Auswahl der wissenschaftlichen Literatur zum Thema „RNA-Targeted small molecules“

As the area of small molecules interacting with RNA advances, general routes to provide bioactive compounds are needed as ligands can bind RNA avidly to sites that will not affect function. Small-molecule targeted RNA degradation will thus provide a general route to affect RNA biology. A non–oligonucleotide-containing compound was designed from sequence to target the precursor to oncogenic microRNA-21 (pre–miR-21) for enzymatic destruction with selectivity that can exceed that for protein-targeted medicines. The compound specifically binds the target and contains a heterocycle that recruits and activates a ribonuclease to pre–miR-21 to substoichiometrically effect its cleavage and subsequently impede metastasis of breast cancer to lung in a mouse model. Transcriptomic and proteomic analyses demonstrate that the compound is potent and selective, specifically modulating oncogenic pathways. Thus, small molecules can be designed from sequence to have all of the functional repertoire of oligonucleotides, including inducing enzymatic degradation, and to selectively and potently modulate RNA function in vivo.

Abstract Interaction analysis between small molecules and RNA as well as structure determination of RNA–small molecule complexes will be the clues to search for compounds that bind to specific mRNA or non-coding RNA in drug discovery. In this study, the RNA-binding ability of a fluoroquinolone derivative, KG022, was examined against single-residue bulge-containing hairpin RNAs as RNA models. Nuclear magnetic resonance analysis indicated that KG022 interacts with the RNAs in the vicinity of the bulge residue, with preferring C and G as the bulge residues. The solution structures of the RNA–KG022 complexes showed that the KG022 binds to the RNAs at the bulge-out regions. Each substituent in KG022 interacts with specific position of RNAs around the bulge-out region probably contributing the specificity of the binding. This work provides a novel member for the RNA-targeted small molecules.

RNA molecules can fold into complex and stable 3D structures, allowing them to carry out important genetic, structural, and regulatory roles inside the cell. These complex structures often contain 3D pockets made up of secondary structural motifs that can be potentially targeted by small molecule ligands. Indeed, many RNA structures in PDB contain bound small molecules, and high-throughput experimental studies have generated a large number of interacting RNA and ligand pairs. There is considerable interest in developing small molecule lead compounds targeting viral RNAs or those RNAs implicated in neurological diseases or cancer. We hypothesize that RNAs that have similar secondary structural motifs may bind to similar small molecule ligands. Toward this goal, we established a database collecting RNA secondary structural motifs and bound small molecule ligands. We further developed a computational pipeline, which takes as input an RNA sequence, predicts its secondary structure, extracts structural motifs, and searches the database for similar secondary structure motifs and interacting small molecule. We demonstrated the utility of the server by querying α-synuclein mRNA 5′ UTR sequence and finding potential matches which were validated as correct. The server is publicly available at http://RNALigands.ccbr.utoronto.ca. The source code can also be downloaded at https://github.com/SaisaiSun/RNALigands.

MicroRNAs (miRs) have been implicated in numerous diseases, presenting an attractive target for the development of novel therapeutics. The various regulatory roles of miRs in cellular processes underscore the need for precise strategies. Recent advances in RNA research offer hope by enabling the identification of small molecules capable of selectively targeting specific disease-associated miRs. This understanding paves the way for developing small molecules that can modulate the activity of disease-associated miRs. Herein, we discuss the progress made in the field of drug discovery processes, transforming the landscape of miR-targeted therapeutics by small molecules. By leveraging various approaches, researchers can systematically identify compounds to modulate miR function, providing a more potent intervention either by inhibiting or degrading miRs. The implementation of these multidisciplinary approaches bears the potential to revolutionize treatments for diverse diseases, signifying a significant stride towards the targeting of miRs by precision medicine.

ABSTRACT A genetic approach utilizing the yeast Saccharomyces cerevisiae was used to identify the target of antifungal compounds. This analysis led to the identification of small molecule inhibitors of RNA polymerase (Pol) III from Saccharomyces cerevisiae. Three lines of evidence show that UK-118005 inhibits cell growth by targeting RNA Pol III in yeast. First, a dominant mutation in the g domain of Rpo31p, the largest subunit of RNA Pol III, confers resistance to the compound. Second, UK-118005 rapidly inhibits tRNA synthesis in wild-type cells but not in UK-118005 resistant mutants. Third, in biochemical assays, UK-118005 inhibits tRNA gene transcription in vitro by the wild-type but not the mutant Pol III enzyme. By testing analogs of UK-118005 in a template-specific RNA Pol III transcription assay, an inhibitor with significantly higher potency, ML-60218, was identified. Further examination showed that both compounds are broad-spectrum inhibitors, displaying activity against RNA Pol III transcription systems derived from Candida albicans and human cells. The identification of these inhibitors demonstrates that RNA Pol III can be targeted by small synthetic molecules.

Myotonic dystrophy type 1 (DM1) is an incurable neuromuscular disorder caused by an expanded CTG repeat that is transcribed into r(CUG)exp. The RNA repeat expansion sequesters regulatory proteins such as Muscleblind-like protein 1 (MBNL1), which causes pre-mRNA splicing defects. The disease-causing r(CUG)exp has been targeted by antisense oligonucleotides, CRISPR-based approaches, and RNA-targeting small molecules. Herein, we describe a designer small molecule, Cugamycin, that recognizes the structure of r(CUG)exp and cleaves it in both DM1 patient-derived myotubes and a DM1 mouse model, leaving short repeats of r(CUG) untouched. In contrast, oligonucleotides that recognize r(CUG) sequence rather than structure cleave both long and short r(CUG)-containing transcripts. Transcriptomic, histological, and phenotypic studies demonstrate that Cugamycin broadly and specifically relieves DM1-associated defects in vivo without detectable off-targets. Thus, small molecules that bind and cleave RNA have utility as lead chemical probes and medicines and can selectively target disease-causing RNA structures to broadly improve defects in preclinical animal models.

Gene expression can be regulated by transcriptional or post-transcriptional gene silencing. Recently, we described nuclear nascent RNA silencing that is mediated by Dicer-dependent tRNA-derived small RNA molecules. In addition to tRNA, RNA polymerase III also transcribes vault RNA, a component of the ribonucleoprotein complex vault. Here, we show that Dicer-dependent small vault RNA1-2 (svtRNA1-2) associates with Argonaute 2 (Ago2). Although endogenous vtRNA1-2 is present mostly in the cytoplasm, svtRNA1-2 localises predominantly in the nucleus. Furthermore, in Ago2 and Dicer knockdown cells, a subset of genes that are up-regulated at the nascent level were predicted to be targeted by svtRNA1-2 in the intronic region. Genomic deletion of vtRNA1-2 results in impaired cellular proliferation and the up-regulation of genes associated with cell membrane physiology and cell adhesion. Silencing activity of svtRNA1-2 molecules is dependent on seed-plus-complementary-paired hybridisation features and the presence of a 5-nucleotide loop protrusion on target RNAs. Our data reveal a role of Dicer-dependent svtRNA1-2, possessing unique molecular features, in modulation of the expression of membrane-associated proteins at the nascent RNA level.

Given the therapeutic interest of targeting TDP-43, this review focuses on the current landscape of strategies, ranging from biologics to small molecules, that directly target TDP-43. Regions targeted are shown on the 3D structure of RNA-bound TDP-43.

Abstract The MYC gene, with its oncogenic potential, has long been a formidable challenge in conventional drug discovery efforts, and its critical role in cancer progression and resistance has underscored the need for innovative therapeutic strategies. Here we demonstrate the capabilities of the Ribometrix RNA-targeting platform to modulate the c-MYC mRNA with small molecules with the aim of reducing c-MYC protein levels. Using our comprehensive platform of RNA-targeting drug discovery tools and analyses including chemical probing, structure modeling, high-purity RNA production, high-throughput screening, and biophysical characterization, we evaluated the potential to directly target c-MYC mRNA using small molecules. Our analysis revealed six high-confidence structured elements throughout the c-MYC mRNA expected to harbor tertiary structures amenable to drug-like ligand binding. Leveraging the multifaceted chemical probing and structure modeling components of our platform, we confirmed that our in vitro-transcribed RNA screening constructs adopt the same structures found in endogenous cellular c-MYC transcripts. After large-scale in vitro RNA preparation, we subjected four of these RNA elements to high-throughput screens of chemically diverse drug-like libraries using mass spectrometry affinity-selection that identified multiple chemical series with sub-micromolar affinity. We validated binding affinity using orthogonal methods including isothermal titration calorimetry and NMR. To eliminate pan-binding ligands, we evaluated of selectivity against a panel of non-target mRNA structures. Importantly, these compounds lead to rapid (4 hr) reduction of MYC protein levels in a small cell lung cancer cell line, DMS-273, with no cellular toxicity at 72 hr suggesting an on-target effect. Employing our suite of chemical probing tools, we confirmed that compounds from multiple series engage the c-MYC mRNA in cells. Medicinal chemistry efforts are ongoing to increase potency and define the precise mechanism of action in clinically relevant models. The discovery of these c-MYC mRNA-binding small molecules not only validates the utility of the Ribometrix RNA-targeted small molecule discovery platform but also showcases its potential in tackling traditionally 'undruggable' targets and provides a promising avenue for developing novel anti-cancer therapies. As we learn more about the intricacies of c-MYC mRNA biology and further refine effective small molecules, our results provide practical insights into previously-unknown vulnerabilities of MYC and present tangible opportunities for advancing targeted cancer therapies. Citation Format: Matthew J. Smola, Krista Marran, Sarah E. Thompson, Brittani Patterson, Roheeth K. Pavana, Caleb Sutherland, Jessica A. Sorrentino, Katherine D. Warner. Leveraging an RNA-targeting platform for the discovery of cell-active c-MYC mRNA-binding small molecules [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 680.

As research uncovers the underpinnings of cancer biology, new targeted therapies have been developed. Many of these therapies are small molecules, such as kinase inhibitors, that target specific proteins; however, only 1% of the genome encodes for proteins and only a subset of these proteins has ‘druggable’ active binding sites. In recent decades, RNA therapeutics have gained popularity due to their ability to affect targets that small molecules cannot. Additionally, they can be manufactured more rapidly and cost-effectively than small molecules or recombinant proteins. RNA therapeutics can be synthesised chemically and altered quickly, which can enable a more personalised approach to cancer treatment. Even though a wide range of RNA therapeutics are being developed for various indications in the oncology setting, none has reached the clinic to date. One of the main reasons for this is attributed to the lack of safe and effective delivery systems for this type of therapeutic. This review focuses on current strategies to overcome these challenges and enable the clinical utility of these novel therapeutic agents in the cancer clinic.

Les molécules d'ARN sont devenues des cibles thérapeutiques majeures, et le ciblage par petites molécules se révèle particulièrement prometteur. Cependant, malgré leur potentiel, le domaine est encore en développement, avec un nombre limité de médicaments spécifiquement conçus pour l'ARN. La flexibilité intrinsèque de l'ARN, bien qu'elle constitue un obstacle, introduit des opportunités thérapeutiques que les outils computationnels actuels ne parviennent pas pleinement à exploiter malgré leur prédisposition. Le projet de cette thèse est de construire un cadre computationnel plus complet pour la conception rationnelle de composés ciblant l'ARN. La première étape pour toute approche structure-based est l'analyse des connaissances structurales disponibles. Cependant, il manquait une base de données complète, organisée et régulièrement mise à jour pour la communauté scientifique. Pour combler cette lacune, j'ai créé HARIBOSS, une base de données de toutes les structures expérimentalement déterminées des complexes ARN-petites molécules extraites de la base de données PDB. Chaque entrée de HARIBOSS, accessible via une interface web dédiée (https://hariboss.pasteur.cloud), est annotée avec les propriétés physico-chimiques des ligands et des poches d'ARN. Cette base de données constamment mise à jour facilitera l'exploration des composés drug-like liées à l'ARN, l'analyse des propriétés des ligands et des poches, et en fin de compte, le développement de stratégies in silico pour identifier des petites molécules ciblant l'ARN. Lors de sa sortie, il a été possible de souligner que la majorité des poches de liaison à l'ARN ne conviennent pas aux interactions avec des molécules drug-like. Cela est dû à une hydrophobicité moindre et une exposition au solvant accrue par rapport aux sites de liaison des protéines. Cependant, cela résulte d'une représentation statique de l'ARN, qui peut ne pas capturer pleinement les mécanismes d'interaction avec de petites molécules. Il était nécessaire d'introduire des techniques computationnelles avancées pour une prise en compte efficace de la flexibilité de l'ARN. Dans cette direction, j'ai mis en œuvre SHAMAN, une technique computationnelle pour identifier les sites de liaison potentiels des petites molécules dans les ensembles structuraux d'ARN. SHAMAN permet d'explorer le paysage conformationnel de l'ARN cible par des simulations de dynamique moléculaire atomistique. Dans le même temps, il identifie efficacement les poches d'ARN en utilisant de petits fragments dont l'exploration de la surface de l'ARN est accélérée par des techniques d'enhanced sampling. Dans un ensemble de données comprenant divers riboswitches structurés ainsi que de petits ARN viraux flexibles, SHAMAN a précisément localisé des poches résolues expérimentalement, les classant les régions d’interaction préférées. Notamment, la précision de SHAMAN est supérieure à celle d'autres outils travaillant sur des structures statiques d'ARN dans un scénario réaliste de découverte de médicaments où seules les structures apo de la cible sont disponibles. Cela confirme que SHAMAN est une plateforme robuste pour les futures initiatives de conception de médicaments ciblant l'ARN avec de petites molécules, en particulier compte tenu de sa pertinence potentielle dans les campagnes de criblage virtuel. Dans l'ensemble, ma recherche contribue à améliorer notre compréhension et notre utilisation de l'ARN en tant que cible pour les médicaments à petites molécules, ouvrant la voie à des stratégies thérapeutiques plus efficaces dans ce domaine en évolution
RNA molecules have recently gained huge relevance as therapeutic targets. The direct targeting of RNA with small molecule drugs emerges for its wide applicability to different classes of RNAs. Despite this potential, the field is still in its infancy and the number of available RNA-targeted drugs remains limited. A major challenge is constituted by the highly flexible and elusive nature of the RNA targets. Nonetheless, RNA flexibility also presents unique opportunities that could be leveraged to enhance the efficacy and selectivity of newly designed therapeutic agents. To this end, computer-aided drug design techniques emerge as a natural and comprehensive approach. However, existing tools do not fully account for the flexibility of the RNA. The project of this PhD work aims to build a computational framework toward the rational design of compounds targeting RNA. The first essential step for any structure-based approach is the analysis of the available structural knowledge. However, a comprehensive, curated, and regularly updated repository for the scientific community was lacking. To fill this gap, I curated the creation of HARIBOSS ("Harnessing RIBOnucleic acid - Small molecule Structures"), a database of all the experimentally-determined structures of RNA-small molecule complexes retrieved from the PDB database. HARIBOSS is available via a dedicated web interface (https://hariboss.pasteur.cloud), and is regularly updated with all the structures resolved by X-ray, NMR, and cryo-EM, in which ligands with drug-like properties interact with RNA molecules. Each HARIBOSS entry is annotated with physico-chemical properties of ligands and RNA pockets. HARIBOSS repository, constantly updated, will facilitate 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. In coincidence of its release, it was possible to highlight that the majority of RNA binding pockets are unsuitable for interactions with drug-like molecules, attributed to the lower hydrophobicity and increased solvent exposure compared to protein binding sites. However, this emerges from a static depiction of RNA, which may not fully capture their interaction mechanisms with small molecules. In a broader perspective, it was necessary to introduce more advanced computational techniques for an effective accounting of RNA flexibility in the characterization of potential binding sites. In this direction, I implemented SHAMAN, a computational technique to identify potential small-molecule binding sites in RNA structural ensembles. SHAMAN enables the exploration of the target RNA conformational landscape through atomistic molecular dynamics. Simultaneously, it efficiently identifies RNA pockets using small probe compounds whose exploration of the RNA surface is accelerated by enhanced-sampling techniques. In a benchmark encompassing diverse large, structured riboswitches as well as small, flexible viral RNAs, SHAMAN accurately located experimentally resolved pockets, ranking them as preferred probe hotspots. Notably, SHAMAN accuracy was superior to other tools working on static RNA structures in the realistic drug discovery scenario where only apo structures of the target are available. This establishes SHAMAN as a robust platform for future drug design endeavors targeting RNA with small molecules, especially considering its potential applicability in virtual screening campaigns. Overall, my research contributed to enhance our understanding and utilization of RNA as a target for small molecule drugs, paving the way for more effective drug design strategies in this evolving field

Abstract A diverse set of small RNAs is involved in the regulation of genome organization and gene expression in plants. These regulatory sRNAs play a central role for RNA in evolution and ontogeny in complex organisms, including forest tree species, providers of indispensable ecosystem services. RNA interference is a process that inhibits gene expression by double-stranded RNA and thus causes the degradation of target messenger RNA molecules. Targeted gene silencing by RNAi has been utilized in various crop plants in order to enhance their characteristics. For forest tree species, most of the successful RNAi modification has been conducted in poplar. Over the past 20 years, successful RNAi-mediated suppression of gene expression has been achieved with a variety of economically important traits. Moreover, the stability of RNAi-mediated transgene suppression has been confirmed in field-grown poplars. In this chapter, we describe examples of successful RNAi applications mainly in poplar but also provide some information about application of RNAi in pest control in forest tree species. Advantages and disadvantages of this technology with respect to the particular features of forest tree species will be discussed.

Abstract A diverse set of small RNAs is involved in the regulation of genome organization and gene expression in plants. These regulatory sRNAs play a central role for RNA in evolution and ontogeny in complex organisms, including forest tree species, providers of indispensable ecosystem services. RNA interference is a process that inhibits gene expression by double-stranded RNA and thus causes the degradation of target messenger RNA molecules. Targeted gene silencing by RNAi has been utilized in various crop plants in order to enhance their characteristics. For forest tree species, most of the successful RNAi modification has been conducted in poplar. Over the past 20 years, successful RNAi-mediated suppression of gene expression has been achieved with a variety of economically important traits. Moreover, the stability of RNAi-mediated transgene suppression has been confirmed in field-grown poplars. In this chapter, we describe examples of successful RNAi applications mainly in poplar but also provide some information about application of RNAi in pest control in forest tree species. Advantages and disadvantages of this technology with respect to the particular features of forest tree species will be discussed.

Historically, small molecules have targeted double helical DNA through intercalation and minor groove complexes. Initially, small molecules to target RNA were focused on RNAs involved in protein biosynthesis. Now, many more compounds to target diverse RNA structures have been designed or discovered. This coincides with the exciting discovery that, while only a small amount of the genome is transcribed into RNA for protein synthesis, much of the genome is used to synthesize a variety of non-coding RNAs (ncRNAs). These have important cell functions, including the involvement of ncRNAs in disease development when they undergo mutation, moreover, their dysregulation has been found to be relevant not only to tumorigenesis, but also to neurological, cardiovascular, developmental and other diseases. Although it has been known for some time that four guanine bases can associate into a tetraplex, our knowledge of how these tetraplexes associate into a variety of four-stranded DNA quadruplexes has greatly advanced. A wide variety of biological functions for these quadruplexes have been discovered. They have a major role in cancer that makes them exciting targets for development of new anticancer agents. At the beginning of our search for new small molecule targets a key structure are the four-way junction and other junction types. The design of new agents to attack these targets will provide many new insights into molecular recognition studies of nucleic acids. The new compounds generated will help us to define the cellular functions of nucleic acid structures and will provide new ideas for the development of nucleic-acid targeted therapeutics.

Small molecules that enter chemical reactions as a substrate inside or outside the cell, or that emerge as a result of the reactions are known as metabolites. So far, only a fraction of the existing metabolites, numbering in the millions, have yet been identified, and even a smaller portion have been measured. Two main technologies are commonly used for metabolite analysis: analytes, which are usually separated by liquid or gas chromatography, are examined with the aid of either mass spectrometry or nuclear magnetic resonance. With the understanding that metabolites play roles in gene regulation by influencing epigenetic mechanisms, the interest in this field has grown and the field of ‘metabolomics’ emerged, akin to the ‘omics’ approaches applied to the examination of DNA, RNA, and proteins. In addition to the ‘shotgun’ approach, in which a large number of metabolites are measured simultaneously, targeted approaches that monitor the changes of a small number of metabolites under various conditions are also frequently used. In this section, the issues that should be considered in every metabolomics study, regardless of the methodological approach adopted, are discussed; examples of the use of metabolomics approaches, especially in the field of cancer metabolism, are presented; and the importance of big data and biobanks are emphasized.

This chapter explains the RNA interference (RNAi) machinery that regulates post-transcriptional gene silencing. The RNAi technology is considered a vital tool in basic molecular and cellular genetic research, functional genomics, gene expression profiling, drug discovery, prospective disease targeting, and therapies. The chapter describes how the two main classes of small regulatory RNAs-short interfering RNA (siRNA) and microRNA (miRNA)-are generated and how they silence gene expression. It gives an overview of the RNAi pathway and looks at the two main approaches currently used to silence gene expression in vitro , namely, the siRNA technology and the short hairpin RNA (shRNA) technology. Moreover, it discusses the advantages and limitations of the two. The chapter also explores the therapeutic possibilities available using targeted gene silencing.

The development of sequencing of the next generation (NGS) technology has facilitated the study of cancer. Massive parallel sequencing made possible by NGS provides for the most thorough genomic analysis of tumors. Different NGS methods focus on DNA and RNA analysis. Genome on the whole part, whole-exome, and targeted DNA sequencing are several classes of sequencing that concentrate on a subdivision of genetic factors that may be related to a certain condition. Alternative gene-spliced transcripts, small and long non-coding RNAs, mutations/single-nucleotide polymorphisms, post-transcriptional alterations, gene fusions and variations in genetic expression are all more easily found using RNA sequencing. The majority of NGS implementations are in the realm of cancer research, but recently, NGS technology has revolutionized molecular diagnosis of cancer because of the many benefits it provides over conventional approaches.

Targeted molecular therapies have significantly improved the therapeutic management of advanced lung cancer. The possibility of detecting lung cancer at an early stage is surely an important event in order to improve patient survival. Liquid biopsy has recently demonstrated its clinical utility in advanced non-small cell lung cancer (NSCLC) as a possible alternative to tissue biopsy for non-invasive evaluation of specific genomic alterations, thus providing prognostic and predictive information when the tissue is difficult to find or the material is not sufficient for the numerous investigations to be carried out. Several biosources from liquid biopsy, including free circulating tumor DNA (ctDNA) and RNA (ctRNA), circulating tumor cells (CTCs), exosomes and tumor-educated platelets (TEPs), have been extensively studied for their potential role in the diagnosis of lung cancer. This chapter proposes an overview of the circulating biomarkers assessed for the detention and monitoring of disease evolution with a particular focus on cell-free DNA, on the techniques developed to perform the evaluation and on the results of the most recent studies. The text will analyze in greater depth the liquid biopsy applied to the clinical practice of the management of NSCLC.