small molecule drug discovery

INTRODUCTION

Targeting RNAs with small molecules offers an alternative to the conventional protein-targeted drug discovery and can potentially address unmet and emerging medical needs. The recent rise of interest in the strategy has already resulted in large amounts of data on disease associated RNAs, as well as on small molecules that bind to such RNAs. Artificial intelligence (AI) approaches, including machine learning and deep learning, present an opportunity to speed up the discovery of RNA-targeted small molecules by improving decision-making efficiency and quality.

AREAS COVERED

The topics described in this review include the recent applications of AI in the identification of RNA targets, RNA structure determination, screening of chemical compound libraries, and hit-to-lead optimization. The impact and limitations of the recent AI applications are discussed, along with an outlook on the possible applications of next-generation AI tools for the discovery of novel RNA-targeted small molecule drugs.

EXPERT OPINION

Key areas for improvement include developing AI tools for understanding RNA dynamics and RNA - small molecule interactions. High-quality and comprehensive data still need to be generated especially on the biological activity of small molecules that target RNAs.

Contrastive pre-training and 3D convolution neural network for RNA and small molecule binding affinity prediction

MOTIVATION

The diverse structures and functions inherent in RNAs present a wealth of potential drug targets. Some small molecules are anticipated to serve as leading compounds, providing guidance for the development of novel RNA-targeted therapeutics. Consequently, the determination of RNA-small molecule binding affinity is a critical undertaking in the landscape of RNA-targeted drug discovery and development. Nevertheless, to date, only one computational method for RNA-small molecule binding affinity prediction has been proposed. The prediction of RNA-small molecule binding affinity remains a significant challenge. The development of a computational model is deemed essential to effectively extract relevant features and predict RNA-small molecule binding affinity accurately.

RESULTS

In this study, we introduced RLaffinity, a novel deep learning model designed for the prediction of RNA-small molecule binding affinity based on 3D structures. RLaffinity integrated information from RNA pockets and small molecules, utilizing a 3D convolutional neural network (3D-CNN) coupled with a contrastive learning-based self-supervised pre-training model. To the best of our knowledge, RLaffinity was the first deep learning based method for the prediction of RNA-small molecule binding affinity. Our experimental results exhibited RLaffinity's superior performance compared to baseline methods, revealed by all metrics. The efficacy of RLaffinity underscores the capability of 3D-CNN to accurately extract both global pocket information and local neighbor nucleotide information within RNAs. Notably, the integration of a self-supervised pre-training model significantly enhanced predictive performance. Ultimately, RLaffinity was also proved as a potential tool for RNA-targeted drugs virtual screening.

AVAILABILITY AND IMPLEMENTATION

https://github.com/SaisaiSun/RLaffinity.

RNA-Small-Molecule Interaction: Challenging the "Undruggable" Tag

RNA targeting, specifically with small molecules, is a relatively new and rapidly emerging avenue with the promise to expand the target space in the drug discovery field. From being "disregarded" as an "undruggable" messenger molecule to FDA approval of an RNA-targeting small-molecule drug Risdiplam, a radical change in perspective toward RNA has been observed in the past decade. RNAs serve important regulatory functions beyond canonical protein synthesis, and their dysregulation has been reported in many diseases. A deeper understanding of RNA biology reveals that RNA molecules can adopt a variety of structures, carrying defined binding pockets that can accommodate small-molecule drugs. Due to its functional diversity and structural complexity, RNA can be perceived as a prospective target for therapeutic intervention. This perspective highlights the proof of concept of RNA-small-molecule interactions, exemplified by targeting of various transcripts with functional modulators. The advent of RNA-oriented knowledge would help expedite drug discovery.

Small molecule approaches to targeting RNA

The development of innovative methodologies to identify RNA binders has attracted enormous attention in chemical biology and drug discovery. Although antibiotics targeting bacterial ribosomal RNA have been on the market for decades, the renewed interest in RNA targeting reflects the need to better understand complex intracellular processes involving RNA. In this context, small molecules are privileged tools used to explore the biological functions of RNA and to validate RNAs as therapeutic targets, and they eventually are to become new drugs. Despite recent progress, the rational design of specific RNA binders requires a better understanding of the interactions which occur with the RNA target to reach the desired biological response. In this Review, we discuss the challenges to approaching this underexplored chemical space, together with recent strategies to bind, interact and affect biologically relevant RNAs.

Dynamic geometry design of cyclic peptide architectures for RNA structure

Designing inhibitors for RNA is still challenging due to the bottleneck of maintaining the binding interaction of inhibitor-RNA accompanied by subtle RNA flexibility. Thus, the current approach usually needs to screen thousands of candidate inhibitors for binding. Here, we propose a dynamic geometry design approach to enrich the hits with only a tiny pool of designed geometrically compatible scaffold candidates. First, our method uses graph-based tree decomposition to explore the complementarity rigid binding cyclic peptide and design the amino acid side chain length and charge to fit the RNA pocket. Then, we perform an energy-based dynamical network algorithm to optimize the inhibitor-RNA hydrogen bonds. Dynamic geometry-guided design yields successful inhibitors with low micromolar binding affinity scaffolds and experimentally competes with the natural RNA chaperone. The results indicate that the dynamic geometry method yields higher efficiency and accuracy than traditional methods. The strategy could be further optimized to design the length and chirality by adopting nonstandard amino acids and facilitating RNA engineering for biological or medical applications.

Chemical-guided SHAPE sequencing (cgSHAPE-seq) informs the binding site of RNA-degrading chimeras targeting SARS-CoV-2 5' untranslated region

One of the hallmarks of RNA viruses is highly structured untranslated regions (UTRs) in their genomes. These conserved RNA structures are often essential for viral replication, transcription, or translation. In this report, we discovered and optimized a new type of coumarin derivatives, such as C30 and C34, which bind to a four-way RNA helix called SL5 in the 5' UTR of the SARS-CoV-2 RNA genome. To locate the binding site, we developed a novel sequencing-based method namely cgSHAPE-seq, in which the acylating chemical probe was directed to crosslink with the 2'-OH groups of ribose at the ligand binding site. This crosslinked RNA could then create read-through mutations during reverse transcription (i.e., primer extension) at single-nucleotide resolution to uncover the acylation locations. cgSHAPE-seq unambiguously determined that a bulged G in SL5 was the primary binding site of C30 in the SARS-CoV-2 5' UTR, which was validated through mutagenesis and in vitro binding experiments. C30 was further used as a warhead in RNA-degrading chimeras to reduce viral RNA expression levels. We demonstrated that replacing the acylating moiety in the cgSHAPE probe with ribonuclease L recruiter (RLR) moieties yielded RNA degraders active in the in vitro RNase L degradation assay and SARS-CoV-2 5' UTR expressing cells. We further explored another RLR conjugation site on the E ring of C30/C34 and discovered improved RNA degradation activities in vitro and in cells. The optimized RNA-degrading chimera C64 inhibited live virus replication in lung epithelial carcinoma cells.

RNA-Selective Small-Molecule Ligands: Recent Advances in Live-Cell Imaging and Drug Discovery

RNA structures, including those formed from coding and noncoding RNAs, alternative to protein-based drug targets, could be a promising target of small molecules for drug discovery against various human diseases, particularly in anticancer, antibacterial and antivirus development. The normal cellular activity of cells is critically dependent on the function of various RNA molecules generated from DNA transcription. Moreover, many studies support that mRNA-targeting small molecules may regulate the synthesis of disease-related proteins via the non-covalent mRNA-ligand interactions that do not involve gene modification. RNA-ligand interaction is thus an attractive approach to address the challenge of "undruggable" proteins in drug discovery because the intracellular activity of these proteins is hard to be suppressed with small molecule ligands. We selectively surveyed a specific area of RNA structure-selective small molecule ligands in fluorescence live cell imaging and drug discovery because the area was currently underexplored. This state-of-the-art review thus mainly focuses on the research published within the past three years and aims to provide the most recent information on this research area; hopefully, it could be complementary to the previously reported reviews and give new insights into the future development on RNA-specific small molecule ligands for live cell imaging and drug discovery.

Pervasive transcriptome interactions of protein-targeted drugs

The off-target toxicity of drugs targeted to proteins imparts substantial health and economic costs. Proteome interaction studies can reveal off-target effects with unintended proteins; however, little attention has been paid to intracellular RNAs as potential off-targets that may contribute to toxicity. To begin to assess this, we developed a reactivity-based RNA profiling methodology and applied it to uncover transcriptome interactions of a set of Food and Drug Administration-approved small-molecule drugs in vivo. We show that these protein-targeted drugs pervasively interact with the human transcriptome and can exert unintended biological effects on RNA functions. In addition, we show that many off-target interactions occur at RNA loci associated with protein binding and structural changes, allowing us to generate hypotheses to infer the biological consequences of RNA off-target binding. The results suggest that rigorous characterization of drugs' transcriptome interactions may help assess target specificity and potentially avoid toxicity and clinical failures.

Probing Bioactive Chemical Space to Discover RNA-Targeted Small Molecules

Small molecules have become increasingly recognized as invaluable tools to study RNA structure and function and to develop RNA-targeted therapeutics. To rationally design RNA-targeting ligands, a comprehensive understanding and explicit testing of small molecule properties that govern molecular recognition is crucial. To date, most studies have primarily evaluated properties of small molecules that bind RNA in vitro, with little to no assessment of properties that are distinct to selective and bioactive RNA-targeted ligands. Therefore, we curated an RNA-focused library, termed the Duke RNA-Targeted Library (DRTL), that was biased towards the physicochemical and structural properties of biologically active and non-ribosomal RNA-targeted small molecules. The DRTL represents one of the largest academic RNA-focused small molecule libraries curated to date with more than 800 small molecules. These ligands were selected using computational approaches that measure similarity to known bioactive RNA ligands and that diversify the molecules within this space. We evaluated DRTL binding in vitro to a panel of four RNAs using two optimized fluorescent indicator displacement assays, and we successfully identified multiple small molecule hits, including several novel scaffolds for RNA. The DRTL has and will continue to provide insights into biologically relevant RNA chemical space, such as the identification of additional RNA-privileged scaffolds and validation of RNA-privileged molecular features. Future DRTL screening will focus on expanding both the targets and assays used, and we welcome collaboration from the scientific community. We envision that the DRTL will be a valuable resource for the discovery of RNA-targeted chemical probes and therapeutic leads.

Programming inactive RNA-binding small molecules into bioactive degraders

Target occupancy is often insufficient to elicit biological activity, particularly for RNA, compounded by the longstanding challenges surrounding the molecular recognition of RNA structures by small molecules. Here we studied molecular recognition patterns between a natural-product-inspired small-molecule collection and three-dimensionally folded RNA structures. Mapping these interaction landscapes across the human transcriptome defined structure-activity relationships. Although RNA-binding compounds that bind to functional sites were expected to elicit a biological response, most identified interactions were predicted to be biologically inert as they bind elsewhere. We reasoned that, for such cases, an alternative strategy to modulate RNA biology is to cleave the target through a ribonuclease-targeting chimera, where an RNA-binding molecule is appended to a heterocycle that binds to and locally activates RNase L1. Overlay of the substrate specificity for RNase L with the binding landscape of small molecules revealed many favourable candidate binders that might be bioactive when converted into degraders. We provide a proof of concept, designing selective degraders for the precursor to the disease-associated microRNA-155 (pre-miR-155), JUN mRNA and MYC mRNA. Thus, small-molecule RNA-targeted degradation can be leveraged to convert strong, yet inactive, binding interactions into potent and specific modulators of RNA function.

Fragment-Based Approaches to Identify RNA Binders

Although fragment-based drug discovery (FBDD) has been successfully implemented and well-explored for protein targets, its feasibility for RNA targets is emerging. Despite the challenges associated with the selective targeting of RNA, efforts to integrate known methods of RNA binder discovery with fragment-based approaches have been fruitful, as a few bioactive ligands have been identified. Here, we review various fragment-based approaches implemented for RNA targets and provide insights into experimental design and outcomes to guide future work in the area. Indeed, investigations surrounding the molecular recognition of RNA by fragments address rather important questions such as the limits of molecular weight that confer selective binding and the physicochemical properties favorable for RNA binding and bioactivity.

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.

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.

4-Aminoquinolines modulate RNA structure and function: Pharmacophore implications of a conformationally restricted polyamine

RNA structure plays an important role in regulating cellular function and there is a significant emerging interest in targeting RNA for drug discovery. Here we report the identification of 4-aminoquinolines as modulators of RNA structure and function. Aminoquinolines have a broad range of pharmacological activities, but their specific mechanism of action is often not fully understood. Using electrophoretic mobility shift assays and enzymatic probing we identified 4-aminoquinolines that bind the stem-loop II motif (s2m) of SARS-CoV-2 RNA site-specifically and induce dimerization. Using fluorescence-based RNA binding and T-box riboswitch functional assays we identified that hydroxychloroquine binds the T-box riboswitch antiterminator RNA element and inhibits riboswitch function. Based on its structure and riboswitch dose-response activity we identified that the antagonist activity of hydroxychloroquine is consistent with it being a conformationally restricted analog of the polyamine spermidine. Given the known role that polyamines play in RNA function, the identification of an RNA binding ligand with the pharmacophore of a conformationally restricted polyamine has significant implications for further elucidation of RNA structure-function relationships and RNA-targeted drug discovery.

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.

Small-Molecule 3D Ligand for RNA Recognition: Tuning Selectivity through Scaffold Hopping

Targeting RNAs with small molecules is considered the next frontier for drug discovery. In this context, the development of compounds capable of binding RNA structural motifs of low complexity with high affinity and selectivity would greatly expand the number of targets of potential therapeutic value. In this study, we demonstrate that tuning the three-dimensional shape of promiscuous nucleic acid binders is a valuable strategy for the design of new selective RNA ligands. Indeed, starting from a known cyanine, the simple replacement of a phenyl ring with a [2.2]paracyclophane moiety led to a new compound able to discriminate between nucleic acids showing different structural characteristics with a marked affinity and selectivity for an octahairpin loop RNA sequence. This shape modification also affected the in cellulo behavior of the cyanine. These results suggest that scaffold hopping is a valuable strategy to improve the selectivity of RNA/small-molecule interactions and highlight the need to explore a new chemical space for the design of selective RNA ligands.

Targeting RNA structures with small molecules

RNA adopts 3D structures that confer varied functional roles in human biology and dysfunction in disease. Approaches to therapeutically target RNA structures with small molecules are being actively pursued, aided by key advances in the field including the development of computational tools that predict evolutionarily conserved RNA structures, as well as strategies that expand mode of action and facilitate interactions with cellular machinery. Existing RNA-targeted small molecules use a range of mechanisms including directing splicing - by acting as molecular glues with cellular proteins (such as branaplam and the FDA-approved risdiplam), inhibition of translation of undruggable proteins and deactivation of functional structures in noncoding RNAs. Here, we describe strategies to identify, validate and optimize small molecules that target the functional transcriptome, laying out a roadmap to advance these agents into the next decade.

Multiassay Profiling of a Focused Small Molecule Library Reveals Predictive Bidirectional Modulation of the lncRNA MALAT1 Triplex Stability In Vitro

The rapidly accelerating characterization of RNA tertiary structures has revealed their pervasiveness and active roles in human diseases. Small molecule-mediated modulation of RNA tertiary structures constitutes an attractive avenue for the development of tools for therapeutically targeting and/or uncovering the pathways associated with these RNA motifs. This potential has been highlighted by targeting of the triple helix present at the 3'-end of the noncoding RNA MALAT1, a transcript implicated in several human diseases. This triplex has been reported to decrease the susceptibility of the transcript to degradation and promote its cellular accumulation. While small molecules have been shown to bind to and impact the stability of the MALAT1 triple helix, the small molecule properties that lead to these structural modulations are not well understood. We designed a library utilizing the diminazene scaffold, which is underexplored but precedented for nucleic acid binding, to target the MALAT1 triple helix. We employed multiple assays to holistically assess what parameters, if any, could predict the small molecule affinity and effect on triplex stability. We designed and/or optimized competition, calorimetry, and thermal shift assays as well as an enzymatic degradation assay, the latter of which led to the discovery of bidirectional modulators of triple helix stability within the scaffold-centric library. Determination of quantitative structure-activity relationships afforded predictive models for both affinity- and stability-based assays. This work establishes a suite of powerful orthogonal biophysical tools for the evaluation of small molecule:RNA triplex interactions that generate predictive models and will allow small molecule interrogation of the growing body of disease-associated RNA triple helices.

HARIBOSS: a curated database of RNA-small molecules structures to aid rational drug design

MOTIVATION

RNA molecules are implicated in numerous fundamental biological processes and many human pathologies, such as cancer, neurodegenerative disorders, muscular diseases and bacterial infections. Modulating the mode of action of disease-implicated RNA molecules can lead to the discovery of new therapeutical agents and even address pathologies linked to 'undruggable' protein targets. This modulation can be achieved by direct targeting of RNA with small molecules. As of today, only a few RNA-targeting small molecules are used clinically. One of the main obstacles that have hampered the development of a rational drug design protocol to target RNA with small molecules is the lack of a comprehensive understanding of the molecular mechanisms at the basis of RNA-small molecule (RNA-SM) recognition.

RESULTS

Here, we present Harnessing RIBOnucleic acid-Small molecule Structures (HARIBOSS), a curated collection of RNA-SM structures determined by X-ray crystallography, nuclear magnetic resonance spectroscopy and cryo-electron microscopy. HARIBOSS facilitates the exploration of drug-like compounds known to bind RNA, the analysis of ligands and pockets properties and ultimately the development of in silico strategies to identify RNA-targeting small molecules.

AVAILABILITY AND IMPLEMENTATION

HARIBOSS can be explored via a web interface available at http://hariboss.pasteur.cloud.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Protein-Based Virtual Screening Tools Applied for RNA-Ligand Docking Identify New Binders of the preQ1-Riboswitch

Targeting RNA with small molecules is an emerging field. While several ligands for different RNA targets are reported, structure-based virtual screenings (VSs) against RNAs are still rare. Here, we elucidated the general capabilities of protein-based docking programs to reproduce native binding modes of small-molecule RNA ligands and to discriminate known binders from decoys by the scoring function. The programs were found to perform similar compared to the RNA-based docking tool rDOCK, and the challenges faced during docking, namely, protomer and tautomer selection, target dynamics, and explicit solvent, do not largely differ from challenges in conventional protein-ligand docking. A prospective VS with the Bacillus subtilis preQ₁-riboswitch aptamer domain performed with FRED, HYBRID, and FlexX followed by microscale thermophoresis assays identified six active compounds out of 23 tested VS hits with potencies between 29.5 nM and 11.0 μM. The hits were selected not solely based on their docking score but for resembling key interactions of the native ligand. Therefore, this study demonstrates the general feasibility to perform structure-based VSs against RNA targets, while at the same time it highlights pitfalls and their potential solutions when executing RNA-ligand docking.

Determination of RNA-ligand interactions with the photoaffinity platform PEARL-seq

In the development of therapeutics, it is important to establish engagement of a compound to its intended target and identify other targets it binds to. Methods for demonstrating target engagement in the growing field of RNA-targeted therapeutics are therefore needed. We present a detailed protocol for Photoaffinity Evaluation of RNA Ligation-Sequencing (PEARL-seq), a platform for determining interactions between small molecule ligands and their target RNA(s). PEARL-seq allows detection of binding and crosslinking events with single nucleotide resolution and allows measurement of enrichment of the target RNA relative to all other RNAs. PEARL-seq is a valuable tool in the effort to verify bona fide RNA-ligand interactions.

R-BIND 2.0: An Updated Database of Bioactive RNA-Targeting Small Molecules and Associated RNA Secondary Structures

Discoveries of RNA roles in cellular physiology and pathology are increasing the need for new tools that modulate the structure and function of these biomolecules, and small molecules are proving useful. In 2017, we curated the RNA-targeted BIoactive ligaNd Database (R-BIND) and discovered distinguishing physicochemical properties of RNA-targeting ligands, leading us to propose the existence of an "RNA-privileged" chemical space. Biennial updates of the database and the establishment of a website platform (rbind.chem.duke.edu) have provided new insights and tools to design small molecules based on the analyzed physicochemical and spatial properties. In this report and R-BIND 2.0 update, we refined the curation approach and ligand classification system as well as conducted analyses of RNA structure elements for the first time to identify new targeting strategies. Specifically, we curated and analyzed RNA target structural motifs to determine the properties of small molecules that may confer selectivity for distinct RNA secondary and tertiary structures. Additionally, we collected sequences of target structures and incorporated an RNA structure search algorithm into the website that outputs small molecules targeting similar motifs without a priori secondary structure knowledge. Cheminformatic analyses revealed that, despite the 50% increase in small molecule library size, the distinguishing properties of R-BIND ligands remained significantly different from that of proteins and are therefore still relevant to RNA-targeted probe discovery. Combined, we expect these novel insights and website features to enable the rational design of RNA-targeted ligands and to serve as a resource and inspiration for a variety of scientists interested in RNA targeting.

Pharmacophore-Based Discovery of Viral RNA Conformational Modulators

New RNA-binding small-molecule scaffolds are needed to unleash the pharmacological potential of RNA targets. Here we have applied a pharmacophore-based virtual screening approach, seldom used in the RNA recognition field, to identify novel conformational inhibitors of the hepatitis C virus internal ribosome entry site. The conformational effect of the screening hits was assessed with a fluorescence resonance energy transfer assay, and the affinity, specificity, and binding site of the ligands were determined using a combination of fluorescence intensity and NMR spectroscopy experiments. The results indicate that this strategy can be successfully applied to discover RNA conformational inhibitors bearing substantially less positive charge than the reference ligands. This methodology can potentially be accommodated to other RNA motifs of pharmacological interest, facilitating the discovery of novel RNA-targeted molecules.

Quantitative Structure-Activity Relationship (QSAR) Study Predicts Small-Molecule Binding to RNA Structure

The diversity of RNA structural elements and their documented role in human diseases make RNA an attractive therapeutic target. However, progress in drug discovery and development has been hindered by challenges in the determination of high-resolution RNA structures and a limited understanding of the parameters that drive RNA recognition by small molecules, including a lack of validated quantitative structure-activity relationships (QSARs). Herein, we develop QSAR models that quantitatively predict both thermodynamic- and kinetic-based binding parameters of small molecules and the HIV-1 transactivation response (TAR) RNA model system. Small molecules bearing diverse scaffolds were screened against TAR using surface plasmon resonance. Multiple linear regression (MLR) combined with feature selection afforded robust models that allowed direct interpretation of the properties critical for both binding strength and kinetic rate constants. These models were validated with new molecules, and their accurate performance was confirmed via comparison to ensemble tree methods, supporting the general applicability of this platform.

Subsite Ligand Recognition and Cooperativity in the TPP Riboswitch: Implications for Fragment-Linking in RNA Ligand Discovery

RNA molecules can show high levels of cooperativity in their global folding and interactions with divalent ions. However, cooperativity at individual ligand-RNA interaction sites remains poorly understood. Here, we investigated the binding of thiamine and methylene diphosphonic acid (MDP, a soluble structural analogue of pyrophosphate) to the thiamine pyrophosphate riboswitch. These ligands each bind weakly at proximal subsites, with 10 μM and 1 mM affinities, respectively. The affinity of MDP moderately improves when thiamine or thiamine-like fragments are pre-bound to the RNA. Covalent linking of thiamine and MDP substantially increases riboswitch binding to a notable high affinity of 20 nM. Crystal structures and single-molecule correlated chemical probing revealed favorable induced fit effects upon binding of individual ligands and, unexpectedly, a substantial thermodynamically unfavorable RNA structural rearrangement upon binding of the linked thiamine-MDP ligand. Thus, linking of two ligands of modest affinity, accompanied by an unfavorable structural rearrangement, still yields a potent linked RNA-binding compound. Since complex ligands often bind riboswitches and other RNAs at proximal subsites, principles derived from this work inform and support fragment-linking strategies for identifying small molecules that interact with RNA specifically and with high affinity.

Expanding the known structure space for RNA binding: a test of 2,5-diketopiperazine

As the importance of RNA as a therapeutic target has become increasingly recognized, the need for new chemotypes able to bind RNA has grown in significance. We hypothesized that diketopiperazines (DKPs), common substructures in natural products and protein-targeting therapeutic agents, could serve as effective scaffolds for targeting RNA. To confirm this hypothesis, we designed and synthesized two analogs, one incorporating a DKP and one not, of compounds previously demonstrated to bind an RNA critical to the life cycle of HIV-1 with high affinity and specificity. Prior to compound synthesis, calculations employing density functional methods and molecular mechanics conformational searches were used to confirm that the DKP could present functionality in a similar (albeit not identical) orientation to the non DKP-containing compound. We found that both the DKP-containing and parent compound had similar affinities to the target RNA as measured by surface plasmon resonance (SPR). Both compounds were found to have modest but equal anti-HIV activity. These results establish the feasibility of using DKPs to target RNA.

Discovery of Small-Molecule CD33 Pre-mRNA Splicing Modulators

CD33/Siglec 3 is a myeloid lineage cell surface receptor that is known to regulate microglia activity. Multiple genome-wide association studies (GWAS) have identified genetic variants in the CD33 gene that convey protection from late-onset Alzheimer's disease. Furthermore, mechanistic studies into GWAS-linked variants suggest that disease protection is attributed to the alternative splicing of exon 2 of the CD33 pre-mRNA. Using a phenomimetic screen, a series of compounds were found to enhance the exclusion of CD33 exon 2, acting as a chemomimetic of the GWAS-linked gene variants. Additional studies confirmed that meyloid lineage cells treated with several of these compounds have a reduced full-length V-domain containing CD33 protein, while targeted RNA-seq concordantly demonstrated that compound 1 increases exon 2 skipping in cellular mRNA pools. These studies demonstrate how pharmacological interventions can be used to manipulate disease-relevant pre-mRNA splicing and provide a starting point for future efforts to identify small molecules that alter neuroimmune function that is rooted in the human biology of neurodegenerative disease.

Noncoding RNAs: biology and applications-a Keystone Symposia report

The human transcriptome contains many types of noncoding RNAs, which rival the number of protein-coding species. From long noncoding RNAs (lncRNAs) that are over 200 nucleotides long to piwi-interacting RNAs (piRNAs) of only 20 nucleotides, noncoding RNAs play important roles in regulating transcription, epigenetic modifications, translation, and cell signaling. Roles for noncoding RNAs in disease mechanisms are also being uncovered, and several species have been identified as potential drug targets. On May 11-14, 2021, the Keystone eSymposium "Noncoding RNAs: Biology and Applications" brought together researchers working in RNA biology, structure, and technologies to accelerate both the understanding of RNA basic biology and the translation of those findings into clinical applications.

Exploring the Druggability of Conserved RNA Regulatory Elements in the SARS-CoV-2 Genome

SARS-CoV-2 contains a positive single-stranded RNA genome of approximately 30 000 nucleotides. Within this genome, 15 RNA elements were identified as conserved between SARS-CoV and SARS-CoV-2. By nuclear magnetic resonance (NMR) spectroscopy, we previously determined that these elements fold independently, in line with data from in vivo and ex-vivo structural probing experiments. These elements contain non-base-paired regions that potentially harbor ligand-binding pockets. Here, we performed an NMR-based screening of a poised fragment library of 768 compounds for binding to these RNAs, employing three different 1 H-based 1D NMR binding assays. The screening identified common as well as RNA-element specific hits. The results allow selection of the most promising of the 15 RNA elements as putative drug targets. Based on the identified hits, we derive key functional units and groups in ligands for effective targeting of the RNA of SARS-CoV-2.

Recognition of single-stranded nucleic acids by small-molecule splicing modulators

Risdiplam is the first approved small-molecule splicing modulator for the treatment of spinal muscular atrophy (SMA). Previous studies demonstrated that risdiplam analogues have two separate binding sites in exon 7 of the SMN2 pre-mRNA: (i) the 5'-splice site and (ii) an upstream purine (GA)-rich binding site. Importantly, the sequence of this GA-rich binding site significantly enhanced the potency of risdiplam analogues. In this report, we unambiguously determined that a known risdiplam analogue, SMN-C2, binds to single-stranded GA-rich RNA in a sequence-specific manner. The minimum required binding sequence for SMN-C2 was identified as GAAGGAAGG. We performed all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method, which captured spontaneous binding of a risdiplam analogue to the target nucleic acids. We uncovered, for the first time, a ligand-binding pocket formed by two sequential GAAG loop-like structures. The simulation findings were highly consistent with experimental data obtained from saturation transfer difference (STD) NMR and structure-affinity-relationship studies of the risdiplam analogues. Together, these studies illuminate us to understand the molecular basis of single-stranded purine-rich RNA recognition by small-molecule splicing modulators with an unprecedented binding mode.

Fragment-Based Drug Discovery for RNA Targets

Rapid development within the fields of both fragment-based drug discovery (FBDD) and medicinal targeting of RNA provides possibilities for combining technologies and methods in novel ways. This review provides an overview of fragment-based screening (FBS) against RNA targets, including a discussion of the most recently used screening and hit validation methods such as NMR spectroscopy, X-ray crystallography, and virtual screening methods. A discussion of fragment library design based on research from small-molecule RNA binders provides an overview on both the currently limited guidelines within RNA-targeting fragment library design, and future possibilities. Finally, future perspectives are provided on screening and hit validation methods not yet used in combination with both fragment screening and RNA targets.

DrugPred_RNA-A Tool for Structure-Based Druggability Predictions for RNA Binding Sites

RNA is an emerging target for drug discovery. However, like for proteins, not all RNA binding sites are equally suited to be addressed with conventional drug-like ligands. To this end, we have developed the structure-based druggability predictor DrugPred_RNA to identify druggable RNA binding sites. Due to the paucity of annotated RNA binding sites, the predictor was trained on protein pockets, albeit using only descriptors that can be calculated for both RNA and protein binding sites. DrugPred_RNA performed well in discriminating druggable from less druggable binding sites for the protein set and delivered predictions for selected RNA binding sites that agreed with manual assignment. In addition, most drug-like ligands contained in an RNA test set were found in pockets predicted to be druggable, further adding confidence to the performance of DrugPred_RNA. The method is robust against conformational and sequence changes in the binding sites and can contribute to direct drug discovery efforts for RNA targets.

Targeting RNA structures in diseases with small molecules

RNA is crucial for gene expression and regulation. Recent advances in understanding of RNA biochemistry, structure and molecular biology have revealed the importance of RNA structure in cellular processes and diseases. Various approaches to discovering drug-like small molecules that target RNA structure have been developed. This review provides a brief introduction to RNA structural biology and how RNA structures function as disease regulators. We summarize approaches to targeting RNA with small molecules and highlight their advantages, shortcomings and therapeutic potential.

Systematically Studying the Effect of Small Molecules Interacting with RNA in Cellular and Preclinical Models

The interrogation and manipulation of biological systems by small molecules is a powerful approach in chemical biology. Ideal compounds selectively engage a target and mediate a downstream phenotypic response. Although historically small molecule drug discovery has focused on proteins and enzymes, targeting RNA is an attractive therapeutic alternative, as many disease-causing or -associated RNAs have been identified through genome-wide association studies. As the field of RNA chemical biology emerges, the systematic evaluation of target validation and modulation of target-associated pathways is of paramount importance. In this Review, through an examination of case studies, we outline the experimental characterization, including methods and tools, to evaluate comprehensively the impact of small molecules that target RNA on cellular phenotype.

Screening strategies for identifying RNA- and ribonucleoprotein-targeted compounds

The past few years have witnessed important breakthroughs in the identification of compounds that specifically bind and regulate RNAs and in optimizing them for therapeutic use. Here, we review successful and unsuccessful approaches in screening for RNA-targeted small molecules. We discuss advantages and disadvantages of the different screening techniques and variables that affect the outcome of RNA-screening projects. We also highlight key challenges that hamper the development of quality RNA ligands, especially the still-low availability of RNA-specific compound libraries and the poor understanding of RNA structural dynamics. We conclude that the development of new RNA-targeting drugs would greatly benefit from integration of the power of high-throughput screening technologies with improved biochemical, structural, and computational characterization of RNA targets.

Programmable technologies to manipulate gene expression at the RNA level

RNA has long been an enticing therapeutic target, but is now garnering increased attention, largely driven by clinical successes of RNA interference-based drugs. While gene knockdown by well-established RNA interference- and other oligonucleotide-based strategies continues to advance in the clinic, the repertoire of targetable effectors capable of altering gene expression at the RNA level is also rapidly expanding. In this review, we focus on several recently developed bifunctional molecular technologies that both interact with and act upon a target RNA. These new approaches for programmable RNA knockdown, editing, splicing, translation, and chemical modifications stand to provide impactful new modalities for therapeutic development in the coming decades.

RNA-Targeting Splicing Modifiers: Drug Development and Screening Assays

RNA splicing is an essential step in producing mature messenger RNA (mRNA) and other RNA species. Harnessing RNA splicing modifiers as a new pharmacological modality is promising for the treatment of diseases caused by aberrant splicing. This drug modality can be used for infectious diseases by disrupting the splicing of essential pathogenic genes. Several antisense oligonucleotide splicing modifiers were approved by the U.S. Food and Drug Administration (FDA) for the treatment of spinal muscular atrophy (SMA) and Duchenne muscular dystrophy (DMD). Recently, a small-molecule splicing modifier, risdiplam, was also approved for the treatment of SMA, highlighting small molecules as important warheads in the arsenal for regulating RNA splicing. The cellular targets of these approved drugs are all mRNA precursors (pre-mRNAs) in human cells. The development of novel RNA-targeting splicing modifiers can not only expand the scope of drug targets to include many previously considered “undruggable” genes but also enrich the chemical-genetic toolbox for basic biomedical research. In this review, we summarized known splicing modifiers, screening methods for novel splicing modifiers, and the chemical space occupied by the small-molecule splicing modifiers.

Targeting RNA with small molecules: from fundamental principles towards the clinic

Recent advances in our understanding of RNA biology have uncovered crucial roles for RNA in multiple disease states, ranging from viral and bacterial infections to cancer and neurological disorders. As a result, multiple laboratories have become interested in developing drug-like small molecules to target RNA. However, this development comes with multiple unique challenges. For example, RNA is inherently dynamic and has limited chemical diversity. In addition, promiscuous RNA-binding ligands are often identified during screening campaigns. This Tutorial Review overviews important considerations and advancements for generating RNA-targeted small molecules, ranging from fundamental chemistry to promising small molecule examples with demonstrated clinical efficacy. Specifically, we begin by exploring RNA functional classes, structural hierarchy, and dynamics. We then discuss fundamental RNA recognition principles along with methods for small molecule screening and RNA structure determination. Finally, we review unique challenges and emerging solutions from both the RNA and small molecule perspectives for generating RNA-targeted ligands before highlighting a selection of the "Greatest Hits" to date. These molecules target RNA in a variety of diseases, including cancer, neurodegeneration, and viral infection, in cellular and animal model systems. Additionally, we explore the recently FDA-approved small molecule regulator of RNA splicing, risdiplam, for treatment of spinal muscular atrophy. Together, this Tutorial Review showcases the fundamental role of chemical and molecular recognition principles in enhancing our understanding of RNA biology and contributing to the rapidly growing number of RNA-targeted probes and therapeutics. In particular, we hope this widely accessible review will serve as inspiration for aspiring small molecule and/or RNA researchers.

Frameworks for targeting RNA with small molecules

Since the characterization of mRNA in 1961, our understanding of the roles of RNA molecules has significantly grown. Beyond serving as a link between DNA and proteins, RNA molecules play direct effector roles by binding to various ligands, including proteins, DNA, other RNAs, and metabolites. Through these interactions, RNAs mediate cellular processes such as the regulation of gene transcription and the enhancement or inhibition of protein activity. As a result, the misregulation of RNA molecules is often associated with disease phenotypes, and RNA molecules have been increasingly recognized as potential targets for drug development efforts, which in the past had focused primarily on proteins. Although both small molecule-based and oligonucleotide-based therapies have been pursued in efforts to target RNA, small-molecule modalities are often favored owing to several advantages including greater oral bioavailability. In this review, we discuss three general frameworks (sets of premises and hypotheses) that, in our view, have so far dominated the discovery of small-molecule ligands for RNA. We highlight the unique merits of each framework as well as the pitfalls associated with exclusive focus of ligand discovery efforts within only one framework. Finally, we propose that RNA ligand discovery can benefit from using progress made within these three frameworks to move toward a paradigm that formulates RNA-targeting questions at the level of RNA structural subclasses.

Three-Color Imaging Enables Simultaneous Screening of Multiple RNA Targets on Small Molecule Microarrays

Small molecule microarray (SMM) technology has become a powerful tool used in high-throughput screening for target-based drug discovery. One area in which SMMs have found use is the identification of small molecule ligands for RNA. RNAs with unique secondary or tertiary three-dimensional structures are considered to be attractive targets for small molecules. Complex RNA structures can form hydrophobic pockets suitable for small molecule binding, representing an opportunity for developing novel therapeutics. Our lab has previously taken a target-based approach, screening a single target against many small molecules on an SMM platform. Here, we report a screening protocol for SMMs to investigate multiple RNAs simultaneously using multi-color imaging. By introducing a mixture containing different fluorophore-labeled RNAs, the fluorescence signal of each binding event can be observed simultaneously. Thus, the specificity of a hit compound binding to one RNA target over other highly abundant RNAs (such as tRNA or rRNA) can be easily evaluated. © 2020 Wiley Periodicals LLC. Basic Protocol: RNA screening on SMMs by multi-color imaging Support Protocol 1: Preparation of SMM slides Support Protocol 2: Fluorophore labeling of RNA through maleimide chemistry.

Small molecule-RNA targeting: starting with the fundamentals

The structural and regulatory elements in therapeutically relevant RNAs offer many opportunities for targeting by small molecules, yet fundamental understanding of what drives selectivity in small molecule:RNA recognition has been a recurrent challenge. In particular, RNAs tend to be more dynamic and offer less chemical functionality than proteins, and biologically active ligands must compete with the highly abundant and highly structured RNA of the ribosome. Indeed, the only small molecule drug targeting RNA other than the ribosome was just approved in August 2020, and our recent survey of the literature revealed fewer than 150 reported chemical probes that target non-ribosomal RNA in biological systems. This Feature outlines our efforts to improve small molecule targeting strategies and gain fundamental insights into small molecule:RNA recognition by analyzing patterns in both RNA-biased small molecule chemical space and RNA topological space privileged for differentiation. First, we synthesized libraries based on RNA binding scaffolds that allowed us to reveal general principles in small molecule:recognition and to ask precise chemical questions about drivers of affinity and selectivity. Elaboration of these scaffolds has led to recognition of medicinally relevant RNA targets, including viral and long noncoding RNA structures. More globally, we identified physicochemical, structural, and spatial properties of biologically active RNA ligands that are distinct from those of protein-targeted ligands, and we have provided the dataset and associated analytical tools as part of a publicly available online platform to facilitate RNA ligand discovery. At the same time, we used pattern recognition protocols to identify RNA topologies that can be differentially recognized by small molecules and have elaborated this technique to visualize conformational changes in RNA secondary structure. These fundamental insights into the drivers of RNA recognition in vitro have led to functional targeting of RNA structures in biological systems. We hope that these initial guiding principles, as well as the approaches and assays developed in their pursuit, will enable rapid progress toward the development of RNA-targeted chemical probes and ultimately new therapeutic approaches to a wide range of deadly human diseases.

Template-guided selection of RNA ligands using imine-based dynamic combinatorial chemistry

This study establishes the applicability of imine-based dynamic combinatorial chemistry to discover non-covalent ligands for RNA targets. We elucidate properties underlying the reactivity of arylamines and demonstrate target-guided amplification of tight binders in an amiloride-based dynamic library.

RNA Drugs and RNA Targets for Small Molecules: Principles, Progress, and Challenges

RNA-based therapies, including RNA molecules as drugs and RNA-targeted small molecules, offer unique opportunities to expand the range of therapeutic targets. Various forms of RNAs may be used to selectively act on proteins, transcripts, and genes that cannot be targeted by conventional small molecules or proteins. Although development of RNA drugs faces unparalleled challenges, many strategies have been developed to improve RNA metabolic stability and intracellular delivery. A number of RNA drugs have been approved for medical use, including aptamers (e.g., pegaptanib) that mechanistically act on protein target and small interfering RNAs (e.g., patisiran and givosiran) and antisense oligonucleotides (e.g., inotersen and golodirsen) that directly interfere with RNA targets. Furthermore, guide RNAs are essential components of novel gene editing modalities, and mRNA therapeutics are under development for protein replacement therapy or vaccination, including those against unprecedented severe acute respiratory syndrome coronavirus pandemic. Moreover, functional RNAs or RNA motifs are highly structured to form binding pockets or clefts that are accessible by small molecules. Many natural, semisynthetic, or synthetic antibiotics (e.g., aminoglycosides, tetracyclines, macrolides, oxazolidinones, and phenicols) can directly bind to ribosomal RNAs to achieve the inhibition of bacterial infections. Therefore, there is growing interest in developing RNA-targeted small-molecule drugs amenable to oral administration, and some (e.g., risdiplam and branaplam) have entered clinical trials. Here, we review the pharmacology of novel RNA drugs and RNA-targeted small-molecule medications, with a focus on recent progresses and strategies. Challenges in the development of novel druggable RNA entities and identification of viable RNA targets and selective small-molecule binders are discussed. SIGNIFICANCE STATEMENT: With the understanding of RNA functions and critical roles in diseases, as well as the development of RNA-related technologies, there is growing interest in developing novel RNA-based therapeutics. This comprehensive review presents pharmacology of both RNA drugs and RNA-targeted small-molecule medications, focusing on novel mechanisms of action, the most recent progress, and existing challenges.

19 F NMR-Based Fragment Screening for 14 Different Biologically Active RNAs and 10 DNA and Protein Counter-Screens

We report here the nuclear magnetic resonance ¹⁹F screening of 14 RNA targets with different secondary and tertiary structure to systematically assess the druggability of RNAs. Our RNA targets include representative bacterial riboswitches that naturally bind with nanomolar affinity and high specificity to cellular metabolites of low molecular weight. Based on counter‐screens against five DNAs and five proteins, we can show that RNA can be specifically targeted. To demonstrate the quality of the initial fragment library that has been designed for easy follow‐up chemistry, we further show how to increase binding affinity from an initial fragment hit by chemistry that links the identified fragment to the intercalator acridine. Thus, we achieve low‐micromolar binding affinity without losing binding specificity between two different terminator structures.

Target-Directed Approaches for Screening Small Molecules against RNA Targets

RNA molecules have a variety of cellular functions that can drive disease pathologies. They are without a doubt one of the most intriguing yet controversial small-molecule drug targets. The ability to widely target RNA with small molecules could be revolutionary, once the right tools, assays, and targets are selected, thereby defining which biomolecules are targetable and what constitutes drug-like small molecules. Indeed, approaches developed over the past 5-10 years have changed the face of small molecule-RNA targeting by addressing historic concerns regarding affinity, selectivity, and structural dynamics. Presently, selective RNA-protein complex stabilizing drugs such as branaplam and risdiplam are in clinical trials for the modulation of SMN2 splicing, compounds identified from phenotypic screens with serendipitous outcomes. Fully developing RNA as a druggable target will require a target engagement-driven approach, and evolving chemical collections will be important for the industrial development of this class of target. In this review we discuss target-directed approaches that can be used to identify RNA-binding compounds and the chemical knowledge we have today of small-molecule RNA binders.