RNA modulation via small molecules is a novel approach in pharmacotherapies, where the determination of the structural properties of RNA motifs is considered a promising way to develop drugs capable of targeting RNA structures to control diseases. However, due to the complexity and dynamic nature of RNA molecules, the determination of RNA structures using experimental approaches is not always feasible, and computational models employing force fields can provide important insight. The quality of the force field will determine how well the predictions are compared to experimental observables. Stacking in nucleic acids is one such structural property, originating mainly from London dispersion forces, which are quantum mechanical and are included in molecular mechanics force fields through nonbonded interactions. Geometric descriptions are utilized to decide if two residues are stacked and hence to calculate the stacking free energies for RNA dinucleoside monophosphates (DNMPs) through statistical mechanics for comparison with experimental thermodynamics data. Here, we benchmark four different stacking definitions using molecular dynamics (MD) trajectories for 16 RNA DNMPs produced by two different force fields (RNA-IL and ff99OL3) and show that our stacking definition better correlates with the experimental thermodynamics data. While predictions within an accuracy of 0.2 kcal/mol at 300 K were observed in RNA CC, CU, UC, AG, GA, and GG, stacked states of purine−pyrimidine and pyrimidine− purine DNMPs, respectively, were typically underpredicted and overpredicted. Additionally, population distributions of RNA UU DNMPs were poorly predicted by both force fields, implying a requirement for further force field revisions. We further discuss the differences predicted by each RNA force field. Finally, we show that discrete path sampling (DPS) calculations can provide valuable information and complement the MD simulations. We propose the use of experimental thermodynamics data for RNA DNMPs as benchmarks for testing RNA force fields.

RNA is challenging to target with bioactive small molecules, particularly those of low molecular weight that bind with sufficient affinity and specificity. In this report, we developed a platform to address this challenge, affording a novel bioactive interaction. An RNA-focused small-molecule fragment collection (n = 2500) was constructed by analyzing features in all publicly reported compounds that bind RNA, the largest collection of RNA-focused fragments to date. The RNA-binding landscape for each fragment was studied by using a library-versus-library selection with an RNA library displaying a discrete structural element, probing over 12.8 million interactions, the greatest number of interactions between fragments and biomolecules probed experimentally. Mining of this dataset across the human transcriptome defined a drug-like fragment that potently and specifically targeted the microRNA-372 hairpin precursor, inhibiting its processing into the mature, functional microRNA and alleviating invasive and proliferative oncogenic phenotypes in gastric cancer cells. Importantly, this fragment has favorable properties, including an affinity for the RNA target of 300 ± 130 nM, a molecular weight of 273 Da, and quantitative estimate of drug-likeness (QED) score of 0.8. (For comparison, the mean QED of oral medicines is 0.6 ± 0.2). Thus, these studies demonstrate that a low-molecular weight, fragment-like compound can specifically and potently modulate RNA targets.

A solid-phase DNA-encoded library (DEL) was studied for binding the RNA repeat expansion r(CUG)exp, the causative agent of the most common form of adult-onset muscular dystrophy, myotonic dystrophy type 1 (DM1). A variety of uncharged and novel RNA binders were identified to selectively bind r(CUG)exp by using a two-color flow cytometry screen. The cellular activity of one binder was augmented by attaching it with a module that directly cleaves r(CUG)exp. In DM1 patient-derived muscle cells, the compound specifically bound r(CUG)exp and allele-specifically eliminated r(CUG)exp, improving disease-associated defects. The approaches herein can be used to identify and optimize ligands and bind RNA that can be further augmented for functionality including degradation.

The hexanucleotide repeat expansion GGGGCC [r­(G4C2)exp] within intron 1 of C9orf72 causes genetically defined amyotrophic lateral sclerosis and frontotemporal dementia, collectively named c9ALS/FTD. , the repeat expansion causes neurodegeneration via deleterious phenotypes stemming from r­(G4C2)exp RNA gain- and loss-of-function mechanisms. The r­(G4C2)exp RNA folds into both a hairpin structure with repeating 1 × 1 nucleotide GG internal loops and a G-quadruplex structure. Here, we report the identification of a small molecule (CB253) that selectively binds the hairpin form of r­(G4C2)exp. Interestingly, the small molecule binds to a previously unobserved conformation in which the RNA forms 2 × 2 nucleotide GG internal loops, as revealed by a series of binding and structural studies. NMR and molecular dynamics simulations suggest that the r­(G4C2)exp hairpin interconverts between 1 × 1 and 2 × 2 internal loops through the process of strand slippage. We provide experimental evidence that CB253 binding indeed shifts the equilibrium toward the 2 × 2 GG internal loop conformation, inhibiting mechanisms that drive c9ALS/FTD pathobiology, such as repeat-associated non-ATG translation formation of stress granules and defective nucleocytoplasmic transport in various cellular models of c9ALS/FTD.