Principles for targeting RNA with drug-like small molecules

The binding of diruthenium (II,III) and dirhodium (II,II) paddlewheel complexes at DNA/RNA nucleobases: Computational evidences of an appreciable selectivity toward the AU base pairs

Multiple medicinal strategies involve modifications of the structure of DNA or RNA, which disrupt their correct functioning. Metal complexes with medicinal effects, also known as metallodrugs, are among the agents intended specifically for the attack onto nucleosides. The diruthenium (II,III) and dirhodium (II,II) paddlewheel complexes constitute promising dual acting drugs due to their ability to release the therapeutically active bridging ligands upon their substitution by endogenous ligands. In this paper, we study the structure and the stability of the complexes formed by the diruthenium (II,III) and dirhodium (II,II) paddlewheel complexes coordinated in axial positions with the DNA/RNA nucleobases or base pairs, assuming the attainable metalation at all the accessible pyridyl nitrogens. Dirhodium complexes coordinate at the pyridyl nitrogens more strongly than the diruthenium complexes. On the other hand, we found that the diruthenium scaffold binds more selectively to nucleobase targets. Furthermore, we reveal a tighter coordination of diruthenium complex at the adenine-uracil base pair, compared to adenine-thymine, hence constituting a scarce instance of RNA-selectivity. We envision that the here reported computational outcomes may pace future experiments addressing the binding of diruthenium and dirhodium paddlewheel complexes at either single nucleobases or DNA/RNA fragments.

The West Nile virus genome harbors essential riboregulatory elements with conserved and host-specific functional roles

West Nile virus (WNV) is an arthropod-borne, positive-sense RNA virus that poses an increasing global threat due to warming climates and lack of effective therapeutics. Like other enzootic viruses, little is known about how host context affects the structure of the full-length RNA genome. Here, we report a complete secondary structure of the entire WNV genome within infected mammalian and arthropod cell lines. Our analysis affords structural insights into multiple, conserved aspects of flaviviral biology. We show that the WNV genome folds with minimal host dependence, and we prioritize well-folded regions for functional validation using structural homology between hosts as a guide. Using structure-disrupting, antisense locked nucleic acids, we then demonstrate that the WNV genome contains riboregulatory structures with conserved and host-specific functional roles. These results reveal promising RNA drug targets within flaviviral genomes, and they highlight the therapeutic potential of ASO-LNAs as both WNV-specific and pan-flaviviral therapeutic agents.

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.

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

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

PRDM16-DT: A Brain and Astrocyte-Specific lncRNA Implicated in Alzheimer's Disease

Astrocytes provide crucial support for neurons, contributing to synaptogenesis, synaptic maintenance, and neurotransmitter recycling. Under pathological conditions, deregulation of astrocytes contributes to neurodegenerative diseases such as Alzheimer's disease (AD), highlighting the growing interest in targeting astrocyte function to address early phases of AD pathogenesis. While most research in this field has focused on protein-coding genes, non-coding RNAs, particularly long non-coding RNAs (lncRNAs), have emerged as significant regulatory molecules. In this study, we identified the lncRNA PRDM16-DT as highly enriched in the human brain, where it is almost exclusively expressed in astrocytes. PRDM16-DT and its murine homolog, Prdm16os, are downregulated in the brains of AD patients and in AD models. In line with this, knockdown of PRDM16-DT and Prdm16os revealed its critical role in maintaining astrocyte homeostasis and supporting neuronal function by regulating genes essential for glutamate uptake, lactate release, and neuronal spine density through interactions with the RE1-Silencing Transcription factor (Rest) and Polycomb Repressive Complex 2 (PRC2). Notably, CRISPR-mediated overexpression of Prdm16os mitigated functional deficits in astrocytes induced by stimuli linked to AD pathogenesis. These findings underscore the importance of PRDM16-DT in astrocyte function and its potential as a novel therapeutic target for neurodegenerative disorders characterized by astrocyte dysfunction.

Identification of RNA structures and their roles in RNA functions

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

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

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

Targeting the conserved active site of splicing machines with specific and selective small molecule modulators

The self-splicing group II introns are bacterial and organellar ancestors of the nuclear spliceosome and retro-transposable elements of pharmacological and biotechnological importance. Integrating enzymatic, crystallographic, and simulation studies, we demonstrate how these introns recognize small molecules through their conserved active site. These RNA-binding small molecules selectively inhibit the two steps of splicing by adopting distinctive poses at different stages of catalysis, and by preventing crucial active site conformational changes that are essential for splicing progression. Our data exemplify the enormous power of RNA binders to mechanistically probe vital cellular pathways. Most importantly, by proving that the evolutionarily-conserved RNA core of splicing machines can recognize small molecules specifically, our work provides a solid basis for the rational design of splicing modulators not only against bacterial and organellar introns, but also against the human spliceosome, which is a validated drug target for the treatment of congenital diseases and cancers.

NMR characterization and ligand binding site of the stem-loop 2 motif from the Delta variant of SARS-CoV-2

The stem-loop 2 motif (s2m) in SARS-CoV-2 (SCoV-2) is located in the 3'-UTR. Although s2m has been reported to display characteristics of a mobile genomic element that might lead to an evolutionary advantage, its function has remained unknown. The secondary structure of the original SCoV-2 RNA sequence (Wuhan-Hu-1) was determined by NMR in late 2020, delineating the base-pairing pattern and revealing substantial differences in secondary structure compared to SARS-CoV-1 (SCoV-1). The existence of a single G29742-A29756 mismatch in the upper stem of s2m leads to its destabilization and impedes a complete NMR analysis. With Delta, a variant of concern has evolved with one mutation compared to the original sequence that replaces G29742 by U29742. We show here that this mutation results in a more defined structure at ambient temperature accompanied by a rise in melting temperature. Consequently, we were able to identify >90% of the relevant NMR resonances using a combination of selective RNA labeling and filtered 2D NOESY as well as 4D NMR experiments. We present a comprehensive NMR analysis of the secondary structure, (sub)nanosecond dynamics, and ribose conformation of s2m Delta based on heteronuclear 13C NOE and T 1 measurements and ribose carbon chemical shift-derived canonical coordinates. We further show that the G29742U mutation in Delta has no influence on the druggability of s2m compared to the Wuhan-Hu-1 sequence. With the assignment at hand, we identify the flexible regions of s2m as the primary site for small molecule binding.

Big data and deep learning for RNA biology

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

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

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

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

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

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

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

Scaffold-enabled high-resolution cryo-EM structure determination of RNA

Cryo-EM structure determination of protein-free RNAs has remained difficult with most attempts yielding low to moderate resolution and lacking nucleotide-level detail. These difficulties are compounded for small RNAs as cryo-EM is inherently more difficult for lower molecular weight macromolecules. Here we present a strategy for fusing small RNAs to a group II intron that yields high resolution structures of the appended RNA, which we demonstrate with the 86-nucleotide thiamine pyrophosphate (TPP) riboswitch, and visualizing the riboswitch ligand binding pocket at 2.5 Å resolution. We also determined the structure of the ligand-free apo state and observe that the aptamer domain of the riboswitch undergoes a large-scale conformational change upon ligand binding, illustrating how small molecule binding to an RNA can induce large effects on gene expression. This study both sets a new standard for cryo-EM riboswitch visualization and offers a versatile strategy applicable to a broad range of small to moderate-sized RNAs, which were previously intractable for high-resolution cryo-EM studies.

Molecular therapy for polyQ disorders: from bench to clinical trials

Polyglutamine (polyQ) disorders are monogenic neurodegenerative disorders. Currently, no therapies are available for this complex group of disorders. Here, we aim to provide an overview of recent promising preclinical studies and the ongoing clinical trials focusing on molecular therapies for polyQ disorders.

Perspective and Therapeutic Potential of the Noncoding RNA-Connexin Axis

Noncoding RNAs (ncRNAs) are a class of nucleotide sequences that cannot be translated into peptides. ncRNAs can function post-transcriptionally by splicing complementary sequences of mRNAs or other ncRNAs or by directly engaging in protein interactions. Over the past few decades, the pervasiveness of ncRNAs in cell physiology and their pivotal roles in various diseases have been identified. One target regulated by ncRNAs is connexin (Cx), a protein that forms gap junctions and hemichannels and facilitates intercellular molecule exchange. The aberrant expression and misdistribution of connexins have been implicated in central nervous system diseases, cardiovascular diseases, bone diseases, and cancer. Current databases and technologies have enabled researchers to identify the direct or indirect relationships between ncRNAs and connexins, thereby elucidating their correlation with diseases. In this review, we selected the literature published in the past five years concerning disorders regulated by ncRNAs via corresponding connexins. Among it, microRNAs that regulate the expression of Cx43 play a crucial role in disease development and are predominantly reviewed. The distinctive perspective of the ncRNA-Cx axis interprets pathology in an epigenetic manner and is expected to motivate research for the development of biomarkers and therapeutics.

Carrimycin inhibits coronavirus replication by decreasing the efficiency of programmed -1 ribosomal frameshifting through directly binding to the RNA pseudoknot of viral frameshift-stimulatory element

The pandemic of SARS-CoV-2 worldwide with successive emerging variants urgently calls for small-molecule oral drugs with broad-spectrum antiviral activity. Here, we show that carrimycin, a new macrolide antibiotic in the clinic and an antiviral candidate for SARS-CoV-2 in phase III trials, decreases the efficiency of programmed -1 ribosomal frameshifting of coronaviruses and thus impedes viral replication in a broad-spectrum fashion. Carrimycin binds directly to the coronaviral frameshift-stimulatory element (FSE) RNA pseudoknot, interrupting the viral protein translation switch from ORF1a to ORF1b and thereby reducing the level of the core components of the viral replication and transcription complexes. Combined carrimycin with known viral replicase inhibitors yielded a synergistic inhibitory effect on coronaviruses. Because the FSE mechanism is essential in all coronaviruses, carrimycin could be a new broad-spectrum antiviral drug for human coronaviruses by directly targeting the conserved coronaviral FSE RNA. This finding may open a new direction in antiviral drug discovery for coronavirus variants.

How exascale computing can shape drug design: A perspective from multiscale QM/MM molecular dynamics simulations and machine learning-aided enhanced sampling algorithms

Molecular simulations are an essential asset in the first steps of drug design campaigns. However, the requirement of high-throughput limits applications mainly to qualitative approaches with low computational cost, but also low accuracy. Unlocking the potential of more rigorous quantum mechanical/molecular mechanics (QM/MM) models combined with molecular dynamics-based free energy techniques could have a tremendous impact. Indeed, these two relatively old techniques are emerging as promising methods in the field. This has been favored by the exponential growth of computer power and the proliferation of powerful data-driven methods. Here, we briefly review recent advances and applications, and give our perspective on the impact that QM/MM and free-energy methods combined with machine learning-aided algorithms can have on drug design.

Ailanthone inhibits non-small cell lung cancer growth and metastasis through targeting UPF1/GAS5/ULK1 signaling pathway

BACKGROUND

Targeting long non-coding RNAs (LncRNAs) is a novel and promising approach in cancer therapy. In our previous study, we investigated the effects of ailanthone (aila), the main active compound derived from the stem barks of Ailanthus altissima (Mill.) Swingle, on the growth of non-small cell lung cancer (NSCLC) cells. Although we observed significant inhibition of NSCLC cell growth of aila, the underlying mechanisms involving LncRNAs, specifically LncRNA growth arrest specific 5 (GAS5), remain largely unknown.

METHODS

To further explore the impact of aila on NSCLC, we performed a series of experiments. Firstly, we confirmed the inhibitory effect of aila on NSCLC cell growth using multiple assays, including MTT, wound healing, transwell assay, as well as subcutaneous and metastasis tumor mice models in vivo. Next, we utilized cDNA microarray and RT-QPCR to identify GAS5 as the primary target of aila. To verify the importance of GAS5 in aila-induced tumor inhibition, we manipulated GAS5 expression levels by constructing GAS5 over-expression and knockdown NSCLC cell lines. Furthermore, we investigated the upstream and downstream signaling pathways of GAS5 through western blot and RT-QPCR analysis.

RESULTS

Our results showed that aila effectively increased GAS5 expression, as determined by microarray analysis. We also observed that aila significantly enhanced GAS5 expression in a dose- and time-dependent manner across various NSCLC cell lines. Notably, over-expression of GAS5 led to a significant suppression of NSCLC cell tumor growth; while aila had minimal inhibitory effect on GAS5-knockdown NSCLC cells. Additionally, we discovered that aila inhibited ULK1 and autophagy, and this inhibition was reversed by GAS5 knockdown. Moreover, we found that aila up-regulated GAS5 expression by suppressing UPF1-mediated nonsense-mediated mRNA decay (NMD).

CONCLUSION

In summary, our findings suggest that aila promotes GAS5 expression by inhibiting UPF1-mediated NMD, leading to the repression of ULK1-mediated autophagy and subsequent inhibitory effects on NSCLC cells. These results indicate that aila is a potent enhancer of GAS5 and holds promising potential for application in NSCLC therapy. However, our research is currently focused only on NSCLC. It remains to be determined whether aila can also inhibit the growth of other types of tumors through the UPF1/GAS5/ULK1 signaling pathway. In future studies, we can further investigate the mechanisms by which aila suppresses other types of tumors and potentially broaden the scope of its application in cancer therapy.

Advances in machine-learning approaches to RNA-targeted drug design

RNA molecules play multifaceted functional and regulatory roles within cells and have garnered significant attention in recent years as promising therapeutic targets. With remarkable successes achieved by artificial intelligence (AI) in different fields such as computer vision and natural language processing, there is a growing imperative to harness AI's potential in computer-aided drug design (CADD) to discover novel drug compounds that target RNA. Although machine-learning (ML) approaches have been widely adopted in the discovery of small molecules targeting proteins, the application of ML approaches to model interactions between RNA and small molecule is still in its infancy. Compared to protein-targeted drug discovery, the major challenges in ML-based RNA-targeted drug discovery stem from the scarcity of available data resources. With the growing interest and the development of curated databases focusing on interactions between RNA and small molecule, the field anticipates a rapid growth and the opening of a new avenue for disease treatment. In this review, we aim to provide an overview of recent advancements in computationally modeling RNA-small molecule interactions within the context of RNA-targeted drug discovery, with a particular emphasis on methodologies employing ML techniques.

Ocular RNA nanomedicine: engineered delivery nanoplatforms in treating eye diseases

Ocular disorders remain a major global health challenge with unmet medical needs. RNA nanomedicine has shown significant therapeutic benefits and safety profiles in patients with complex eye disorders, already benefiting numerous patients with gene-related eye disorders. The effective delivery of RNA to the unique structure of the eye is challenging owing to RNA instability, off-target effects, and ocular physiological barriers. Specifically tailored RNA medication, coupled with sophisticated engineered delivery platforms, is crucial to guide and advance developments in treatments for oculopathy. Herein we review recent advances in RNA-based nanomedicine, innovative delivery strategies, and current clinical progress and present challenges in ocular disease therapy.

Prediction of 3D RNA Structures from Sequence Using Energy Landscapes of RNA Dimers: Application to RNA Tetraloops

Access to the three-dimensional structure of RNA enables an ability to gain a more profound understanding of its biological mechanisms, as well as the ability to design RNA-targeting drugs, which can take advantage of the unique chemical environment imposed by a folded RNA structure. Due to the dynamic and structurally complex properties of RNA, both experimental and traditional computational methods have difficulty in determining RNA's 3D structure. Herein, we introduce TAPERSS (Theoretical Analyses, Prediction, and Evaluation of RNA Structures from Sequence), a physics-based fragment assembly method for predicting 3D RNA structures from sequence. Using a fragment library created using discrete path sampling calculations of RNA dinucleoside monophosphates, TAPERSS can sample the physics-based energy landscapes of any RNA sequence with relatively low computational complexity. We have benchmarked TAPERSS on 21 RNA tetraloops, using a combinatorial algorithm as a proof-of-concept. We show that TAPERSS was successfully able to predict the apo-state structures of all 21 RNA hairpins, with 16 of those structures also having low predicted energies as well. We demonstrate that TAPERSS performs most accurately on GNRA-like tetraloops with mostly stacked loop-nucleotides, while having limited success with more dynamic UNCG and CUYG tetraloops, most likely due to the influence of the RNA force field used to create the fragment library. Moreover, we show that TAPERSS can successfully predict the majority of the experimental non-apo states, highlighting its potential in anticipating biologically significant yet unobserved states. This holds great promise for future applications in drug design and related studies. With discussed improvements and implementation of more efficient sampling algorithms, we believe TAPERSS may serve as a useful tool for a physics-based conformational sampling of large RNA structures.

Aptamer-RIBOTAC Strategy Enabling Tumor-Specific Targeted Degradation of MicroRNA for Precise Cancer Therapy

MicroRNA (miRNA) molecules play crucial roles in a variety of diseases, making miRNA targeting a burgeoning field in medicinal chemistry. Ribonuclease targeting chimeras (RIBOTACs) present a compelling approach for RNA degradation. However, small molecule-based RIBOTAC requires an expensive and time-consuming screening process, and is difficult to directly target miRNA due to its short length lacking secondary structure. Antisense oligonucleotide (ASO)-based RIBOTAC is easy to design but with poor cell permeability. While both of them lack the specificity for tumor targeting. In this study, the first Aptamer-RIBOTAC (ARIBOTAC) chimera is designed based on ASO to achieve precise degradation of miRNA in a tumor cell-specific manner for precise cancer therapy. This chimera exhibits a remarkable ability to specifically identify and enter cancer cells, trigger localized activation of endogenous RNase L, and selectively cleave miRNAs that are complementary to ASO. The efficacy and universality of the ARIBOTAC strategy both in vitro and in vivo by degrading oncogenic miR-210-3p and miR-155-5p are validated. These findings underscore the potential of the ARIBOTAC strategy as a promising avenue for cancer therapy by precisely targeting cancer-associated miRNAs.

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.

High-resolution RNA tertiary structures in Zika virus stem-loop A for the development of inhibitory small molecules

Flaviviruses such as Zika (ZIKV) and dengue virus (DENV) are positive-sense RNA viruses belonging to Flaviviridae The flavivirus genome contains a 5' end stem-loop promoter sequence known as stem-loop A (SLA) that is recognized by the flavivirus polymerase NS5 during viral RNA synthesis and 5' guanosine cap methylation. The crystal structures of ZIKV and DENV SLAs show a well-defined fold, consisting of a bottom stem, side loop, and top stem-loop, providing unique interaction sites for small molecule inhibitors to disrupt the promoter function. To facilitate the identification of small molecule binding sites in flavivirus SLA, we determined high-resolution structures of the bottom and top stems of ZIKV SLA, which contain a single U- or G-bulge, respectively. Both bulge nucleotides exhibit multiple orientations, from folded back on the adjacent nucleotide to flipped out of the helix, and are stabilized by stacking or base triple interactions. These structures suggest that even a single unpaired nucleotide can provide flexibility to RNA structures, and its conformation is mainly determined by the stabilizing chemical environment. To facilitate discovery of small molecule inhibitors that interfere with the functions of ZIKV SLA, we screened and identified compounds that bind to the bottom and top stems of ZIKV SLA.

Resolving the intricate binding of neomycin B to multiple binding motifs of a neomycin-sensing riboswitch aptamer by native top-down mass spectrometry and NMR spectroscopy

Understanding small molecule binding to RNA can be complicated by an intricate interplay between binding stoichiometry, multiple binding motifs, different occupancies of different binding motifs, and changes in the structure of the RNA under study. Here, we use native top-down mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy to experimentally resolve these factors and gain a better understanding of the interactions between neomycin B and the 40 nt aptamer domain of a neomycin-sensing riboswitch engineered in yeast. Data from collisionally activated dissociation of the 1:1, 1:2 and 1:3 RNA-neomycin B complexes identified a third binding motif C of the riboswitch in addition to the two motifs A and B found in our previous study, and provided occupancies of the different binding motifs for each complex stoichiometry. Binding of a fourth neomycin B molecule was unspecific according to both MS and NMR data. Intriguingly, all major changes in the aptamer structure can be induced by the binding of the first neomycin B molecule regardless of whether it binds to motif A or B as evidenced by stoichiometry-resolved MS data together with titration data from 1H NMR spectroscopy in the imino proton region. Specific binding of the second and third neomycin B molecules further stabilizes the riboswitch aptamer, thereby allowing for a gradual response to increasing concentrations of neomycin B, which likely leads to a fine-tuning of the cellular regulatory mechanism.

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.

Interaction of 3,9-disubstituted acridine with single stranded poly(rA), double stranded poly(rAU) and triple stranded poly(rUAU): molecular docking - A spectroscopic tandem study

RNA plays an important role in many biological processes which are crucial for cell survival, and it has been suggested that it may be possible to inhibit individual processes involved in many diseases by targeting specific sequences of RNA. The aim of this work is to determine the affinity of novel 3,9-disubstited acridine derivative 1 with three different RNA molecules, namely single stranded poly(rA), double stranded homopolymer poly(rAU) and triple stranded poly(rUAU). The results of the absorption titration assays show that the binding constant of the novel derivative to the RNA molecules was in the range of 1.7-6.2 × 104 mol dm-3. The fluorescence and circular dichroism titration assays revealed considerable changes. The most significant results in terms of interpreting the nature of the interactions were the melting temperatures of the RNA samples in complexes with the 1. In the case of poly(rA), denaturation resulted in a self-structure formation; increased stabilization was observed for poly(rAU), while the melting points of the ligand-poly(rUAU) complex showed significant destabilization as a result of the interaction. The principles of molecular mechanics were applied to propose the non-bonded interactions within the binding complex, pentariboadenylic acid and acridine ligand as the study model. Initial molecular docking provided the input structure for advanced simulation techniques. Molecular dynamics simulation and cluster analysis reveal π - π stacking and the hydrogen bonds formation as the main forces that can stabilize the binding complex. Subsequent MM-GBSA calculations showed negative binding enthalpy accompanied the complex formation and proposed the most preferred conformation of the interaction complex.

Quinazoline sulfonamide derivatives targeting MicroRNA-34a/MDM4/p53 apoptotic axis with radiosensitizing activity

Aim: New quinazoline benzenesulfonamide hybrids 4a-n were synthesized to determine their cytotoxicity and effect on the miR-34a/MDM4/p53 apoptotic pathway. Materials & methods: Cytotoxicity against hepatic, breast, lung and colon cancer cell lines was estimated using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay. Results: Compound 4d was the most potent against HepG2 and MCF-7 cancer cells, with potential apoptotic activity verified by a significant upregulation of miR-34a and p53 gene expressions. The apoptotic effect of 4d was further investigated and showed downregulation of miR-21, VEGF, STAT3 and MDM4 gene expression. Conclusion: The anticancer and apoptotic activities of 4d were enhanced post irradiation by a single dose of 8 Gy γ-radiation. Docking analysis demonstrated a valuable affinity of 4d toward VEGFR2 and MDM4 active sites.

The application of single-molecule optical tweezers to study disease-related structural dynamics in RNA

RNA, a dynamic and flexible molecule with intricate three-dimensional structures, has myriad functions in disease development. Traditional methods, such as X-ray crystallography and nuclear magnetic resonance, face limitations in capturing real-time, single-molecule dynamics crucial for understanding RNA function. This review explores the transformative potential of single-molecule force spectroscopy using optical tweezers, showcasing its capability to directly probe time-dependent structural rearrangements of individual RNA molecules. Optical tweezers offer versatility in exploring diverse conditions, with the potential to provide insights into how environmental changes, ligands and RNA-binding proteins impact RNA behaviour. By enabling real-time observations of large-scale structural dynamics, optical tweezers emerge as an invaluable tool for advancing our comprehension of RNA structure and function. Here, we showcase their application in elucidating the dynamics of RNA elements in virology, such as the pseudoknot governing ribosomal frameshifting in SARS-CoV-2.

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.

Developing nucleoside tailoring strategies against SARS-CoV-2 via ribonuclease targeting chimera

In response to the urgent need for potent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) therapeutics, this study introduces an innovative nucleoside tailoring strategy leveraging ribonuclease targeting chimeras. By seamlessly integrating ribonuclease L recruiters into nucleosides, we address RNA recognition challenges and effectively inhibit severe acute respiratory syndrome coronavirus 2 replication in human cells. Notably, nucleosides tailored at the ribose 2'-position outperform those modified at the nucleobase. Our in vivo validation using hamster models further bolsters the promise of this nucleoside tailoring approach, positioning it as a valuable asset in the development of innovative antiviral drugs.

Structural Landscape of nsp Coding Genomic Regions of SARS-CoV-2-ssRNA Genome: A Structural Genomics Approach Toward Identification of Druggable Genome, Ligand-Binding Pockets, and Structure-Based Druggability

SARS-CoV-2 has a single-stranded RNA genome (+ssRNA), and synthesizes structural and non-structural proteins (nsps). All 16 nsp are synthesized from the ORF1a, and ORF1b regions associated with different life cycle preprocesses, including replication. The regions of ORF1a synthesizes nsp1 to 11, and ORF1b synthesizes nsp12 to 16. In this paper, we have predicted the secondary structure conformations, entropy & mountain plots, RNA secondary structure in a linear fashion, and 3D structure of nsp coding genes of the SARS-CoV-2 genome. We have also analyzed the A, T, G, C, A+T, and G+C contents, GC-profiling of these genes, showing the range of the GC content from 34.23 to 48.52%. We have observed that the GC-profile value of the nsp coding genomic regions was less (about 0.375) compared to the whole genome (about 0.38). Additionally, druggable pockets were identified from the secondary structure-guided 3D structural conformations. For secondary structure generation of all the nsp coding genes (nsp 1-16), we used a recent algorithm-based tool (deep learning-based) along with the conventional algorithms (centroid and MFE-based) to develop secondary structural conformations, and we found stem-loop, multi-branch loop, pseudoknot, and the bulge structural components, etc. The 3D model shows bound and unbound forms, branched structures, duplex structures, three-way junctions, four-way junctions, etc. Finally, we identified binding pockets of nsp coding genes which will help as a fundamental resource for future researchers to develop RNA-targeted therapeutics using the druggable genome.

Recent applications of artificial intelligence in RNA-targeted small molecule drug discovery

INTRODUCTION

Targeting RNAs with small molecules offers an alternative to the conventional protein-targeted drug discovery and can potentially address unmet and emerging medical needs. The recent rise of interest in the strategy has already resulted in large amounts of data on disease associated RNAs, as well as on small molecules that bind to such RNAs. Artificial intelligence (AI) approaches, including machine learning and deep learning, present an opportunity to speed up the discovery of RNA-targeted small molecules by improving decision-making efficiency and quality.

AREAS COVERED

The topics described in this review include the recent applications of AI in the identification of RNA targets, RNA structure determination, screening of chemical compound libraries, and hit-to-lead optimization. The impact and limitations of the recent AI applications are discussed, along with an outlook on the possible applications of next-generation AI tools for the discovery of novel RNA-targeted small molecule drugs.

EXPERT OPINION

Key areas for improvement include developing AI tools for understanding RNA dynamics and RNA - small molecule interactions. High-quality and comprehensive data still need to be generated especially on the biological activity of small molecules that target RNAs.

The current perspective and opportunities of small nucleic acid-based therapeutics

Compared to traditional small molecule and antibody drugs, RNA-based drugs offer a simple design, short research and development cycles, high specificity, broad treatment fields, and long-term efficacy. As a result, RNA-based drugs are extensively used to treat genetic diseases, tumors, viral infections, and other illnesses, suggesting that they have the potential to become the third-largest drug class after small molecule and antibody drugs. Currently, more than 10 small nucleic acid drugs have gained regulatory approval. The commercialization successes of small nucleic acid drugs will stimulate the development of RNA-based drugs. Small nucleic acid drugs primarily target liver diseases, metabolic diseases, genetic diseases, and tumors, and there is also significant potential for expanding indications in the future. This review provides a brief overview of the advantages and development of small nucleic acid-based therapeutics and shows a focus on platform technologies such as chemical modifications and delivery systems that have enabled the clinical translation of small nucleic acid-based therapeutics. Additionally, we summarize the latest clinical progress in small nucleic acid-based therapeutics for the treatment of various diseases, including rare diseases, liver diseases, metabolic diseases, and tumors. Finally, we highlight the future prospects for this promising treatment approach.

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.

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.

The pancancer overexpressed NFYC Antisense 1 controls cell cycle mitotic progression through in cis and in trans modes of action

Antisense RNAs (asRNAs) represent an underappreciated yet crucial layer of gene expression regulation. Generally thought to modulate their sense genes in cis through sequence complementarity or their act of transcription, asRNAs can also regulate different molecular targets in trans, in the nucleus or in the cytoplasm. Here, we performed an in-depth molecular characterization of NFYC Antisense 1 (NFYC-AS1), the asRNA transcribed head-to-head to NFYC subunit of the proliferation-associated NF-Y transcription factor. Our results show that NFYC-AS1 is a prevalently nuclear asRNA peaking early in the cell cycle. Comparative genomics suggests a narrow phylogenetic distribution, with a probable origin in the common ancestor of mammalian lineages. NFYC-AS1 is overexpressed pancancer, preferentially in association with RB1 mutations. Knockdown of NFYC-AS1 by antisense oligonucleotides impairs cell growth in lung squamous cell carcinoma and small cell lung cancer cells, a phenotype recapitulated by CRISPR/Cas9-deletion of its transcription start site. Surprisingly, expression of the sense gene is affected only when endogenous transcription of NFYC-AS1 is manipulated. This suggests that regulation of cell proliferation is at least in part independent of the in cis transcription-mediated effect on NFYC and is possibly exerted by RNA-dependent in trans effects converging on the regulation of G2/M cell cycle phase genes. Accordingly, NFYC-AS1-depleted cells are stuck in mitosis, indicating defects in mitotic progression. Overall, NFYC-AS1 emerged as a cell cycle-regulating asRNA with dual action, holding therapeutic potential in different cancer types, including the very aggressive RB1-mutated tumors.

tRNA-derived fragments: Key determinants of cancer metastasis with emerging therapeutic and diagnostic potentials

Metastasis is a significant clinical challenge responsible for cancer mortality and non-response to treatment. However, the molecular mechanisms driving metastasis remain unclear, limiting the development of efficient diagnostic and therapeutic approaches. Recent breakthroughs in cancer biology have discovered a group of small non-coding RNAs called tRNA-derived fragments (tRFs), which play a critical role in the metastatic behavior of various tumors. tRFs are produced from cleavage modifications of tRNAs and have different functional classes based on the pattern of these modifications. They perform post-transcriptional regulation through microRNA-like functions, displacing RNA-binding proteins, and play a role in translational regulation by inducing ribosome synthesis, translation initiation, and epigenetic regulation. Tumor cells manipulate tRFs to develop and survive the tumor mass, primarily by inducing metastasis. Multiple studies have demonstrated the potential of tRFs as therapeutic, diagnostic, and prognostic targets for tumor metastasis. This review discusses the production and function of tRFs in cells, their aberrant molecular contributions to the metastatic environment, and their potential as promising targets for anti-metastasis treatment strategies.

Role of long noncoding RNAs in pathological cardiac remodeling after myocardial infarction: An emerging insight into molecular mechanisms and therapeutic potential

Myocardial infarction (MI) is the leading cause of heart failure (HF), accounting for high mortality and morbidity worldwide. As a consequence of ischemia/reperfusion injury during MI, multiple cellular processes such as oxidative stress-induced damage, cardiomyocyte death, and inflammatory responses occur. In the next stage, the proliferation and activation of cardiac fibroblasts results in myocardial fibrosis and HF progression. Therefore, developing a novel therapeutic strategy is urgently warranted to restrict the progression of pathological cardiac remodeling. Recently, targeting long non-coding RNAs (lncRNAs) provided a novel insight into treating several disorders. In this regard, numerous investigations have indicated that several lncRNAs could participate in the pathogenesis of MI-induced cardiac remodeling, suggesting their potential therapeutic applications. In this review, we summarized lncRNAs displayed in the pathophysiology of cardiac remodeling after MI, emphasizing molecular mechanisms. Also, we highlighted the possible translational role of lncRNAs as therapeutic targets for this condition and discussed the potential role of exosomes in delivering the lncRNAs involved in post-MI cardiac remodeling.

Non-coding RNAs in disease: from mechanisms to therapeutics

Non-coding RNAs (ncRNAs) are a heterogeneous group of transcripts that, by definition, are not translated into proteins. Since their discovery, ncRNAs have emerged as important regulators of multiple biological functions across a range of cell types and tissues, and their dysregulation has been implicated in disease. Notably, much research has focused on the link between microRNAs (miRNAs) and human cancers, although other ncRNAs, such as long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), are also emerging as relevant contributors to human disease. In this Review, we summarize our current understanding of the roles of miRNAs, lncRNAs and circRNAs in cancer and other major human diseases, notably cardiovascular, neurological and infectious diseases. Further, we discuss the potential use of ncRNAs as biomarkers of disease and as therapeutic targets.

Specificity, synergy, and mechanisms of splice-modifying drugs

Drugs that target pre-mRNA splicing hold great therapeutic potential, but the quantitative understanding of how these drugs work is limited. Here we introduce mechanistically interpretable quantitative models for the sequence-specific and concentration-dependent behavior of splice-modifying drugs. Using massively parallel splicing assays, RNA-seq experiments, and precision dose-response curves, we obtain quantitative models for two small-molecule drugs, risdiplam and branaplam, developed for treating spinal muscular atrophy. The results quantitatively characterize the specificities of risdiplam and branaplam for 5' splice site sequences, suggest that branaplam recognizes 5' splice sites via two distinct interaction modes, and contradict the prevailing two-site hypothesis for risdiplam activity at SMN2 exon 7. The results also show that anomalous single-drug cooperativity, as well as multi-drug synergy, are widespread among small-molecule drugs and antisense-oligonucleotide drugs that promote exon inclusion. Our quantitative models thus clarify the mechanisms of existing treatments and provide a basis for the rational development of new therapies.

Exploring the Landscape of Aptamers: From Cross-Reactive to Selective to Specific, High-Affinity Receptors for Cocaine

We reported over 20 years ago MNS-4.1, the first DNA aptamer with a micromolar affinity for cocaine. MNS-4.1 is based on a structural motif that is very common in any random pool of oligonucleotides, and it is actually a nonspecific hydrophobic receptor with wide cross-reactivity with alkaloids and steroids. Despite such weaknesses preventing broad applications, this aptamer became widely used in proof-of-concept demonstrations of new formats of biosensors. We now report a series of progressively improved DNA aptamers recognizing cocaine, with the final optimized receptors having low nanomolar affinity and over a thousand-fold selectivity over the initial cross-reactants. In the process of optimization, we tested different methods to eliminate cross-reactivities and improve affinity, eventually achieving properties that are comparable to those of the reported monoclonal antibody candidates for the therapy of overdose. Multiple aptamers that we now report share structural motifs with the previously reported receptor for serotonin. Further mutagenesis studies revealed a palindromic, highly adaptable, broadly cross-reactive hydrophobic motif that could be rebuilt through mutagenesis, expansion of linker regions, and selections into receptors with exceptional affinities and varying specificities.

Mechanistic Analysis of Riboswitch Ligand Interactions Provides Insights into Pharmacological Control over Gene Expression

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

Recent Advances in RNA-Targeted Cancer Therapy

Ribonucleic acid (RNA) plays a pivotal role in gene regulation and protein biosynthesis. Interfering the physiological function of key RNAs to induce cell apoptosis holds great promise for cancer treatment. Many RNA-targeted anti-cancer strategies have emerged continuously. Among them, RNA interference (RNAi) has been recognized as a promising therapeutic modality for various disease treatments. Nevertheless, the primary obstacle in siRNA delivery-escaping the endosome and crossing the plasma membrane severely impedes its therapeutic potential. Thus far, a variety of nanosystems as well as carrier-free bioconjugation for siRNA delivery have been developed and employed to enhance the drug delivery and anti-tumor efficiency. Besides, the use of small molecules to target specific RNA structures and disrupt their function, along with the covalent modification of RNA, has also drawn tremendous attention recently owing to high therapeutic efficacy. In this review, we will provide an overview of recent progress in RNA-targeted cancer therapy including various siRNA delivery strategies, RNA-targeting small molecules, and newly emerged covalent RNA modification. Finally, challenges and future perspectives faced in this research field will be discussed.

Triplex-forming peptide nucleic acids as emerging ligands to modulate structure and function of complex RNAs

Over the last three decades, our view of RNA has changed from a simple intermediate supporting protein synthesis to a major regulator of biological processes. In the expanding area of RNA research, peptide nucleic acid (PNA) is emerging as a promising ligand for triple-helical recognition of complex RNAs. As discussed in this feature article, the key advantages of PNAs are high sequence specificity and affinity for RNA (>10 fold higher than for DNA) that are difficult to achieve with small molecule ligands. Emerging studies demonstrate that triple-helical binding of PNAs can modulate biological function and control dynamic conformational equilibria of complex folded RNAs. These results suggest that PNA has a unique potential as a research tool and therapeutic compound targeting RNA. The remaining problems hampering advances in these directions are limitations of sequences that can be recognized by Hoogsteen triplexes (typically purine rich tracts), poor cellular uptake and bioavailability of PNA, and potential off-target effects in biological systems. Recent exciting studies are discussed that illustrate how synthetic nucleic acid chemistry provides innovative solutions for these problems.

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.

Mechanism of Ligand Binding to Theophylline RNA Aptamer

Studying RNA-ligand interactions and quantifying their binding thermodynamics and kinetics are of particular relevance in the field of drug discovery. Here, we combined biochemical binding assays and accelerated molecular simulations to investigate ligand binding and dissociation in RNA using the theophylline-binding RNA as a model system. All-atom simulations using a Ligand Gaussian accelerated Molecular Dynamics method (LiGaMD) have captured repetitive binding and dissociation of theophylline and caffeine to RNA. Theophylline's binding free energy and kinetic rate constants align with our experimental data, while caffeine's binding affinity is over 10,000 times weaker, and its kinetics could not be determined. LiGaMD simulations allowed us to identify distinct low-energy conformations and multiple ligand binding pathways to RNA. Simulations revealed a "conformational selection" mechanism for ligand binding to the flexible RNA aptamer, which provides important mechanistic insights into ligand binding to the theophylline-binding model. Our findings suggest that compound docking using a structural ensemble of representative RNA conformations would be necessary for structure-based drug design of flexible RNA.

Proline-Hinged α-Helical Peptides Sensitize Gram-Positive Antibiotics, Expanding Their Physicochemical Properties to Be Used as Gram-Negative Antibiotics

The outer membrane (OM) of Gram-negative bacteria is the most difficult obstacle for small-molecule antibiotics to reach their targets in the cytosol. The molecular features of Gram-negative antibiotics required for passing through the OM are that they should be positively charged rather than neutral, flat rather than globular, less flexible, or more increased amphiphilic moment. Because of these specific molecular characteristics, developing Gram-negative antibiotics is difficult. We focused on sensitizer peptides to facilitate the passage of hydrophobic Gram-positive antibiotics through the OM. We explored ways of improving the sensitizing ability of proline-hinged α-helical peptides by adjusting their length, hydrophobicity, and N-terminal groups. A novel peptide, 1403, improves the potentiation of rifampicin in vitro and in vivo and potentiates most Gram-positive antibiotics. The "sensitizer" approach is more plausible than those that rely on conventional drug discovery methods concerning drug development costs and the development of drug resistance.

Small molecule approaches to targeting RNA

The development of innovative methodologies to identify RNA binders has attracted enormous attention in chemical biology and drug discovery. Although antibiotics targeting bacterial ribosomal RNA have been on the market for decades, the renewed interest in RNA targeting reflects the need to better understand complex intracellular processes involving RNA. In this context, small molecules are privileged tools used to explore the biological functions of RNA and to validate RNAs as therapeutic targets, and they eventually are to become new drugs. Despite recent progress, the rational design of specific RNA binders requires a better understanding of the interactions which occur with the RNA target to reach the desired biological response. In this Review, we discuss the challenges to approaching this underexplored chemical space, together with recent strategies to bind, interact and affect biologically relevant RNAs.