Computational investigation of RNA CUG repeats responsible for myotonic dystrophy 1

NMR structures of small molecules bound to a model of an RNA CUG repeat expansion

Trinucleotide repeat expansions fold into long, stable hairpins and cause a variety of incurable RNA gain-of-function diseases such as Huntington's disease, the myotonic dystrophies, and spinocerebellar ataxias. One approach for treating these diseases is to bind small molecules to the structured RNAs. Both Huntington's disease-like 2 (HDL2) and myotonic dystrophy type 1 (DM1) are caused by a r(CUG) repeat expansion, or r(CUG)exp. The RNA folds into a hairpin structure with a periodic array of 1×1 nucleotide UU loops (5'CUG/3'GUC; where the underlined nucleotides indicate the Us in the internal loop) that sequester various RNA-binding proteins (RBP) and hence the source of its gain-of-function. Here, we report NMR-refined structures of single 5'CUG/3'GUC motifs in complex with three different small molecules, a di-guandinobenzoate (1), a derivative of 1 where the guanidino groups have been exchanged for imidazole (2), and a quinoline with improved drug-like properties (3). These structures were determined using nuclear magnetic resonance (NMR) spectroscopy and simulated annealing with restrained molecular dynamics (MD). Compounds 1, 2, and 3 formed stacking and hydrogen bonding interactions with the 5'CUG/3'GUC motif. Compound 3 also formed van der Waals interactions with the internal loop. The global structure of each RNA-small molecule complexes retains an A-form conformation, while the internal loops are still dynamic but to a lesser extent compared to the unbound form. These results aid our understanding of ligand-RNA interactions and enable structure-based design of small molecules with improved binding affinity for and biological activity against r(CUG)exp. As the first ever reported structures of RNA r(CUG) repeats bound to ligands, these structures can enable virtual screening campaigns combined with machine learning assisted de novo design.

Prediction of 3D RNA Structures from Sequence Using Energy Landscapes of RNA Dimers: Application to RNA Tetraloops

Access to the three-dimensional structure of RNA enables an ability to gain a more profound understanding of its biological mechanisms, as well as the ability to design RNA-targeting drugs, which can take advantage of the unique chemical environment imposed by a folded RNA structure. Due to the dynamic and structurally complex properties of RNA, both experimental and traditional computational methods have difficulty in determining RNA's 3D structure. Herein, we introduce TAPERSS (Theoretical Analyses, Prediction, and Evaluation of RNA Structures from Sequence), a physics-based fragment assembly method for predicting 3D RNA structures from sequence. Using a fragment library created using discrete path sampling calculations of RNA dinucleoside monophosphates, TAPERSS can sample the physics-based energy landscapes of any RNA sequence with relatively low computational complexity. We have benchmarked TAPERSS on 21 RNA tetraloops, using a combinatorial algorithm as a proof-of-concept. We show that TAPERSS was successfully able to predict the apo-state structures of all 21 RNA hairpins, with 16 of those structures also having low predicted energies as well. We demonstrate that TAPERSS performs most accurately on GNRA-like tetraloops with mostly stacked loop-nucleotides, while having limited success with more dynamic UNCG and CUYG tetraloops, most likely due to the influence of the RNA force field used to create the fragment library. Moreover, we show that TAPERSS can successfully predict the majority of the experimental non-apo states, highlighting its potential in anticipating biologically significant yet unobserved states. This holds great promise for future applications in drug design and related studies. With discussed improvements and implementation of more efficient sampling algorithms, we believe TAPERSS may serve as a useful tool for a physics-based conformational sampling of large RNA structures.

Structure and Dynamics of DNA and RNA Double Helices Formed by d(CTG), d(GTC), r(CUG), and r(GUC) Trinucleotide Repeats and Associated DNA-RNA Hybrids

Myotonic dystrophy type 1 is the most frequent form of muscular dystrophy in adults caused by an abnormal expansion of the CTG trinucleotide. Both the expanded DNA and the expanded CUG RNA transcript can fold into hairpins. Co-transcriptional formation of stable RNA·DNA hybrids can also enhance the instability of repeat tracts. We performed molecular dynamics simulations of homoduplexes associated with the disease, d(CTG)n and r(CUG)n, and their corresponding r(CAG)n:d(CTG)n and r(CUG)n:d(CAG)n hybrids that can form under bidirectional transcription and of non-pathological d(GTC)n and d(GUC)n homoduplexes. We characterized their conformations, stability, and dynamics and found that the U·U and T·T mismatches are dynamic, favoring anti-anti conformations inside the helical core, followed by anti-syn and syn-syn conformations. For DNA, the secondary minima in the non-expanding d(GTC)n helices are deeper, wider, and longer-lived than those in d(CTG)n, which constitutes another biophysical factor further differentiating the expanding and non-expanding sequences. The hybrid helices are closer to A-RNA, with the A-T and A-U pairs forming two stable Watson-Crick hydrogen bonds. The neutralizing ion distribution around the non-canonical pairs is also described.

Structural basis for water modulating RNA duplex formation in the CUG repeats of myotonic dystrophy type 1

Secondary structures formed by expanded CUG RNA are involved in the pathobiology of myotonic dystrophy type 1. Understanding the molecular basis of toxic RNA structures can provide insights into the mechanism of disease pathogenesis and accelerate the drug discovery process. Here, we report the crystal structure of CUG repeat RNA containing three U-U mismatches between C-G and G-C base pairs. The CUG RNA crystallizes as an A-form duplex, with the first and third U-U mismatches adopting a water-mediated asymmetric mirror isoform geometry. We found for the first time that a symmetric, water-bridged U-H₂O-U mismatch is well tolerated within the CUG RNA duplex, which was previously suspected but not observed. The new water-bridged U-U mismatch resulted in high base-pair opening and single-sided cross-strand stacking interactions, which in turn dominate the CUG RNA structure. Furthermore, we performed molecular dynamics (MD) simulations that complemented the structural findings and proposed that the first and third U-U mismatches are interchangeable conformations, while the central water-bridged U-U mismatch represents an intermediate state that modulates the RNA duplex conformation. Collectively, the new structural features provided in this work are important for understanding the recognition of U-U mismatches in CUG repeats by external ligands such as proteins or small molecules.

Dynamic docking of small molecules targeting RNA CUG repeats causing myotonic dystrophy type 1

Expansion of RNA CUG repeats causes myotonic dystrophy type 1 (DM1). Once transcribed, the expanded CUG repeats strongly attract muscleblind-like 1 (MBNL1) proteins and disturb their functions in cells. Because of its unique structural form, expanded RNA CUG repeats are prospective drug targets, where small molecules can be utilized to target RNA CUG repeats to inhibit MBNL1 binding and ameliorate DM1-associated defects. In this contribution, we developed two physics-based dynamic docking approaches (DynaD and DynaD/Auto) and applied them to nine small molecules known to specifically target RNA CUG repeats. While DynaD uses a distance-based reaction coordinate to study the binding phenomenon, DynaD/Auto combines results of umbrella sampling calculations performed on 1 × 1 UU internal loops and AutoDock calculations to efficiently sample the energy landscape of binding. Predictions are compared with experimental data, displaying a positive correlation with correlation coefficient (R) values of 0.70 and 0.81 for DynaD and DynaD/Auto, respectively. Furthermore, we found that the best correlation was achieved with MM/3D-RISM calculations, highlighting the importance of solvation in binding calculations. Moreover, we detected that DynaD/Auto performed better than DynaD because of the use of prior knowledge about the binding site arising from umbrella sampling calculations. Finally, we developed dendrograms to present how bound states are connected to each other in a binding process. Results are exciting, as DynaD and DynaD/Auto will allow researchers to utilize two novel physics-based and computer-aided drug-design methodologies to perform in silico calculations on drug-like molecules aiming to target complex RNA loops.

Evaluating Geometric Definitions of Stacking for RNA Dinucleoside Monophosphates Using Molecular Mechanics Calculations

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.

Computational Investigation of Bending Properties of RNA AUUCU, CCUG, CAG, and CUG Repeat Expansions Associated With Neuromuscular Disorders

Expansions of RNA AUUCU, CCUG, CAG, and CUG repeats cause spinocerebellar ataxia type 10, myotonic dystrophy type 2, Huntington’s disease, and myotonic dystrophy type 1, respectively. By performing extensive molecular dynamic simulations, we investigated the bending propensities and conformational landscapes adopted by 3×3, 2×2, and 1×1 internal loops observed in RNA AUUCU, CCUG, CAG, and CUG repeat expansions using model systems having biologically relevant repeat sizes. We show that the conformational variability experienced by these loops is more complex than previous reports where a variety of unconventional hydrogen bonds are formed. At the global scale, strong bending propensity was observed in r(AUUCU)₁₀, r(CCUG)₁₅, r(CAG)_20, and r(CUG)_20, and, to a lesser extent, in r(AUUCU)₄, r(CCUG)₁₀, r(CAG)₁₀, and r(CUG)₁₀. Furthermore, RNA CAG repeats exhibit a tendency toward bent states with more than 50% of observed conformations having bending angles greater than 50°, while RNA CUG repeats display relatively linear-like conformations with extremely bent conformations accounting for less than 25% of the observed structures. Conformations experienced by RNA AUUCU repeats are a combination of strongly bent and kinked structures. The bent states in RNA CCUG repeats mostly fall into the moderately bent category with a marginal ensemble experiencing extreme bending. The general pattern observed in all the bent structures indicates the collapse of the major groove width as the mechanical trigger for bending, which is caused by alteration of base pair step parameters at multiple locations along the RNA due to local distortions at the loop sites. Overextension is also observed in all the RNA repeats that is attributed to widening of the major groove width as well as undertwisting phenomenon. This information and the rich structural repository could be applied for structure based small molecule design targeting disease-causing RNAs. The bending propensities of these constructs, at the global level, could also have implications on how expanded RNA repeats interact with proteins.

Role of salt-bridging interactions in recognition of viral RNA by arginine-rich peptides

Interactions between RNA molecules and proteins are critical to many cellular processes and are implicated in various diseases. The RNA-peptide complexes are good model systems to probe the recognition mechanism of RNA by proteins. In this work, we report studies on the binding-unbinding process of a helical peptide from a viral RNA element using nonequilibrium molecular dynamics simulations. We explored the existence of various dissociation pathways with distinct free-energy profiles that reveal metastable states and distinct barriers to peptide dissociation. We also report the free-energy differences for each of the four pathways to be 96.47 ± 12.63, 96.1 ± 10.95, 91.83 ± 9.81, and 92 ± 11.32 kcal/mol. Based on the free-energy analysis, we further propose the preferred pathway and the mechanism of peptide dissociation. The preferred pathway is characterized by the formation of sequential hydrogen-bonding and salt-bridging interactions between several key arginine amino acids and the viral RNA nucleotides. Specifically, we identified one arginine amino acid (R8) of the peptide to play a significant role in the recognition mechanism of the peptide by the viral RNA molecule.

Molecular conformations and dynamics of nucleotide repeats associated with neurodegenerative diseases: double helices and CAG hairpin loops

Pathogenic DNA secondary structures have been identified as a common and causative factor for expansion in trinucleotide, hexanucleotide, and other simple sequence repeats. These expansions underlie about fifty neurological and neuromuscular disorders known as “anticipation diseases”. Cell toxicity and death have been linked to the pathogenic conformations and functional changes of the RNA transcripts, of DNA itself and, when trinucleotides are present in exons, of the translated proteins. We review some of our results for the conformations and dynamics of pathogenic structures for both RNA and DNA, which include mismatched homoduplexes formed by trinucleotide repeats CAG and GAC; CCG and CGG; CTG(CUG) and GTC(GUC); the dynamics of DNA CAG hairpins; mismatched homoduplexes formed by hexanucleotide repeats (GGGGCC) and (GGCCCC); and G-quadruplexes formed by (GGGGCC) and (GGGCCT). We also discuss the dynamics of strand slippage in DNA hairpins formed by CAG repeats as observed with single-molecule Fluorescence Resonance Energy Transfer. This review focuses on the rich behavior exhibited by the mismatches associated with these simple sequence repeat noncanonical structures.

Computational Investigation of RNA A-Bulges Related to the Microtubule-Associated Protein Tau Causing Frontotemporal Dementia and Parkinsonism

Mutations in the human tau gene result in alternative splicing of the tau protein, which causes frontotemporal dementia and Parkinsonism. One disease mechanism is linked to the stability of a hairpin within the microtubule-associated protein tau (MAPT) mRNA, which contains an A-bulge. Here we employ computational methods to investigate the structural and thermodynamic properties of several A-bulge RNAs with different closing base-pairs. We find that the current amber RNA force field has a preference to overstabilize base-triple over stacked states, even though some of the A-bulges are known to prefer stacked states according to NMR studies. We further determined that if the neighboring base-pairs of A-bulges are AU, this situation can lead to base slippage. However, when the 3'-side of the A-bulge has an UA base-pair, the stacked state is stabilized by an extra interaction that is not observed in the other sequences. We suggest that these A-bulge RNA systems could be used as benchmarks to improve the current RNA force fields.

Improvement of RNA Simulations with Torsional Revisions of the AMBER Force Field

Our current knowledge on the unique roles of RNA in cells makes it vital to investigate the properties of RNA systems using computational methods because of the potential pharmaceutical applications. With the continuous advancement of computer technology, it is now possible to study RNA folding. Molecular mechanics calculations are useful in discovering the structural and thermodynamic properties of RNA systems. Yet, the predictions depend on the quality of the RNA force field, which is a set of parameters describing the potential energy of the system. Torsional parameters are one of the terms in a force field that can be revised using physics-based approaches. This chapter focuses on improvements provided by revisions of torsional parameters of the AMBER (Assisted Model Building with Energy Refinement) RNA force field. The theory behind torsional revisions and re-parameterization of several RNA torsions is briefly described. Applications of the revised torsional parameters to study RNA nucleosides, single-stranded RNA tetramers, and RNA repeat expansions are described in detail. It is concluded that RNA force fields require constant revisions and should be benchmarked against diverse RNA systems such as single strands and internal loops in order to test their qualities.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

Exploring RNA structure and dynamics through enhanced sampling simulations

RNA function is intimately related to its structural dynamics. Molecular dynamics simulations are useful for exploring biomolecular flexibility but are severely limited by the accessible timescale. Enhanced sampling methods allow this timescale to be effectively extended in order to probe biologically relevant conformational changes and chemical reactions. Here, we review the role of enhanced sampling techniques in the study of RNA systems. We discuss the challenges and promises associated with the application of these methods to force-field validation, exploration of conformational landscapes and ion/ligand-RNA interactions, as well as catalytic pathways. Important technical aspects of these methods, such as the choice of the biased collective variables and the analysis of multi-replica simulations, are examined in detail. Finally, a perspective on the role of these methods in the characterization of RNA dynamics is provided.

Myotonic dystrophy: candidate small molecule therapeutics

Myotonic dystrophy type 1 (DM1) is a rare multisystemic neuromuscular disorder caused by expansion of CTG trinucleotide repeats in the noncoding region of the DMPK gene. Mutant DMPK transcripts are toxic and alter gene expression at several levels. Chiefly, the secondary structure formed by CUGs has a strong propensity to capture and retain proteins, like those of the muscleblind-like (MBNL) family. Sequestered MBNL proteins cannot then fulfill their normal functions. Many therapeutic approaches have been explored to reverse these pathological consequences. Here, we review the myriad of small molecules that have been proposed for DM1, including examples obtained from computational rational design, HTS, drug repurposing, and therapeutic gene modulation.

Structure and Dynamics of RNA Repeat Expansions That Cause Huntington's Disease and Myotonic Dystrophy Type 1

RNA repeat expansions cause a host of incurable, genetically defined diseases. The most common class of RNA repeats consists of trinucleotide repeats. These long, repeating transcripts fold into hairpins containing 1 × 1 internal loops that can mediate disease via a variety of mechanism(s) in which RNA is the central player. Two of these disorders are Huntington's disease and myotonic dystrophy type 1, which are caused by r(CAG) and r(CUG) repeats, respectively. We report the structures of two RNA constructs containing three copies of a r(CAG) [r(3×CAG)] or r(CUG) [r(3×CUG)] motif that were modeled with nuclear magnetic resonance spectroscopy and simulated annealing with restrained molecular dynamics. The 1 × 1 internal loops of r(3×CAG) are stabilized by one-hydrogen bond (cis Watson-Crick/Watson-Crick) AA pairs, while those of r(3×CUG) prefer one- or two-hydrogen bond (cis Watson-Crick/Watson-Crick) UU pairs. Assigned chemical shifts for the residues depended on the identity of neighbors or next nearest neighbors. Additional insights into the dynamics of these RNA constructs were gained by molecular dynamics simulations and a discrete path sampling method. Results indicate that the global structures of the RNA are A-form and that the loop regions are dynamic. The results will be useful for understanding the dynamic trajectory of these RNA repeats but also may aid in the development of therapeutics.

In silico discovery of substituted pyrido[2,3-d]pyrimidines and pentamidine-like compounds with biological activity in myotonic dystrophy models

Myotonic dystrophy type 1 (DM1) is a rare multisystemic disorder associated with an expansion of CUG repeats in mutant DMPK (dystrophia myotonica protein kinase) transcripts; the main effect of these expansions is the induction of pre-mRNA splicing defects by sequestering muscleblind-like family proteins (e.g. MBNL1). Disruption of the CUG repeats and the MBNL1 protein complex has been established as the best therapeutic approach for DM1, hence two main strategies have been proposed: targeted degradation of mutant DMPK transcripts and the development of CUG-binding molecules that prevent MBNL1 sequestration. Herein, suitable CUG-binding small molecules were selected using in silico approaches such as scaffold analysis, similarity searching, and druggability analysis. We used polarization assays to confirm the CUG repeat binding in vitro for a number of candidate compounds, and went on to evaluate the biological activity of the two with the strongest affinity for CUG repeats (which we refer to as compounds 1–2 and 2–5) in DM1 mutant cells and Drosophila DM1 models with an impaired locomotion phenotype. In particular, 1–2 and 2–5 enhanced the levels of free MBNL1 in patient-derived myoblasts in vitro and greatly improved DM1 fly locomotion in climbing assays. This work provides new computational approaches for rational large-scale virtual screens of molecules that selectively recognize CUG structures. Moreover, it contributes valuable knowledge regarding two compounds with desirable biological activity in DM1 models.

Improving Computational Predictions of Single-Stranded RNA Tetramers with Revised α/γ Torsional Parameters for the Amber Force Field

With current advancements in RNA based therapeutics, it is becoming crucial to utilize theoretical and computational methods to describe properly the physical properties of RNA molecules. NMR and X-ray crystallography are two powerful techniques for investigating structural properties. However, if the RNA molecules are complex or dynamic, these methods might not be adequate. For computational approaches, the quality of the force field will determine accuracy of our predictions. In this contribution, we revise the α/γ torsional parameters of RNA for amber force field using a model system representing an RNA dimer backbone. Combined with revised χ torsional parameters, previously shown to improve computational predictions, we benchmarked the revised force field on five single-stranded RNA (ssRNA) tetramers, three RNA dodecamer duplexes, and an RNA hairpin. A total of 60 μs of molecular dynamics (MD) simulations were run. We also employ the discrete path sampling (DPS) approach to compare the predictions for the revised amber force field with those for amber10. Our results indicate that the unphysical states observed with amber10 in ssRNA MD simulations are suppressed for the revised amber force field. In line with NMR experimental observations, incorporation of the revised α/γ and χ torsional parameters leads to A-form-like conformational states as the most favorable ssRNA tetramer conformations. Furthermore, the revised force field maintains the A-form geometry in regular RNA duplexes. Our revised amber force field for RNA should therefore improve structural and thermodynamic predictions for challenging RNA systems.

RNA toxicity and foci formation in microsatellite expansion diseases

More than 30 incurable neurological and neuromuscular diseases are caused by simple microsatellite expansions consisted of 3-6 nucleotides. These repeats can occur in non-coding regions and often result in a dominantly inherited disease phenotype that is characteristic of a toxic RNA gain-of-function. The expanded RNA adopts unusual secondary structures, sequesters various RNA binding proteins to form insoluble nuclear foci, and causes cellular defects at a multisystem level. Nuclear foci are dynamic in size, shape and colocalization of RNA binding proteins in different expansion diseases and tissue types. This review sets to provide new insights into the disease mechanisms of RNA toxicity and foci modulation, in light of recent advancement on bi-directional transcription, antisense RNA, repeat-associated non-ATG translation and beyond.