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

Structure of Essential RNA Regulatory Elements in the West Nile Virus 3'-Terminal Stem Loop

Flaviviruses, such as West Nile and Dengue Virus, pose a significant and growing threat to global health. Central to the flavivirus life cycle are highly structured 5'- and 3'-untranslated regions (UTRs), which harbor conserved cis-acting RNA elements critical for viral replication and host adaptation. Despite their essential roles, detailed molecular insights into these RNA elements have been limited. By employing nuclear magnetic resonance (NMR) spectroscopy in conjunction with SAXS experiments, we determined the three-dimensional structure of the West Nile Virus (WNV) 3'-terminal stem-loop core, a highly conserved element critical for viral genome cyclization and replication. Single nucleotide mutations at several sites within this RNA abolish the ability of the virus to replicate. These critical sites are located within a short 18-nucleotide hairpin stem, a substructure notable for its conformational flexibility, while the adjoining main stem-loop adopts a well-defined extended helix interrupted by three non-Watson-Crick pairs. This study enhances our understanding of several metastable RNA structures that play key roles in regulating the flavivirus lifecycle, and thereby also opens up potential new avenues for the development of antivirals targeting these conserved RNA structures. In particular, the structure we observe suggests that the plastic junction between the small hairpin and the tail of the longer stem-loop could provide a binding pocket for small molecules, for example potentially stabilizing the RNA in a conformation which hinders the conformational rearrangements critical for viral replication.

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.

Reducing CRISPR-Cas9 off-target effects by optically controlled chemical modifications of guide RNA

A photocatalytic click chemistry approach, offering a significant advancement over conventional methods in RNA function modulation is described. This innovative method, utilizing light-activated small molecules, provides a high level of precision and control in RNA regulation, particularly effective in intricate cellular processes. By applying this strategy to CRISPR-Cas9 gene editing, we demonstrate its effectiveness in enhancing gene editing specificity and markedly reducing off-target effects. Our approach employs a vinyl ether modification in RNA, which activated under visible light with a phenanthrenequinone derivative, creating a CRISPR-OFF switch that precisely regulates CRISPR system activity. This method not only represents an advancement in genomic interventions but also offers broad applications in gene regulation, paving the way for safer and more reliable gene editing in therapeutic genomics.

KHDRBS3 facilitates self-renewal and temozolomide resistance of glioblastoma cell lines

Glioblastoma is a deadly tumor which possesses glioblastoma stem cell populations involved in temozolomide (TMZ) resistance. To gain insight into the mechanisms of self-renewing and therapy-resistant cancer stem cells, subcellular proteomics was utilized to identify proteins whose expression is enriched in U251-derived glioblastoma stem-like cells. The KH RNA Binding Domain Containing, Signal Transduction Associated 3, KHDRBS3, was successfully identified as a gene up-regulated in the cancer stem cell population compared with its differentiated derivatives. Depletion of KHDRBS3 by RNA silencing led to a decrease in cell proliferation, neurosphere formation, migration, and expression of genes involved in glioblastoma stemness. Importantly, TMZ sensitivity can be induced by the gene knockdown. Collectively, our results highlight KHDRBS3 as a novel factor associated with self-renewal of glioblastoma stem-like cells and TMZ resistance. As a consequence, targeting KHDRBS3 may help eradicate glioblastoma stem-like cells.

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.

Disulfide Tethering to Map Small Molecule Binding Sites Transcriptome-wide

We report the development of Tether-seq, a transcriptome-wide screen to probe RNA-small molecule interactions using disulfide tethering. This technique uses s4U metabolic labeling to provide sites for reversible and covalent attachment of small molecule disulfides to the transcriptome. By screening under reducing conditions, we identify interactions that are stabilized by binding over those driven by the reactivity of the RNA sites. When applied to cellular RNA, Tether-seq with a disulfide analogue of risdiplam, an FDA-approved drug that targets RNA to treat spinal muscular atrophy (SMA), revealed a number of potential binding sites, most prominently at a site within the cytochrome C oxidase 1 (COX1) transcript. Structure probing by SHAPE-MaP revealed a structured motif and confirmed binding to the lead molecule. This work demonstrates that these screens have the power to identify binding sites throughout the transcriptome and provide invaluable insight into the thermodynamic properties that define small molecule binding.

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

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

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.

Identifying small-molecules binding sites in RNA conformational ensembles with SHAMAN

The rational targeting of RNA with small molecules is hampered by our still limited understanding of RNA structural and dynamic properties. Most in silico tools for binding site identification rely on static structures and therefore cannot face the challenges posed by the dynamic nature of RNA molecules. Here, we present SHAMAN, a computational technique to identify potential small-molecule binding sites in RNA structural ensembles. SHAMAN enables exploring the conformational landscape of RNA with atomistic molecular dynamics simulations and at the same time identifying RNA pockets in an efficient way with the aid of probes and enhanced-sampling techniques. In our benchmark composed of large, structured riboswitches as well as small, flexible viral RNAs, SHAMAN successfully identifies all the experimentally resolved pockets and ranks them among the most favorite probe hotspots. Overall, SHAMAN sets a solid foundation for future drug design efforts targeting RNA with small molecules, effectively addressing the long-standing challenges in the field.

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.

Biomarkers in Thyroid Cancer: Emerging Opportunities from Non-Coding RNAs and Mitochondrial Space

Thyroid cancer diagnosis primarily relies on imaging techniques and cytological analyses. In cases where the diagnosis is uncertain, the quantification of molecular markers has been incorporated after cytological examination. This approach helps physicians to make surgical decisions, estimate cancer aggressiveness, and monitor the response to treatments. Despite the availability of commercial molecular tests, their widespread use has been hindered in our experience due to cost constraints and variability between them. Thus, numerous groups are currently evaluating new molecular markers that ultimately will lead to improved diagnostic certainty, as well as better classification of prognosis and recurrence. In this review, we start reviewing the current preoperative testing methodologies, followed by a comprehensive review of emerging molecular markers. We focus on micro RNAs, long non-coding RNAs, and mitochondrial (mt) signatures, including mtDNA genes and circulating cell-free mtDNA. We envision that a robust set of molecular markers will complement the national and international clinical guides for proper assessment of the disease.

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.

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.

Advancements in clinical RNA therapeutics: Present developments and prospective outlooks

RNA molecules have emerged as promising clinical therapeutics due to their ability to target "undruggable" proteins or molecules with high precision and minimal side effects. Nevertheless, the primary challenge in RNA therapeutics lies in rapid degradation and clearance from systemic circulation, the inability to traverse cell membranes, and the efficient intracellular delivery of bioactive RNA molecules. In this review, we explore the implications of RNAs in diseases and provide a chronological overview of the development of RNA therapeutics. Additionally, we summarize the technological advances in RNA-screening design, encompassing various RNA databases and design platforms. The paper then presents an update on FDA-approved RNA therapeutics and those currently undergoing clinical trials for various diseases, with a specific emphasis on RNA medicine and RNA vaccines.

Large-scale analysis of small molecule-RNA interactions using multiplexed RNA structure libraries

The large-scale analysis of small-molecule binding to diverse RNA structures is key to understanding the required interaction properties and selectivity for developing RNA-binding molecules toward RNA-targeted therapies. Here, we report a new system for performing the large-scale analysis of small molecule-RNA interactions using a multiplexed pull-down assay with RNA structure libraries. The system profiled the RNA-binding landscapes of G-clamp and thiazole orange derivatives, which recognizes an unpaired guanine base and are good probes for fluorescent indicator displacement (FID) assays, respectively. We discuss the binding preferences of these molecules based on their large-scale affinity profiles. In addition, we selected combinations of fluorescent indicators and different ranks of RNA based on the information and screened for RNA-binding molecules using FID. RNAs with high- and intermediate-rank RNA provided reliable results. Our system provides fundamental information about small molecule-RNA interactions and facilitates the discovery of novel RNA-binding molecules.

Aminothiazolone Inhibitors Disrupt the Protein-RNA Interaction of METTL16 and Modulate the m6A RNA Modification

Targeting RNA-binding and modifying proteins via small molecules to modulate post-transcriptional modifications have emerged as a new frontier for chemical biology and therapeutic research. One such RNA-binding protein that regulates the most prevalent eukaryotic RNA modification, N6-methyladenosine (m6A), is the methyltransferase-like protein 16 (METTL16), which plays an oncogenic role in cancers by cofunctioning with other nucleic acid-binding proteins. To date, no potent small-molecule inhibitor of METTL16 or modulator interfering with the METTL16-RNA interaction has been reported and validated, highlighting the unmet need to develop such small molecules to investigate the METTL16-involved regulatory network. Herein, we described the identification of a series of first-in-class aminothiazolone METTL16 inhibitors via a discovery pipeline that started with a fluorescence-polarization (FP)-based screening. Structural optimization of the initial hit yielded inhibitors, such as compound 45, that showed potent single-digit micromolar inhibition activity against the METTL16-RNA binding. The identified aminothiazolone inhibitors can be useful probes to elucidate the biological function of METTL16 upon perturbation and evaluate the therapeutic potential of METTL16 inhibition via small molecules at the post-transcriptional level.

Adenine Methylation Enhances the Conformational Flexibility of an RNA Hairpin Tetraloop

The N6-methyladenosine modification is one of the most abundant post-transcriptional modifications in ribonucleic acid (RNA) molecules. Using molecular dynamics simulations and alchemical free-energy calculations, we studied the structural and energetic implications of incorporating this modification in an adenine mononucleotide and an RNA hairpin structure. At the mononucleotide level, we found that the syn configuration is more favorable than the anti configuration by 2.05 ± 0.15 kcal/mol. The unfavorable effect of methylation was due to the steric overlap between the methyl group and a nitrogen atom in the purine ring. We then probed the effect of methylation in an RNA hairpin structure containing an AUCG tetraloop, which is recognized by a "reader" protein (YTHDC1) to promote transcriptional silencing of long noncoding RNAs. While methylation had no significant conformational effect on the hairpin stem, the methylated tetraloop showed enhanced conformational flexibility compared to the unmethylated tetraloop. The increased flexibility was associated with the outward flipping of two bases (A6 and U7) which formed stacking interactions with each other and with the C8 and G9 bases in the tetraloop, leading to a conformation similar to that in the RNA/reader protein complex. Therefore, methylation-induced conformational flexibility likely facilitates RNA recognition by the reader protein.

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

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

Monitoring host-pathogen interactions using chemical proteomics

With the rapid emergence and the dissemination of microbial resistance to conventional chemotherapy, the shortage of novel antimicrobial drugs has raised a global health threat. As molecular interactions between microbial pathogens and their mammalian hosts are crucial to establish virulence, pathogenicity, and infectivity, a detailed understanding of these interactions has the potential to reveal novel therapeutic targets and treatment strategies. Bidirectional molecular communication between microbes and eukaryotes is essential for both pathogenic and commensal organisms to colonise their host. In particular, several devastating pathogens exploit host signalling to adjust the expression of energetically costly virulent behaviours. Chemical proteomics has emerged as a powerful tool to interrogate the protein interaction partners of small molecules and has been successfully applied to advance host-pathogen communication studies. Here, we present recent significant progress made by this approach and provide a perspective for future studies.

RNA G-quadruplex in functional regulation of noncoding RNA: Challenges and emerging opportunities

G-quadruplexes (G4s) are stable, noncanonical structures formed in guanine (G)-rich sequences of DNA/RNA. G4 structures are reported to play a regulatory role in various cellular processes and, recently, a considerable number of studies have attributed new biological functions to these structures, especially in RNA. Noncoding RNA (ncRNA), which does not translate into a functional protein, is widely expressed and has been shown to play a key role in shaping cellular activity. There has been growing evidence of G4 formation in several ncRNA classes, and it has been identified as a key part for diverse biological functions and physio-pathological contexts in neurodegenerative diseases and cancer. This review discusses RNA G4s (rG4s) in ncRNA, focusing on the molecular mechanism underlying its function. This review also aims to highlight potential and emerging opportunities to identify and target the rG4s in ncRNA to understand its function and, ultimately, treat many diseases.

A computational method for small molecule-RNA binding sites identification by utilizing position specificity and complex network information

Some computational methods have been given for small molecule-RNA binding site identification due to that it plays a significant role in revealing biology function researches. However, it is still challenging to design an accurate model, especially for MCC. We designed a feature extraction technology from two aspects (position specificity and complex network information). Specifically, complex network was employed to express the space topological structure and sequence position information for improving prediction effect. Then, the features fused position specificity and complex network information were input into random forest classifier for model construction. The AUC of 88.22%, 77.92% and 81.46% were obtained on three independent datasets (RB19, CS71, RB78). Compared with the existing method, the best MCC were obtained on three datasets, which were 8.19%, 0.59% and 4.35% higher than the state-of-the-art prediction methods, respectively. The outstanding performances show that our method is a powerful tool to identify RNA binding sites, helping to the design RNA-targeting small molecule drugs. The data and resource codes are available at https://github.com/Kangxiaoneuq/PCN_RNAsite.

RNet: a network strategy to predict RNA binding preferences

Determining the RNA binding preferences remains challenging because of the bottleneck of the binding interactions accompanied by subtle RNA flexibility. Typically, designing RNA inhibitors involves screening thousands of potential candidates for binding. Accurate binding site information can increase the number of successful hits even with few candidates. There are two main issues regarding RNA binding preference: binding site prediction and binding dynamical behavior prediction. Here, we propose one interpretable network-based approach, RNet, to acquire precise binding site and binding dynamical behavior information. RNetsite employs a machine learning-based network decomposition algorithm to predict RNA binding sites by analyzing the local and global network properties. Our research focuses on large RNAs with 3D structures without considering smaller regulatory RNAs, which are too small and dynamic. Our study shows that RNetsite outperforms existing methods, achieving precision values as high as 0.701 on TE18 and 0.788 on RB9 tests. In addition, RNetsite demonstrates remarkable robustness regarding perturbations in RNA structures. We also developed RNetdyn, a distance-based dynamical graph algorithm, to characterize the interface dynamical behavior consequences upon inhibitor binding. The simulation testing of competitive inhibitors indicates that RNetdyn outperforms the traditional method by 30%. The benchmark testing results demonstrate that RNet is highly accurate and robust. Our interpretable network algorithms can assist in predicting RNA binding preferences and accelerating RNA inhibitor design, providing valuable insights to the RNA research community.

Optimization of a Protein-Targeted Medicine into an RNA-Specific Small Molecule

Protein-targeted small molecule medicines often bind RNAs and affect RNA-mediated pathways in cells. Historically, small molecule engagement and modulation of RNA have not been considered in medicine development; however, RNA should be considered both a potential on- and off-target. Kinase inhibitors have emecrged as common RNA binders with dovitinib, a classic receptor tyrosine kinase (RTK) inhibitor, inhibiting RTKs and the biogenesis of oncogenic microRNA-21 through direct engagement. In this study, we use knowledge of the molecular recognition of both protein and RNA targets by dovitinib to design molecules that specifically inhibit the RNA target but lack activity against canonical protein targets in cells. As it is now becoming apparent that RNA can be both an on- and off-target for small molecule medicines, this study lays a foundation to use design principles to maximize desired compound activity while minimizing off-target effects.

Pervasive transcriptome interactions of protein-targeted drugs

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

Small molecule-mediated targeting of microRNAs for drug discovery: Experiments, computational techniques, and disease implications

Small molecules have been providing medical breakthroughs for human diseases for more than a century. Recently, identifying small molecule inhibitors that target microRNAs (miRNAs) has gained importance, despite the challenges posed by labour-intensive screening experiments and the significant efforts required for medicinal chemistry optimization. Numerous experimentally-verified cases have demonstrated the potential of miRNA-targeted small molecule inhibitors for disease treatment. This new approach is grounded in their posttranscriptional regulation of the expression of disease-associated genes. Reversing dysregulated gene expression using this mechanism may help control dysfunctional pathways. Furthermore, the ongoing improvement of algorithms has allowed for the integration of computational strategies built on top of laboratory-based data, facilitating a more precise and rational design and discovery of lead compounds. To complement the use of extensive pharmacogenomics data in prioritising potential drugs, our previous work introduced a computational approach based on only molecular sequences. Moreover, various computational tools for predicting molecular interactions in biological networks using similarity-based inference techniques have been accumulated in established studies. However, there are a limited number of comprehensive reviews covering both computational and experimental drug discovery processes. In this review, we outline a cohesive overview of both biological and computational applications in miRNA-targeted drug discovery, along with their disease implications and clinical significance. Finally, utilizing drug-target interaction (DTIs) data from DrugBank, we showcase the effectiveness of deep learning for obtaining the physicochemical characterization of DTIs.

Spirocyclic Chromenopyrazole Inhibitors Disrupting the Interaction between the RNA-Binding Protein LIN28 and Let-7

Small-molecule inhibitors of the RNA-binding and regulating protein LIN28 have the potential to be developed as chemical probes for biological perturbation and as therapeutic candidates. Reported small molecules disrupting the interaction between LIN28 and let-7 miRNA suffer from moderate to weak inhibitory activity and flat structure-activity relationship, which hindered the development of next-generation LIN28 inhibitors that warrant further evaluations. We report herein the identification of new LIN28 inhibitors utilizing a spirocyclization strategy based on a chromenopyrazole scaffold. Representative compounds 2-5 showed potent in vitro inhibitory activity against LIN28-let-7 interaction and single-digit micromolar potency in inhibiting the proliferation of LIN28-expressing JAR cancer cells. The spirocyclic compound 5 incorporated a position that is amenable for functional group appendage and further structural modifications. The binding mode of compound 5 with the LIN28 cold shock domain was rationalized via a molecular docking analysis.

Chromenopyrazole-Peptide Conjugates as Small-Molecule Based Inhibitors Disrupting the Protein-RNA Interaction of LIN28-let-7

Targeting the protein-RNA interaction of LIN28 and let-7 is a promising strategy for the development of novel anticancer therapeutics. However, a limited number of small-molecule inhibitors disrupting the LIN28-let-7 interaction with potent efficacy are available. Herein, we developed a novel LIN28-inhibiting strategy by targeting selective hotspot amino acids at the LIN28-let-7 binding interface with small-molecule-based bifunctional conjugates. Starting from reported small-molecule LIN28 inhibitors, we identified a feasible linker-attachment position after performing a structure-activity relationship exploration based on the LIN28-targeting chromenopyrazoles. In parallel, a virtual alanine scan identified hotspot residues at the protein-RNA binding interface, based on which we designed a set of peptides to enhance the interaction with the identified hotspot residues. Conjugation of the tailor-designed peptides with linker-attached chromenopyrazoles yielded a series of bifunctional small-molecule-peptide conjugates, represented by compound 83 (PH-223), as a new LIN28-targeting chemical modality. Our result demonstrated an unexplored rational design approach using bifunctional conjugates to target protein-RNA interactions.

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.

Conformational dynamics of RNA G4C2 and G2C4 repeat expansions causing ALS/FTD using NMR and molecular dynamics studies

G4C2 and G2C4 repeat expansions in chromosome 9 open reading frame 72 (C9orf72) are the most common cause of genetically defined amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), or c9ALS/FTD. The gene is bidirectionally transcribed, producing G4C2 repeats [r(G4C2)exp] and G2C4 repeats [r(G2C4)exp]. The c9ALS/FTD repeat expansions are highly structured, and structural studies showed that r(G4C2)exp predominantly folds into a hairpin with a periodic array of 1 × 1 G/G internal loops and a G-quadruplex. A small molecule probe revealed that r(G4C2)exp also adopts a hairpin structure with 2 × 2 GG/GG internal loops. We studied the conformational dynamics adopted by 2 × 2 GG/GG loops using temperature replica exchange molecular dynamics (T-REMD) and further characterized the structure and underlying dynamics using traditional 2D NMR techniques. These studies showed that the loop's closing base pairs influence both structure and dynamics, particularly the configuration adopted around the glycosidic bond. Interestingly, r(G2C4) repeats, which fold into an array of 2 × 2 CC/CC internal loops, are not as dynamic. Collectively, these studies emphasize the unique sensitivity of r(G4C2)exp to small changes in stacking interactions, which is not observed in r(G2C4)exp, providing important considerations for further principles in structure-based drug design.

RNA editing: Expanding the potential of RNA therapeutics

RNA therapeutics have had a tremendous impact on medicine, recently exemplified by the rapid development and deployment of mRNA vaccines to combat the COVID-19 pandemic. In addition, RNA-targeting drugs have been developed for diseases with significant unmet medical needs through selective mRNA knockdown or modulation of pre-mRNA splicing. Recently, RNA editing, particularly antisense RNA-guided adenosine deaminase acting on RNA (ADAR)-based programmable A-to-I editing, has emerged as a powerful tool to manipulate RNA to enable correction of disease-causing mutations and modulate gene expression and protein function. Beyond correcting pathogenic mutations, the technology is particularly well suited for therapeutic applications that require a transient pharmacodynamic effect, such as the treatment of acute pain, obesity, viral infection, and inflammation, where it would be undesirable to introduce permanent alterations to the genome. Furthermore, transient modulation of protein function, such as altering the active sites of enzymes or the interface of protein-protein interactions, opens the door to therapeutic avenues ranging from regenerative medicine to oncology. These emerging RNA-editing-based toolsets are poised to broadly impact biotechnology and therapeutic applications. Here, we review the emerging field of therapeutic RNA editing, highlight recent laboratory advancements, and discuss the key challenges on the path to clinical development.

Influence of Mg2+ Distribution on the Stability of Folded States of the Twister Ribozyme Revealed Using Grand Canonical Monte Carlo and Generative Deep Learning Enhanced Sampling

Metal ions, particularly magnesium ions (Mg2+), play a role in stabilizing the tertiary structures of RNA molecules. Theoretical models and experimental techniques show that metal ions can change RNA dynamics and how it transitions through different stages of folding. However, the specific ways in which metal ions contribute to the formation and stabilization of RNA's tertiary structure are not fully understood at the atomic level. Here, we combined oscillating excess chemical potential Grand Canonical Monte Carlo (GCMC) and metadynamics to bias toward the sampling of unfolded states using reaction coordinates generated by machine learning allowing for examination of Mg2+-RNA interactions that contribute to stabilizing folded states of the pseudoknot found in the Twister ribozyme. GCMC is used to sample diverse ion distributions around the RNA with deep learning applied to iteratively generate system-specific reaction coordinates to maximize conformational sampling during metadynamics simulations. Results from 6 μs simulations performed on 9 individual systems indicate that Mg2+ ions play a crucial role in stabilizing the three-dimensional (3D) structure of the RNA by stabilizing specific interactions of phosphate groups or phosphate groups and bases of neighboring nucleotides. While many phosphates are accessible to interactions with Mg2+, it is observed that multiple, specific interactions are required to sample conformations close to the folded state; coordination of Mg2+ at individual specific sites facilitates sampling of folded conformations though unfolding ultimately occurs. It is only when multiple specific interactions occur, including the presence of specific inner-shell cation interactions linking two nucleotides, that conformations close to the folded state are stable. While many of the identified Mg2+ interactions are observed in the X-ray crystal structure of Twister, the present study suggests two new Mg2+ ion sites in the Twister ribozyme that contribute to stabilization. In addition, specific interactions with Mg2+ are observed that destabilize the local RNA structure, a process that may facilitate the folding of RNA into its correct structure.

Programming inactive RNA-binding small molecules into bioactive degraders

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

Group I Intron as a Potential Target for Antifungal Compounds: Development of a Trans-Splicing High-Throughput Screening Strategy

The search for safe and efficient new antifungal compounds for agriculture has led to more efforts in finding new modes of action. This involves the discovery of new molecular targets, including coding and non-coding RNA. Rarely found in plants and animals but present in fungi, group I introns are of interest as their complex tertiary structure may allow selective targeting using small molecules. In this work, we demonstrate that group I introns present in phytopathogenic fungi have a self-splicing activity in vitro that can be adapted in a high-throughput screening to find new antifungal compounds. Ten candidate introns from different filamentous fungi were tested and one group ID intron found in F. oxysporum showed high self-splicing efficiency in vitro. We designed the Fusarium intron to act as a trans-acting ribozyme and used a fluorescence-based reporter system to monitor its real time splicing activity. Together, these results are opening the way to study the druggability of such introns in crop pathogen and potentially discover small molecules selectively targeting group I introns in future high-throughput screenings.

Targeting RNA with small molecules: lessons learned from Xist RNA

Although more than 98% of the human genome is noncoding, nearly all drugs on the market target one of about 700 disease-related proteins. However, an increasing number of diseases are now being attributed to noncoding RNA and the ability to target them would vastly expand the chemical space for drug development. We recently devised a screening strategy based upon affinity-selection mass spectrometry and succeeded in identifying bioactive compounds for the noncoding RNA prototype, Xist. One such compound, termed X1, has drug-like properties and binds specifically to the RepA motif of Xist in vitro and in vivo. Small-angle X-ray scattering analysis reveals that X1 changes the conformation of RepA in solution, thereby explaining the displacement of cognate interacting protein factors (PRC2 and SPEN) and inhibition of X-chromosome inactivation. In this Perspective, we discuss lessons learned from these proof-of-concept experiments and suggest that RNA can be systematically targeted by drug-like compounds to disrupt RNA structure and function.

PSL Chemical Biology Symposia Third Edition: A Branch of Science in its Explosive Phase

This symposium is the third PSL (Paris Sciences & Lettres) Chemical Biology meeting (2016, 2019, 2023) held at Institut Curie. This initiative originally started at Institut de Chimie des Substances Naturelles (ICSN) in Gif-sur-Yvette (2013, 2014), under the directorship of Professor Max Malacria, with a strong focus on chemistry. It was then continued at the Institut Curie (2015) covering a larger scope, before becoming the official PSL Chemical Biology meeting. This latest edition was postponed twice for the reasons that we know. This has given us the opportunity to invite additional speakers of great standing. This year, Institut Curie hosted around 300 participants, including 220 on site and over 80 online. The pandemic has had, at least, the virtue of promoting online meetings, which we came to realize is not perfect but has its own merits. In particular, it enables those with restricted time and resources to take part in events and meetings, which can now accommodate unlimited participants. We apologize to all those who could not attend in person this time due to space limitation at Institut Curie.

A Small-Molecule Probe with a Dual Function of miRNA Inhibition and Target identification

By virtue of their key roles in pathologies, miRNAs represent a promising class of therapeutic targets. While high-fidelity small-molecule modulators of miRNAs can be identified via high-throughput screening using cellular reporter systems, their modes of action are elusive due to the lack of proper tools. Here, we report a small-molecule probe, 1 a, that is capable of elucidating its biological target along miRNA inhibition. Derived from norathyriol, a nature product, 1 a possessed a bioorthogonal alkyne moiety for subsequent labeling via copper-catalyzed azide-alkyne cycloaddition chemistry. We demonstrated that 1 a inhibited a panel of different miRNAs by blocking their loading onto argonaute 2 (AGO2), which is the key protein responsible for miRNA function. With the alkyne handle, we successfully identified AGO2 as an intracellular target of 1 a. Therefore, this work presents a novel small-molecule tool for suppressing and probing miRNA regulatory pathways.

Discovery and validation of bladder cancer related excreted nucleosides biomarkers by dilution approach in cell culture supernatant and urine using UHPLC-MS/MS

The exploration of nucleoside changes in human biofluids has profound potential for cancer diagnosis. Herein, we developed a rapid methodology to quantify 17 nucleosides by UHPLC-MS/MS. Five pairs of isomers were successfully separated within 8 min. The ME was mostly eliminated by sample dilution folds of 1000 for urine and 40 for CCS. The optimized method was firstly applied to screen potential nucleoside biomarkers in CCS by comprising bladder cancer cell lines (5637 and T24) and normal human bladder cell line SV-HUC-1 together with student's t-test and OPLS-DA. Nucleosides with significant differences in the supernatant of urine samples were also uncovered comparing BCa with the non-tumor group, as well as a comparison of BCa recurrence group with the non-recurrence group. By intersecting the differential nucleosides in CCS and urine supernatant, and then further confirmed using validation sets, the combination of m³C and m¹A with AUC of 0.775 was considered as a potential biomarker for bladder cancer diagnosis. A panel of m³C, m¹A, m¹G, and m²₂G was defined as potential biomarkers for bladder cancer prognosis with an AUC of 0.819. Above all, this method provided a new perspective for diagnosis and recurrence monitoring of bladder cancer. SIGNIFICANCE: The exploration of nucleoside changes in body fluids has profound potential for the diagnosis and elucidation of the pathogenesis of cancer. In this study, we developed a rapid methodology for the simultaneous quantitative determination of 17 nucleosides in the supernatant of cells and urine samples using UHPLC-MS/MS to discover and validate bladder cancer related excreted nucleoside biomarkers. The results of this paper provide a new strategy for diagnosis and postoperative recurrence monitoring of bladder cancer and provide theoretical support for the exploration of its pathogenesis.

Application of Molecular Dynamics to Expand Docking Program's Exploratory Capabilities and to Evaluate Its Predictions

Recognition of the growing importance of RNA as a target for therapeutic or diagnostic ligands brings the importance of computational predictions of docking poses to such receptors to the forefront. Most docking programs have been optimized for protein targets, based on a relatively rich pool of known docked protein structures. Unfortunately, despite progress, numbers of known docked RNA complexes are low and the accuracy of the computational predictions trained on those inadequate samples lags behind that achieved for proteins. Compared to proteins, RNA structures generally have fewer docking pockets, have less diverse electrostatic surfaces, and are more flexible, raising the possibility of producing only transiently available good docking targets. We are presenting a docking prediction protocol that adds molecular dynamics simulations before and after the actual docking in order to explore the conformational space of the target RNA and then to reevaluate the stability of the predicted RNA-ligand complex. In this way we are attempting to overcome important limitations of the docking programs: the rigid (fully or mostly) target structure and imperfect nature of the docking scoring functions.

Noncoding RNA therapeutics for substance use disorder

Although noncoding RNAs (ncRNAs) have been shown to regulate maladaptive neuroadaptations that drive compulsive drug use, ncRNA-targeting therapeutics for substance use disorder (SUD) have yet to be clinically tested. Recent advances in RNA-based drugs have improved many therapeutic issues related to immune response, specificity, and delivery, leading to multiple successful clinical trials for other diseases. As the need for safe and effective treatments for SUD continues to grow, novel nucleic acid-based therapeutics represent an appealing approach to target ncRNA mechanisms in SUD. Here, we review ncRNA processes implicated in SUD, discuss recent therapeutic approaches for targeting ncRNAs, and highlight potential opportunities and challenges of ncRNA-targeting therapeutics for SUD.

Bridged Proteolysis Targeting Chimera (PROTAC) Enables Degradation of Undruggable Targets

Proteolysis Targeting Chimeras (PROTACs) are attractive therapeutic modalities for degrading disease-causing proteins. While many PROTACs have been developed for numerous protein targets, current small-molecule PROTAC approaches cannot target undruggable proteins that do not have small-molecule binders. Here, we present a novel PROTAC approach, termed bridged PROTAC, which utilizes a small-molecule binder of the target protein's binding partner to recruit the protein complex into close proximity with an E3 ubiquitin ligase to target undruggable proteins. Applying this bridged PROTAC strategy, we discovered MS28, the first-in-class degrader of cyclin D1, which lacks a small-molecule binder. MS28 effectively degrades cyclin D1, with faster degradation kinetics and superior degradation efficiency than CDK4/6, through recruiting the CDK4/6-cyclin D1 complex to the von Hippel-Lindau E3 ligase. MS28 also suppressed the proliferation of cancer cells more effectively than CDK4/6 inhibitors and degraders. Altogether, the bridged PROTAC strategy could provide a generalizable platform for targeting undruggable proteins.

Investigating RNA-protein recognition mechanisms through supervised molecular dynamics (SuMD) simulations

Ribonucleic acid (RNA) plays a key regulatory role within the cell, cooperating with proteins to control the genome expression and several biological processes. Due to its characteristic structural features, this polymer can mold itself into different three-dimensional structures able to recognize target biomolecules with high affinity and specificity, thereby attracting the interest of drug developers and medicinal chemists. One successful example of the exploitation of RNA's structural and functional peculiarities is represented by aptamers, a class of therapeutic and diagnostic tools that can recognize and tightly bind several pharmaceutically relevant targets, ranging from small molecules to proteins, making use of the available structural and conformational freedom to maximize the complementarity with their interacting counterparts. In this scientific work, we present the first application of Supervised Molecular Dynamics (SuMD), an enhanced sampling Molecular Dynamics-based method for the study of receptor-ligand association processes in the nanoseconds timescale, to the study of recognition pathways between RNA aptamers and proteins, elucidating the main advantages and limitations of the technique while discussing its possible role in the rational design of RNA-based therapeutics.

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.

ScanFold 2.0: a rapid approach for identifying potential structured RNA targets in genomes and transcriptomes

A major limiting factor in target discovery for both basic research and therapeutic intervention is the identification of structural and/or functional RNA elements in genomes and transcriptomes. This was the impetus for the original ScanFold algorithm, which provides maps of local RNA structural stability, evidence of sequence-ordered (potentially evolved) structure, and unique model structures comprised of recurring base pairs with the greatest structural bias. A key step in quantifying this propensity for ordered structure is the prediction of secondary structural stability for randomized sequences which, in the original implementation of ScanFold, is explicitly evaluated. This slow process has limited the rapid identification of ordered structures in large genomes/transcriptomes, which we seek to overcome in this current work introducing ScanFold 2.0. In this revised version of ScanFold, we no longer explicitly evaluate randomized sequence folding energy, but rather estimate it using a machine learning approach. For high randomization numbers, this can increase prediction speeds over 100-fold compared to ScanFold 1.0, allowing for the analysis of large sequences, as well as the use of additional folding algorithms that may be computationally expensive. In the testing of ScanFold 2.0, we re-evaluate the Zika, HIV, and SARS-CoV-2 genomes and compare both the consistency of results and the time of each run to ScanFold 1.0. We also re-evaluate the SARS-CoV-2 genome to assess the quality of ScanFold 2.0 predictions vs several biochemical structure probing datasets and compare the results to those of the original ScanFold program.

Trading places: Peptide and small molecule alternatives to oligonucleotide-based modulation of microRNA expression

It is well established that microRNA (miRNA) dysregulation is involved in the development and progression of various diseases, especially cancer. Emerging evidence suggests that small molecule and peptide agents can interfere with miRNA disease pathways. Despite this, very little is known about structural features that drive drug-miRNA interactions and subsequent inhibition. In this review, we highlight the advances made in the development of small molecule and peptide inhibitors of miRNA processing. Specifically, we attempt to draw attention to peptide features that may be critical for interaction with the miRNA secondary structure to regulate miRNA expression. We hope that this review will help to establish peptides as exciting miRNA expression modulators and will contribute towards the development of the first miRNA-targeting peptide therapy.

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.

SILCS-RNA: Toward a Structure-Based Drug Design Approach for Targeting RNAs with Small Molecules

RNA molecules can act as potential drug targets in different diseases, as their dysregulated expression or misfolding can alter various cellular processes. Noncoding RNAs account for ∼70% of the human genome, and these molecules can have complex tertiary structures that present a great opportunity for targeting by small molecules. In the present study, the site identification by ligand competitive saturation (SILCS) computational approach is extended to target RNA, termed SILCS-RNA. Extensions to the method include an enhanced oscillating excess chemical potential protocol for the grand canonical Monte Carlo calculations and individual simulations of the neutral and charged solutes from which the SILCS functional group affinity maps (FragMaps) are calculated for subsequent binding site identification and docking calculations. The method is developed and evaluated against seven RNA targets and their reported small molecule ligands. SILCS-RNA provides a detailed characterization of the functional group affinity pattern in the small molecule binding sites, recapitulating the types of functional groups present in the ligands. The developed method is also shown to be useful for identification of new potential binding sites and identifying ligand moieties that contribute to binding, granular information that can facilitate ligand design. However, limitations in the method are evident including the ability to map the regions of binding sites occupied by ligand phosphate moieties and to fully account for the wide range of conformational heterogeneity in RNA associated with binding of different small molecules, emphasizing inherent challenges associated with applying computer-aided drug design methods to RNA. While limitations are present, the current study indicates how the SILCS-RNA approach may enhance drug discovery efforts targeting RNAs with small molecules.

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

MOTIVATION

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

RESULTS

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

AVAILABILITY AND IMPLEMENTATION

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

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Expansion of the RNAStructuromeDB to include secondary structural data spanning the human protein-coding transcriptome

RNA plays vital functional roles in almost every component of biology, and these functional roles are often influenced by its folding into secondary and tertiary structures. An important role of RNA secondary structure is in maintaining proper gene regulation; therefore, making accurate predictions of the structures involved in these processes is important. In this study, we have expanded on our previous work that led to the creation of the RNAStructuromeDB. Unlike this previous study that analyzed the human genome at low resolution, we have now scanned the protein-coding human transcriptome at high (single nt) resolution. This provides more robust structure predictions for over 100,000 isoforms of known protein-coding genes. Notably, we also utilize the motif identification tool, ScanFold, to model structures with high propensity for ordered/evolved stability. All data have been uploaded to the RNAStructuromeDB, allowing for easy searching of transcripts, visualization of data tracks (via the Integrative Genomics Viewer or IGV), and download of ScanFold data—including unique highly-ordered motifs. Herein, we provide an example analysis of MAT2A to demonstrate the utility of ScanFold at finding known and novel secondary structures, highlighting regions of potential functionality, and guiding generation of functional hypotheses through use of the data.