Targeting RNA structures with small molecules

NMR structures of small molecules bound to a model of a CUG RNA repeat expansion

Trinucleotide repeat expansions fold into long, stable hairpins and cause a variety of incurable RNA gain-of-function diseases such as Huntington's disease, the myotonic dystrophies, and spinocerebellar ataxias. One approach for treating these diseases is to bind small molecules to these structured RNAs. Both Huntington's disease-like 2 (HDL2) and myotonic dystrophy type 1 (DM1) are caused by a r(CUG) repeat expansion, or r(CUG)exp. The RNA folds into a hairpin structure with a periodic array of 1 × 1 nucleotide UU loops (5'CUG/3'GUC; where the underlined nucleotides indicate the Us in the internal loop) that sequester various RNA-binding proteins (RBPs) and hence the source of its gain-of-function. Here, we report nuclear magnetic resonance (NMR)-refined structures of single 5'CUG/3'GUC motifs in complex with three different small molecules, a di-guandinobenzoate (1), a derivative of 1 where the guanidino groups have been exchanged for imidazole (2), and a quinoline with improved drug-like properties (3). These structures were determined using NMR spectroscopy and simulated annealing with restrained molecular dynamics (MD). Compounds 1, 2, and 3 formed stacking and hydrogen bonding interactions with the 5'CUG/3'GUC motif. Compound 3 also formed van der Waals interactions with the internal loop. The global structure of each RNA-small molecule complexes retains an A-form conformation, while the internal loops are still dynamic but to a lesser extent compared to the unbound form. These results aid our understanding of ligand-RNA interactions and enable structure-based design of small molecules with improved binding affinity for and biological activity against r(CUG)exp. As the first ever reported structures of a r(CUG) repeat bound to ligands, these structures can enable virtual screening campaigns combined with machine learning assisted de novo design.

Identification of RNA structures and their roles in RNA functions

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

Hit me with your best shot: Integrated hit discovery for the next generation of drug targets

Identification of high-quality hit chemical matter is of vital importance to the success of drug discovery campaigns. However, this goal is becoming ever harder to achieve as the targets entering the portfolios of pharmaceutical and biotechnology companies are increasingly trending towards novel and traditionally challenging to drug. This demand has fuelled the development and adoption of numerous new screening approaches, whereby the contemporary hit identification toolbox comprises a growing number of orthogonal and complementary technologies including high-throughput screening, fragment-based ligand design, affinity screening (affinity-selection mass spectrometry, differential scanning fluorimetry, DNA-encoded library screening), as well as increasingly sophisticated computational predictive approaches. Herein we describe how an integrated strategy for hit discovery, whereby multiple hit identification techniques are tactically applied, selected in the context of target suitability and resource priority, represents an optimal and often essential approach to maximise the likelihood of identifying quality starting points from which to develop the next generation of medicines.

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

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

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

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

Protocol for transcriptome-wide mapping of small-molecule RNA-binding sites in live cells

Small molecules targeting RNA can be valuable chemical probes and potential therapeutics. The interactions between small molecules, particularly fragments, and RNA, however, can be difficult to detect due to their modest affinities and short residence times. Here, we present a protocol for mapping the molecular fingerprints of small molecules in vitro and throughout the human transcriptome in live cells. We describe steps for compound treatment, cross-linking, RNA extraction, fragmentation, and pull-down. We then detail procedures for RNA sequencing and data analysis. For complete details on the use and execution of this protocol, please refer to Tong et al.1.

RNA and condensates: Disease implications and therapeutic opportunities

Biomolecular condensates are dynamic membraneless organelles that compartmentalize proteins and RNA molecules to regulate key cellular processes. Diverse RNA species exert their effects on the cell by their roles in condensate formation and function. RNA abnormalities such as overexpression, modification, and mislocalization can lead to pathological condensate behaviors that drive various diseases, including cancer, neurological disorders, and infections. Here, we review RNA's role in condensate biology, describe the mechanisms of RNA-induced condensate dysregulation, note the implications for disease pathogenesis, and discuss novel therapeutic strategies. Emerging approaches to targeting RNA within condensates, including small molecules and RNA-based therapies that leverage the unique properties of condensates, may revolutionize treatment for complex diseases.

Mechanistic analysis of Riboswitch Ligand interactions provides insights into pharmacological control over gene expression

Riboswitches are structured RNA elements that regulate gene expression upon binding to small molecule ligands. Understanding the mechanisms by which small molecules impact riboswitch activity is key to developing potent, selective ligands for these and other RNA targets. We report the structure-informed design of chemically diverse synthetic ligands for PreQ1 riboswitches. Multiple X-ray co-crystal structures of synthetic ligands with the Thermoanaerobacter tengcongensis (Tte)-PreQ1 riboswitch confirm a common binding site with the cognate ligand, despite considerable chemical differences among the ligands. Structure probing assays demonstrate that one ligand causes conformational changes similar to PreQ1 in six structurally and mechanistically diverse PreQ1 riboswitch aptamers. Single-molecule force spectroscopy is used to demonstrate differential modes of riboswitch stabilization by the ligands. Binding of the natural ligand brings about the formation of a persistent, folded pseudoknot structure, whereas a synthetic ligand decreases the rate of unfolding through a kinetic mechanism. Single round transcription termination assays show the biochemical activity of the ligands, while a GFP reporter system reveals compound activity in regulating gene expression in live cells without toxicity. Taken together, this study reveals that diverse small molecules can impact gene expression in live cells by altering conformational changes in RNA structures through distinct mechanisms.

Machine learning-augmented molecular dynamics simulations (MD) reveal insights into the disconnect between affinity and activation of ZTP riboswitch ligands

The challenge of targeting RNA with small molecules necessitates a better understanding of RNA-ligand interaction mechanisms. However, the dynamic nature of nucleic acids, their ligand-induced stabilization, and how conformational changes influence gene expression pose significant difficulties for experimental investigation. This work employs a combination of computational and experimental methods to address these challenges. By integrating structure-informed design, crystallography, and machine learning-augmented all-atom molecular dynamics simulations (MD) we synthesized, biophysically and biochemically characterized, and studied the dissociation of a library of small molecule activators of the ZTP riboswitch, a ligand-binding RNA motif that regulates bacterial gene expression. We uncovered key interaction mechanisms, revealing valuable insights into the role of ligand binding kinetics on riboswitch activation. Further, we established that ligand on-rates determine activation potency as opposed to binding affinity and elucidated RNA structural differences, which provide mechanistic insights into the interplay of RNA structure on riboswitch activation.

Extrapolating Lessons from Targeted Protein Degradation to Other Proximity-Inducing Drugs

Targeted protein degradation (TPD) is an emerging pharmacologic strategy. It relies on small-molecule "degraders" that induce proximity of a component of an E3 ubiquitin ligase complex and a target protein to induce target ubiquitination and subsequent proteasomal degradation. Essentially, degraders thus expand the function of E3 ligases, allowing them to degrade proteins they would not recognize in the absence of the small molecule. Over the past decade, insights gained from identifying, designing, and characterizing various degraders have significantly enhanced our understanding of TPD mechanisms, precipitating in rational degrader discovery strategies. In this Account, I aim to explore how these insights can be extrapolated to anticipate both opportunities and challenges of utilizing the overarching concept of proximity-inducing pharmacology to manipulate other cellular circuits for the dissection of biological mechanisms and for therapeutic purposes.

Identification of an RNA-binding perturbing characteristic for thiopurine drugs and their derivatives to disrupt CELF1-RNA interaction

RNA-binding proteins (RBPs) are attractive targets in human pathologies. Despite a number of efforts to target RBPs with small molecules, it is still difficult to develop RBP inhibitors, asking for a deeper understanding of how to chemically perturb RNA-binding activity. In this study, we found that the thiopurine drugs (6-mercaptopurine and 6-thioguanine) effectively disrupt CELF1-RNA interaction. The disrupting activity relies on the formation of disulfide bonds between the thiopurine drugs and CELF1. Mutating the cysteine residue proximal to the RNA recognition motifs (RRMs), or adding reducing agents, abolishes the disrupting activity. Furthermore, the 1,2,4-triazole-3-thione, a thiopurine analogue, was identified with 20-fold higher disrupting activity. Based on this analogue, we found that compound 9 disrupts CELF1-RNA interaction in living cells and ameliorates CELF1-mediated myogenesis deficiency. In summary, we identified a thiol-mediated binding mechanism for thiopurine drugs and their derivatives to perturb protein-RNA interaction, which provides novel insight for developing RBP inhibitors. Additionally, this work may benefit the pharmacological and toxicity research of thiopurine drugs.

RNA-Activatable Near-Infrared Photosensitizer for Cancer Therapy

Photodynamic therapy (PDT) has recently come to the forefront as an exceptionally powerful and promising method for the treatment of cancer. Existing photosensitizers are predominantly engineered to target diverse biomolecules, including proteins, DNA, lipids, and carbohydrates, and have proven to greatly enhance the efficacy or specificity of PDT. However, it is noteworthy that there exists a conspicuous scarcity of photosensitizers specifically designed to target RNAs. Recognizing the crucial and multifaceted roles played by RNAs in various cellular processes and disease states, we have ventured into the development of a novel RNA-targeting photosensitizer, named Se-718, designed specifically for PDT-based cancer therapy. Se-718 has been engineered to exhibit a high molar absorption coefficient in the NIR region, which is crucial for effective PDT. More importantly, Se-718 has demonstrated a distinct RNA-targeting capability, as evidenced through rigorous testing in both circular dichroism and fluorescence experiments. Furthermore, Se-718 has been shown to display both type I and type II photodynamic properties. This unique characteristic enables the efficient killing of cancer cells under a wide range of oxygen conditions, both normoxic (21% O2) and hypoxic (2% O2). The IC50 of Se-718 can be as low as 100 nM, and its light-to-dark toxicity ratio is an impressive 215 times higher, outperforming most photosensitizers currently available. Moreover, in vivo studies conducted with tumor-bearing mice have demonstrated the excellent antitumor effects and high safety profile of Se-718. Considering the outstanding PDT efficacy of Se-718, we are optimistic that the development of RNA-targeting photosensitizers may provide an innovative and highly effective option for cancer therapeutics in the near future.

Current landscape of mRNA technologies and delivery systems for new modality therapeutics

Realizing the immense clinical potential of mRNA-based drugs will require continued development of methods to safely deliver the bioactive agents with high efficiency and without triggering side effects. In this regard, lipid nanoparticles have been successfully utilized to improve mRNA delivery and protect the cargo from extracellular degradation. Encapsulation in lipid nanoparticles was an essential factor in the successful clinical application of mRNA vaccines, which conclusively demonstrated the technology's potential to yield approved medicines. In this review, we begin by describing current advances in mRNA modifications, design of novel lipids and development of lipid nanoparticle components for mRNA-based drugs. Then, we summarize key points pertaining to preclinical and clinical development of mRNA therapeutics. Finally, we cover topics related to targeted delivery systems, including endosomal escape and targeting of immune cells, tumors and organs for use with mRNA vaccines and new treatment modalities for human diseases.

SMTRI: A deep learning-based web service for predicting small molecules that target miRNA-mRNA interactions

Mature microRNAs (miRNAs) are short, single-stranded RNAs that bind to target mRNAs and induce translational repression and gene silencing. Many miRNAs discovered in animals have been implicated in diseases and have recently been pursued as therapeutic targets. However, conventional pharmacological screening for candidate small-molecule drugs can be time-consuming and labor-intensive. Therefore, developing a computational program to assist mature miRNA-targeted drug discovery in silico is desirable. Our previous work (https://doi.org/10.1002/advs.201903451) revealed that the unique functional loops formed during Argonaute-mediated miRNA-mRNA interactions have stable structural characteristics and may serve as potential targets for small-molecule drug discovery. Developing drugs specifically targeting disease-related mature miRNAs and their target mRNAs would avoid affecting unrelated ones. Here, we present SMTRI, a convolutional neural network-based approach for efficiently predicting small molecules that target RNA secondary structural motifs formed by interactions between miRNAs and their target mRNAs. Measured on three additional testing sets, SMTRI outperformed state-of-the-art algorithms by 12.9%-30.3% in AUC and 2.0%-18.4% in accuracy. Moreover, four case studies on the published experimentally validated RNA-targeted small molecules also revealed the reliability of SMTRI.

RNA dynamics from experimental and computational approaches

Conformational dynamics is crucial for the biological function of RNA molecules and for their potential as therapeutic targets. This meeting report outlines key "take-home" messages that emerged from the presentations and discussions during the CECAM workshop "RNA dynamics from experimental and computational approaches" in Paris, June 26-28, 2023.

Predicting Small Molecule Binding Nucleotides in RNA Structures Using RNA Surface Topography

RNA small molecule interactions play a crucial role in drug discovery and inhibitor design. Identifying RNA small molecule binding nucleotides is essential and requires methods that exhibit a high predictive ability to facilitate drug discovery and inhibitor design. Existing methods can predict the binding nucleotides of simple RNA structures, but it is hard to predict binding nucleotides in complex RNA structures with junctions. To address this limitation, we developed a new deep learning model based on spatial correlation, ZHmolReSTasite, which can accurately predict binding nucleotides of small and large RNA with junctions. We utilize RNA surface topography to consider the spatial correlation, characterizing nucleotides from sequence and tertiary structures to learn a high-level representation. Our method outperforms existing methods for benchmark test sets composed of simple RNA structures, achieving precision values of 72.9% on TE18 and 76.7% on RB9 test sets. For a challenging test set composed of RNA structures with junctions, our method outperforms the second best method by 11.6% in precision. Moreover, ZHmolReSTasite demonstrates robustness regarding the predicted RNA structures. In summary, ZHmolReSTasite successfully incorporates spatial correlation, outperforms previous methods on small and large RNA structures using RNA surface topography, and can provide valuable insights into RNA small molecule prediction and accelerate RNA inhibitor design.

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

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

Small molecules targeting microRNAs: new opportunities and challenges in precision cancer therapy

Noncoding RNAs, especially miRNAs, play a pivotal role in cancer initiation and metastasis, underscoring their susceptibility to precise modulation via small molecule inhibitors. This review examines the innovative strategy of targeting oncogenic miRNAs with small drug-like molecules, an approach that can reshape the cancer treatment landscape. We review the current understanding of the multifaceted roles of miRNAs in oncogenesis, highlighting emerging therapeutic paradigms that have the potential to expand cancer treatment options. As research on small molecule inhibitors of miRNA is still in its early stages, ongoing investigative efforts and the development of new technologies and chemical matter are essential to fulfill the significant potential of this innovative approach to cancer treatment.

Exploring single-cell RNA sequencing as a decision-making tool in the clinical management of Fuchs' endothelial corneal dystrophy

Single-cell RNA sequencing (scRNA-seq) has enabled the identification of novel gene signatures and cell heterogeneity in numerous tissues and diseases. Here we review the use of this technology for Fuchs' Endothelial Corneal Dystrophy (FECD). FECD is the most common indication for corneal endothelial transplantation worldwide. FECD is challenging to manage because it is genetically heterogenous, can be autosomal dominant or sporadic, and progress at different rates. Single-cell RNA sequencing has enabled the discovery of several FECD subtypes, each with associated gene signatures, and cell heterogeneity. Current FECD treatments are mainly surgical, with various Rho kinase (ROCK) inhibitors used to promote endothelial cell metabolism and proliferation following surgery. A range of emerging therapies for FECD including cell therapies, gene therapies, tissue engineered scaffolds, and pharmaceuticals are in preclinical and clinical trials. Unlike conventional disease management methods based on clinical presentations and family history, targeting FECD using scRNA-seq based precision-medicine has the potential to pinpoint the disease subtypes, mechanisms, stages, severities, and help clinicians in making the best decision for surgeries and the applications of therapeutics. In this review, we first discuss the feasibility and potential of using scRNA-seq in clinical diagnostics for FECD, highlight advances from the latest clinical treatments and emerging therapies for FECD, integrate scRNA-seq results and clinical notes from our FECD patients and discuss the potential of applying alternative therapies to manage these cases clinically.

A computational workflow to determine drug candidates alternative to aminoglycosides targeting the decoding center of E. coli ribosome

The global antibiotic resistance problem necessitates fast and effective approaches to finding novel inhibitors to treat bacterial infections. In this study, we propose a computational workflow to identify plausible high-affinity compounds from FDA-approved, investigational, and experimental libraries for the decoding center on the small subunit 30S of the E. coli ribosome. The workflow basically consists of two molecular docking calculations on the intact 30S, followed by molecular dynamics (MD) simulations coupled with MM-GBSA calculations on a truncated ribosome structure. The parameters used in the molecular docking suits, Glide and AutoDock Vina, as well as in the MD simulations with Desmond were carefully adjusted to obtain expected interactions for the ligand-rRNA complexes. A filtering procedure was followed, considering a fingerprint based on aminoglycoside's binding site on the 30S to obtain seven hit compounds either with different clinical usages or aminoglycoside derivatives under investigation, suggested for in vitro studies. The detailed workflow developed in this study promises an effective and fast approach for the estimation of binding free energies of large protein-RNA and ligand complexes.

Force-enhanced sensitive and specific detection of DNA-intercalative agents directly from microorganisms at single-molecule level

Microorganisms can produce a vast array of bioactive secondary metabolites, including DNA-intercalating agents like actinomycin D, doxorubicin, which hold great potential for cancer chemotherapy. However, discovering novel DNA-intercalating compounds remains challenging due to the limited sensitivity and specificity of conventional activity assays, which require large-scale fermentation and purification. Here, we introduced the single-molecule stretching assay (SMSA) directly to microbial cultures or extracts for discovering DNA-intercalating agents, even in trace amounts of microbial cultures (5 μl). We showed that the unique changes of dsDNA in contour length and overstretching transition enable the specific detection of intercalators from complex samples without the need for extensive purification. Applying force to dsDNA also enhanced the sensitivity by increasing both the binding affinity Ka and the quantity of ligands intercalation, thus allowing the detection of weak intercalators, which are often overlooked using traditional methods. We demonstrated the effectiveness of SMSA, identified two DNA intercalator-producing strains: Streptomyces tanashiensis and Talaromyces funiculosus, and isolated three DNA intercalators: medermycin, kalafungin and ligustrone B. Interestingly, both medermycin and kalafungin, classified as weak DNA intercalators (Ka ∼103 M-1), exhibited potent anti-cancer activity against HCT-116 cancer cells, with IC50 values of 52 ± 6 and 70 ± 7 nM, respectively.

M6A-modified lncRNA FAM83H-AS1 promotes colorectal cancer progression through PTBP1

LncRNA plays a crucial role in cancer progression and targeting, but it has been difficult to identify the critical lncRNAs involved in colorectal cancer (CRC) progression. We identified FAM83H-AS1 as a tumor-promoting associated lncRNA using 21 pairs of stage IV CRC tissues and adjacent normal tissues. In vitro and in vivo experiments revealed that knockdown of FAM83H-AS1 in CRC cells inhibited tumor proliferation and metastasis, and vice versa. M6A modification is critical for FAM83H-AS1 RNA stability through the writer METTL3 and the readers IGF2BP2/IGFBP3. PTBP1-an RNA binding protein-is responsible for the FAM83H-AS1 function in CRC. T4 (1770-2440 nt) and T5 (2440-2743 nt) on exon 4 of FAM83H-AS1 provide a platform for PTBP1 RRM2 interactions. Our results demonstrated that m6A modification dysregulated the FAM83H-AS1 oncogenic role by phosphorylated PTBP1 on its RNA splicing effect. In patient-derived xenograft models, ASO-FAM83H-AS1 significantly suppressed the growth of gastrointestinal (GI) tumors, not only CRC but also GC and ESCC. The combination of ASO-FAM83H-AS1 and oxaliplatin/cisplatin significantly suppressed tumor growth compared with treatment with either agent alone. Notably, there was pathological complete response in all these three GI cancers. Our findings suggest that FAM83H-AS1 targeted therapy would benefit patients primarily receiving platinum-based therapy in GI cancers.

Symmetry breaking of fluorophore binding to a G-quadruplex generates an RNA aptamer with picomolar KD

Fluorogenic RNA aptamer tags with high affinity enable RNA purification and imaging. The G-quadruplex (G4) based Mango (M) series of aptamers were selected to bind a thiazole orange based (TO1-Biotin) ligand. Using a chemical biology and reselection approach, we have produced a MII.2 aptamer-ligand complex with a remarkable set of properties: Its unprecedented KD of 45 pM, formaldehyde resistance (8% v/v), temperature stability and ligand photo-recycling properties are all unusual to find simultaneously within a small RNA tag. Crystal structures demonstrate how MII.2, which differs from MII by a single A23U mutation, and modification of the TO1-Biotin ligand to TO1-6A-Biotin achieves these results. MII binds TO1-Biotin heterogeneously via a G4 surface that is surrounded by a stadium of five adenosines. Breaking this pseudo-rotational symmetry results in a highly cooperative and homogeneous ligand binding pocket: A22 of the G4 stadium stacks on the G4 binding surface while the TO1-6A-Biotin ligand completely fills the remaining three quadrants of the G4 ligand binding face. Similar optimization attempts with MIII.1, which already binds TO1-Biotin in a homogeneous manner, did not produce such marked improvements. We use the novel features of the MII.2 complex to demonstrate a powerful optically-based RNA purification system.

Transcriptome-Wide, Unbiased Profiling of Ribonuclease Targeting Chimeras

Various approaches have been developed to target RNA and modulate its function with modes of action including binding and cleavage. Herein, we explored how small molecule binding is correlated with cleavage induced by heterobifunctional ribonuclease targeting chimeras (RiboTACs), where RNase L is recruited to cleave the bound RNA target, in a transcriptome-wide, unbiased fashion. Only a fraction of bound targets was cleaved by RNase L, induced by RiboTAC binding. Global analysis suggested that (i) cleaved targets generally form a region of stable structure that encompasses the small molecule binding site; (ii) cleaved targets have preferred RNase L cleavage sites nearby small molecule binding sites; (iii) RiboTACs facilitate a cellular interaction between cleaved targets and RNase L; and (iv) the expression level of the target influences the extent of cleavage observed. In one example, we converted a binder of LGALS1 (galectin-1) mRNA into a RiboTAC. In MDA-MB-231 cells, the binder had no effect on galectin-1 protein levels, while the RiboTAC cleaved LGALS1 mRNA, reduced galectin-1 protein abundance, and affected galectin-1-associated oncogenic cellular phenotypes. Using LGALS1, we further assessed additional factors including the length of the linker that tethers the two components of the RiboTAC, cellular uptake, and the RNase L-recruiting module on RiboTAC potency. Collectively, these studies may facilitate triangulation of factors to enable the design of RiboTACs.

Structure-Informed Design of an Ultra Bright RNA-activated Fluorophore

Fluorogenic RNAs such as the Mango aptamers are uniquely powerful tools for imaging RNA. A central challenge has been to develop brighter, more specific, and higher affinity aptamer-ligand systems for cellular imaging. Here, we report an ultra-bright fluorophore for the Mango II system discovered using a structure-informed, fragment-based small molecule microarray approach. The new dye, Structure informed, Array-enabled LigAnD 1 (SALAD1) exhibits 3.5-fold brighter fluorescence than TO1-Biotin and subnanomolar aptamer affinity. Improved performance comes solely from alteration of dye-RNA interactions, without alteration of the chromophore itself. Multiple high-resolution structures reveal a unique and specific binding mode for the new dye resulting from improved pocket occupancy, a more defined binding pose, and a novel bonding interaction with potassium. The dye notably improves in-cell confocal RNA imaging. This work provides both introduces a new RNA-activated fluorophore and also a powerful demonstration of how to leverage fragment-based ligand discovery against RNA targets.

Targeting and engineering long non-coding RNAs for cancer therapy

RNA therapeutics (RNATx) aim to treat diseases, including cancer, by targeting or employing RNA molecules for therapeutic purposes. Amongst the most promising targets are long non-coding RNAs (lncRNAs), which regulate oncogenic molecular networks in a cell type-restricted manner. lncRNAs are distinct from protein-coding genes in important ways that increase their therapeutic potential yet also present hurdles to conventional clinical development. Advances in genome editing, oligonucleotide chemistry, multi-omics and RNA engineering are paving the way for efficient and cost-effective lncRNA-focused drug discovery pipelines. In this Review, we present the emerging field of lncRNA therapeutics for oncology, with emphasis on the unique strengths and challenges of lncRNAs within the broader RNATx framework. We outline the necessary steps for lncRNA therapeutics to deliver effective, durable, tolerable and personalized treatments for cancer.

Fluorogenic RNA-Based Biosensors of Small Molecules: Current Developments, Uses, and Perspectives

Small molecules are highly relevant targets for detection and quantification. They are also used to diagnose and monitor the progression of disease and infectious processes and track the presence of contaminants. Fluorogenic RNA-based biosensors (FRBs) represent an appealing solution to the problem of detecting these targets. They combine the portability of molecular systems with the sensitivity and multiplexing capacity of fluorescence, as well as the exquisite ligand selectivity of RNA aptamers. In this review, we first present the different sensing and reporting aptamer modules currently available to design an FRB, together with the main methodologies used to discover modules with new specificities. We next introduce and discuss how both modules can be functionally connected prior to exploring the main applications for which FRB have been used. Finally, we conclude by discussing how using alternative nucleotide chemistries may improve FRB properties and further widen their application scope.

Out of the dark: the emerging roles of lncRNAs in pain

The dark genome, the nonprotein-coding part of the genome, is replete with long noncoding RNAs (lncRNAs). These functionally versatile transcripts, with specific temporal and spatial expression patterns, are critical gene regulators that play essential roles in health and disease. In recent years, FAAH-OUT was identified as the first lncRNA associated with an inherited human pain insensitivity disorder. Several other lncRNAs have also been studied for their contribution to chronic pain and genome-wide association studies are frequently identifying single nucleotide polymorphisms that map to lncRNAs. For a long time overlooked, lncRNAs are coming out of the dark and into the light as major players in human pain pathways and as potential targets for new RNA-based analgesic medicines.

Modulation of prion protein expression through cryptic splice site manipulation

Lowering expression of prion protein (PrP) is a well-validated therapeutic strategy in prion disease, but additional modalities are urgently needed. In other diseases, small molecules have proven capable of modulating pre-mRNA splicing, sometimes by forcing inclusion of cryptic exons that reduce gene expression. Here, we characterize a cryptic exon located in human PRNP's sole intron and evaluate its potential to reduce PrP expression through incorporation into the 5' untranslated region. This exon is homologous to exon 2 in nonprimate species but contains a start codon that would yield an upstream open reading frame with a stop codon prior to a splice site if included in PRNP mRNA, potentially downregulating PrP expression through translational repression or nonsense-mediated decay. We establish a minigene transfection system and test a panel of splice site alterations, identifying mutants that reduce PrP expression by as much as 78%. Our findings nominate a new therapeutic target for lowering PrP.

High-throughput sensitive screening of small molecule modulators of microexon alternative splicing using dual Nano and Firefly luciferase reporters

Disruption of alternative splicing frequently causes or contributes to human diseases and disorders. Consequently, there is a need for efficient and sensitive reporter assays capable of screening chemical libraries for compounds with efficacy in modulating important splicing events. Here, we describe a screening workflow employing dual Nano and Firefly luciferase alternative splicing reporters that affords efficient, sensitive, and linear detection of small molecule responses. Applying this system to a screen of ~95,000 small molecules identified compounds that stimulate or repress the splicing of neuronal microexons, a class of alternative exons often disrupted in autism and activated in neuroendocrine cancers. One of these compounds rescues the splicing of several analyzed microexons in the cerebral cortex of an autism mouse model haploinsufficient for Srrm4, a major activator of brain microexons. We thus describe a broadly applicable high-throughput screening system for identifying candidate splicing therapeutics, and a resource of small molecule modulators of microexons with potential for further development in correcting aberrant splicing patterns linked to human disorders and disease.

Structural Unfolding of G-Quadruplexes: From Small Molecules to Antisense Strategies

G-quadruplexes (G4s) are non-canonical nucleic acid secondary structures that have gathered significant interest in medicinal chemistry over the past two decades due to their unique structural features and potential roles in a variety of biological processes and disorders. Traditionally, research efforts have focused on stabilizing G4s, while in recent years, the attention has progressively shifted to G4 destabilization, unveiling new therapeutic perspectives. This review provides an in-depth overview of recent advances in the development of small molecules, starting with the controversial role of TMPyP4. Moreover, we described effective metal complexes in addition to G4-disrupting small molecules as well as good G4 stabilizing ligands that can destabilize G4s in response to external stimuli. Finally, we presented antisense strategies as a promising approach for destabilizing G4s, with a particular focus on 2'-OMe antisense oligonucleotide, peptide nucleic acid, and locked nucleic acid. Overall, this review emphasizes the importance of understanding G4 dynamics as well as ongoing efforts to develop selective G4-unfolding strategies that can modulate their biological function and therapeutic potential.

Comparative analysis of RNA 3D structure prediction methods: towards enhanced modeling of RNA-ligand interactions

Accurate RNA structure models are crucial for designing small molecule ligands that modulate their functions. This study assesses six standalone RNA 3D structure prediction methods-DeepFoldRNA, RhoFold, BRiQ, FARFAR2, SimRNA and Vfold2, excluding web-based tools due to intellectual property concerns. We focus on reproducing the RNA structure existing in RNA-small molecule complexes, particularly on the ability to model ligand binding sites. Using a comprehensive set of RNA structures from the PDB, which includes diverse structural elements, we found that machine learning (ML)-based methods effectively predict global RNA folds but are less accurate with local interactions. Conversely, non-ML-based methods demonstrate higher precision in modeling intramolecular interactions, particularly with secondary structure restraints. Importantly, ligand-binding site accuracy can remain sufficiently high for practical use, even if the overall model quality is not optimal. With the recent release of AlphaFold 3, we included this advanced method in our tests. Benchmark subsets containing new structures, not used in the training of the tested ML methods, show that AlphaFold 3's performance was comparable to other ML-based methods, albeit with some challenges in accurately modeling ligand binding sites. This study underscores the importance of enhancing binding site prediction accuracy and the challenges in modeling RNA-ligand interactions accurately.

Unraveling the complexity: Advanced methods in analyzing DNA, RNA, and protein interactions

Exploring the intricate interplay within and between nucleic acids, as well as their interactions with proteins, holds pivotal significance in unraveling the molecular complexities steering cancer initiation and progression. To investigate these interactions, a diverse array of highly specific and sensitive molecular techniques has been developed. The selection of a particular technique depends on the specific nature of the interactions. Typically, researchers employ an amalgamation of these different techniques to obtain a comprehensive and holistic understanding of inter- and intramolecular interactions involving DNA-DNA, RNA-RNA, DNA-RNA, or protein-DNA/RNA. Examining nucleic acid conformation reveals alternative secondary structures beyond conventional ones that have implications for cancer pathways. Mutational hotspots in cancer often lie within sequences prone to adopting these alternative structures, highlighting the importance of investigating intra-genomic and intra-transcriptomic interactions, especially in the context of mutations, to deepen our understanding of oncology. Beyond these intramolecular interactions, the interplay between DNA and RNA leads to formations like DNA:RNA hybrids (known as R-loops) or even DNA:DNA:RNA triplex structures, both influencing biological processes that ultimately impact cancer. Protein-nucleic acid interactions are intrinsic cellular phenomena crucial in both normal and pathological conditions. In particular, genetic mutations or single amino acid variations can alter a protein's structure, function, and binding affinity, thus influencing cancer progression. It is thus, imperative to understand the differences between wild-type (WT) and mutated (MT) genes, transcripts, and proteins. The review aims to summarize the frequently employed methods and techniques for investigating interactions involving nucleic acids and proteins, highlighting recent advancements and diverse adaptations of each technique.

Delivery Strategies of siRNA Therapeutics for Hair Loss Therapy

Therapeutic needs for hair loss are intended to find small interfering ribonucleic acid (siRNA) therapeutics for breakthrough. Since naked siRNA is restricted to meet a druggable target in clinic,, delivery systems are indispensable to overcome intrinsic and pathophysiological barriers, enhancing targetability and persistency to ensure safety, efficacy, and effectiveness. Diverse carriers repurposed from small molecules to siRNA can be systematically or locally employed in hair loss therapy, followed by the adoption of new compositions associated with structural and environmental modification. The siRNA delivery systems have been extensively studied via conjugation or nanoparticle formulation to improve their fate in vitro and in vivo. In this review, we introduce clinically tunable siRNA delivery systems for hair loss based on design principles, after analyzing clinical trials in hair loss and currently approved siRNA therapeutics. We further discuss a strategic research framework for optimized siRNA delivery in hair loss from the scientific perspective of clinical translation.

The Potential Links between lncRNAs and Drug Tolerance in Lung Adenocarcinoma

Lung cancer patients treated with targeted therapies frequently respond well but invariably relapse due to the development of drug resistance. Drug resistance is in part mediated by a subset of cancer cells termed "drug-tolerant persisters" (DTPs), which enter a dormant, slow-cycling state that enables them to survive drug exposure. DTPs also exhibit stem cell-like characteristics, broad epigenetic reprogramming, altered metabolism, and a mutagenic phenotype mediated by adaptive mutability. While several studies have characterised the transcriptional changes that lead to the altered phenotypes exhibited in DTPs, these studies have focused predominantly on protein coding changes. As long non-coding RNAs (lncRNAs) are also implicated in the phenotypes altered in DTPs, it is likely that they play a role in the biology of drug tolerance. In this review, we outline how lncRNAs may contribute to the key characteristics of DTPs, their potential roles in tolerance to targeted therapies, and the emergence of genetic resistance in lung adenocarcinoma.

SHAPEwarp-web: sequence-agnostic search for structurally homologous RNA regions across databases of chemical probing data

RNA molecules perform a variety of functions in cells, many of which rely on their secondary and tertiary structures. Chemical probing methods coupled with high-throughput sequencing have significantly accelerated the mapping of RNA structures, and increasingly large datasets of transcriptome-wide RNA chemical probing data are becoming available. Analogously to what has been done for decades in the protein world, this RNA structural information can be leveraged to aid the discovery of structural similarity to a known RNA (or RNA family), which, in turn, can inform about the function of transcripts. We have previously developed SHAPEwarp, a sequence-agnostic method for the search of structurally homologous RNA segments in a database of reactivity profiles derived from chemical probing experiments. In its original implementation, however, SHAPEwarp required substantial computational resources, even for moderately sized databases, as well as significant Linux command line know-how. To address these limitations, we introduce here SHAPEwarp-web, a user-friendly web interface to rapidly query large databases of RNA chemical probing data for structurally similar RNAs. Aside from featuring a completely rewritten core, which speeds up by orders of magnitude the search inside large databases, the web server hosts several high-quality chemical probing databases across multiple species. SHAPEwarp-web is available from https://shapewarp.incarnatolab.com.

Glioblastoma stem cell long non-coding RNAs: therapeutic perspectives and opportunities

Glioblastoma poses a formidable challenge among primary brain tumors: its tumorigenic stem cells, capable of self-renewal, proliferation, and differentiation, contribute substantially to tumor initiation and therapy resistance. These glioblastoma stem cells (GSCs), resembling conventional stem and progenitor cells, adopt pathways critical for tissue development and repair, promoting uninterrupted tumor expansion. Long non-coding RNAs (lncRNAs), a substantial component of the human transcriptome, have garnered considerable interest for their pivotal roles in normal physiological processes and cancer pathogenesis. They display cell- or tissue-specific expression patterns, and extensive investigations have highlighted their impact on regulating GSC properties and cellular differentiation, thus offering promising avenues for therapeutic interventions. Consequently, lncRNAs, with their ability to exert regulatory control over tumor initiation and progression, have emerged as promising targets for innovative glioblastoma therapies. This review explores notable examples of GSC-associated lncRNAs and elucidates their functional roles in driving glioblastoma progression. Additionally, we delved deeper into utilizing a 3D in vitro model for investigating GSC biology and elucidated four primary methodologies for targeting lncRNAs as potential therapeutics in managing glioblastoma.

Synthetic antibodies for accelerated RNA crystallography

RNA structure is crucial to a wide range of cellular processes. The intimate relationship between macromolecular structure and function necessitates the determination of high-resolution structures of functional RNA molecules. X-ray crystallography is the predominant technique used for macromolecular structure determination; however, solving RNA structures has been more challenging than their protein counterparts, as reflected in their poor representation in the Protein Data Bank (<1%). Antibody-assisted RNA crystallography is a relatively new technique that promises to accelerate RNA structure determination by employing synthetic antibodies (Fabs) as crystallization chaperones that are specifically raised against target RNAs. Antibody chaperones facilitate the formation of ordered crystal lattices by minimizing RNA flexibility and replacing unfavorable RNA-RNA contacts with contacts between chaperone molecules. Atomic coordinates of these antibody fragments can also be used as search models to obtain phase information during structure determination. Antibody-assisted RNA crystallography has enabled the structure determination of 15 unique RNA targets, including 11 in the last 6 years. In this review, I cover the historical development of antibody fragments as crystallization chaperones and their application to diverse RNA targets. I discuss how the first structures of antibody-RNA complexes informed the design of second-generation antibodies and led to the development of portable crystallization modules that have greatly reduced the uncertainties associated with RNA crystallography. Finally, I outline unexplored avenues that can increase the impact of this technology in structural biology research and discuss potential applications of antibodies as affinity reagents for interrogating RNA biology outside of their use in crystallography. This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes.

Targeting fusion oncoproteins in childhood cancers: challenges and future opportunities for developing therapeutics

Fusion oncoproteins are associated with childhood cancers and have proven challenging to target, aside from those that include kinases. As part of its efforts for targeting childhood cancers, the National Cancer Institute recently conducted a series on Novel Chemical Approaches for Targeting Fusion Oncoproteins. Key learnings on leading platforms and technologies that can be used to advance the development of molecular therapeutics that target fusion oncoproteins in childhood cancers are described. Recent breakthroughs in medicinal chemistry and chemical biology provide new ground and creative strategies to exploit for the development of targeted agents for improving outcomes against these recalcitrant cancers.

Structure of an RNA G-quadruplex from the West Nile virus genome

Potential G-quadruplex sites have been identified in the genomes of DNA and RNA viruses and proposed as regulatory elements. The genus Orthoflavivirus contains arthropod-transmitted, positive-sense, single-stranded RNA viruses that cause significant human disease globally. Computational studies have identified multiple potential G-quadruplex sites that are conserved across members of this genus. Subsequent biophysical studies established that some G-quadruplexes predicted in Zika and tickborne encephalitis virus genomes can form and known quadruplex binders reduced viral yields from cells infected with these viruses. The susceptibility of RNA to degradation and the variability of loop regions have made structure determination challenging. Despite these difficulties, we report a high-resolution structure of the NS5-B quadruplex from the West Nile virus genome. Analysis reveals two stacked tetrads that are further stabilized by a stacked triad and transient noncanonical base pairing. This structure expands the landscape of solved RNA quadruplex structures and demonstrates the diversity and complexity of biological quadruplexes. We anticipate that the availability of this structure will assist in solving further viral RNA quadruplexes and provides a model for a conserved antiviral target in Orthoflavivirus genomes.

Antisense RNA C9orf72 hexanucleotide repeat associated with amyotrophic lateral sclerosis and frontotemporal dementia forms a triplex-like structure and binds small synthetic ligand

The abnormal expansion of GGGGCC/GGCCCC hexanucleotide repeats (HR) in C9orf72 is associated with amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Structural polymorphisms of HR result in the multifactorial pathomechanism of ALS/FTD. Consequently, many ongoing studies are focused at developing therapies targeting pathogenic HR RNA. One of them involves small molecules blocking sequestration of important proteins, preventing formation of toxic nuclear foci. However, rational design of potential therapeutics is hindered by limited number of structural studies of RNA-ligand complexes. We determined the crystal structure of antisense HR RNA in complex with ANP77 ligand (1.1 Å resolution) and in the free form (0.92 and 1.5 Å resolution). HR RNA folds into a triplex structure composed of four RNA chains. ANP77 interacted with two neighboring single-stranded cytosines to form pseudo-canonical base pairs by adopting sandwich-like conformation and adjusting the position of its naphthyridine units to the helical twist of the RNA. In the unliganded structure, the cytosines formed a peculiar triplex i-motif, assembled by trans C•C+ pair and a third cytosine located at the Hoogsteen edge of the C•C+ pair. These results extend our knowledge of the structural polymorphisms of HR and can be used for rational design of small molecules targeting disease-related RNAs.

NMR structures of small molecules bound to a model of an RNA CUG repeat expansion

Trinucleotide repeat expansions fold into long, stable hairpins and cause a variety of incurable RNA gain-of-function diseases such as Huntington's disease, the myotonic dystrophies, and spinocerebellar ataxias. One approach for treating these diseases is to bind small molecules to the structured RNAs. Both Huntington's disease-like 2 (HDL2) and myotonic dystrophy type 1 (DM1) are caused by a r(CUG) repeat expansion, or r(CUG)exp. The RNA folds into a hairpin structure with a periodic array of 1×1 nucleotide UU loops (5'CUG/3'GUC; where the underlined nucleotides indicate the Us in the internal loop) that sequester various RNA-binding proteins (RBP) and hence the source of its gain-of-function. Here, we report NMR-refined structures of single 5'CUG/3'GUC motifs in complex with three different small molecules, a di-guandinobenzoate (1), a derivative of 1 where the guanidino groups have been exchanged for imidazole (2), and a quinoline with improved drug-like properties (3). These structures were determined using nuclear magnetic resonance (NMR) spectroscopy and simulated annealing with restrained molecular dynamics (MD). Compounds 1, 2, and 3 formed stacking and hydrogen bonding interactions with the 5'CUG/3'GUC motif. Compound 3 also formed van der Waals interactions with the internal loop. The global structure of each RNA-small molecule complexes retains an A-form conformation, while the internal loops are still dynamic but to a lesser extent compared to the unbound form. These results aid our understanding of ligand-RNA interactions and enable structure-based design of small molecules with improved binding affinity for and biological activity against r(CUG)exp. As the first ever reported structures of RNA r(CUG) repeats bound to ligands, these structures can enable virtual screening campaigns combined with machine learning assisted de novo design.

RNATACs: Multispecific small molecules targeting RNA by induced proximity

RNA-targeting small molecules (rSMs) have become an attractive modality to tackle traditionally undruggable proteins and expand the druggable space. Among many innovative concepts, RNA-targeting chimeras (RNATACs) represent a new class of multispecific, induced proximity small molecules that act by chemically bringing RNA targets into proximity with an endogenous RNA effector, such as a ribonuclease (RNase). Depending on the RNA effector, RNATACs can alter the stability, localization, translation, or splicing of the target RNA. Although still in its infancy, this new modality has the potential for broad applications in the future to treat diseases with high unmet need. In this review, we discuss potential advantages of RNATACs, recent progress in the field, and challenges to this cutting-edge technology.

Competitive Microarray Screening Reveals Functional Ligands for the DHX15 RNA G-Quadruplex

RNAs are increasingly considered valuable therapeutic targets, and the development of methods to identify and validate both RNA targets and ligands is more important than ever. Here, we utilized a bioinformatic approach to identify a hairpin-containing RNA G-quadruplex (rG4) in the 5' untranslated region (5' UTR) of DHX15 mRNA. By using a novel competitive small molecule microarray (SMM) approach, we identified a compound that specifically binds to the DHX15 rG4 (K D = 12.6 ± 1.0 μM). This rG4 directly impacts translation of a DHX15 reporter mRNA in vitro, and binding of our compound (F1) to the structure inhibits translation up to 57% (IC50 = 22.9 ± 3.8 μM). This methodology allowed us to identify and target the mRNA of a cancer-relevant helicase with no known inhibitors. Our target identification method and the novelty of our screening approach make our work informative for future development of novel small molecule cancer therapeutics for RNA targets.

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.

The Rise of Bacterial G-Quadruplexes in Current Antimicrobial Discovery

Antimicrobial resistance (AMR) is a silent critical issue that poses several challenges to health systems. While the discovery of novel antibiotics is currently stalled and prevalently focused on chemical variations of the scaffolds of available drugs, novel targets and innovative strategies are urgently needed to face this global threat. In this context, bacterial G-quadruplexes (G4s) are emerging as timely and profitable targets for the design and development of antimicrobial agents. Indeed, they are expressed in regulatory regions of bacterial genomes, and their modulation has been observed to provide antimicrobial effects with translational perspectives in the context of AMR. In this work, we review the current knowledge of bacterial G4s as well as their modulation by small molecules, including tools and techniques suitable for these investigations. Finally, we critically analyze the needs and future directions in the field, with a focus on the development of small molecules as bacterial G4s modulators endowed with remarkable drug-likeness.

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.

Assessment of Nucleobase Protomeric and Tautomeric States in Nucleic Acid Structures for Interaction Analysis and Structure-Based Ligand Design

With increasing interest in RNA as a therapeutic and a potential target, the role of RNA structures has become more important. Even slight changes in nucleobases, such as modifications or protomeric and tautomeric states, can have a large impact on RNA structure and function, while local environments in turn affect protonation and tautomerization. In this work, the application of empirical tools for pKa and tautomer prediction for RNA modifications was elucidated and compared with ab initio quantum mechanics (QM) methods and expanded toward macromolecular RNA structures, where QM is no longer feasible. In this regard, the Protonate3D functionality within the molecular operating environment (MOE) was expanded for nucleobase protomer and tautomer predictions and applied to reported examples of altered protonation states depending on the local environment. Overall, observations of nonstandard protomers and tautomers were well reproduced, including structural C+G:C(A) and A+GG motifs, several mismatches, and protonation of adenosine or cytidine as the general acid in nucleolytic ribozymes. Special cases, such as cobalt hexamine-soaked complexes or the deprotonation of guanosine as the general base in nucleolytic ribozymes, proved to be challenging. The collected set of examples shall serve as a starting point for the development of further RNA protonation prediction tools, while the presented Protonate3D implementation already delivers reasonable protonation predictions for RNA and DNA macromolecules. For cases where higher accuracy is needed, like following catalytic pathways of ribozymes, incorporation of QM-based methods can build upon the Protonate3D-generated starting structures. Likewise, this protonation prediction can be used for structure-based RNA-ligand design approaches.

Transcriptome-wide mapping of small-molecule RNA-binding sites in live cells

Small molecules targeting RNA can be valuable chemical probes and potential therapeutics. The interactions between small molecules, particularly fragments, and RNA, however, can be difficult to detect due to their modest affinities and short residence times. Here, we describe the procedures for mapping the molecular fingerprints of small molecules in vitro and throughout the human transcriptome in live cells, identifying both the targets bound by the small molecule and the sites of binding therein. For complete details on the use and execution of this protocol, please refer to 1.

Big data and deep learning for RNA biology

The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL studies in other fields, the successful implementation of DL in RB depends heavily on the effective utilization of large-scale datasets from public databases. In achieving this goal, data encoding methods, learning algorithms, and techniques that align well with biological domain knowledge have played pivotal roles. In this review, we provide guiding principles for applying these DL concepts to various problems in RB by demonstrating successful examples and associated methodologies. We also discuss the remaining challenges in developing DL models for RB and suggest strategies to overcome these challenges. Overall, this review aims to illuminate the compelling potential of DL for RB and ways to apply this powerful technology to investigate the intriguing biology of RNA more effectively.