Recognition of single-stranded nucleic acids by small-molecule splicing modulators

Genome-Wide Analysis of Stable RNA Secondary Structures across Multiple Organisms Using Chemical Probing Data: Insights into Short Structural Motifs and RNA-Targeting Therapeutics

Small molecules targeting specific RNA-binding sites, including stable and transient RNA structures, are emerging as effective pharmacological approaches for modulating gene expression. However, little is understood about how stable RNA secondary structures are shared across organisms, which is an important factor in controlling drug selectivity. In this study, I provide an analytical pipeline named RNA secondary structure finder (R2S-Finder) to discover short, stable RNA structural motifs in humans, Escherichia coli (E. coli), SARS-CoV-2, and Zika virus by leveraging existing in vivo and in vitro genome-wide chemical RNA-probing datasets. I found several common features across the organisms. For example, apart from the well-documented tetraloops, AU-rich tetraloops are widely present in different organisms. I also validated that the 5' untranslated region (UTR) contains a higher proportion of stable structures than the coding sequences in humans and Zika virus. In general, stable structures predicted from in vitro (protein-free) and in vivo datasets are consistent across different organisms, indicating that stable structure formation is mostly driven by RNA folding, while a larger variation was found between in vitro and in vivo data for certain RNA types, such as human long intergenic noncoding RNAs (lincRNAs). Finally, I predicted stable three- and four-way RNA junctions that exist under both in vivo and in vitro conditions and can potentially serve as drug targets. All results of stable structures, stem-loops, internal loops, bulges, and n-way junctions have been collated in the R2S-Finder database (https://github.com/JingxinWangLab/R2S-Finder), which is coded in hyperlinked HTML pages and tabulated in CSV files.

The evolution and application of RNA-focused small molecule libraries

RNA structure plays a role in nearly every disease. Therefore, approaches that identify tractable small molecule chemical matter that targets RNA and affects its function would transform drug discovery. Despite this potential, discovery of RNA-targeted small molecule chemical probes and medicines remains in its infancy. Advances in RNA-focused libraries are key to enable more successful primary screens and to define structure-activity relationships amongst hit molecules. In this review, we describe how RNA-focused small molecule libraries have been used and evolved over time and provide underlying principles for their application to develop bioactive small molecules. We also describe areas that need further investigation to advance the field, including generation of larger data sets to inform machine learning approaches.

Chemical-guided SHAPE sequencing (cgSHAPE-seq) informs the binding site of RNA-degrading chimeras targeting SARS-CoV-2 5' untranslated region

One of the hallmarks of RNA viruses is highly structured untranslated regions (UTRs) which are often essential for viral replication, transcription, or translation. In this report, we discovered a series of coumarin derivatives that bind to a four-way RNA helix called SL5 in the 5' UTR of the SARS-CoV-2 RNA genome. To locate the binding site, we developed a sequencing-based method namely cgSHAPE-seq, in which an acylating probe was directed to crosslink with the 2'-OH group of ribose at the binding site to create read-through mutations during reverse transcription. cgSHAPE-seq unambiguously determined a bulged G in SL5 as the primary binding site, which was validated through mutagenesis and in vitro binding experiments. The coumarin derivatives were further used as a warhead in designing RNA-degrading chimeras to reduce viral RNA expression levels. The optimized RNA-degrading chimera C64 inhibited live virus replication in lung epithelial carcinoma cells.

Mechanistic Studies of Small Molecule Ligands Selective to RNA Single G Bulges

Small-molecule RNA binders have emerged as an important pharmacological modality. A profound understanding of the ligand selectivity, binding mode, and influential factors governing ligand engagement with RNA targets is the foundation for rational ligand design. Here, we report a novel class of coumarin derivatives exhibiting selective binding affinity towards single G RNA bulges. Harnessing the computational power of all-atom Gaussian accelerated Molecular Dynamics (GaMD) simulations, we unveiled a rare minor groove binding mode of the ligand with a key interaction between the coumarin moiety and the G bulge. This predicted binding mode is consistent with results obtained from structure-activity-relationship (SAR) studies and transverse relaxation measurements by NMR spectroscopy. We further generated 444 molecular descriptors from 69 coumarin derivatives and identified key contributors to the binding events, such as charge state and planarity, by lasso (least absolute shrinkage and selection operator) regression. Strikingly, small structure perturbations on these key contributors, such as the addition of a methyl group that disrupts the planarity of the ligand resulted in > 100-fold reduction in the binding affinity. Our work deepened the understanding of RNA-small molecule interactions and integrated a new generalizable platform for the rational design of selective small-molecule RNA binders.

Genome-Wide Identification of Stable RNA Secondary Structures Across Multiple Organisms Using Chemical Probing Data: Insights into Short Structural Motifs and RNA-Targeting Therapeutics

Small molecules targeting specific RNA binding sites, including stable and transient RNA structures, are emerging as effective pharmacological approaches for modulating gene expression. However, little is understood about how stable RNA secondary structures are shared across organisms, an important factor in controlling drug selectivity. In this study, I provide an analytical pipeline named RNA Secondary Structure Finder (R2S-Finder) to discover short, stable RNA structural motifs for humans, Escherichia coli ( E. coli ), SARS-CoV-2, and Zika virus by leveraging existing in vivo and in vitro genome-wide chemical RNA-probing datasets. I found several common features across organisms. For example, apart from the well-documented tetraloops, AU-rich tetraloops are widely present in different organisms. I also found that the 5' untranslated region (UTR) contains a higher proportion of stable structures than the coding sequences in humans, SARS-CoV-2, and Zika virus. In general, stable structures predicted from in vitro (protein-free) and in vivo datasets are consistent in humans, E. coli , and SARS-CoV-2, indicating that most stable structure formation were driven by RNA folding alone, while a larger variation was found between in vitro and in vivo data with certain RNA types, such as human long intergenic non-coding RNAs (lincRNAs). Finally, I predicted stable three- and four-way RNA junctions that exist both in vivo and in vitro conditions, which can potentially serve as drug targets. All results of stable sequences, stem-loops, internal loops, bulges, and three- and four-way junctions have been collated in the R2S-Finder database ( https://github.com/JingxinWangLab/R2S-Finder ), which is coded in hyperlinked HTML pages and tabulated in CSV files.

On the Power and Challenges of Atomistic Molecular Dynamics to Investigate RNA Molecules

RNA molecules play a vital role in biological processes within the cell, with significant implications for science and medicine. Notably, the biological functions exerted by specific RNA molecules are often linked to the RNA conformational ensemble. However, the experimental characterization of such three-dimensional RNA structures is challenged by the structural heterogeneity of RNA and by its multiple dynamic interactions with binding partners such as small molecules, proteins, and metal ions. Consequently, our current understanding of the structure-function relationship of RNA molecules is still limited. In this context, we highlight molecular dynamics (MD) simulations as a powerful tool to complement experimental efforts on RNAs. Despite the recognized limitations of current force fields for RNA MD simulations, examining the dynamics of selected RNAs has provided valuable functional insights into their structures.

Exploration of adverse events associated with risdiplam use: Retrospective cases from the US Food and Drug Administration Adverse Event Reporting System (FAERS) database

Risdiplam is a new drug for treating spinal muscular atrophy (SMA). However, pharmacovigilance analyses are necessary to objectively evaluate its safety-a crucial step in preventing severe adverse events (AEs). Accordingly, the primary objective of the current study was to examine the AEs associated with risdiplam use based on real-world data obtained from the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. More specifically, we examined incidents reported between the third quarter of 2020 and the second quarter of 2023. The imbalance of risdiplam-related AEs was evaluated by computing the reporting odds ratio. A total of 5,406,334 reports were thoroughly reviewed. By removing duplicate reports, we identified 1588 reports in which risdiplam was the main suspected drug whose use was accompanied by 3470 associated AEs. Among the included AEs, 703 were categorized as serious and 885 as non-serious. Risdiplam use induced AEs across 18 organ systems, resulting in 130 positive signals. Notably, we detected new AE signals, including cardiac arrest, nephrolithiasis, tachycardia, loss of libido, and elevated hepatic enzyme activities; however, no ophthalmologic toxicity was reported. Although these new adverse reaction signals associated with risdiplam have been defined, long-term clinical studies are needed to confirm these findings. Nevertheless, our findings provide a valuable reference for improving the clinical management of SMA.

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.

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.

Chemical-guided SHAPE sequencing (cgSHAPE-seq) informs the binding site of RNA-degrading chimeras targeting SARS-CoV-2 5' untranslated region

One of the hallmarks of RNA viruses is highly structured untranslated regions (UTRs) in their genomes. These conserved RNA structures are often essential for viral replication, transcription, or translation. In this report, we discovered and optimized a new type of coumarin derivatives, such as C30 and C34, which bind to a four-way RNA helix called SL5 in the 5' UTR of the SARS-CoV-2 RNA genome. To locate the binding site, we developed a novel sequencing-based method namely cgSHAPE-seq, in which the acylating chemical probe was directed to crosslink with the 2'-OH groups of ribose at the ligand binding site. This crosslinked RNA could then create read-through mutations during reverse transcription (i.e., primer extension) at single-nucleotide resolution to uncover the acylation locations. cgSHAPE-seq unambiguously determined that a bulged G in SL5 was the primary binding site of C30 in the SARS-CoV-2 5' UTR, which was validated through mutagenesis and in vitro binding experiments. C30 was further used as a warhead in RNA-degrading chimeras to reduce viral RNA expression levels. We demonstrated that replacing the acylating moiety in the cgSHAPE probe with ribonuclease L recruiter (RLR) moieties yielded RNA degraders active in the in vitro RNase L degradation assay and SARS-CoV-2 5' UTR expressing cells. We further explored another RLR conjugation site on the E ring of C30/C34 and discovered improved RNA degradation activities in vitro and in cells. The optimized RNA-degrading chimera C64 inhibited live virus replication in lung epithelial carcinoma cells.

Global impact of aberrant splicing on human gene expression levels

Alternative splicing (AS) is pervasive in human genes, yet the specific function of most AS events remains unknown. It is widely assumed that the primary function of AS is to diversify the proteome, however AS can also influence gene expression levels by producing transcripts rapidly degraded by nonsense-mediated decay (NMD). Currently, there are no precise estimates for how often the coupling of AS and NMD (AS-NMD) impacts gene expression levels because rapidly degraded NMD transcripts are challenging to capture. To better understand the impact of AS on gene expression levels, we analyzed population-scale genomic data in lymphoblastoid cell lines across eight molecular assays that capture gene regulation before, during, and after transcription and cytoplasmic decay. Sequencing nascent mRNA transcripts revealed frequent aberrant splicing of human introns, which results in remarkably high levels of mRNA transcripts subject to NMD. We estimate that ~15% of all protein-coding transcripts are degraded by NMD, and this estimate increases to nearly half of all transcripts for lowly-expressed genes with many introns. Leveraging genetic variation across cell lines, we find that GWAS trait-associated loci explained by AS are similarly likely to associate with NMD-induced expression level differences as with differences in protein isoform usage. Additionally, we used the splice-switching drug risdiplam to perturb AS at hundreds of genes, finding that ~3/4 of the splicing perturbations induce NMD. Thus, we conclude that AS-NMD substantially impacts the expression levels of most human genes. Our work further suggests that much of the molecular impact of AS is mediated by changes in protein expression levels rather than diversification of the proteome.

Targeting RNA-binding proteins with small molecules: Perspectives, pitfalls and bifunctional molecules

RNA-binding proteins (RBPs) play vital roles in organisms through binding with RNAs to regulate their functions. Small molecules affecting the function of RBPs have been developed, providing new avenues for drug discovery. Herein, we describe the perspectives on developing small molecule regulators of RBPs. The following types of small molecule modulators are of great interest in drug discovery: small molecules binding to RBPs to affect interactions with RNA molecules, bifunctional molecules binding to RNA or RBP to influence their interactions, and other types of molecules that affect the stability of RNA or RBPs. Moreover, we emphasize that the bifunctional molecules may play important roles in small molecule development to overcome the challenges encountered in the process of drug discovery.

Diverse targets of SMN2-directed splicing-modulating small molecule therapeutics for spinal muscular atrophy

Designing an RNA-interacting molecule that displays high therapeutic efficacy while retaining specificity within a broad concentration range remains a challenging task. Risdiplam is an FDA-approved small molecule for the treatment of spinal muscular atrophy (SMA), the leading genetic cause of infant mortality. Branaplam is another small molecule which has undergone clinical trials. The therapeutic merit of both compounds is based on their ability to restore body-wide inclusion of Survival Motor Neuron 2 (SMN2) exon 7 upon oral administration. Here we compare the transcriptome-wide off-target effects of these compounds in SMA patient cells. We captured concentration-dependent compound-specific changes, including aberrant expression of genes associated with DNA replication, cell cycle, RNA metabolism, cell signaling and metabolic pathways. Both compounds triggered massive perturbations of splicing events, inducing off-target exon inclusion, exon skipping, intron retention, intron removal and alternative splice site usage. Our results of minigenes expressed in HeLa cells provide mechanistic insights into how these molecules targeted towards a single gene produce different off-target effects. We show the advantages of combined treatments with low doses of risdiplam and branaplam. Our findings are instructive for devising better dosing regimens as well as for developing the next generation of small molecule therapeutics aimed at splicing modulation.

Reversible Control of RNA Splicing by Photoswitchable Small Molecules

Dynamics are intrinsic to both RNA function and structure. Yet, the available means to precisely provide RNA-based processes with spatiotemporal resolution are scarce. Here, our work pioneers a reversible approach to regulate RNA splicing within primary patient-derived cells by synthetic photoswitches. Our small molecule enables conditional real-time control at mRNA and protein levels. NMR experiments, together with theoretical calculations, photochemical characterization, fluorescence polarization measurements, and living cell-based assays, confirmed light-dependent exon inclusion as well as an increase in the target functional protein. Therefore, we first demonstrated the potential of photopharmacology modulation in splicing, tweaking the current optochemical toolkit. The timeliness on the consolidation of RNA research as the driving force toward therapeutical innovation holds the promise that our approach will contribute to redrawing the vision of RNA.

Structure and function analysis of Sam68 and hnRNP A1 synergy in the exclusion of exon 7 from SMN2 transcripts

Spinal muscular atrophy (SMA) is a neurodegenerative disease caused by the absence of a functional copy of the Survival of Motor Neuron 1 gene (SMN1). The nearly identical paralog, SMN2, cannot compensate for the loss of SMN1 because exon 7 is aberrantly skipped from most SMN2 transcripts, a process mediated by synergistic activities of Src-associated during mitosis, 68 kDa (Sam68/KHDRBS1) and heterogeneous nuclear ribonucleoprotein (hnRNP) A1. This results in the production of a truncated, nonfunctional protein that is rapidly degraded. Here, we present several crystal structures of Sam68 RNA-binding domain (RBD). Sam68-RBD forms stable symmetric homodimers by antiparallel association of helices α3 from two monomers. However, the details of domain organization and the dimerization interface differ significantly from previously characterized homologs. We demonstrate that Sam68 and hnRNP A1 can simultaneously bind proximal motifs within the central region of SMN2 (ex7). Furthermore, we show that the RNA-binding pockets of the two proteins are close to each other in their heterodimeric complex and identify contact residues using crosslinking-mass spectrometry. We present a model of the ternary Sam68·SMN2 (ex7)·hnRNP A1 complex that reconciles all available information on SMN1/2 splicing. Our findings have important implications for the etiology of SMA and open new avenues for the design of novel therapeutics to treat splicing diseases.

Interaction between a fluoroquinolone derivative KG022 and RNAs: Effect of base pairs 3′ adjacent to the bulged residues

RNA-targeted small molecules are a promising modality in drug discovery. Recently, we found that a fluoroquinolone derivative, KG022, can bind to RNAs with bulged C or G. To clarify the RNA specificity of KG022, we analyzed the effect of the base pair located at the 3′side of the bulged residue. It was found that KG022 prefers G-C and A-U base pairs at the 3′side. Solution structures of the complexes of KG022 with the four RNA molecules with bulged C or G and G-C or A-U base pairs at the 3′side of the bulged residue were determined to find that the fluoroquinolone moiety is located between two purine bases, and this may be the mechanism of the specificity. This work provides an important example of the specificity of RNA-targeted small molecules.

Role of computational and structural biology in the development of small-molecule modulators of the spliceosome

INTRODUCTION

RNA splicing is a pivotal step of eukaryotic gene expression during which the introns are excised from the precursor (pre-)RNA and the exons are joined together to form mature RNA products (i.e a protein-coding mRNA or long non-coding (lnc)RNAs). The spliceosome, a complex ribonucleoprotein machine, performs pre-RNA splicing with extreme precision. Deregulated splicing is linked to cancer, genetic, and neurodegenerative diseases. Hence, the discovery of small-molecules targeting core spliceosome components represents an appealing therapeutic opportunity.

AREA COVERED

Several atomic-level structures of the spliceosome and distinct splicing-modulators bound to its protein/RNA components have been solved. Here, we review recent advances in the discovery of small-molecule splicing-modulators, discuss opportunities and challenges for their therapeutic applicability, and showcase how structural data and/or all-atom simulations can illuminate key facets of their mechanism, thus contributing to future drug-discovery campaigns.

EXPERT OPINION

This review highlights the potential of modulating pre-RNA splicing with small-molecules, and anticipates how the synergy of computer and wet-lab experiments will enrich our understanding of splicing regulation/deregulation mechanisms. This information will aid future structure-based drug-discovery efforts aimed to expand the currently limited portfolio of selective splicing-modulators.

Gaussian Accelerated Molecular Dynamics in OpenMM

Gaussian accelerated molecular dynamics (GaMD) is a computational technique that provides both unconstrained enhanced sampling and free energy calculations of biomolecules. Here, we present the implementation of GaMD in the OpenMM simulation package and validate it on model systems of alanine dipeptide and RNA folding. For alanine dipeptide, 30 ns GaMD production simulations reproduced free energy profiles of 1000 ns conventional molecular dynamics (cMD) simulations. In addition, GaMD simulations captured the folding pathways of three hyperstable RNA tetraloops (UUCG, GCAA, and CUUG) and binding of the rbt203 ligand to the HIV-1 Tar RNA, both of which involved critical electrostatic interactions such as hydrogen bonding and base stacking. Together with previous implementations, GaMD in OpenMM will allow for wider applications in simulations of proteins, RNA, and other biomolecules.

A Chemical Biology Perspective to Therapeutic Regulation of RNA Splicing in Spinal Muscular Atrophy (SMA)

Manipulation of RNA splicing machinery has emerged as a drug modality. Here, we illustrate the potential of this novel paradigm to correct aberrant splicing events focused on the recent therapeutic advances in spinal muscular atrophy (SMA). SMA is an incurable neuromuscular disorder and at present the primary genetic cause of early infant death. This Review summarizes the exciting journey from the first reported SMA cases to the currently approved splicing-switching treatments, i.e., antisense oligonucleotides and small-molecule modifiers. We emphasize both chemical structures and molecular bases for recognition. We briefly discuss the advantages and disadvantages of these treatments and include the remaining challenges and future directions. Finally, we also predict that these success stories will contribute to further therapies for human diseases by RNA-splicing control.

GLOW: A Workflow Integrating Gaussian-Accelerated Molecular Dynamics and Deep Learning for Free Energy Profiling

We introduce a Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and free energy profiling workflow (GLOW) to predict molecular determinants and map free energy landscapes of biomolecules. All-atom GaMD-enhanced sampling simulations are first performed on biomolecules of interest. Structural contact maps are then calculated from GaMD simulation frames and transformed into images for building DL models using a convolutional neural network. Important structural contacts are further determined from DL models of attention maps of the structural contact gradients, which allow us to identify the system reaction coordinates. Finally, free energy profiles are calculated for the selected reaction coordinates through energetic reweighting of the GaMD simulations. We have also successfully demonstrated GLOW for the characterization of activation and allosteric modulation of a G protein-coupled receptor, using the adenosine A₁ receptor (A₁AR) as a model system. GLOW findings are highly consistent with previous experimental and computational studies of the A₁AR, while also providing further mechanistic insights into the receptor function. In summary, GLOW provides a systematic approach to mapping free energy landscapes of biomolecules. The GLOW workflow and its user manual can be downloaded at http://miaolab.org/GLOW.

CRISPR-mediated Enzyme Fragment Complementation Assay for Quantification of the Stability of Splice Isoforms

Small-molecule splicing modulators exemplified by an FDA-approved drug, risdiplam, are a new pharmacological modality for regulating the expression and stability of splice isoforms. We report a CRISPR-mediated enzyme fragment complementation (EFC) assay to quantify the splice isoform stability. The EFC assay harnessed a 42 amino acid split of a β-galactosidase (designate α-tag), which could be fused at the termini of the target genes using CRISPR/cas9. The α-tagged splice isoform would be quantified by measuring the enzymatic activity upon complementation with the rest of β-galactosidase. This EFC assay retained all the sequences of introns and exons of the target gene in the native genomic environment that recapitulates the cell biology of the diseases of interest. For a proof-of-concept, we developed a CRISPR-mediated EFC assay targeting the exon 7 of the survival of motor neuron 2 (SMN2) gene. The EFC assay compatible with 384-well plates robustly quantified the splicing modulation activity of small molecules. In this study, we also discovered that a coumarin derivative, compound 4, potently modulate SMN2 splicing at as low as 1.1 nM.

The prediction of protein-ligand unbinding for modern drug discovery

INTRODUCTION

Drug-target thermodynamic and kinetic information have perennially important roles in drug design. The prediction of protein-ligand unbinding, which can provide important kinetic information, in experiments continues to face great challenges. Uncovering protein-ligand unbinding through molecular dynamics simulations has become efficient and inexpensive with the progress and enhancement of computing power and sampling methods.

AREAS COVERED

In this review, various sampling methods for protein-ligand unbinding and their basic principles are firstly briefly introduced. Then, their applications in predicting aspects of protein-ligand unbinding, including unbinding pathways, dissociation rate constants, residence time and binding affinity, are discussed.

EXPERT OPINION

Although various sampling methods have been successfully applied in numerous systems, they still have shortcomings and deficiencies. Most enhanced sampling methods require researchers to possess a wealth of prior knowledge of collective variables or reaction coordinates. In addition, most systems studied at present are relatively simple, and the study of complex systems in real drug research remains greatly challenging. Through the combination of machine learning and enhanced sampling methods, prediction accuracy can be further improved, and some problems encountered in complex systems also may be solved.