The competitive landscape of the dsRNA world.

The ability to sense and respond to infection is essential for life. Viral infection produces double-stranded RNAs (dsRNAs) that are sensed by proteins that recognize the structure of dsRNA. This structure-based recognition of viral dsRNA allows dsRNA sensors to recognize infection by many viruses, but it comes at a cost-the dsRNA sensors cannot always distinguish between "self" and "nonself" dsRNAs. "Self" RNAs often contain dsRNA regions, and not surprisingly, mechanisms have evolved to prevent aberrant activation of dsRNA sensors by "self" RNA. Here, we review current knowledge about the life of endogenous dsRNAs in mammals-the biosynthesis and processing of dsRNAs, the proteins they encounter, and their ultimate degradation. We highlight mechanisms that evolved to prevent aberrant dsRNA sensor activation and the importance of competition in the regulation of dsRNA sensors and other dsRNA-binding proteins.

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

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

Synthesis and reactivity of donor stabilized thionylium (SO2+) dications.

Robust mono-, di-, and tridentate base-stabilized thionylium (SO2+) dications were synthesized from the treatment of SOCl2 with Me3SiO3SCF3 and pyridine-based ligands. Computational and experimental data are consistent with Lewis acidities comparable to BF3 and PF5 and these compounds were shown to activate C-F bonds of fluoroalkanes. These dications also react with Ph3PO and CuO to effect O2- abstraction in an overall redox-neutral deoxygenation process driven by the evolution of SO2.

Analyses of human cancer driver genes uncovers evolutionarily conserved RNA structural elements involved in posttranscriptional control.

Experimental breakthroughs have provided unprecedented insights into the genes involved in cancer. The identification of such cancer driver genes is a major step in gaining a fuller understanding of oncogenesis and provides novel lists of potential therapeutic targets. A key area that requires additional study is the posttranscriptional control mechanisms at work in cancer driver genes. This is important not only for basic insights into the biology of cancer, but also to advance new therapeutic modalities that target RNA-an emerging field with great promise toward the treatment of various cancers. In the current study we performed an in silico analysis on the transcripts associated with 800 cancer driver genes (10,390 unique transcripts) that identified 179,190 secondary structural motifs with evidence of evolutionarily ordered structures with unusual thermodynamic stability. Narrowing to one transcript per gene, 35,426 predicted structures were subjected to phylogenetic comparisons of sequence and structural conservation. This identified 7,001 RNA secondary structures embedded in transcripts with evidence of covariation between paired sites, supporting structure models and suggesting functional significance. A select set of seven structures were tested in vitro for their ability to regulate gene expression; all were found to have significant effects. These results indicate potentially widespread roles for RNA structure in posttranscriptional control of human cancer driver genes.

Prediction and analysis of functional RNA structures within the integrative genomics viewer.

In recent years, interest in RNA secondary structure has exploded due to its implications in almost all biological functions and its newly appreciated capacity as a therapeutic agent/target. This surge of interest has driven the development and adaptation of many computational and biochemical methods to discover novel, functional structures across the genome/transcriptome. To further enhance efforts to study RNA secondary structure, we have integrated the functional secondary structure prediction tool ScanFold, into IGV. This allows users to directly perform structure predictions and visualize results-in conjunction with probing data and other annotations-in one program. We illustrate the utility of this new tool by mapping the secondary structural landscape of the human MYC precursor mRNA. We leverage the power of vast 'omics' resources by comparing individually predicted structures with published data including: biochemical structure probing, RNA binding proteins, microRNA binding sites, RNA modifications, single nucleotide polymorphisms, and others that allow functional inferences to be made and aid in the discovery of potential drug targets. This new tool offers the RNA community an easy to use tool to find, analyze, and characterize RNA secondary structures in the context of all available data, in order to find those worthy of further analyses.

9-BBN and chloride catalyzed reduction of chlorophosphines to phosphines and diphosphines.

The commercially available Lewis acid, 9-BBN and Lewis basic [Et4N]Cl are used as catalysts for the reduction of chlorophosphines R2PCl in the presence of phenylsilane. Aryl-chlorophosphines afford primarily diphosphines (P2R4) while secondary phosphines predominate for alkyl-substituted precursors. Use of the combined catalysts leads to reduced reaction time and temperature, providing a rapid, scalable, and facile protocol for the preparation of diphosphines or secondary phosphines.

Multiresponsive Cyclometalated Crown Ether Bearing a Platinum(II) Metal Center.

Multiresponsive materials can adapt to numerous changes in their local environment, which makes them highly valuable for various applications. Although nanostructured and polymeric multiresponsive materials are plentiful, small-molecule analogues are scarce. This work presents a compact cyclometalated platinum(II) complex that bears a crown ether cavity (18C6-PtII); the intimate ring/emitter connectivity is key to unlocking multiresponsiveness. Complex 18C6-PtII responds to (i) cationic guests, producing changes in luminescence in both solution and the solid state, (ii) solvent molecules, which perturb the packing of the complex in the solid state and cause reversible color changes, and (iii) solvent polarity, which leads to controlled aggregation. These responses may enable 18C6-PtII to function as a sensor for ions and solvents, or as a functional unit for the fabrication of hybrid supramolecular polymers and metallogels.

Bipyridinium and Phenanthrolinium Dications for Metal-Free Hydrodefluorination: Distinctive Carbon-Based Reactivity.

The development of novel Lewis acids derived from bipyridinium and phenanthrolinium dications is reported. Calculations of Hydride Ion Affinity (HIA) values indicate high carbon-based Lewis acidity at the ortho and para positions. This arises in part from extensive LUMO delocalization across the aromatic backbones. Species [C10 H6 R2 N2 CH2 CH2 ]2+ (R=H [1 a]2+ , Me [1 f]2+ , tBu [1 g]2+ ), and [C12 H4 R4 N2 CH2 CH2 ]2+ (R=H [2 a]2+ , Me [2 b]2+ ) were prepared and evaluated for use in the initiation of hydrodefluorination (HDF) catalysis. Compound [2 a]2+ proved highly effective towards generating catalytically active silylium cations via Lewis acid-mediated hydride abstraction from silane. This enabled the HDF of a range of aryl- and alkyl- substituted sp3 (C-F) bonds under mild conditions. The protocol was also adapted to effect the deuterodefluorination of cis-2,4,6-(CF3 )3 C6 H9 . The dications are shown to act as hydride acceptors with the isolation of neutral species C16 H14 N2 (3 a) and C16 H10 Me4 N2 (3 b) and monocationic species [C14 H13 N2 ]+ ([4 a]+ ) and [C18 H21 N2 ]+ ([4 b]+ ). Experimental and computational data provide further support that the dications are initiators in the generation of silylium cations.

A map of the SARS-CoV-2 RNA structurome.

SARS-CoV-2 has exploded throughout the human population. To facilitate efforts to gain insights into SARS-CoV-2 biology and to target the virus therapeutically, it is essential to have a roadmap of likely functional regions embedded in its RNA genome. In this report, we used a bioinformatics approach, ScanFold, to deduce the local RNA structural landscape of the SARS-CoV-2 genome with the highest likelihood of being functional. We recapitulate previously-known elements of RNA structure and provide a model for the folding of an essential frameshift signal. Our results find that SARS-CoV-2 is greatly enriched in unusually stable and likely evolutionarily ordered RNA structure, which provides a large reservoir of potential drug targets for RNA-binding small molecules. Results are enhanced via the re-analyses of publicly-available genome-wide biochemical structure probing datasets that are broadly in agreement with our models. Additionally, ScanFold was updated to incorporate experimental data as constraints in the analysis to facilitate comparisons between ScanFold and other RNA modelling approaches. Ultimately, ScanFold was able to identify eight highly structured/conserved motifs in SARS-CoV-2 that agree with experimental data, without explicitly using these data. All results are made available via a public database (the RNAStructuromeDB: https://structurome.bb.iastate.edu/sars-cov-2) and model comparisons are readily viewable at https://structurome.bb.iastate.edu/sars-cov-2-global-model-comparisons.

Targeting the SARS-CoV-2 RNA Genome with Small Molecule Binders and Ribonuclease Targeting Chimera (RIBOTAC) Degraders.

COVID-19 is a global pandemic, thus requiring multiple strategies to develop modalities against it. Herein, we designed multiple bioactive small molecules that target a functional structure within the SARS-CoV-2's RNA genome, the causative agent of COVID-19. An analysis to characterize the structure of the RNA genome provided a revised model of the SARS-CoV-2 frameshifting element, in particular its attenuator hairpin. By studying an RNA-focused small molecule collection, we identified a drug-like small molecule (C5) that avidly binds to the revised attenuator hairpin structure with a K d of 11 nM. The compound stabilizes the hairpin's folded state and impairs frameshifting in cells. The ligand was further elaborated into a ribonuclease targeting chimera (RIBOTAC) to recruit a cellular ribonuclease to destroy the viral genome (C5-RIBOTAC) and into a covalent molecule (C5-Chem-CLIP) that validated direct target engagement and demonstrated its specificity for the viral RNA, as compared to highly expressed host mRNAs. The RIBOTAC lead optimization strategy improved the bioactivity of the compound at least 10-fold. Collectively, these studies demonstrate that the SARS-CoV-2 RNA genome should be considered druggable.

A survey of RNA secondary structural propensity encoded within human herpesvirus genomes: global comparisons and local motifs.

There are nine herpesviruses known to infect humans, of which Epstein-Barr virus (EBV) is the most widely distributed (>90% of adults infected). This ubiquitous virus is implicated in a variety of cancers and autoimmune diseases. Previous analyses of the EBV genome revealed numerous regions with evidence of generating unusually stable and conserved RNA secondary structures and led to the discovery of a novel class of EBV non-coding (nc)RNAs: the stable intronic sequence (sis)RNAs. To gain a better understanding of the roles of RNA structure in EBV biology and pathogenicity, we revisit EBV using recently developed tools for genome-wide motif discovery and RNA structural characterization. This corroborated previous results and revealed novel motifs with potential functionality; one of which has been experimentally validated. Additionally, since many herpesviruses increasingly rival the seroprevalence of EBV (VZV, HHV-6 and HHV-7 being the most notable), analyses were expanded to include all sequenced human Herpesvirus RefSeq genomes, allowing for genomic comparisons. In total 10 genomes were analyzed, for EBV (types 1 and 2), HCMV, HHV-6A, HHV-6B, HHV-7, HSV-1, HSV-2, KSHV, and VZV. All resulting data were archived in the RNAStructuromeDB (https://structurome.bb.iastate.edu/herpesvirus) to make them available to a wide array of researchers.

Design of small molecules targeting RNA structure from sequence.

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

An in silico map of the SARS-CoV-2 RNA Structurome.

SARS-CoV-2 is a positive-sense single-stranded RNA virus that has exploded throughout the global human population. This pandemic coronavirus strain has taken scientists and public health researchers by surprise and knowledge of its basic biology (e.g. structure/function relationships in its genomic, messenger and template RNAs) and modes for therapeutic intervention lag behind that of other human pathogens. In this report we used a recently-developed bioinformatics approach, ScanFold, to deduce the RNA structural landscape of the SARS-CoV-2 transcriptome. We recapitulate known elements of RNA structure and provide a model for the folding of an essential frameshift signal. Our results find that the SARS-CoV-2 is greatly enriched in unusually stable and likely evolutionarily ordered RNA structure, which provides a huge reservoir of potential drug targets for RNA-binding small molecules. Our results also predict regions that are accessible for intermolecular interactions, which can aid in the design of antisense therapeutics. All results are made available via a public database (the RNAStructuromeDB) where they may hopefully drive drug discovery efforts to inhibit SARS-CoV-2 pathogenesis.

Plasmodium falciparum translational machinery condones polyadenosine repeats.

Plasmodium falciparum is a causative agent of human malaria. Sixty percent of mRNAs from its extremely AT-rich (81%) genome harbor long polyadenosine (polyA) runs within their ORFs, distinguishing the parasite from its hosts and other sequenced organisms. Recent studies indicate polyA runs cause ribosome stalling and frameshifting, triggering mRNA surveillance pathways and attenuating protein synthesis. Here, we show that P. falciparum is an exception to this rule. We demonstrate that both endogenous genes and reporter sequences containing long polyA runs are efficiently and accurately translated in P. falciparum cells. We show that polyA runs do not elicit any response from No Go Decay (NGD) or result in the production of frameshifted proteins. This is in stark contrast to what we observe in human cells or T. thermophila, an organism with similar AT-content. Finally, using stalling reporters we show that Plasmodium cells evolved not to have a fully functional NGD pathway.

Isolable Anionic, Neutral and Cationic Radicals from Reactions of N,N'-Dimesityldiamidocarbene and Lewis Acids.

B(C6 F5 )3 undergoes nucleophilic attack by N,N'-dimesityldiamidocarbene (DAC) with fluoride transfer to the boron center, resulting in a new zwitterion (1). This B-F fluoride can be replaced or abstracted to give the corresponding hydride (2) or triflate (3) derivatives or the corresponding cation (4). These species are reduced with KC8 or Cp2 Co to give isolable anionic and neutral radicals (5-8). Similarly, the [Ph3 C] cation undergoes nucleophilic attack by DAC resulting in the spontaneous formation of the radical cation (9).

Structural Elucidation of Selective Solvatochromism in a Responsive-at-Metal Cyclometalated Platinum(II) Complex.

We report the synthesis, characterization, and spectroscopic investigations of a new responsive-at-metal cyclometalated platinum(II) complex. With mild chemical oxidants and reductants, it was possible to obtain the same complex in three different oxidation states and each of these complexes was structurally characterized by single-crystal X-ray diffraction. We discovered that the platinum(II) complex displays strong solvatochromism in the solid state, which can be attributed to modulation of Pt⋅⋅⋅Pt interactions that results in switching between optical and photoluminescent states. Incorporating responsive-at-metal species as dynamic components in nanostructured materials might facilitate response amplification, sensing, actuation, or self-healing processes.

Cardiorespiratory Fitness Is Associated With Better Cardiometabolic Health and Lower PTSD Severity in Post-9/11 Veterans.

INTRODUCTION: Post-traumatic stress disorder (PTSD) is associated with an increased risk of cardiovascular and metabolic diseases and physical inactivity. Cardiorespiratory fitness (CRF), which is modifiable by physical activity, is a strong independent predictor of cardiometabolic health. However, the relationship between CRF and cardiometabolic health in veterans with PTSD is unknown. Thus, this study aimed to explore the cross-sectional relationships among CRF, indices of cardiometabolic health (ie, HbA1c, blood lipids, blood pressure, waist-hip ratio, and body mass index), and PTSD severity in veterans with PTSD. MATERIALS AND METHODS: This study was approved by the local Institutional Review Board. All participants were informed of the study risks and provided consent prior to participation. Participants (n = 13) completed a cardiopulmonary exercise test, a fasting blood draw, and the Clinician Administered PTSD Scale. Correlations between CRF and cardiometabolic health were examined with Spearman's rank correlations, and differences in PTSD symptom severity were explored as a function of CRF (ie, low-to-moderate vs. high CRF), using multiple linear regression. RESULTS: Peak oxygen uptake ($\dot{\mathrm{V}}$O2peak) was correlated with high-density lipoproteins rho = 0.60, P = 0.04 and diastolic blood pressure rho = -0.56, P = 0.05. Ventilatory threshold was correlated with HbA1c rho = -0.61, P = 0.03 and diastolic blood pressure rho = -0.56, P = 0.05. Higher CRF was associated with lower total PTSD severity standardized ß = -0.84, P = 0.01, adjusted R2 = 0.47, total Cluster C symptoms (avoidance/numbing) ß = -0.71, P = 0.02, adjusted R2 = 0.49, and total Cluster D symptoms (hyperarousal) ß = -0.89, P = 0.01, adjusted R2 = 0.41, while adjusting for age and smoking status. CONCLUSIONS: These preliminary findings suggest that CRF and by proxy physical activity may be important factors in understanding the increased risk of cardiovascular and metabolic disease associated with PTSD.

Structure-Specific Cleavage of an RNA Repeat Expansion with a Dimeric Small Molecule Is Advantageous over Sequence-Specific Recognition by an Oligonucleotide.

Myotonic dystrophy type 2 (DM2) is a genetically defined muscular dystrophy that is caused by an expanded repeat of r(CCUG) [r(CCUG)exp] in intron 1 of a CHC-type zinc finger nucleic acid binding protein (CNBP) pre-mRNA. Various mechanisms contribute to DM2 pathology including pre-mRNA splicing defects caused by sequestration of the RNA splicing regulator muscleblind-like-1 (MBNL1) by r(CCUG)exp. Herein, we study the biological impacts of the molecular recognition of r(CCUG)exp's structure by a designer dimeric small molecule that directly cleaves the RNA in patient-derived cells. The compound is comprised of two RNA-binding modules conjugated to a derivative of the natural product bleomycin. Careful design of the chimera affords RNA-specific cleavage, as attachment of the bleomycin cleaving module was done in a manner that disables DNA cleavage. The chimeric cleaver is more potent than the parent binding compound for alleviating DM2-associated defects. Importantly, oligonucleotides targeting the r(CCUG)exp sequence for cleavage exacerbate DM2 defects due to recognition of a short r(CCUG) sequence that is embedded in CNBP, argonaute-1 (AGO1), and MBNL1, reducing their levels. The latter event causes a greater depletion of functional MBNL1 than the amount already sequestered by r(CCUG)exp. Thus, compounds targeting RNA structures can have functional advantages over oligonucleotides that target the sequence in some disease settings, particularly in DM2.

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

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

Mapping the RNA structural landscape of viral genomes.

Functional RNA structures are prevalent in viral genomes, and have been shown to play roles in almost every aspect of their biology. However, the majority of viral RNA remains structurally uncharacterized. This is likely to remain true as the cost of sequencing decreases much faster than the cost of structural characterizations. Because of this, there is a need for rapid, inexpensive methods to highlight regions of viral RNA which are ideal candidates for structure-function analyses. The ScanFold method was developed as a single sequence alternative to traditional RNA structural motif discovery pipelines, which rely heavily on well curated sequence alignments to identify conserved RNA structures. ScanFold focuses on identifying (based on their more stable than expected folding energies) the most likely functional structures encoded within a single large RNA sequence, while allowing predicted motifs to be tested for evidence of structural conservation later. Decoupling these processes can be a benefit to researchers studying viruses lacking the ideal phylogenetic depth to yield evidence of structural conservation. Here, we demonstrate how the most significant ScanFold predicted structures correspond to higher base pairing probabilities, SHAPE reactivities, and predict known functional structures within the ZIKV and HIV-1 genomes with accuracy. Best practices and examples are also shown to aid users in utilizing ScanFold for their own systems of interest. ScanFold is available as a Webserver (https://mosslabtools.bb.iastate.edu/scanfold) or can be downloaded (https://github.com/moss-lab/ScanFold) and run locally.