Synthetic RNA Modulators in Drug Discovery

Stacking Interactions of Druglike Heterocycles with Nucleobases

Stacking interactions contribute significantly to the interaction of small molecules with RNA, and harnessing the power of these interactions will likely prove important in the development of RNA-targeting inhibitors. To this end, we present a comprehensive computational analysis of stacking interactions between a set of 54 druglike heterocycles and the natural nucleobases. We first show that heterocycle choice can tune the strength of stacking interactions with nucleobases over a large range and that heterocycles favor stacked geometries that cluster around a discrete set of stacking loci characteristic of each nucleobase. Symmetry-adapted perturbation theory results indicate that the strengths of these interactions are modulated primarily by electrostatic and dispersion effects. Based on this, we present a multivariate predictive model of the maximum strength of stacking interactions between a given heterocycle and nucleobase that depends on molecular descriptors derived from the electrostatic potential. These descriptors can be readily computed using density functional theory or predicted directly from atom connectivity (e.g., SMILES). This model is used to predict the maximum possible stacking interactions of a set of 1854 druglike heterocycles with the natural nucleobases. Finally, we show that trivial modifications of standard (fixed-charge) molecular mechanics force fields reduce errors in predicted stacking interaction energies from around 2 kcal/mol to below 1 kcal/mol, providing a pragmatic means of predicting more reliable stacking interaction energies using existing computational workflows. We also analyze the stacking interactions between ribocil and a bacterial riboswitch, showing that two of the three aromatic heterocyclic components engage in near-optimal stacking interactions with binding site nucleobases.

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.

Long Non-Coding RNAs in Colorectal Cancer: Navigating the Intersections of Immunity, Intercellular Communication, and Therapeutic Potential

This comprehensive review elucidates the intricate roles of long non-coding RNAs (lncRNAs) within the colorectal cancer (CRC) microenvironment, intersecting the domains of immunity, intercellular communication, and therapeutic potential. lncRNAs, which are significantly involved in the pathogenesis of CRC, immune evasion, and the treatment response to CRC, have crucial implications in inflammation and serve as promising candidates for novel therapeutic strategies and biomarkers. This review scrutinizes the interaction of lncRNAs with the Consensus Molecular Subtypes (CMSs) of CRC, their complex interplay with the tumor stroma affecting immunity and inflammation, and their conveyance via extracellular vesicles, particularly exosomes. Furthermore, we delve into the intricate relationship between lncRNAs and other non-coding RNAs, including microRNAs and circular RNAs, in mediating cell-to-cell communication within the CRC microenvironment. Lastly, we propose potential strategies to manipulate lncRNAs to enhance anti-tumor immunity, thereby underlining the significance of lncRNAs in devising innovative therapeutic interventions in CRC.

Synthesis of Bleomycin-Inspired RNA Ligands Targeting the Biogenesis of Oncogenic miRNAs

Noncoding RNAs (ncRNAs) play pivotal roles in the regulation of gene expression and represent a promising target for the development of new therapeutic approaches. Among these ncRNAs, microRNAs (miRNAs or miRs) are involved in the regulation of gene expression, and their dysregulation has been linked to several diseases such as cancers. Indeed, oncogenic miRNAs are overexpressed in cancer cells, thus promoting tumorigenesis and maintenance of cancer stem cells that are resistant to chemotherapy and often responsible for therapeutic failure. Here, we describe the design and synthesis of new small-molecule RNA binders able to inhibit the biogenesis of oncogenic miRNAs and target efficiently cancer stem cells. Through the biochemical study of their interaction with the target and thanks to intracellular assays, we describe the structure-activity relationships for this new series of RNA ligands, and we identify compounds bearing a very promising antiproliferative activity against cancer stem cells.

Recognizing the power of machine learning and other computational methods to accelerate progress in small molecule targeting of RNA

RNA structures regulate a wide range of processes in biology and disease, yet small molecule chemical probes or drugs that can modulate these functions are rare. Machine learning and other computational methods are well poised to fill gaps in knowledge and overcome the inherent challenges in RNA targeting, such as the dynamic nature of RNA and the difficulty of obtaining RNA high-resolution structures. Successful tools to date include principal component analysis, linear discriminate analysis, k-nearest neighbor, artificial neural networks, multiple linear regression, and many others. Employment of these tools has revealed critical factors for selective recognition in RNA:small molecule complexes, predictable differences in RNA- and protein-binding ligands, and quantitative structure activity relationships that allow the rational design of small molecules for a given RNA target. Herein we present our perspective on the value of using machine learning and other computation methods to advance RNA:small molecule targeting, including select examples and their validation as well as necessary and promising future directions that will be key to accelerate discoveries in this important field.

Innovations in targeting RNA by fragment-based ligand discovery

A subset of functional regions within large RNAs fold into complex structures able to bind small-molecule ligands with high affinity and specificity. Fragment-based ligand discovery (FBLD) offers notable opportunities for discovery and design of potent small molecules that bind pockets in RNA. Here we share an integrated analysis of recent innovations in FBLD, emphasizing opportunities resulting from fragment elaboration via both linking and growing. Analysis of elaborated fragments emphasizes that high-quality interactions form with complex tertiary structures in RNA. FBLD-inspired small molecules have been shown to modulate RNA functions by competitively inhibiting protein binding and by selectively stabilizing dynamic RNA states. FBLD is creating a foundation to interrogate the relatively unknown structural space for RNA ligands and for discovery of RNA-targeted therapeutics.

Small-Molecule 3D Ligand for RNA Recognition: Tuning Selectivity through Scaffold Hopping

Targeting RNAs with small molecules is considered the next frontier for drug discovery. In this context, the development of compounds capable of binding RNA structural motifs of low complexity with high affinity and selectivity would greatly expand the number of targets of potential therapeutic value. In this study, we demonstrate that tuning the three-dimensional shape of promiscuous nucleic acid binders is a valuable strategy for the design of new selective RNA ligands. Indeed, starting from a known cyanine, the simple replacement of a phenyl ring with a [2.2]paracyclophane moiety led to a new compound able to discriminate between nucleic acids showing different structural characteristics with a marked affinity and selectivity for an octahairpin loop RNA sequence. This shape modification also affected the in cellulo behavior of the cyanine. These results suggest that scaffold hopping is a valuable strategy to improve the selectivity of RNA/small-molecule interactions and highlight the need to explore a new chemical space for the design of selective RNA ligands.

Discovery of a Novel Small-Molecule Inhibitor Disrupting TRBP-Dicer Interaction against Hepatocellular Carcinoma via the Modulation of microRNA Biogenesis

MicroRNAs (miRNAs) are key players in human hepatocellular carcinoma (HCC) tumorigenesis. Therefore, small molecules targeting components of miRNA biogenesis may provide new therapeutic means for HCC treatment. By a high-throughput screening and structural simplification, we identified a small molecule, CIB-3b, which suppresses the growth and metastasis of HCC in vitro and in vivo by modulating expression profiles of miRNAome and proteome in HCC cells. Mechanistically, CIB-3b physically binds to transactivation response (TAR) RNA-binding protein 2 (TRBP) and disrupts the TRBP-Dicer interaction, thereby altering the activity of Dicer and mature miRNA production. Structure-activity relationship study via the synthesis of 45 CIB-3b derivatives showed that some compounds exhibited a similar inhibitory effect on miRNA biogenesis to CIB-3b. These results support TRBP as a potential therapeutic target in HCC and warrant further development of CIB-3b along with its analogues as a novel therapeutic strategy for the treatment of HCC.

A low-cost 3D-printable differential scanning fluorometer for protein and RNA melting experiments

Differential scanning fluorimetry (DSF) is a widely used biophysical technique with applications to drug discovery and protein biochemistry. DSF experiments are commonly performed in commercial real-time polymerase chain reaction (qPCR) thermal cyclers or nanoDSF instruments. Here, we report the construction, validation, and example applications of an open-source DSF system for 176 €, which, in addition to protein-DSF experiments, also proved to be a versatile biophysical instrument for less conventional RNA-DSF experiments. Using 3D-printed parts made of polyoxymethylene, we were able to fabricate a thermostable machine chassis for protein-melting experiments. The combination of blue high-power LEDs as the light source and stage light foil as filter components was proven to be a reliable and affordable alternative to conventional optics equipment for the detection of SYPRO Orange or Sybr Gold fluorescence. The ESP32 microcontroller is the core piece of this openDSF instrument, while the in-built I²S interface was found to be a powerful analog-to-digital converter for fast acquisition of fluorescence and temperature data. Airflow heating and inline temperature control by thermistors enabled high-accuracy temperature management in PCR tubes (±0.1 °C) allowing us to perform high-resolution thermal shift assays (TSA) from exemplary biological applications.

Development of 2-deoxystreptamine-nucleobase conjugates for the inhibition of oncogenic miRNA production

The discovery of new original scaffolds for selective RNA targeting is one of the main challenges of current medicinal chemistry since therapeutically relevant RNAs represent potential targets for a number of pathologies. Recent efforts have been devoted to the search for RNA ligands targeting the biogenesis of oncogenic miRNAs whose overexpression has been directly linked to the development of various cancers. In this work, we developed a new series of RNA ligands for the targeting of oncogenic miRNA biogenesis based on the 2-deoxystreptamine scaffold. The latter is part of the aminoglycoside neomycin and is known to play an essential role in the RNA interaction of this class of RNA binders. 2-deoxystreptamine was thus conjugated to natural and artificial nucleobases to obtain new binders of the oncogenic miR-372 precursor (pre-miR-372). We identified some conjugates exhibiting a similar biological activity to previously synthesized neomycin analogs and studied their mode of binding with the target pre-miR-372.