A Massively Parallel Selection of Small Molecule-RNA Motif Binding Partners Informs Design of an Antiviral from Sequence

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.

MultiModRLBP: A Deep Learning Approach for Multi-Modal RNA-Small Molecule Ligand Binding Sites Prediction

This study aims to tackle the intricate challenge of predicting RNA-small molecule binding sites to explore the potential value in the field of RNA drug targets. To address this challenge, we propose the MultiModRLBP method, which integrates multi-modal features using deep learning algorithms. These features include 3D structural properties at the nucleotide base level of the RNA molecule, relational graphs based on overall RNA structure, and rich RNA semantic information. In our investigation, we gathered 851 interactions between RNA and small molecule ligand from the RNAglib dataset and RLBind training set. Unlike conventional training sets, this collection broadened its scope by including RNA complexes that have the same RNA sequence but change their respective binding sites due to structural differences or the presence of different ligands. This enhancement enables the MultiModRLBP model to more accurately capture subtle changes at the structural level, ultimately improving its ability to discern nuances among similar RNA conformations. Furthermore, we evaluated MultiModRLBP on two classic test sets, Test18 and Test3, highlighting its performance disparities on small molecules based on metal and non-metal ions. Additionally, we conducted a structural sensitivity analysis on specific complex categories, considering RNA instances with varying degrees of structural changes and whether they share the same ligands. The research results indicate that MultiModRLBP outperforms the current state-of-the-art methods on multiple classic test sets, particularly excelling in predicting binding sites for non-metal ions and instances where the binding sites are widely distributed along the sequence. MultiModRLBP also can be used as a potential tool when the RNA structure is perturbed or the RNA experimental tertiary structure is not available. Most importantly, MultiModRLBP exhibits the capability to distinguish binding characteristics of RNA that are structurally diverse yet exhibit sequence similarity. These advancements hold promise in reducing the costs associated with the development of RNA-targeted drugs.

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.

Structure-based virtual screening of unbiased and RNA-focused libraries to identify new ligands for the HCV IRES model system

Targeting RNA including viral RNAs with small molecules is an emerging field. The hepatitis C virus internal ribosome entry site (HCV IRES) is a potential target for translation inhibitor development to raise drug resistance mutation preparedness. Using RNA-focused and unbiased molecule libraries, a structure-based virtual screening (VS) by molecular docking and pharmacophore analysis was performed against the HCV IRES subdomain IIa. VS hits were validated by a microscale thermophoresis (MST) binding assay and a Förster resonance energy transfer (FRET) assay elucidating ligand-induced conformational changes. Ten hit molecules were identified with potencies in the high to medium micromolar range proving the suitability of structure-based virtual screenings against RNA-targets. Hit compounds from a 2-guanidino-quinazoline series, like the strongest binder, compound 8b with an EC50 of 61 μM, show low molecular weight, moderate lipophilicity and reduced basicity compared to previously reported IRES ligands. Therefore, it can be considered as a potential starting point for further optimization by chemical derivatization.

Targeting MicroRNAs with Small Molecules

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.

Probing Bioactive Chemical Space to Discover RNA-Targeted Small Molecules

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

Contemporary Progress and Opportunities in RNA-Targeted Drug Discovery

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

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

INTRODUCTION

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

AREAS COVERED

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

EXPERT OPINION

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

A blood-brain penetrant RNA-targeted small molecule triggers elimination of r(G4C2)exp in c9ALS/FTD via the nuclear RNA exosome

A hexanucleotide repeat expansion in intron 1 of the C9orf72 gene is the most common genetic cause of amyotrophic lateral sclerosis and frontotemporal dementia, or c9ALS/FTD. The RNA transcribed from the expansion, r(G4C2)exp, causes various pathologies, including intron retention, aberrant translation that produces toxic dipeptide repeat proteins (DPRs), and sequestration of RNA-binding proteins (RBPs) in RNA foci. Here, we describe a small molecule that potently and selectively interacts with r(G4C2)exp and mitigates disease pathologies in spinal neurons differentiated from c9ALS patient-derived induced pluripotent stem cells (iPSCs) and in two c9ALS/FTD mouse models. These studies reveal a mode of action whereby a small molecule diminishes intron retention caused by the r(G4C2)exp and allows the liberated intron to be eliminated by the nuclear RNA exosome, a multi-subunit degradation complex. Our findings highlight the complexity of mechanisms available to RNA-binding small molecules to alleviate disease pathologies and establishes a pipeline for the design of brain penetrant small molecules targeting RNA with novel modes of action in vivo.

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

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

Targeting RNA structures with small molecules

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

Rapid identification of polypeptide from carbapenem-resistant and susceptible Escherichia coli via Orbitrap-MS and pattern recognition analyses

A rapid and accurate analytical method was established to identify CREC and CSEC. Orbitrap-MS was used to detect the polypeptide of CREC and CSEC strains, and MS data were analyzed by pattern recognition analyses such as hierarchical cluster analysis (HCA), principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA). HCA based on the farthest distance method could well distinguish the two types of E. coli, and the cophenetic correlation coefficient of the farthest distance method was 0.901. Comparing the results of PCA, PLS-DA, and OPLS-DA, OPLS-DA exhibited the highest accuracy in predicting the CREC and CSEC strains. A total of 26 compounds were identified, and six of the compounds were the highly significant difference between the two types of strains. MS combined with pattern recognition can achieve a more comprehensive and efficient statistical analysis of complex biological samples.

Recent advancement in small molecules as HCV inhibitors

Hepatitis C virus (HCV) has caused a considerable threat to human health. To date, no treatments are without side effects. The proteins and RNA associated with HCV have specific functions during the viral life cycle. The vulnerabilities to virus are associated with those proteins or RNA. Thus, targeting these proteins and RNA is an efficient strategy to develop anti-HCV therapeutics. The treatment for HCV-infected patients has been greatly improved after the approval of direct-acting antivirals (DAAs). However, the cost of DAAs is unusually high, which adds to the economic burden on patients with chronic liver diseases. So far, many efforts have been devoted to the development of small molecules as novel HCV inhibitors. Investigations on the inhibitory activities of these small molecules have involved the target identification and the mechanism of action. In this mini-review, these small molecules divided into four kinds were elaborated, which focused on their targets and structural features. Furthermore, we raised the current challenges and promising prospects. This mini-review may facilitate the development of small molecules with improved activities targeting HCV based on the chemical scaffolds of HCV inhibitors.

Deep structural insights into RNA-binding disordered protein regions

Recent efforts to identify RNA binding proteins in various organisms and cellular contexts have yielded a large collection of proteins that are capable of RNA binding in the absence of conventional RNA recognition domains. Many of the recently identified RNA interaction motifs fall into intrinsically disordered protein regions (IDRs). While the recognition mode and specificity of globular RNA binding elements have been thoroughly investigated and described, much less is known about the way IDRs can recognize their RNA partners. Our aim was to summarize the current state of structural knowledge on the RNA binding modes of disordered protein regions and to propose a classification system based on their sequential and structural properties. Through a detailed structural analysis of the complexes that contain disordered protein regions binding to RNA, we found two major binding modes that represent different recognition strategies and, most likely, functions. We compared these examples with DNA binding disordered proteins and found key differences stemming from the nucleic acids as well as similar binding strategies, implying a broader substrate acceptance by these proteins. Due to the very limited number of known structures, we integrated molecular dynamics simulations in our study, whose results support the proposed structural preferences of specific RNA‐binding IDRs. To broaden the scope of our review, we included a brief analysis of RNA‐binding small molecules and compared their structural characteristics and RNA recognition strategies to the RNA‐binding IDRs.

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 > Small Molecule–RNA Interactions

Bioinformatic Searching for Optimal RNA Targets of Dimeric Compounds Informs Design of a MicroRNA-27a Inhibitor

Various studies have shown that selective molecular recognition of RNA targets by small molecules in cells, although challenging, is indeed possible. One facile strategy to enhance selectivity and potency is binding two or more sites within an RNA simultaneously with a single molecule. To simplify the identification of targets amenable to such a strategy, we informatically mined all human microRNA (miRNA) precursors to identify those with two proximal noncanonically paired sites. We selected oncogenic microRNA-27a (miR-27a) for further study as a lead molecule binds its Drosha site and a nearby internal loop, affording a homodimer that potently and specifically inhibits miR-27a processing in both breast cancer and prostate cancer cells. This reduction of mature miR-27a ameliorates an oncogenic cellular phenotype with nanomolar activity. Collectively, these studies demonstrate that synergistic bioinformatic and experimental approaches can define targets that may be more amenable to small molecule targeting than others.

A Small Molecule Exploits Hidden Structural Features within the RNA Repeat Expansion That Causes c9ALS/FTD and Rescues Pathological Hallmarks

The hexanucleotide repeat expansion GGGGCC [r(G₄C₂)^exp] within intron 1 of C9orf72 causes genetically defined amyotrophic lateral sclerosis and frontotemporal dementia, collectively named c9ALS/FTD. , the repeat expansion causes neurodegeneration via deleterious phenotypes stemming from r(G₄C₂)^exp RNA gain- and loss-of-function mechanisms. The r(G₄C₂)^exp RNA folds into both a hairpin structure with repeating 1 × 1 nucleotide GG internal loops and a G-quadruplex structure. Here, we report the identification of a small molecule (CB253) that selectively binds the hairpin form of r(G₄C₂)^exp. Interestingly, the small molecule binds to a previously unobserved conformation in which the RNA forms 2 × 2 nucleotide GG internal loops, as revealed by a series of binding and structural studies. NMR and molecular dynamics simulations suggest that the r(G₄C₂)^exp hairpin interconverts between 1 × 1 and 2 × 2 internal loops through the process of strand slippage. We provide experimental evidence that CB253 binding indeed shifts the equilibrium toward the 2 × 2 GG internal loop conformation, inhibiting mechanisms that drive c9ALS/FTD pathobiology, such as repeat-associated non-ATG translation formation of stress granules and defective nucleocytoplasmic transport in various cellular models of c9ALS/FTD.

Ribonuclease recruitment using a small molecule reduced c9ALS/FTD r(G4C2) repeat expansion in vitro and in vivo ALS models

[Figure: see text].

Deep learning integration of molecular and interactome data for protein-compound interaction prediction

Motivation

Virtual screening, which can computationally predict the presence or absence of protein–compound interactions, has attracted attention as a large-scale, low-cost, and short-term search method for seed compounds. Existing machine learning methods for predicting protein–compound interactions are largely divided into those based on molecular structure data and those based on network data. The former utilize information on proteins and compounds, such as amino acid sequences and chemical structures; the latter rely on interaction network data, such as protein–protein interactions and compound–compound interactions. However, there have been few attempts to combine both types of data in molecular information and interaction networks.

Results

We developed a deep learning-based method that integrates protein features, compound features, and multiple types of interactome data to predict protein–compound interactions. We designed three benchmark datasets with different difficulties and applied them to evaluate the prediction method. The performance evaluations show that our deep learning framework for integrating molecular structure data and interactome data outperforms state-of-the-art machine learning methods for protein–compound interaction prediction tasks. The performance improvement is statistically significant according to the Wilcoxon signed-rank test. This finding reveals that the multi-interactome data captures perspectives other than amino acid sequence homology and chemical structure similarity and that both types of data synergistically improve the prediction accuracy. Furthermore, experiments on the three benchmark datasets show that our method is more robust than existing methods in accurately predicting interactions between proteins and compounds that are unseen in training samples.

Recognition of small molecule-RNA binding sites using RNA sequence and structure

Motivation

RNA molecules become attractive small molecule drug targets to treat disease in recent years. Computer-aided drug design can be facilitated by detecting the RNA sites that bind small molecules. However, very limited progress has been reported for the prediction of small molecule–RNA binding sites.

Results

We developed a novel method RNAsite to predict small molecule–RNA binding sites using sequence profile- and structure-based descriptors. RNAsite was shown to be competitive with the state-of-the-art methods on the experimental structures of two independent test sets. When predicted structure models were used, RNAsite outperforms other methods by a large margin. The possibility of improving RNAsite by geometry-based binding pocket detection was investigated. The influence of RNA structure’s flexibility and the conformational changes caused by ligand binding on RNAsite were also discussed. RNAsite is anticipated to be a useful tool for the design of RNA-targeting small molecule drugs.

Availability and implementation

http://yanglab.nankai.edu.cn/RNAsite.

Supplementary information

Supplementary data are available at Bioinformatics online.

Frameworks for targeting RNA with small molecules

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

Design of small molecules targeting RNA structure from sequence

The design and discovery of small molecule medicines has largely been focused on a small number of druggable protein families. A new paradigm is emerging, however, in which small molecules exert a biological effect by interacting with RNA, both to study human disease biology and provide lead therapeutic modalities. Due to this potential for expanding target pipelines and treating a larger number of human diseases, robust platforms for the rational design and optimization of small molecules interacting with RNAs (SMIRNAs) are in high demand. This review highlights three major pillars in this area. First, the transcriptome-wide identification and validation of structured RNA elements, or motifs, within disease-causing RNAs directly from sequence is presented. Second, we provide an overview of high-throughput screening approaches to identify SMIRNAs as well as discuss the lead identification strategy, Inforna, which decodes the three-dimensional (3D) conformation of RNA motifs with small molecule binding partners, directly from sequence. An emphasis is placed on target validation methods to study the causality between modulating the RNA motif in vitro and the phenotypic outcome in cells. Third, emergent modalities that convert occupancy-driven mode of action SMIRNAs into event-driven small molecule chemical probes, such as RNA cleavers and degraders, are presented. Finally, the future of the small molecule RNA therapeutics field is discussed, as well as hurdles to overcome to develop potent and selective RNA-centric chemical probes.

Small molecule recognition of disease-relevant RNA structures

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

A New Approach to 3D Modeling of Inhomogeneous Populations of Viral Regulatory RNA

Tertiary structure (3D) is the physical context of RNA regulatory activity. Retroviruses are RNA viruses that replicate through the proviral DNA intermediate transcribed by hosts. Proviral transcripts form inhomogeneous populations due to variable structural ensembles of overlapping regulatory RNA motifs in the 5′-untranslated region (UTR), which drive RNAs to be spliced or translated, and/or dimerized and packaged into virions. Genetic studies and structural techniques have provided fundamental input constraints to begin predicting HIV 3D conformations in silico. Using SimRNA and sets of experimentally-determined input constraints of HIV^NL4-3 trans-activation responsive sequence (TAR) and pairings of unique-5′ (U5) with dimerization (DIS) or AUG motifs, we calculated a series of 3D models that differ in proximity of 5′-Cap and the junction of TAR and PolyA helices; configuration of primer binding site (PBS)-segment; and two host cofactors binding sites. Input constraints on U5-AUG pairings were most compatible with intramolecular folding of 5′-UTR motifs in energetic minima. Introducing theoretical constraints predicted metastable PolyA region drives orientation of 5′-Cap with TAR, U5 and PBS-segment helices. SimRNA and the workflow developed herein provides viable options to predict 3D conformations of inhomogeneous populations of large RNAs that have been intractable to conventional ensemble methods.

2-Amino-1,3-benzothiazole-6-carboxamide Preferentially Binds the Tandem Mismatch Motif r(UY:GA)

RNA helices are often punctuated with non-Watson-Crick features that may be targeted by chemical compounds, but progress toward identifying such compounds has been slow. We embedded a tandem UU:GA mismatch motif (5'-UG-3':5'-AU-3') within an RNA hairpin stem to identify compounds that bind the motif specifically. The three-dimensional structure of the RNA hairpin and its interaction with a small molecule identified through virtual screening are presented. The G-A mismatch forms a sheared pair upon which the U-U base pair stacks. The hydrogen bond configuration of the U-U pair involves O2 of the U adjacent to the G and O4 of the U adjacent to the A. The G-A and U-U pairs are flanked by A-U and G-C base pairs, respectively, and the stability of the mismatch is greater than when the motif is within the context of other flanking base pairs or when the 5'-3' orientation of the G-A and U-U pairs is swapped. Residual dipolar coupling constants were used to generate an ensemble of structures against which a virtual screen of 64480 small molecules was performed. The tandem mismatch was found to be specific for one compound, 2-amino-1,3-benzothiazole-6-carboxamide, which binds with moderate affinity but extends the motif to include the flanking A-U and G-C base pairs. The finding that the affinity for the UU:GA mismatch is dependent on flanking sequence emphasizes the importance of the motif context and potentially increases the number of small noncanonical features within RNA that can be specifically targeted by small molecules.

Target-Directed Approaches for Screening Small Molecules against RNA Targets

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

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

Vascular endothelial growth factor A (VEGFA) stimulates angiogenesis in human endothelial cells, and increasing its expression is a potential treatment for heart failure. Here, we report the design of a small molecule (TGP-377) that specifically and potently enhances VEGFA expression by the targeting of a non-coding microRNA that regulates its expression. A selection-based screen, named two-dimensional combinatorial screening, revealed preferences in small-molecule chemotypes that bind RNA and preferences in the RNA motifs that bind small molecules. The screening program increased the dataset of known RNA motif–small molecule binding partners by 20-fold. Analysis of this dataset against the RNA-mediated pathways that regulate VEGFA defined that the microRNA-377 precursor, which represses Vegfa messenger RNA translation, is druggable in a selective manner. We designed TGP-377 to potently and specifically upregulate VEGFA in human umbilical vein endothelial cells. These studies illustrate the power of two-dimensional combinatorial screening to define molecular recognition events between ‘undruggable’ biomolecules and small molecules, and the ability of sequence-based design to deliver efficacious structure-specific compounds.

Small molecule targeting of RNA structures in neurological disorders

Aberrant RNA structure and function operate in neurological disease progression and severity. As RNA contributes to disease pathology in a complex fashion, that is, via various mechanisms, it has become an attractive therapeutic target for small molecules and oligonucleotides. In this review, we discuss the identification of RNA structures that cause or contribute to neurological diseases as well as recent progress toward the development of small molecules that target them, including small molecule modulators of pre-mRNA splicing and RNA repeat expansions that cause microsatellite disorders such as Huntington's disease and amyotrophic lateral sclerosis. The use of oligonucleotide-based modalities is also discussed. There are key differences between small molecule and oligonucleotide targeting of RNA. The former targets RNA structure, while the latter prefers unstructured regions. Thus, some targets will be preferentially targeted by oligonucleotides and others by small molecules.

Progress toward the development of the small molecule equivalent of small interfering RNA

Given that many small molecules could bind to structured regions at sites that will not affect function, approaches that trigger degradation of RNA could provide a general way to affect biology. Indeed, targeted RNA degradation is an effective strategy to selectively and potently modulate biology. We describe several approaches to endow small molecules with the power to cleave RNAs. Central to these strategies is Inforna, which designs small molecules targeting RNA from human genome sequence. Inforna deduces the uniqueness of a druggable pocket, enables generation of hypotheses about functionality of the pocket, and defines on- and off-targets to drive compound optimization. RNA-binding compounds are then converted into cleavers that degrade the target directly or recruit an endogenous nuclease to do so. Cleaving compounds have significantly contributed to understanding and manipulating biological functions. Yet, there is much to be learned about how to affect human RNA biology with small molecules.

The mRNA encoding the JUND tumor suppressor detains nuclear RNA-binding proteins to assemble polysomes that are unaffected by mTOR

One long-standing knowledge gap is the role of nuclear proteins in mRNA translation. Nuclear RNA helicase A (DHX9/RHA) is necessary for the translation of the mRNAs of JUND (JunD proto-oncogene AP-1 transcription factor subunit) and HIV-1 genes, and nuclear cap-binding protein 1 (NCBP1)/CBP80 is a component of HIV-1 polysomes. The protein kinase mTOR activates canonical messenger ribonucleoproteins by post-translationally down-regulating the eIF4E inhibitory protein 4E-BP1. We posited here that NCBP1 and DHX9/RHA (RHA) support a translation pathway of JUND RNA that is independent of mTOR. We present evidence from reciprocal immunoprecipitation experiments indicating that NCBP1 and RHA both are components of messenger ribonucleoproteins in several cell types. Moreover, tandem affinity and RT-quantitative PCR results revealed that JUND mRNA is a component of a previously unknown ribonucleoprotein complex. Results from the tandem IP indicated that another component of the JUND-containing ribonucleoprotein complex is NCBP3, a recently identified ortholog of NCBP2/CBP20. We also found that NCBP1, NCBP3, and RHA, but not NCBP2, are components of JUND-containing polysomes. Mutational analysis uncovered two dsRNA-binding domains of RHA that are necessary to tether JUND-NCBP1/NCBP3 to polysomes. We also found that JUND translation is unaffected by inhibition of mTOR, unless RHA was down-regulated by siRNA. These findings uncover a noncanonical cap-binding complex consisting of NCBP1/NCBP3 and RHA substitutes for the eukaryotic translation initiation factors 4E and 4G and activates mTOR-independent translation of the mRNA encoding the tumor suppressor JUND.

Translation of the intrinsically disordered protein α-synuclein is inhibited by a small molecule targeting its structured mRNA

Many proteins are refractory to targeting because they lack small-molecule binding pockets. An alternative to drugging these proteins directly is to target the messenger (m)RNA that encodes them, thereby reducing protein levels. We describe such an approach for the difficult-to-target protein α-synuclein encoded by the SNCA gene. Multiplication of the SNCA gene locus causes dominantly inherited Parkinson's disease (PD), and α-synuclein protein aggregates in Lewy bodies and Lewy neurites in sporadic PD. Thus, reducing the expression of α-synuclein protein is expected to have therapeutic value. Fortuitously, the SNCA mRNA has a structured iron-responsive element (IRE) in its 5' untranslated region (5' UTR) that controls its translation. Using sequence-based design, we discovered small molecules that target the IRE structure and inhibit SNCA translation in cells, the most potent of which is named Synucleozid. Both in vitro and cellular profiling studies showed Synucleozid directly targets the α-synuclein mRNA 5' UTR at the designed site. Mechanistic studies revealed that Synucleozid reduces α-synuclein protein levels by decreasing the amount of SNCA mRNA loaded into polysomes, mechanistically providing a cytoprotective effect in cells. Proteome- and transcriptome-wide studies showed that the compound's selectivity makes Synucleozid suitable for further development. Importantly, transcriptome-wide analysis of mRNAs that encode intrinsically disordered proteins revealed that each has structured regions that could be targeted with small molecules. These findings demonstrate the potential for targeting undruggable proteins at the level of their coding mRNAs. This approach, as applied to SNCA, is a promising disease-modifying therapeutic strategy for PD and other α-synucleinopathies.

Mammalian RNA switches: Molecular rheostats in gene regulation, disease, and medicine

Alteration of RNA structure by environmental signals is a fundamental mechanism of gene regulation. For example, the riboswitch is a noncoding RNA regulatory element that binds a small molecule and causes a structural change in the RNA, thereby regulating transcription, splicing, or translation of an mRNA. The role of riboswitches in metabolite sensing and gene regulation in bacteria and other lower species was reported almost two decades ago, but riboswitches have not yet been discovered in mammals. An analog of the riboswitch, the protein-directed RNA switch (PDRS), has been identified as an important regulatory mechanism of gene expression in mammalian cells. RNA-binding proteins and microRNAs are two major executors of PDRS via their interaction with target transcripts in mammals. These protein-RNA interactions influence cellular functions by integrating environmental signals and intracellular pathways from disparate stimuli to modulate stability or translation of specific mRNAs. The discovery of a riboswitch in eukaryotes that is composed of a single class of thiamine pyrophosphate (TPP) suggests that additional ligand-sensing RNAs may be present to control eukaryotic or mammalian gene expression. In this review, we focus on protein-directed RNA switch mechanisms in mammals. We offer perspectives on the potential discovery of mammalian protein-directed and compound-dependent RNA switches that are related to human disease and medicine.

In vivo analysis of influenza A mRNA secondary structures identifies critical regulatory motifs

The influenza A virus (IAV) is a continuous health threat to humans as well as animals due to its recurring epidemics and pandemics. The IAV genome is segmented and the eight negative-sense viral RNAs (vRNAs) are transcribed into positive sense complementary RNAs (cRNAs) and viral messenger RNAs (mRNAs) inside infected host cells. A role for the secondary structure of IAV mRNAs has been hypothesized and debated for many years, but knowledge on the structure mRNAs adopt in vivo is currently missing. Here we solve, for the first time, the in vivo secondary structure of IAV mRNAs in living infected cells. We demonstrate that, compared to the in vitro refolded structure, in vivo IAV mRNAs are less structured but exhibit specific locally stable elements. Moreover, we show that the targeted disruption of these high-confidence structured domains results in an extraordinary attenuation of IAV replicative capacity. Collectively, our data provide the first comprehensive map of the in vivo structural landscape of IAV mRNAs, hence providing the means for the development of new RNA-targeted antivirals.

Predicting Positions of Bridging Water Molecules in Nucleic Acid-Ligand Complexes

Over the past two decades, interests in DNA and RNA as drug targets have been growing rapidly. Following the trends observed with protein drug targets, computational approaches for drug design have been developed for this new class of molecules. Our efforts toward the development of a universal docking program, Fitted, led us to focus on nucleic acids. Throughout the development of this docking program, efforts were directed toward displaceable water molecules which must be accurately located for optimal docking-based drug discovery. However, although there is a plethora of methods to place water molecules in and around protein structures, there is, to the best of our knowledge, no such fully automated method for nucleic acids, which are significantly more polar and solvated than proteins. We report herein a new method, Splash'Em (Solvation Potential Laid around Statistical Hydration on Entire Macromolecules) developed to place water molecules within the binding cavity of nucleic acids. This fast method was shown to have high agreement with water positions in crystal structures and will therefore provide essential information to medicinal chemists.

Targeting RNA with Small Molecules To Capture Opportunities at the Intersection of Chemistry, Biology, and Medicine

The biology of healthy and disease-affected cells is often mediated by RNA structures, desirable targets for small molecule chemical probes and lead medicines. Although structured regions are found throughout the transcriptome, some even with demonstrated functionality, human RNAs are considered recalcitrant to small molecule targeting. However, targeting structured regions with small molecules provides an important alternative to oligonucleotides that target sequence. In this Perspective, we describe challenges and progress in developing small molecules interacting with RNA (SMIRNAs) to capture their significant opportunities at the intersection of chemistry, biology, and medicine. Key to establishing a new paradigm in chemical biology and medicine is the development of methods to obtain, preferably by design, bioactive compounds that modulate RNA targets and companion methods that validate their direct effects in cells and pre-clinical models. While difficult, demonstration of direct target engagement in the complex cellular milieu, along with methods to establish modes of action, is required to push this field forward. We also describe frameworks for accelerated advancements in this burgeoning area, their implications, key new technologies for development of SMIRNAs, and milestones that have led to broader acceptance of RNA as a small molecule druggable target.

Challenges and current status of computational methods for docking small molecules to nucleic acids

Since the development of the first docking program in 1982, the use of docking-based in silico screening for potentially bioactive molecule discovery has become a common strategy in academia and pharmaceutical industry. Up until recently, application of docking programs has largely focused on drugs binding to proteins. However, with the discovery of promising drug targets in nucleic acids, including RNA riboswitches, DNA G-quadruplexes, and extended repeats in RNA, there has been greater interests in developing drugs for nucleic acids. However, due to major biochemical and physical differences in charges, binding pockets, and solvation, existing docking programs, developed for proteins, face difficulties when adopted directly for nucleic acids. In this review, we cover the current field of in silico docking to nucleic acids, available programs, as well as challenges faced in the field.

RNA Structural Differentiation: Opportunities with Pattern Recognition

Our awareness and appreciation of the many regulatory roles of RNA have dramatically increased in the past decade. This understanding, in addition to the impact of RNA in many disease states, has renewed interest in developing selective RNA-targeted small molecule probes. However, the fundamental guiding principles in RNA molecular recognition that could accelerate these efforts remain elusive. While high-resolution structural characterization can provide invaluable insight, examples of well-characterized RNA structures, not to mention small molecule:RNA complexes, remain limited. This Perspective provides an overview of the current techniques used to understand RNA molecular recognition when high-resolution structural information is unavailable. We will place particular emphasis on a new method, pattern recognition of RNA with small molecules (PRRSM), that provides rapid insight into critical components of RNA recognition and differentiation by small molecules as well as into RNA structural features.