While myriad non-coding RNAs are known to be essential in cellular processes and misregulated in diseases, the development of RNA-targeted small molecule probes has met with limited success. To elucidate guiding principles for selective small molecule:RNA recognition, we analyzed cheminformatic and shape-based descriptors for 104 RNA-targeted ligands with demonstrated biological activity (RNA-targeted BIoactive ligaNd Database, R-BIND). We then compared R-BIND to both FDA-approved small molecule drugs and RNA ligands without reported bioactivity. Several striking trends emerged for bioactive RNA ligands, including: i) compliance to medicinal chemistry rules; ii) distinctive structural features; and iii) enrichment in “rod-like” over other shapes. This work provides unique insights that directly facilitate the selection and synthesis of RNA-targeted libraries with the goal of efficiently identifying selective small molecule ligands for therapeutically relevant RNAs.

While the opportunities available for targeting RNA with small molecules have been widely appreciated, the challenges associated with achieving specific RNA recognition in biological systems have hindered progress and prevented many researchers from entering the field. To facilitate the discovery of RNA-targeted chemical probes and their subsequent applications, we curated the RNA-targeted BIoactive ligaNd Database (R-BIND). This collection contains an array of information on reported chemical probes that target non-rRNA and have biological activity, and analysis has led to the discovery of RNA-privileged properties. Herein, we developed an online platform to make this information freely available to the community, offering search options, a suite of tools for probe development, and an updated R-BIND data set with detailed experimental information for each probe. We repeated the previous cheminformatics analysis on the updated R-BIND list and found that the distinguishing physicochemical, structural, and spatial properties remained unchanged, despite an almost 50% increase in the database size. Further, we developed several user-friendly tools, including queries based on cheminformatic parameters, experimental details, functional groups, and substructures. In addition, a nearest neighbor algorithm can assess the similarity of user-uploaded molecules to R-BIND ligands. These tools and resources can be used to design small molecule libraries, optimize lead ligands, or select targets, probes, assays, and control experiments. Chemical probes are critical to the study and discovery of novel functions for RNA, and we expect this resource to greatly assist researchers in exploring and developing successful RNA-targeted probes.

While amyriad non-coding RNAs are knowntobe essential in cellular processes and misregulated in diseases,the development of RNA-targeted small molecule probes has met with limited success.T oe lucidate the guiding principles for selective small molecule/RNArecognition, we analyzed cheminformatic and shape-based descriptors for 104 RNA-targeted ligands with demonstrated biological activity (RNA-targeted BIoactive ligaNd Database,R -BIND). We then compared R-BIND to both FDA-approved small molecule drugs and RNA ligands without reported bioactivity.S everal striking trends emerged for bioactive RNAligands,including:1)Compliance to medicinal chemistry rules,2 )distinctive structural features, and 3) enrichment in rod-like shapes over others.T his work provides unique insights that directly facilitate the selection and synthesis of RNA-targeted libraries with the goal of efficiently identifying selective small molecule ligands for therapeutically relevant RNAs.Supportinginformation and the ORCID identification number(s) for the author(s) of this article can be found under: https://doi.

Over the past decade, the RNA revolution has revealed thousands of non-coding RNAs that are essential for cellular regulation and are misregulated in disease. While the development of methods and tools to study these RNAs has been challenging, the power and promise of small molecule chemical probes is increasingly recognized. To harness existing knowledge, we compiled a list of 116 ligands with reported activity against RNA targets in biological systems (R-BIND). In this survey, we examine the RNA targets, design and discovery strategies, and chemical probe characterization techniques of these ligands. We discuss the applicability of current tools to identify and evaluate RNA-targeted chemical probes, suggest criteria to assess the quality of RNA chemical probes and targets, and propose areas where new tools are particularly needed. We anticipate that this knowledge will expedite the discovery of RNA-targeted ligands and the next phase of the RNA revolution.

Three-dimensional RNA structures are notoriously difficult to determine, and the link between secondary structure and RNA conformation is only beginning to be understood. These challenges have hindered the identification of guiding principles for small molecule:RNA recognition. We herein demonstrate that the strong and differential binding ability of aminoglycosides to RNA structures can be used to classify five canonical RNA secondary structure motifs through principal component analysis (PCA). In these analyses, the aminoglycosides act as receptors, while RNA structures labeled with a benzofuranyluridine fluorophore act as analytes. Complete (100%) predictive ability for this RNA training set was achieved by incorporating two exhaustively guanidinylated aminoglycosides into the receptor library. The PCA was then externally validated using biologically relevant RNA constructs. In bulge-stem-loop constructs of HIV-1 transactivation response element (TAR) RNA, we achieved nucleotide-specific classification of two independent secondary structure motifs. Furthermore, examination of cheminformatic parameters and PCA loading factors revealed trends in aminoglycoside:RNA recognition, including the importance of shape-based discrimination, and suggested the potential for size and sequence discrimination within RNA structural motifs. These studies present a new approach to classifying RNA structure and provide direct evidence that RNA topology, in addition to sequence, is critical for the molecular recognition of RNA.

Selenium (Se) is an essential micronutrient that can be found at toxic concentrations in surface waters contaminated by runoff from agriculture and coal mining. Zebrafish (Danio rerio) embryos were exposed to aqueous Se in the form of selenate, selenite, and L-selenomethionine (SeMet) in an attempt to determine if oxidative stress plays a role in selenium embryo toxicity. Selenate and selenite exposure did not induce embryo deformities (lordosis and craniofacial malformation). L-selenomethionine, however, induced significantly higher deformity rates at 100 μg/L compared to controls. SeMet exposure induced a dose-dependent increase in the catalytic subunit of glutamate-cysteine ligase (gclc) and reached an 11.7-fold increase at 100 μg/L. SeMet exposure also reduced concentrations of TGSH, RGSH, and the TGSH:GSSG ratio. Pretreatment with 100 μM N-acetylcysteine (NAC) significantly reduced deformities in the zebrafish embryos secondarily treated with 400 μg/L SeMet from approximately 50% to 10% as well as rescued all three of the significant glutathione level differences seen with SeMet alone. Selenite exposure induced a 6.6-fold increase in expression of the glutathione-S-transferase pi class 2 (gstp2) gene, which is involved in xenobiotic transformation and possibly oxidative stress. These results suggest that aqueous exposure to SeMet can induce significant embryonic teratogenesis in zebrafish that are at least partially attributed to oxidative stress.

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The original publication incorrectly states that manganese superoxide dismutase-2 (sod2) was measured during the experiment. Copper/zinc superoxide dismutase-1 (sod1) was actually measured using the following primers for sod1 (GeneBank ID Y12236): forward primer 5 0-CTA GCC CGC TGA CAT TAC ATC-3 0 , reverse primer 5 0-TTG CCC ACA TAG AAA TGC AC-3 0. The primer sequences listed in Table 1 for sod2 are incorrect.