Design of a small molecule that stimulates vascular endothelial growth factor A enabled by screening RNA fold-small molecule interactions

G-Quadruplex mRNAs Silencing with Inducible Ribonuclease Targeting Chimera for Precision Tumor Therapy

Ribonuclease targeting chimera (RIBOTAC) represents an emerging strategy for targeted therapy. However, RIBOTAC that is selectively activated by bio-orthogonal or cell-specific triggers has not been explored. We developed a strategy of inducible RIBOTAC (iRIBOTAC) that enables on-demand degradation of G-quadruplex (G4) RNAs for precision cancer therapy. iRIBOTAC is designed by coupling an RNA G4 binder with a caged ribonuclease recruiter, which can be decaged by a bio-orthogonal reaction, tumor-specific enzyme, or metabolite. A bivalent G4 binder is engineered by conjugating a near-infrared (NIR) fluorescence G4 ligand to a noncompetitive G4 ligand, conferring fluorescence activation on binding G4s with synergistically enhanced affinity. iRIBOTAC is demonstrated to greatly knockdown G4 RNAs upon activation under bio-orthogonal or cell-specific stimulus, with dysregulation of gene expressions involving cell killing, channel regulator activity, and metabolism as revealed by RNA sequencing. This strategy also shows a crucial effect on cell fate with remarkable biochemical hallmarks of apoptosis. Mice model studies demonstrate that iRIBOTAC allows selective imaging and growth suppression of tumors with bio-orthogonal and tumor-specific controls, highlighting G4 RNA targeting and inducible silencing as a valuable RIBOTAC paradigm for cancer therapy.

Similarities and Differences in Ligand Binding to Protein and RNA Targets: The Case of Riboflavin

It is nowadays clear that RNA molecules can play active roles in several biological processes. As a result, an increasing number of RNAs are gradually being identified as potentially druggable targets. In particular, noncoding RNAs can adopt highly organized conformations that are suitable for drug binding. However, RNAs are still considered challenging targets due to their complex structural dynamics and high charge density. Thus, elucidating relevant features of drug-RNA binding is fundamental for advancing drug discovery. Here, by using Molecular Dynamics simulations, we compare key features of ligand binding to proteins with those observed in RNA. Specifically, we explore similarities and differences in terms of (i) conformational flexibility of the target, (ii) electrostatic contribution to binding free energy, and (iii) water and ligand dynamics. As a test case, we examine binding of the same ligand, namely riboflavin, to protein and RNA targets, specifically the riboflavin (RF) kinase and flavin mononucleotide (FMN) riboswitch. The FMN riboswitch exhibited enhanced fluctuations and explored a wider conformational space, compared to the protein target, underscoring the importance of RNA flexibility in ligand binding. Conversely, a similar electrostatic contribution to the binding free energy of riboflavin was found. Finally, greater stability of water molecules was observed in the FMN riboswitch compared to the RF kinase, possibly due to the different shape and polarity of the pockets.

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.

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.

Deep Learning-Based Chemical Similarity for Accelerated Organic Light-Emitting Diode Materials Discovery

Thermally activated delayed fluorescence (TADF) material has attracted great attention as a promising metal-free organic light-emitting diode material with a high theoretical efficiency. To accelerate the discovery of novel TADF materials, computer-aided material design strategies have been developed. However, they have clear limitations due to the accessibility of only a few computationally tractable properties. Here, we propose TADF-likeness, a quantitative score to evaluate the TADF potential of molecules based on a data-driven concept of chemical similarity to existing TADF molecules. We used a deep autoencoder to characterize the common features of existing TADF molecules with common chemical descriptors. The score was highly correlated with the four essential electronic properties of TADF molecules and had a high success rate in large-scale virtual screening of millions of molecules to identify promising candidates at almost no cost, validating its feasibility for accelerating TADF discovery. The concept of TADF-likeness can be extended to other fields of materials discovery.

Ligand "switching on" fluorescence of HIV-1 RNA-templated copper nanoclusters for ligand-RNA interaction assays

Ligand-RNA interaction assay provides the basis for developing new RNA-binding small molecules. In this study, fluorescent copper nanoclusters (CuNCs) were first prepared using two kinds of HIV-1 RNA targets, rev-responsive element (RRE) and transactivator response element (TAR) RNA, as new templates, and it was found that the fluorescence of the single RNA-templated CuNCs was negligible. Using neomycin as a model drug, the fluorescence could be augmented (approximately 6 times) for the neomycin/RNA-templated CuNCs. Thus, a novel method was developed for ligand-RNA interactions by observing the fluorescence changes in CuNCs prepared using RNA before and after the addition of ligands. The preparation parameters of neomycin/RNA-CuNCs were optimized. The as-prepared CuNCs were characterized using UV-vis spectroscopy, fluorescence spectroscopy, and high-resolution transmission electron microscope. Circular dichroism spectral analysis showed that RRE and TAR were inclined to form a double-stranded structure after interaction with neomycin, which was more conducive to the formation of CuNCs. The interactions of neomycin and three test drugs (amikacin, gentamicin, and tobramycin) with RNA were investigated using the proposed method, and the binding constants and number of binding sites were obtained through theoretical calculations. This study provides a novel approach for ligand-RNA interaction assays.

Anti-atherosclerotic effects of naringenin and quercetin from Folium Artemisiae argyi by attenuating Interleukin-1 beta (IL-1β)/ matrix metalloproteinase 9 (MMP9): network pharmacology-based analysis and validation

Effective components and related target genes of Folium Artemisiae argyi were screened from Traditional Chinese Medicines for Systems Pharmacology Database and Analysis Platform. The therapeutic targets of atherosclerosis were searched in the MalaCards and OMIM databases. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed in WebGestalt online and verified according to ClueGo and Pedia apps in Cytoscape. Then, the protein-protein interaction network was analyzed using the STRING database and constructed using Cytoscape. Differential expression of target genes was identified in GSE9128 and GSE71226 by GEO2R. And then, molecular docking was performed using the Molecular Operating Environment. Finally, we validated the protein expression of Interleukin-6 (IL-6)/IL-1β /MMP9 by qRT-PCR and Western blot in Raw264.7 which was induced by LPS. A total of 232 potential target genes and 8 ingredients of Folium Artemisiae argyi were identified. Quercetin and naringenin are potential candidate bioactive agents in treating atherosclerosis. Vascular endothelial growth factor (VEGFA), MMP9 and IL-1β could be potential target genes. KEGG analysis demonstrated that the fluid shear stress and atherosclerosis pathway play a crucial role in the anti-atherosclerosis effect of Folium Artemisiae argyi. Gene Expression Omnibus (GEO) validation demonstrated that VEGFA was downregulated, while MMP9 and IL-1β were upregulated in patients with atherosclerosis. Molecular docking suggested that only MMP9 had a good combination with quercetin. The cell experiment results suggested that naringenin and quercetin have strong anti-inflammation effects, and significantly inhibit the expression of MMP9. Practical ApplicationsArtemisiae argyi is a traditional Chinese herbal medicine that has been widely used for its antibacterial and anti-inflammatory effects. This research demonstrated the bioactive ingredients, potential targets, and molecular mechanism of Folium Artemisiae argyi in treating atherosclerosis. It also suggests a reliable approach in investigating the therapeutic effect of traditional Chinese herbal medicine in treating Atherosclerotic cardiovascular disease (ASCVD).

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.

Proximity-Induced Nucleic Acid Degrader (PINAD) Approach to Targeted RNA Degradation Using Small Molecules

Nature has evolved intricate machinery to target and degrade RNA, and some of these molecular mechanisms can be adapted for therapeutic use. Small interfering RNAs and RNase H-inducing oligonucleotides have yielded therapeutic agents against diseases that cannot be tackled using protein-centered approaches. Because these therapeutic agents are nucleic acid-based, they have several inherent drawbacks which include poor cellular uptake and stability. Here we report a new approach to target and degrade RNA using small molecules, proximity-induced nucleic acid degrader (PINAD). We have utilized this strategy to design two families of RNA degraders which target two different RNA structures within the genome of SARS-CoV-2: G-quadruplexes and the betacoronaviral pseudoknot. We demonstrate that these novel molecules degrade their targets using in vitro, in cellulo, and in vivo SARS-CoV-2 infection models. Our strategy allows any RNA binding small molecule to be converted into a degrader, empowering RNA binders that are not potent enough to exert a phenotypic effect on their own. PINAD raises the possibility of targeting and destroying any disease-related RNA species, which can greatly expand the space of druggable targets and 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.

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.

Drug-Like Small Molecules That Inhibit Expression of the Oncogenic MicroRNA-21

We report the discovery of drug-like small molecules that bind specifically to the precursor of the oncogenic and pro-inflammatory microRNA-21 with mid-nanomolar affinity. The small molecules target a local structure at the Dicer cleavage site and induce distinctive structural changes in the RNA, which correlate with specific inhibition of miRNA processing. Structurally conservative single nucleotide substitutions eliminate the conformational change induced by the small molecules, which is also not observed in other miRNA precursors. The most potent of these compounds reduces cellular proliferation and miR-21 levels in cancer cell lines without inhibiting kinases or classical receptors, while closely related compounds without this specific binding activity are inactive in cells. These molecules are highly ligand-efficient (MW < 330) and display specific biochemical and cellular activity by suppressing the maturation of miR-21, thereby providing an avenue toward therapeutic development in multiple diseases where miR-21 is abnormally expressed.

Targeting RNA with small molecules-A safety perspective

RNA is a major player in cellular function, and consequently can drive a number of disease pathologies. Over the past several years, small molecule-RNA targeting (smRNA targeting) has developed into a promising drug discovery approach. Numerous techniques, tools, and assays have been developed to support this field, and significant investments have been made by pharmaceutical and biotechnology companies. To date, the focus has been on identifying disease validated primary targets for smRNA drug development, yet RNA as a secondary (off) target for all small molecule drug programs largely has been unexplored. In this perspective, we discuss structure, target, and mechanism-driven safety aspects of smRNAs and highlight how these parameters can be evaluated in drug discovery programs to produce potentially safer drugs.

Low-Molecular Weight Small Molecules Can Potently Bind RNA and Affect Oncogenic Pathways in Cells

RNA is challenging to target with bioactive small molecules, particularly those of low molecular weight that bind with sufficient affinity and specificity. In this report, we developed a platform to address this challenge, affording a novel bioactive interaction. An RNA-focused small-molecule fragment collection (n = 2500) was constructed by analyzing features in all publicly reported compounds that bind RNA, the largest collection of RNA-focused fragments to date. The RNA-binding landscape for each fragment was studied by using a library-versus-library selection with an RNA library displaying a discrete structural element, probing over 12.8 million interactions, the greatest number of interactions between fragments and biomolecules probed experimentally. Mining of this dataset across the human transcriptome defined a drug-like fragment that potently and specifically targeted the microRNA-372 hairpin precursor, inhibiting its processing into the mature, functional microRNA and alleviating invasive and proliferative oncogenic phenotypes in gastric cancer cells. Importantly, this fragment has favorable properties, including an affinity for the RNA target of 300 ± 130 nM, a molecular weight of 273 Da, and quantitative estimate of drug-likeness (QED) score of 0.8. (For comparison, the mean QED of oral medicines is 0.6 ± 0.2). Thus, these studies demonstrate that a low-molecular weight, fragment-like compound can specifically and potently modulate RNA targets.

Frontiers in Medicinal Chemistry 2022 Goes Virtual

The Frontiers in Medicinal Chemistry (FiMC) meeting, which represents the largest international medicinal chemistry conference in Germany, took place from March 14^th to 16^th 2022 in a fully virtual format. Organized by the Division of Medicinal Chemistry of the German Chemical Society (GDCh) together with the Division of Pharmaceutical & Medicinal Chemistry of the German Pharmaceutical Society (DPhG) and a "local" organization committee from the University of Freiburg headed by Manfred Jung, the meeting brought together 271 participants from around 20 countries. The program included 33 lectures by leading scientists from industry and academia as well as early career investigators. 67 posters were presented in two poster sessions and with over 20.000 poster abstract downloads. The general organization and the time-shift function were very much appreciated as demonstrated by almost 600 on-demand contents retrieved. The online format fitted perfectly to bring together medicinal chemists from academia and industry across the globe.

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.

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.

Extracellular vesicles enriched with an endothelial cell pro-survival microRNA affects skin tissue regeneration

Endothelial cell (EC) activity is essential for tissue regeneration in several (patho)physiological contexts. However, our capacity to deliver in vivo biomolecules capable of controlling EC fate is relatively limited. Here, we screened a library of microRNA (miR) mimics and identified 25 miRs capable of enhancing the survival of ECs exposed to ischemia-mimicking conditions. In vitro, we showed that miR-425-5p, one of the hits, was able to enhance EC survival and migration. In vivo, using a mouse Matrigel plug assay, we showed that ECs transfected with miR-425-5p displayed enhanced survival compared with scramble-transfected ECs. Mechanistically, we showed that miR-425-5p modulated the PTEN/PI3K/AKT pathway and inhibition of miR-425-5p target genes (DACH1, PTEN, RGS5, and VASH1) phenocopied the pro-survival. For the in vivo delivery of miR-425-5p, we modulated small extracellular vesicles (sEVs) with miR-425-5p and showed, in vitro, that miR-425-5p-modulated sEVs were (1) capable of enhancing the survival of ECs exposed to ischemia-mimic conditions, and (2) efficiently internalized by skin cells. Finally, using a streptozotocin-induced diabetic wound healing mouse model, we showed that, compared with miR-scrambled-modulated sEVs, topical administration of miR-425-5p-modulated sEVs significantly enhanced wound healing, a process mediated by enhanced vascularization and skin re-epithelialization.

Multifaceted targeted protein degradation systems for different cellular compartments

Selective protein degradation maintains cellular homeostasis, but this process is disrupted in many diseases. Targeted protein degradation (TPD) approaches, built upon existing cellular mechanisms, are promising methods for therapeutically regulating protein levels. Here, we review the diverse palette of tools that are now available for doing so throughout the gene expression pathway and in specific cellular compartments. These include methods for directly removing targeted proteins via the ubiquitin proteasome system with proteolysis targeting chimeras (PROTACs) or dephosphorylation targeting chimeras (DEPTACs). Similar effects can also be achieved through the lysosomal system with autophagy-targeting chimeras (AUTACs), autophagosome tethering compounds (ATTECs), and lysosome targeting chimeras (LYTACs). Other methods act upstream to degrade RNAs (ribonuclease targeting chimeras; RIBOTACs) or transcription factors (transcription factor targeting chimeras; TRAFTACs), offering control throughout the gene expression process. We highlight the evolution and function of these methods and discuss their clinical implications in diverse disease contexts.

A theoretical study based on DFT calculations on the different influence of functional groups on the C–H activation process via Pd-catalysed β-X elimination

We have performed a series of theoretical calculations for palladium-catalyzed β-X elimination reactions. The DFT calculation combined with energy decomposition analysis shows the determining factors of reactivity. Such as, the elemental composition, the structure of different functional groups and the stronger steric repulsions contribution.

The energy decomposition analysis (EDA) results show the quantitative contribution of nucleophile groups in intramolecular interactions.

Docking and scoring for nucleic acid-ligand interactions: Principles and current status

Nucleic acid (NA)-ligand interactions have crucial roles in many cellular processes and, thus, are increasingly attracting therapeutic interest in drug discovery. Molecular docking is a valuable tool for studying molecular interactions. However, because NAs differ significantly from proteins in both their physical and chemical properties, traditional docking algorithms and scoring functions for protein-ligand interactions might not be applicable to NA-ligand docking. Therefore, various sampling strategies and scoring functions for NA-ligand interactions have been developed. Here, we review the basic principles and current status of docking algorithms and scoring functions for DNA/RNA-ligand interactions. We also discuss challenges and limitations of current docking and scoring approaches.

Complex Conformational Dynamics of the Heart Failure-Associated Pre-miRNA-377 Hairpin Revealed by Single-Molecule Optical Tweezers

Pre-miRNA-377 is a hairpin-shaped regulatory RNA associated with heart failure. Here, we use single-molecule optical tweezers to unzip pre-miRNA-377 and study its stability and dynamics. We show that magnesium ions have a strong stabilizing effect, and that sodium ions stabilize the hairpin more than potassium ions. The hairpin unfolds in a single step, regardless of buffer composition. Interestingly, hairpin folding occurs either in a single step (type 1) or through the formation of intermediates, in multiple steps (type 2) or gradually (type 3). Type 3 occurs only in the presence of both sodium and magnesium, while type 1 and 2 take place in all buffers, with type 1 being the most prevalent. By reducing the size of the native hairpin loop from fourteen to four nucleotides, we demonstrate that the folding heterogeneity originates from the large size of the hairpin loop. Further, while efficient pre-miRNA-377 binders are lacking, we demonstrate that the recently developed C2 ligand displays bimodal activity: it enhances the mechanical stability of the pre-miRNA-377 hairpin and perturbs its folding. The knowledge regarding pre-miRNA stability and dynamics that we provide is important in understanding its regulatory function and how it can be modulated to achieve a therapeutic effect, e.g., in heart failure treatment.

Affecting RNA biology genome-wide by binding small molecules and chemically induced proximity

The ENCODE and genome-wide association projects have shown that much of the genome is transcribed into RNA and much less is translated into protein. These and other functional studies suggest that the druggable transcriptome is much larger than the druggable proteome. This review highlights approaches to define druggable RNA targets and structure-activity relationships across genomic RNA. Binding compounds can be identified and optimized into structure-specific ligands by using sequence-based design with various modes of action, for example, inhibiting translation or directing pre-mRNA splicing outcomes. In addition, strategies to direct protein activity against an RNA of interest via chemically induced proximity is a burgeoning area that has been validated both in cells and in preclinical animal models, and we describe that it may allow rapid access to new avenues to affect RNA biology. These approaches and the unique modes of action suggest that more RNAs are potentially amenable to targeting than proteins.

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.

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.

A single small molecule fluorescent probe for imaging RNA distribution and detecting endogenous SO2 through distinct fluorescence channels

Herein, we developed a novel small molecule fluorescent probe for imaging the distribution of RNA and detecting endogenous SO2 through distinct fluorescence channels in cells.

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.

Red Light-Initiated Cross-Linking of NIR Probes to Cytoplasmic RNA: An Innovative Strategy for Prolonged Imaging and Unexpected Tumor Suppression

Improving the enrichment of drugs or theranostic agents within tumors is very vital to achieve effective cancer diagnosis and therapy while greatly reducing the dosage and damage to normal tissues. Herein, as a proof of concept, we for the first time report a red light-initiated probe-RNA cross-linking (RLIPRC) strategy that can not only robustly promote the accumulation and retention of the probe in the tumor for prolonged imaging but also significantly inhibits the tumor growth. A near-infrared (NIR) fluorescent probe f-CR consisting of a NIR dye (Cyanine 7) as a signal reporter, a cyclic-(arginine-glycine-aspartic acid) (cRGD) peptide for tumor targeting, and a singlet oxygen (¹O₂)-sensitive furan moiety for RNA cross-linking was rationally designed and synthesized. This probe possessed both passive and active tumor targeting abilities and emitted intense NIR/photoacoustic (PA) signals, allowing for specific and sensitive dual-modality imaging of tumors in vivo. Notably, probe f-CR could be specifically and covalently cross-linked to cytoplasmic RNAs via the cycloaddition reaction between furan and adenine, cytosine, or guanine under the oxidation of ¹O₂ generated in situ by irradiation of methylene blue (MB) with 660 nm laser light, which effectively blocks the exocytosis of the probes resulting in enhanced tumor accumulation and retention. More excitingly, for the first time, we revealed that the covalent cross-linking of probe f-CR to cytoplasmic RNAs could induce severe apoptosis of cancer cells leading to remarkable tumor suppression. This study thus represents the first red light-initiated RNA cross-linking system with high potential to improve the diagnostic and therapeutic outcomes of tumors in vivo.

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.

Targeting the SARS-CoV-2 RNA Genome with Small Molecule Binders and Ribonuclease Targeting Chimera (RIBOTAC) Degraders

COVID-19 is a global pandemic, thus requiring multiple strategies to develop modalities against it. Herein, we designed multiple bioactive small molecules that target a functional structure within the SARS-CoV-2's RNA genome, the causative agent of COVID-19. An analysis to characterize the structure of the RNA genome provided a revised model of the SARS-CoV-2 frameshifting element, in particular its attenuator hairpin. By studying an RNA-focused small molecule collection, we identified a drug-like small molecule (C5) that avidly binds to the revised attenuator hairpin structure with a K d of 11 nM. The compound stabilizes the hairpin's folded state and impairs frameshifting in cells. The ligand was further elaborated into a ribonuclease targeting chimera (RIBOTAC) to recruit a cellular ribonuclease to destroy the viral genome (C5-RIBOTAC) and into a covalent molecule (C5-Chem-CLIP) that validated direct target engagement and demonstrated its specificity for the viral RNA, as compared to highly expressed host mRNAs. The RIBOTAC lead optimization strategy improved the bioactivity of the compound at least 10-fold. Collectively, these studies demonstrate that the SARS-CoV-2 RNA genome should be considered druggable.

Small molecule recognition of disease-relevant RNA structures

Targeting RNAs with small molecules represents a new frontier in drug discovery and development. The rich structural diversity of folded RNAs offers a nearly unlimited reservoir of targets for small molecules to bind, similar to small molecule occupancy of protein binding pockets, thus creating the potential to modulate human biology. Although the bacterial ribosome has historically been the most well exploited RNA target, advances in RNA sequencing technologies and a growing understanding of RNA structure have led to an explosion of interest in the direct targeting of human pathological RNAs. This review highlights recent advances in this area, with a focus on the design of small molecule probes that selectively engage structures within disease-causing RNAs, with micromolar to nanomolar affinity. Additionally, we explore emerging RNA-target strategies, such as bleomycin A5 conjugates and ribonuclease targeting chimeras (RIBOTACs), that allow for the targeted degradation of RNAs with impressive potency and selectivity. The compounds discussed in this review have proven efficacious in human cell lines, patient-derived cells, and pre-clinical animal models, with one compound currently undergoing a Phase II clinical trial and another that recently garnerd FDA-approval, indicating a bright future for targeted small molecule therapeutics that affect RNA function.

How We Think about Targeting RNA with Small Molecules

RNA offers nearly unlimited potential as a target for small molecule chemical probes and lead medicines. Many RNAs fold into structures that can be selectively targeted with small molecules. This Perspective discusses molecular recognition of RNA by small molecules and highlights key enabling technologies and properties of bioactive interactions. Sequence-based design of ligands targeting RNA has established rules for affecting RNA targets and provided a potentially general platform for the discovery of bioactive small molecules. The RNA targets that contain preferred small molecule binding sites can be identified from sequence, allowing identification of off-targets and prediction of bioactive interactions by nature of ligand recognition of functional sites. Small molecule targeted degradation of RNA targets (ribonuclease-targeted chimeras, RIBOTACs) and direct cleavage by small molecules have also been developed. These growing technologies suggest that the time is right to provide small molecule chemical probes to target functionally relevant RNAs throughout the human transcriptome.

Systematic analysis of the interactions driving small molecule-RNA recognition

RNA molecules are becoming an important target class in drug discovery. However, the principles for designing RNA-binding small molecules are yet to be fully uncovered. In this study, we examined the Protein Data Bank (PDB) to highlight privileged interactions underlying small molecule-RNA recognition. By comparing this analysis with previously determined small molecule-protein interactions, we find that RNA recognition is driven mostly by stacking and hydrogen bonding interactions, while protein recognition is instead driven by hydrophobic effects. Furthermore, we analyze patterns of interactions to highlight potential strategies to tune RNA recognition, such as stacking and cation-π interactions that favor purine and guanine recognition, and note an unexpected paucity of backbone interactions, even for cationic ligands. Collectively, this work provides further understanding of RNA-small molecule interactions that may inform the design of small molecules targeting RNA.