How to understand atomistic molecular dynamics simulations of RNA and protein-RNA complexes?

Dynamics of Protein-RNA Interfaces Using All-Atom Molecular Dynamics Simulations

Facing the current challenges posed by human health diseases requires the understanding of cell machinery at a molecular level. The interplay between proteins and RNA is key for any physiological phenomenon, as well protein-RNA interactions. To understand these interactions, many experimental techniques have been developed, spanning a very wide range of spatial and temporal resolutions. In particular, the knowledge of tridimensional structures of protein-RNA complexes provides structural, mechanical, and dynamical pieces of information essential to understand their functions. To get insights into the dynamics of protein-RNA complexes, we carried out all-atom molecular dynamics simulations in explicit solvent on nine different protein-RNA complexes with different functions and interface size by taking into account the bound and unbound forms. First, we characterized structural changes upon binding and, for the RNA part, the change in the puckering. Second, we extensively analyzed the interfaces, their dynamics and structural properties, and the structural waters involved in the binding, as well as the contacts mediated by them. Based on our analysis, the interfaces rearranged during the simulation time showing alternative and stable residue-residue contacts with respect to the experimental structure.

Elucidating the influence of RNA modifications and Magnesium ions on tRNA Phe conformational dynamics in S. cerevisiae : Insights from Replica Exchange Molecular Dynamics simulations

Post-transcriptional modifications in RNA can significantly impact their structure and function. In particular, transfer RNAs (tRNAs) are heavily modified, with around 100 different naturally occurring nucleotide modifications contributing to codon bias and decoding efficiency. Here, we describe our efforts to investigate the impact of RNA modifications on the structure and stability of tRNA Phenylalanine (tRNA Phe ) from S. cerevisiae using molecular dynamics (MD) simulations. Through temperature replica exchange MD (T-REMD) studies, we explored the unfolding pathway to understand how RNA modifications influence the conformational dynamics of tRNA Phe , both in the presence and absence of magnesium ions (Mg 2+ ). We observe that modified nucleotides in key regions of the tRNA establish a complex network of hydrogen bonds and stacking interactions which is essential for tertiary structure stability of the tRNA. Furthermore, our simulations show that modifications facilitate the formation of ion binding sites on the tRNA. However, high concentrations of Mg 2+ ions can stabilize the tRNA tertiary structure in the absence of modifications. Our findings illuminate the intricate interactions between modifications, magnesium ions, and RNA structural stability.

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.

Dynamics and Function of sRNA/mRNAs Under the Scrutiny of Computational Simulation Methods

Molecular dynamics simulations have proved extremely useful in investigating the functioning of proteins with atomic-scale resolution. Many applications to the study of RNA also exist, and their number increases by the day. However, implementing MD simulations for RNA molecules in solution faces challenges that the MD practitioner must be aware of for the appropriate use of this tool. In this chapter, we present the fundamentals of MD simulations, in general, and the peculiarities of RNA simulations, in particular. We discuss the strengths and limitations of the technique and provide examples of its application to elucidate small RNA's performance.

Characterization of epitranscriptome reader proteins experimentally and in silico: Current knowledge and future perspectives beyond the YTH domain

To date, over 150 chemical modifications to the four canonical RNA bases have been discovered, known collectively as the epitranscriptome. Many of these modifications have been implicated in a variety of cellular processes and disease states. Additional work has been done to identify proteins known as "readers" that selectively interact with RNAs that contain specific chemical modifications. Protein interactomes with N6-methyladenosine (m⁶A), N1-methyladenosine (m¹A), N5-methylcytosine (m⁵C), and 8-oxo-7,8-dihydroguanosine (8-oxoG) have been determined, mainly through experimental advances in proteomics techniques. However, relatively few proteins have been confirmed to bind directly to RNA containing these modifications. Furthermore, for many of these protein readers, the exact binding mechanisms as well as the exclusivity for recognition of modified RNA species remain elusive, leading to questions regarding their roles within different cellular processes. In the case of the YT-521B homology (YTH) family of proteins, both experimental and in silico techniques have been leveraged to provide valuable biophysical insights into the mechanisms of m⁶A recognition at atomic resolution. To date, the YTH family is one of the best characterized classes of readers. Here, we review current knowledge about epitranscriptome recognition of the YTH domain proteins from previously published experimental and computational studies. We additionally outline knowledge gaps for proteins beyond the well-studied human YTH domains and the current in silico techniques and resources that can enable investigation of protein interactions with modified RNA outside of the YTH-m⁶A context.

Structural, Dynamical, and Entropic Differences between SARS-CoV and SARS-CoV-2 s2m Elements Using Molecular Dynamics Simulations

The functional role of the highly conserved stem-loop II motif (s2m) in SARS-CoV and SARS-CoV-2 in the viral lifecycle remains enigmatic and an intense area of research. Structure and dynamics of the s2m are key to establishing a structure-function connection, yet a full set of atomistic resolution coordinates is not available for SARS-CoV-2 s2m. Our work constructs three-dimensional coordinates consistent with NMR solution phase data for SARS-CoV-2 s2m and provides a comparative analysis with its counterpart SARS-CoV s2m. We employed initial coordinates based on PDB ID 1XJR for SARS-CoV s2m and two models for SARS-CoV-2 s2m: one based on 1XJR in which we introduced the mutations present in SARS-CoV-2 s2m and the second based on the available SARS-CoV-2 NMR NOE data supplemented with knowledge-based methods. For each of the three systems, 3.5 μs molecular dynamics simulations were used to sample the structure and dynamics, and principal component analysis (PCA) reduced the ensembles to hierarchal conformational substates for detailed analysis. Dilute solution simulations of SARS-CoV s2m demonstrate that the GNRA-like terminal pentaloop is rigidly defined by base stacking uniquely positioned for possible kissing dimer formation. However, the SARS-CoV-2 s2m simulation did not retain the reported crystallographic SARS-CoV motifs and the terminal loop expands to a highly dynamic "nonaloop." Increased flexibility and structural disorganization are observed for the larger terminal loop, where an entropic penalty is computed to explain the experimentally observed reduction in kissing complex formation. Overall, both SARS-CoV and SARS-CoV-2 s2m elements have a similarly pronounced L-shape due to different motif interactions. Our study establishes the atomistic three-dimensional structure and uncovers dynamic differences that arise from s2m sequence changes, which sets the stage for the interrogation of different mechanistic pathways of suspected biological function.

Spontaneous binding of single-stranded RNAs to RRM proteins visualized by unbiased atomistic simulations with a rescaled RNA force field

Recognition of single-stranded RNA (ssRNA) by RNA recognition motif (RRM) domains is an important class of protein-RNA interactions. Many such complexes were characterized using nuclear magnetic resonance (NMR) and/or X-ray crystallography techniques, revealing ensemble-averaged pictures of the bound states. However, it is becoming widely accepted that better understanding of protein-RNA interactions would be obtained from ensemble descriptions. Indeed, earlier molecular dynamics simulations of bound states indicated visible dynamics at the RNA-RRM interfaces. Here, we report the first atomistic simulation study of spontaneous binding of short RNA sequences to RRM domains of HuR and SRSF1 proteins. Using a millisecond-scale aggregate ensemble of unbiased simulations, we were able to observe a few dozen binding events. HuR RRM3 utilizes a pre-binding state to navigate the RNA sequence to its partially disordered bound state and then to dynamically scan its different binding registers. SRSF1 RRM2 binding is more straightforward but still multiple-pathway. The present study necessitated development of a goal-specific force field modification, scaling down the intramolecular van der Waals interactions of the RNA which also improves description of the RNA-RRM bound state. Our study opens up a new avenue for large-scale atomistic investigations of binding landscapes of protein-RNA complexes, and future perspectives of such research are discussed.

Exploring the multiple conformational states of RNA genome through interhelical dynamics and network analysis

The structural variation of RNA is often very transient and can be easily missed in experiments. Molecular dynamics simulation studies along with network analysis can be an effective tool to identify prominent conformations of such dynamic biomolecular systems. Here we describe a method to effectively sample different RNA conformations at six different temperatures based on the changes in the interhelical orientations. This method gives the information about prominent states of the RNA as well as the probability of the existence of different conformations and their interconnections during the process of evolution. In the case of the SARS-CoV-2 genome, the change of prominent structures was found to be faster at 333 K as compared to higher temperatures due to the formation of the non-native base pairs. ΔΔG calculated between 288 K and 363 K are found to be 10.31 kcal/mol (88 nt) considering the contribution from the multiple states of the RNA which agrees well with the experimentally reported denaturation energy for E. coli α mRNA pseudoknot (∼16 kcal/mol, 112 nt) determined by calorimetry/UV hyperchromicity and human telomerase RNA telomerase (4.5-6.6 kcal/mol, 54 nt) determined by FRET analysis.

Molecular Dynamics Simulations of Protein RNA Complexes by Using an Advanced Electrostatic Model

Protein-RNA interactions are integral to the biological functions of RNA. It is well recognized that molecular dynamics (MD) simulations of protein-RNA complexes are more challenging than those of each component. The difficulty arises from the strong electrostatic interactions and the delicate balance between various types of physical forces at the interface. Previously, MD simulations of protein-RNA complexes have predominantly employed fixed-charge force fields. Although force field modifications have been developed to address problems identified in the simulations, some protein-RNA structures are still hard to reproduce by simulations. Here, we present MD simulations of two representative protein-RNA complexes using the AMOEBA polarizable force field. The van der Waals parameters were refined to reproduce accurate quantum-mechanical data of base-base and base-amino acid interactions. It was found that the refined parameters produced a more stable hydrogen-bond network in the interface. One of the complexes remained stable during the short simulations, whereas it could quickly break down in previous simulations using fixed-charge force fields. There was reversible breaking and formation of hydrogen bonds that are observed in the crystal structure, which may indicate the difference in solution and crystal structures. While further improvement and validation of the force fields are still needed, this work demonstrates that polarizable force fields are promising for the study of protein-RNA complexes.

A Computational Study of RNA Tetraloop Thermodynamics, Including Misfolded States

An important characteristic of RNA folding is the adoption of alternative configurations of similar stability, often referred to as misfolded configurations. These configurations are considered to compete with correctly folded configurations, although their rigorous thermodynamic and structural characterization remains elusive. Tetraloop motifs found in large ribozymes are ideal systems for an atomistically detailed computational quantification of folding free energy landscapes and the structural characterization of their constituent free energy basins, including nonnative states. In this work, we studied a group of closely related 10-mer tetraloops using a combined parallel tempering and metadynamics technique that allows a reliable sampling of the free energy landscapes, requiring only knowledge that the stem folds into a canonical A-RNA configuration. We isolated and analyzed unfolded, folded, and misfolded populations that correspond to different free energy basins. We identified a distinct misfolded state that has a stability very close to that of the correctly folded state. This misfolded state contains a predominant population that shares the same structural features across all tetraloops studied here and lacks the noncanonical A-G base pair in its loop portion. Further analysis performed with biased trajectories showed that although this competitive misfolded state is not an essential intermediate, it is visited in most of the transitions from unfolded to correctly folded states. Moreover, the tetraloops can transition from this misfolded state to the correctly folded state without requiring extensive unfolding.

Mechanism of RNA recognition by a Musashi RNA-binding protein

The Musashi RNA-binding proteins (RBPs) regulate translation of target mRNAs and maintenance of cell stemness and tumorigenesis. Musashi-1 (MSI1), long considered as an intestinal and neural stem cell marker, has been more recently found to be over expressed in many cancers. It has served as an important drug target for treating acute myeloid leukemia and solid tumors such as ovarian, colorectal and bladder cancer. One of the reported binding targets of MSI1 is Numb, a negative regulator of the Notch signaling. However, the dynamic mechanism of Numb RNA binding to MSI1 remains unknown, largely hindering effective drug design targeting this critical interaction. Here, we have performed extensive all-atom microsecond-timescale simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method, which successfully captured multiple times of spontaneous and highly accurate binding of the Numb RNA from bulk solvent to the MSI1 protein target site. GaMD simulations revealed that Numb RNA binding to MSI1 involved largely induced fit in both the RNA and protein. The simulations also identified important low-energy intermediate conformational states during RNA binding, in which Numb interacted mainly with the β2-β3 loop and C terminus of MSI1. The mechanistic understanding of RNA binding obtained from our GaMD simulations is expected to facilitate rational structure-based drug design targeting MSI1 and other RBPs.

'RNA modulation of transport properties and stability in phase-separated condensates

One of the key mechanisms employed by cells to control their spatiotemporal organization is the formation and dissolution of phase-separated condensates. The balance between condensate assembly and disassembly can be critically regulated by the presence of RNA. In this work, we use a chemically-accurate sequence-dependent coarse-grained model for proteins and RNA to unravel the impact of RNA in modulating the transport properties and stability of biomolecular condensates. We explore the phase behavior of several RNA-binding proteins such as FUS, hnRNPA1, and TDP-43 proteins along with that of their corresponding prion-like domains and RNA recognition motifs from absence to moderately high RNA concentration. By characterizing the phase diagram, key molecular interactions, surface tension, and transport properties of the condensates, we report a dual RNA-induced behavior: on the one hand, RNA enhances phase separation at low concentration as long as the RNA radius of gyration is comparable to that of the proteins, whereas at high concentration, it inhibits the ability of proteins to self-assemble independently of its length. On the other hand, along with the stability modulation, the viscosity of the condensates can be considerably reduced at high RNA concentration as long as the length of the RNA chains is shorter than that of the proteins. Conversely, long RNA strands increase viscosity even at high concentration, but barely modify protein self-diffusion which mainly depends on RNA concentration and on the effect RNA has on droplet density. On the whole, our work rationalizes the different routes by which RNA can regulate phase separation and condensate dynamics, as well as the subsequent aberrant rigidification implicated in the emergence of various neuropathologies and age-related diseases.

'RNA modulation of transport properties and stability in phase-separated condensates

One of the key mechanisms employed by cells to control their spatiotemporal organization is the formation and dissolution of phase-separated condensates. The balance between condensate assembly and disassembly can be critically regulated by the presence of RNA. In this work, we use a chemically-accurate sequence-dependent coarse-grained model for proteins and RNA to unravel the impact of RNA in modulating the transport properties and stability of biomolecular condensates. We explore the phase behavior of several RNA-binding proteins such as FUS, hnRNPA1, and TDP-43 proteins along with that of their corresponding prion-like domains and RNA recognition motifs from absence to moderately high RNA concentration. By characterizing the phase diagram, key molecular interactions, surface tension, and transport properties of the condensates, we report a dual RNA-induced behavior: on the one hand, RNA enhances phase separation at low concentration as long as the RNA radius of gyration is comparable to that of the proteins, whereas at high concentration, it inhibits the ability of proteins to self-assemble independently of its length. On the other hand, along with the stability modulation, the viscosity of the condensates can be considerably reduced at high RNA concentration as long as the length of the RNA chains is shorter than that of the proteins. Conversely, long RNA strands increase viscosity even at high concentration, but barely modify protein self-diffusion which mainly depends on RNA concentration and on the effect RNA has on droplet density. On the whole, our work rationalizes the different routes by which RNA can regulate phase separation and condensate dynamics, as well as the subsequent aberrant rigidification implicated in the emergence of various neuropathologies and age-related diseases.

Salt dependent phase behavior of intrinsically disordered proteins from a coarse-grained model with explicit water and ions

Multivalent proteins and nucleic acids can self-assemble into biomolecular condensates that contribute to compartmentalize the cell interior. Computer simulations offer a unique view to elucidate the mechanisms and key intermolecular interactions behind the dynamic formation and dissolution of these condensates. In this work, we present a novel approach to include explicit water and salt in sequence-dependent coarse-grained (CG) models for proteins and RNA, enabling the study of biomolecular condensate formation in a salt-dependent manner. Our framework combines a reparameterized version of the HPS protein force field with the monoatomic mW water model and the mW-ion potential for NaCl. We show how our CG model qualitatively captures the experimental radius of the gyration trend of a subset of intrinsically disordered proteins and reproduces the experimental protein concentration and water percentage of the human fused in sarcoma (FUS) low-complexity-domain droplets at physiological salt concentration. Moreover, we perform seeding simulations as a function of salt concentration for two antagonist systems: the engineered peptide PR₂₅ and poly-uridine/poly-arginine mixtures, finding good agreement with their reported in vitro phase behavior with salt concentration in both cases. Taken together, our work represents a step forward towards extending sequence-dependent CG models to include water and salt, and to consider their key role in biomolecular condensate self-assembly.

Recognition of N6-Methyladenosine by the YTHDC1 YTH Domain Studied by Molecular Dynamics and NMR Spectroscopy: The Role of Hydration

The YTH domain of YTHDC1 belongs to a class of protein "readers", recognizing the N6-methyladenosine (m⁶A) chemical modification in mRNA. Static ensemble-averaged structures revealed details of N6-methyl recognition via a conserved aromatic cage. Here, we performed molecular dynamics (MD) simulations along with nuclear magnetic resonance (NMR) and isothermal titration calorimetry (ITC) to examine how dynamics and solvent interactions contribute to the m⁶A recognition and negative selectivity toward an unmethylated substrate. The structured water molecules surrounding the bound RNA and the methylated substrate's ability to exclude bulk water molecules contribute to the YTH domain's preference for m⁶A. Intrusions of bulk water deep into the binding pocket disrupt binding of unmethylated adenosine. The YTHDC1's preference for the 5'-Gm⁶A-3' motif is partially facilitated by a network of water-mediated interactions between the 2-amino group of the guanosine and residues in the m⁶A binding pocket. The 5'-Im⁶A-3' (where I is inosine) motif can be recognized too, but disruption of the water network lowers affinity. The D479A mutant also disrupts the water network and destabilizes m⁶A binding. Our interdisciplinary study of the YTHDC1 protein-RNA complex reveals an unusual physical mechanism by which solvent interactions contribute toward m⁶A recognition.

MD simulations reveal the basis for dynamic assembly of Hfq-RNA complexes

The conserved protein Hfq is a key factor in the RNA-mediated control of gene expression in most known bacteria. The transient intermediates Hfq forms with RNA support intricate and robust regulatory networks. In Pseudomonas, Hfq recognizes repeats of adenine–purine–any nucleotide (ARN) in target mRNAs via its distal binding side, and together with the catabolite repression control (Crc) protein, assembles into a translation–repression complex. Earlier experiments yielded static, ensemble-averaged structures of the complex, but details of its interface dynamics and assembly pathway remained elusive. Using explicit solvent atomistic molecular dynamics simulations, we modeled the extensive dynamics of the Hfq–RNA interface and found implications for the assembly of the complex. We predict that syn/anti flips of the adenine nucleotides in each ARN repeat contribute to a dynamic recognition mechanism between the Hfq distal side and mRNA targets. We identify a previously unknown binding pocket that can accept any nucleotide and propose that it may serve as a ‘status quo’ staging point, providing nonspecific binding affinity, until Crc engages the Hfq–RNA binary complex. The dynamical components of the Hfq–RNA recognition can speed up screening of the pool of the surrounding RNAs, participate in rapid accommodation of the RNA on the protein surface, and facilitate competition among different RNAs. The register of Crc in the ternary assembly could be defined by the recognition of a guanine-specific base–phosphate interaction between the first and last ARN repeats of the bound RNA. This dynamic substrate recognition provides structural rationale for the stepwise assembly of multicomponent ribonucleoprotein complexes nucleated by Hfq–RNA binding.

Combining Virtual Reality Visualization with Ensemble Molecular Dynamics to Study Complex Protein Conformational Changes

Molecular dynamics (MD) simulations are increasingly used to elucidate relationships between protein structure, dynamics, and their biological function. Currently, it is extremely challenging to perform MD simulations of large-scale structural rearrangements in proteins that occur on millisecond timescales or beyond, as this requires very significant computational resources, or the use of cumbersome "collective variable" enhanced sampling protocols. Here, we describe a framework that combines ensemble MD simulations and virtual reality visualization (eMD-VR) to enable users to interactively generate realistic descriptions of large amplitude, millisecond timescale protein conformational changes in proteins. Detailed tests demonstrate that eMD-VR substantially decreases the computational cost of folding simulations of a WW domain, without the need to define collective variables a priori. We further show that eMD-VR generated pathways can be combined with Markov state models to describe the thermodynamics and kinetics of large-scale loop motions in the enzyme cyclophilin A. Our results suggest eMD-VR is a powerful tool for exploring protein energy landscapes in bioengineering efforts.

Advanced Methods for Studying Structure and Interactions of Macrolide Antibiotics

Macrolide antibiotics are macrocyclic compounds that are clinically used and prescribed for the treatment of upper and lower respiratory tract infections. They inhibit the synthesis of bacterial proteins by reversible binding to the 23S rRNA at or near the peptidyl transferase center. However, their excellent antibacterial profile was largely compromised by the emergence of bacterial resistance. Today, fighting resistance to antibiotics is one of the greatest challenges in medicinal chemistry. Considering various physicochemical properties of macrolides, understanding their structure and interactions with macromolecular targets is crucial for the design of new antibiotics efficient against resistant pathogens. The solid-state structures of some macrolide-ribosome complexes have recently been solved, throwing new light on the macrolide binding mechanisms. On the other hand, a combination of NMR spectroscopy and molecular modeling calculations can be applied to study free and bound conformations in solution. In this article, a description of advanced physicochemical methods for elucidating the structure and interactions of macrolide antibiotics in solid state and solution will be provided, and their principal advantages and drawbacks will be discussed.

Peptide Inhibitors of Bacterial Protein Synthesis with Broad Spectrum and SbmA-Independent Bactericidal Activity against Clinical Pathogens

Proline-rich antimicrobial peptides (PrAMPs) are promising lead compounds for developing new antimicrobials; however, their narrow spectrum of action is limiting. PrAMPs kill bacteria binding to their ribosomes and inhibiting protein synthesis. In this study, 133 derivatives of the PrAMP Bac7(1-16) were synthesized to identify the crucial residues for ribosome inactivation and antimicrobial activity. Then, five new Bac7(1-16) derivatives were conceived and characterized by antibacterial and membrane permeabilization assays, X-ray crystallography, and molecular dynamics simulations. Some derivatives displayed broad spectrum activity, encompassing Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumanii, Pseudomonas aeruginosa, and Staphylococcus aureus. Two peptides out of five acquired a weak membrane-perturbing activity while maintaining the ability to inhibit protein synthesis. These derivatives became independent of the SbmA transporter, commonly used by native PrAMPs, suggesting that they obtained a novel route to enter bacterial cells. PrAMP-derived compounds could become new-generation antimicrobials to combat antibiotic-resistant pathogens.

Fine-Tuning of the AMBER RNA Force Field with a New Term Adjusting Interactions of Terminal Nucleotides

Determination of RNA structural-dynamic properties is challenging for experimental methods. Thus, atomistic molecular dynamics (MD) simulations represent a helpful technique complementary to experiments. However, contemporary MD methods still suffer from limitations of force fields (ffs), including imbalances in the nonbonded ff terms. We have recently demonstrated that some improvement of state-of-the-art AMBER RNA ff can be achieved by adding a new term for H-bonding called gHBfix, which increases tuning flexibility and reduces risk of side-effects. Still, the first gHBfix version did not fully correct simulations of short RNA tetranucleotides (TNs). TNs are key benchmark systems due to availability of unique NMR data, although giving too much weight on improving TN simulations can easily lead to overfitting to A-form RNA. Here we combine the gHBfix version with another term called tHBfix, which separately treats H-bond interactions formed by terminal nucleotides. This allows to refine simulations of RNA TNs without affecting simulations of other RNAs. The approach is in line with adopted strategy of current RNA ffs, where the terminal nucleotides possess different parameters for terminal atoms than the internal nucleotides. Combination of gHBfix with tHBfix significantly improves the behavior of RNA TNs during well-converged enhanced-sampling simulations using replica exchange with solute tempering. TNs mostly populate canonical A-form like states while spurious intercalated structures are largely suppressed. Still, simulations of r(AAAA) and r(UUUU) TNs show some residual discrepancies with primary NMR data which suggests that future tuning of some other ff terms might be useful. Nevertheless, the tHBfix has a clear potential to improve modeling of key biochemical processes, where interactions of RNA single stranded ends are involved.

Decrypting the Information Exchange Pathways across the Spliceosome Machinery

Intron splicing of a nascent mRNA transcript by spliceosome (SPL) is a hallmark of gene regulation in eukaryotes. SPL is a majestic molecular machine composed of an entangled network of proteins and RNAs that meticulously promotes intron splicing through the formation of eight intermediate complexes. Cross-communication among the critical distal proteins of the SPL assembly is pivotal for fast and accurate directing of the compositional and conformational readjustments necessary to achieve high splicing fidelity. Here, molecular dynamics (MD) simulations of an 800 000 atom model of SPL C complex from yeast Saccharomyces cerevisiae and community network analysis enabled us to decrypt the complexity of this huge molecular machine, by identifying the key channels of information transfer across long distances separating key protein components. The reported study represents an unprecedented attempt in dissecting cross-communication pathways within one of the most complex machines of eukaryotic cells, supporting the critical role of Clf1 and Cwc2 splicing cofactors and specific domains of the Prp8 protein as signal conveyors for pre-mRNA maturation. Our findings provide fundamental advances into mechanistic aspects of SPL, providing a conceptual basis for controlling the SPL via small-molecule modulators able to tackle splicing-associated diseases by altering/obstructing information-exchange paths.

Flexible Binding of m6A Reader Protein YTHDC1 to Its Preferred RNA Motif

N⁶-Methyladenosine (m⁶A) is the most prevalent chemical modification in human mRNAs. Its recognition by reader proteins enables many cellular functions, including splicing and translation of mRNAs. However, the binding mechanisms of m⁶A-containing RNAs to their readers are still elusive due to the unclear roles of m⁶A-flanking ribonucleotides. Here, we use a model system, YTHDC1 with its RNA motif 5'-G_-2G_-1(m⁶A)C₊₁U₊₂-3', to investigate the binding mechanisms by atomistic simulations, X-ray crystallography, and isothermal titration calorimetry. The experimental data and simulation results show that m⁶A is captured by an aromatic cage of YTHDC1 and the 3' terminus nucleotides are stabilized by cation-π-π interactions, while the 5' terminus remains flexible. Notably, simulations of unbound RNA motifs reveal that the methyl group of m⁶A and the 5' terminus shift the conformational preferences of the oligoribonucleotide to the bound-like conformation, thereby facilitating the association process. The binding mechanisms may help in the discovery of chemical probes against m⁶A reader proteins.

Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions

The interactions between RNAs and proteins play critical roles in many biological processes. Therefore, characterizing these interactions becomes critical for mechanistic, biomedical, and clinical studies. Many experimental methods can be used to determine RNA-protein interactions in multiple aspects. However, due to the facts that RNA-protein interactions are tissuespecific and condition-specific, as well as these interactions are weak and frequently compete with each other, those experimental techniques can not be made full use of to discover the complete spectrum of RNA-protein interactions. To moderate these issues, continuous efforts have been devoted to developing high quality computational techniques to study the interactions between RNAs and proteins. Many important progresses have been achieved with the application of novel techniques and strategies, such as machine learning techniques. Especially, with the development and application of CLIP techniques, more and more experimental data on RNA-protein interaction under specific biological conditions are available. These CLIP data altogether provide a rich source for developing advanced machine learning predictors. In this review, recent progresses on computational predictors for RNA-protein interaction were summarized in the following aspects: dataset, prediction strategies, and input features. Possible future developments were also discussed at the end of the review.

Disclosing the Impact of Carcinogenic SF3b Mutations on Pre-mRNA Recognition Via All-Atom Simulations

The spliceosome accurately promotes precursor messenger-RNA splicing by recognizing specific noncoding intronic tracts including the branch point sequence (BPS) and the 3'-splice-site (3'SS). Mutations of Hsh155 (yeast)/SF3B1 (human), which is a protein of the SF3b factor involved in BPS recognition and induces altered BPS binding and 3'SS selection, lead to mis-spliced mRNA transcripts. Although these mutations recur in hematologic malignancies, the mechanism by which they change gene expression remains unclear. In this study, multi-microsecond-long molecular-dynamics simulations of eighth distinct ∼700,000 atom models of the spliceosome Bact complex, and gene sequencing of SF3B1, disclose that these carcinogenic isoforms destabilize intron binding and/or affect the functional dynamics of Hsh155/SF3B1 only when binding non-consensus BPSs, as opposed to the non-pathogenic variants newly annotated here. This pinpoints a cross-talk between the distal Hsh155 mutation and BPS recognition sites. Our outcomes unprecedentedly contribute to elucidating the principles of pre-mRNA recognition, which provides critical insights on the mechanism underlying constitutive/alternative/aberrant splicing.

Understanding the mechanistic basis of non-coding RNA through molecular dynamics simulations

Noncoding RNA (ncRNA) has a key role in regulating gene expression, mediating fundamental processes and diseases via a variety of yet unknown mechanisms. Here, we review recent applications of conventional and enhanced Molecular Dynamics (MD) simulations methods to address the mechanistic function of large biomolecular systems that are tightly involved in the ncRNA function and that are of key importance in life sciences. This compendium focuses of three biomolecular systems, namely the CRISPR-Cas9 genome editing machinery, group II intron ribozyme and the ribonucleoprotein complex of the spliceosome, which edit and process ncRNA. We show how the application of a novel accelerated MD simulations method has been key in disclosing the conformational transitions underlying RNA binding in the CRISPR-Cas9 complex, suggesting a mechanism for RNA recruitment and clarifying the conformational changes required for attaining genome editing. As well, we discuss the use of mixed quantum-classical MD simulations in deciphering the catalytic mechanism of RNA splicing as operated by group II intron ribozyme, one of the largest ncRNA structures crystallized so far. Finally, we debate the future challenges and opportunities in the field, discussing the recent application of MD simulations for unraveling the functional biophysics of the spliceosome, a multi-mega Dalton complex of proteins and small nuclear RNAs that performs RNA splicing in humans. This showcase of applications highlights the current talent of MD simulations to dissect atomic-level details of complex biomolecular systems instrumental for the design of finely engineered genome editing machines. As well, this review aims at inspiring future investigations of several other ncRNA regulatory systems, such as micro and small interfering RNAs, which achieve their function and specificity using RNA-based recognition and targeting strategies.

Improving the Performance of the Amber RNA Force Field by Tuning the Hydrogen-Bonding Interactions

Molecular dynamics (MD) simulations became a leading tool for investigation of structural dynamics of nucleic acids. Despite recent efforts to improve the empirical potentials (force fields, ffs), RNA ffs have persisting deficiencies, which hamper their utilization in quantitatively accurate simulations. Previous studies have shown that at least two salient problems contribute to difficulties in the description of free-energy landscapes of small RNA motifs: (i) excessive stabilization of the unfolded single-stranded RNA ensemble by intramolecular base-phosphate and sugar-phosphate interactions and (ii) destabilization of the native folded state by underestimation of stability of base pairing. Here, we introduce a general ff term (gHBfix) that can selectively fine-tune nonbonding interaction terms in RNA ffs, in particular, the H bonds. The gHBfix potential affects the pairwise interactions between all possible pairs of the specific atom types, while all other interactions remain intact; i.e., it is not a structure-based model. In order to probe the ability of the gHBfix potential to refine the ff nonbonded terms, we performed an extensive set of folding simulations of RNA tetranucleotides and tetraloops. On the basis of these data, we propose particular gHBfix parameters to modify the AMBER RNA ff. The suggested parametrization significantly improves the agreement between experimental data and the simulation conformational ensembles, although our current ff version still remains far from being flawless. While attempts to tune the RNA ffs by conventional reparametrizations of dihedral potentials or nonbonded terms can lead to major undesired side effects, as we demonstrate for some recently published ffs, gHBfix has a clear promising potential to improve the ff performance while avoiding introduction of major new imbalances.

Heterogeneous CPU+GPU-Enabled Simulations for DFTB Molecular Dynamics of Large Chemical and Biological Systems

We introduce a new heterogeneous CPU+GPU-enhanced DFTB approach for the routine and efficient simulation of large chemical and biological systems. Compared to homogeneous computing with conventional CPUs, heterogeneous computing approaches exhibit substantial performance with only a modest increase in power consumption, both of which are essential to upcoming exascale computing initiatives. We show that DFTB-based molecular dynamics is a natural candidate for heterogeneous computing, since the computational bottleneck in these simulations is the diagonalization of the Hamiltonian matrix, which is performed several times during a single molecular dynamics trajectory. To thoroughly test and understand the performance of our heterogeneous CPU+GPU approach, we examine a variety of algorithmic implementations, benchmarks of different hardware configurations, and applications of this methodology on several large chemical and biological systems. Finally, to demonstrate the capability of our implementation, we conclude with a large-scale DFTB MD simulation of explicitly solvated HIV protease (3974 atoms total) as a proof-of-concept example of an extremely large/complex system which, to the best of our knowledge, is the first time that an entire explicitly solvated protein has been treated at a quantum-based MD level of detail.

Can All-Atom Molecular Dynamics Simulations Quantitatively Describe Homeodomain-DNA Binding Equilibria?

We systematically investigate the applicability of a molecular dynamics-based setup for the calculations of standard binding free energies of biologically relevant protein-DNA complexes. The free energies are extracted from a potential of mean force calculated using umbrella sampling simulations. Two protein-DNA systems derived from a homeodomain transcription factor complex are studied in order to investigate the binding of both disordered and globular proteins. Free energies and trajectories obtained using two modern molecular mechanical force fields are compared to each other and to experimental data. The temperature dependence of the calculated standard binding free energies is investigated by performing all simulations over a range of temperatures. We show that the values of standard binding free energies obtained from these simulations are overestimated compared to experimental results. Significant differences are observed between the two protein-DNA systems and between the two force fields, which are explained by different propensities to form inter- and intramolecular contacts. The number of protein-DNA contacts increases with increasing temperature, in agreement with the experimentally known temperature dependence of enthalpies of binding. However, conclusions about the temperature dependence of the standard binding free energies cannot be made with confidence, as the differences among the values are on the order of statistical uncertainty.

Polarizable force field for RNA based on the classical drude oscillator

RNA molecules are highly dynamic and capable of adopting a wide range of complex, folded structures. The factors driving the folding and dynamics of these structures are dependent on a balance of base pairing, hydration, base stacking, ion interactions, and the conformational sampling of the 2'-hydroxyl group in the ribose sugar. The representation of these features is a challenge for empirical force fields used in molecular dynamics simulations. Toward meeting this challenge, the inclusion of explicit electronic polarization is important in accurately modeling RNA structure. In this work, we present a polarizable force field for RNA based on the classical Drude oscillator model, which represents electronic degrees of freedom via negatively charged particles attached to their parent atoms by harmonic springs. Beginning with parametrization against quantum mechanical base stacking interaction energy and conformational energy data, we have extended the Drude-2017 nucleic acid force field to include RNA. The conformational sampling of a range of RNA sequences were used to validate the force field, including canonical A-form RNA duplexes, stem-loops, and complex tertiary folds that bind multiple Mg2+ ions. Overall, the Drude-2017 RNA force field reproduces important properties of these structures, including the conformational sampling of the 2'-hydroxyl and key interactions with Mg2+ ions. © 2018 Wiley Periodicals, Inc.

Combining NMR Spectroscopy and Molecular Dynamic Simulations to Solve and Analyze the Structure of Protein-RNA Complexes

Understanding the RNA binding specificity of protein is of primary interest to decipher their function in the cell. Here, we review the methodology used to solve the structures of protein-RNA complexes using solution-state NMR spectroscopy: from sample preparation to structure calculation procedures. We also describe how molecular dynamics simulations can help providing additional information on the role of key amino acid side chains and of water molecules in protein-RNA recognition.

Molecular basis for the increased affinity of an RNA recognition motif with re-engineered specificity: A molecular dynamics and enhanced sampling simulations study

The RNA recognition motif (RRM) is the most common RNA binding domain across eukaryotic proteins. It is therefore of great value to engineer its specificity to target RNAs of arbitrary sequence. This was recently achieved for the RRM in Rbfox protein, where four mutations R118D, E147R, N151S, and E152T were designed to target the precursor to the oncogenic miRNA 21. Here, we used a variety of molecular dynamics-based approaches to predict specific interactions at the binding interface. Overall, we have run approximately 50 microseconds of enhanced sampling and plain molecular dynamics simulations on the engineered complex as well as on the wild-type Rbfox·pre-miRNA 20b from which the mutated systems were designed. Comparison with the available NMR data on the wild type molecules (protein, RNA, and their complex) served to establish the accuracy of the calculations.

Free energy calculations suggest that further improvements in affinity and selectivity are achieved by the S151T replacement.

RNA is an outstanding target for oncological intervention. Engineering the most common RNA binding motif in human proteins (called RRM) so as to bind to a specific RNA has an enormous pharmacological potential. Yet, it is highly non trivial to design RRM-bearing protein variants with RNA selectivity and affinity sufficiently high for clinical applications. Here we present an extensive molecular simulation study which shed light on the exquisite molecular recognition of the empirically-engineered complex between the RRM-bearing protein Rbfox and its RNA target pre-miR21. The simulations allow predicting a variant, the S151T, which may lead to further enhancement of selectivity and affinity for pre-miR21.

Structural dynamics of propeller loop: towards folding of RNA G-quadruplex

We have carried out an extended set of standard and enhanced-sampling MD simulations (for a cumulative simulation time of 620 μs) with the aim to study folding landscapes of the rGGGUUAGGG and rGGGAGGG parallel G-hairpins (PH) with propeller loop. We identify folding and unfolding pathways of the PH, which is bridged with the unfolded state via an ensemble of cross-like structures (CS) possessing mutually tilted or perpendicular G-strands interacting via guanine-guanine H-bonding. The oligonucleotides reach the PH conformation from the unfolded state via a conformational diffusion through the folding landscape, i.e. as a series of rearrangements of the H-bond interactions starting from compacted anti-parallel hairpin-like structures. Although isolated PHs do not appear to be thermodynamically stable we suggest that CS and PH-types of structures are sufficiently populated during RNA guanine quadruplex (GQ) folding within the context of complete GQ-forming sequences. These structures may participate in compact coil-like ensembles that involve all four G-strands and already some bound ions. Such ensembles can then rearrange into the fully folded parallel GQs via conformational diffusion. We propose that the basic atomistic folding mechanism of propeller loops suggested in this work may be common for their formation in RNA and DNA GQs.

QM/MM Calculations on Protein-RNA Complexes: Understanding Limitations of Classical MD Simulations and Search for Reliable Cost-Effective QM Methods

Although atomistic explicit-solvent Molecular Dynamics (MD) is a popular tool to study protein-RNA recognition, satisfactory MD description of protein-RNA complexes is not always achieved. Unfortunately, it is often difficult to separate MD simulation instabilities primarily caused by the simple point-charge molecular mechanics (MM) force fields from problems related to the notorious uncertainties in the starting structures. Herein, we report a series of large-scale QM/MM calculations on the U1A protein-RNA complex. This experimentally well-characterized system has an intricate protein-RNA interface, which is very unstable in MD simulations. The QM/MM calculations identify several H-bonds poorly described by the MM method and thus indicate the sources of instabilities of the U1A interface in MD simulations. The results suggest that advanced QM/MM computations could be used to indirectly rationalize problems seen in MM-based MD simulations of protein-RNA complexes. As the most accurate QM method, we employ the computationally demanding meta-GGA density functional TPSS-D3(BJ)/def2-TZVP level of theory. Because considerably faster methods would be needed to extend sampling and to study even larger protein-RNA interfaces, a set of low-cost QM/MM methods is compared to the TPSS-D3(BJ)/def2-TZVP data. The PBEh-3c and B97-3c density functional composite methods appear to be suitable for protein-RNA interfaces. In contrast, HF-3c and the tight-binding Hamiltonians DFTB3-D3 and GFN-xTB perform unsatisfactorily and do not provide any advantage over the MM description. These conclusions are supported also by similar analysis of a simple HutP protein-RNA interface, which is well-described by MD with the exception of just one H-bond. Some other methodological aspects of QM/MM calculations on protein-RNA interfaces are discussed.

Bioinformatics Tools and Benchmarks for Computational Docking and 3D Structure Prediction of RNA-Protein Complexes

RNA-protein (RNP) interactions play essential roles in many biological processes, such as regulation of co-transcriptional and post-transcriptional gene expression, RNA splicing, transport, storage and stabilization, as well as protein synthesis. An increasing number of RNP structures would aid in a better understanding of these processes. However, due to the technical difficulties associated with experimental determination of macromolecular structures by high-resolution methods, studies on RNP recognition and complex formation present significant challenges. As an alternative, computational prediction of RNP interactions can be carried out. Structural models obtained by theoretical predictive methods are, in general, less reliable compared to models based on experimental measurements but they can be sufficiently accurate to be used as a basis for to formulating functional hypotheses. In this article, we present an overview of computational methods for 3D structure prediction of RNP complexes. We discuss currently available methods for macromolecular docking and for scoring 3D structural models of RNP complexes in particular. Additionally, we also review benchmarks that have been developed to assess the accuracy of these methods.

Importance of amino acids Leu135 and Tyr236 for the interaction between EhCFIm25 and RNA: a molecular dynamics simulation study

The CFIm25 subunit of the heterotetrameric cleavage factor Im (CFIm) is a critical factor in the formation of the poly(A) tail at mRNA 3' end, regulating the recruitment of polyadenylation factors, poly(A) site selection, and cleavage/polyadenylation reactions. We previously reported the homologous protein (EhCFIm25) in Entamoeba histolytica, the protozoan causing human amoebiasis, and showed the relevance of conserved Leu135 and Tyr236 residues for RNA binding. We also identified the GUUG sequence as the recognition site of EhCFIm25. To understand the interactions network that allows the EhCFIm25 to maintain its three-dimensional structure and function, here we performed molecular dynamics simulations of wild-type (WT) and mutant proteins, alone or interacting with the GUUG molecule. Our results indicated that in the presence of the GUUG sequence, WT converged more quickly to lower RMSD values in comparison with mutant proteins. However, RMSF values showed that movements of amino acids of WT and EhCFIm25*L135 T were almost identical, interacting or not with the GUUG molecule. Interestingly, EhCFIm25*L135 T, which is the only mutant with a slight RNA binding activity experimentally, presents the same stabilization of bend structures and alpha helices as WT, notably in the C-terminus. Moreover, WT and EhCFIm25*L135 T presented almost the same number of contacts that mainly involve lysine residues interacting with the G4 nucleotide. Overall, our data proposed a clear description of the structural and mechanistic data that govern the RNA binding capacity of EhCFIm25.

All-atom simulations disentangle the functional dynamics underlying gene maturation in the intron lariat spliceosome

The spliceosome (SPL) is a majestic macromolecular machinery composed of five small nuclear RNAs and hundreds of proteins. SPL removes noncoding introns from precursor messenger RNAs (pre-mRNAs) and ligates coding exons, giving rise to functional mRNAs. Building on the first SPL structure solved at near-atomic-level resolution, here we elucidate the functional dynamics of the intron lariat spliceosome (ILS) complex through multi-microsecond-long molecular-dynamics simulations of ∼1,000,000 atoms models. The ILS essential dynamics unveils (i) the leading role of the Spp42 protein, which heads the gene maturation by tuning the motions of distinct SPL components, and (ii) the critical participation of the Cwf19 protein in displacing the intron lariat/U2 branch helix. These findings provide unprecedented details on the SPL functional dynamics, thus contributing to move a step forward toward a thorough understanding of eukaryotic pre-mRNA splicing.

Molecular dynamics correctly models the unusual major conformation of the GAGU RNA internal loop and with NMR reveals an unusual minor conformation

The RNA "GAGU" duplex, (5'GACGAGUGUCA)2, contains the internal loop (5'-GAGU-3')2 , which has two conformations in solution as determined by NMR spectroscopy. The major conformation has a loop structure consisting of trans-Watson-Crick/Hoogsteen GG pairs, A residues stacked on each other, U residues bulged outside the helix, and all sugars with a C2'-endo conformation. This differs markedly from the internal loops, (5'-GAGC-3')2, (5'-AAGU-3')2, and (5'-UAGG-3')2, which all have cis-Watson-Crick/Watson-Crick AG "imino" pairs flanked by cis-Watson-Crick/Watson-Crick canonical pairs resulting in maximal hydrogen bonding. Here, molecular dynamics was used to test whether the Amber force field (ff99 + bsc0 + OL3) approximates molecular interactions well enough to keep stable the unexpected conformation of the GAGU major duplex structure and the NMR structures of the duplexes containing (5'-GAGC-3')2, (5'-AAGU-3')2, and (5'-UAGG-3')2 internal loops. One-microsecond simulations were repeated four times for each of the duplexes starting in their NMR conformations. With the exception of (5'-UAGG-3')2, equivalent simulations were also run starting with alternative conformations. Results indicate that the Amber force field keeps the NMR conformations of the duplexes stable for at least 1 µsec. They also demonstrate an unexpected minor conformation for the (5'-GAGU-3')2 loop that is consistent with newly measured NMR spectra of duplexes with natural and modified nucleotides. Thus, unrestrained simulations led to the determination of the previously unknown minor conformation. The stability of the native (5'-GAGU-3')2 internal loop as compared to other loops can be explained by changes in hydrogen bonding and stacking as the flanking bases are changed.

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.

Molecular simulations of the ribosome and associated translation factors

The ribosome is a macromolecular complex which is responsible for protein synthesis in all living cells according to their transcribed genetic information. Using X-ray crystallography and, more recently, cryo-electron microscopy (cryo-EM), the structure of the ribosome was resolved at atomic resolution in many functional and conformational states. Molecular dynamics simulations have added information on dynamics and energetics to the available structural information, thereby have bridged the gap to the kinetics obtained from single-molecule and bulk experiments. Here, we review recent computational studies that brought notable insights into ribosomal structure and function.

Structure and Dynamics of DNA and RNA Double Helices of CAG and GAC Trinucleotide Repeats

CAG trinucleotide repeats are known to cause 10 late-onset progressive neurodegenerative disorders as the repeats expand beyond a threshold, whereas GAC repeats are associated with skeletal dysplasias and expand from the normal five to a maximum of seven repeats. The TR secondary structure is believed to play a role in CAG expansions. We have carried out free energy and molecular dynamics studies to determine the preferred conformations of the A-A noncanonical pairs in (CAG)_n and (GAC)_n trinucleotide repeats (n = 1, 4) and the consequent changes in the overall structure of the RNA and DNA duplexes. We find that the global free energy minimum corresponds to A-A pairs stacked inside the core of the helix with anti-anti conformations in RNA and (high-anti)-(high-anti) conformations in DNA. The next minimum corresponds to anti-syn conformations, whereas syn-syn conformations are higher in energy. Transition rates of the A-A conformations are higher for RNA than DNA. Mechanisms for these various transitions are identified. Additional structural and dynamical aspects of the helical conformations are explored, with a focus on contrasting CAG and GAC duplexes. The neutralizing ion distribution around the noncanonical pairs is described.

Structural study of the Fox-1 RRM protein hydration reveals a role for key water molecules in RRM-RNA recognition

The Fox-1 RNA recognition motif (RRM) domain is an important member of the RRM protein family. We report a 1.8 Å X-ray structure of the free Fox-1 containing six distinct monomers. We use this and the nuclear magnetic resonance (NMR) structure of the Fox-1 protein/RNA complex for molecular dynamics (MD) analyses of the structured hydration. The individual monomers of the X-ray structure show diverse hydration patterns, however, MD excellently reproduces the most occupied hydration sites. Simulations of the protein/RNA complex show hydration consistent with the isolated protein complemented by hydration sites specific to the protein/RNA interface. MD predicts intricate hydration sites with water-binding times extending up to hundreds of nanoseconds. We characterize two of them using NMR spectroscopy, RNA binding with switchSENSE and free-energy calculations of mutant proteins. Both hydration sites are experimentally confirmed and their abolishment reduces the binding free-energy. A quantitative agreement between theory and experiment is achieved for the S155A substitution but not for the S122A mutant. The S155 hydration site is evolutionarily conserved within the RRM domains. In conclusion, MD is an effective tool for predicting and interpreting the hydration patterns of protein/RNA complexes. Hydration is not easily detectable in NMR experiments but can affect stability of protein/RNA complexes.

Noncanonical α/γ Backbone Conformations in RNA and the Accuracy of Their Description by the AMBER Force Field

The sugar-phosphate backbone of RNA can exist in diverse rotameric substates, giving RNA molecules enormous conformational variability. The most frequent noncanonical backbone conformation in RNA is α/γ = t/t, which is derived from the canonical backbone by a crankshaft motion and largely preserves the standard geometry of the RNA duplex. A similar conformation also exists in DNA, where it has been extensively studied and shown to be involved in DNA-protein interactions. However, the function of the α/γ = t/t conformation in RNA is poorly understood. Here, we present molecular dynamics simulations of several prototypical RNA structures obtained from X-ray and NMR experiments, including canonical and mismatched RNA duplexes, UUCG and GAGA tetraloops, Loop E, the sarcin-ricin loop, a parallel guanine quadruplex, and a viral pseudoknot. The stability of various noncanonical α/γ backbone conformations was analyzed with two AMBER force fields, ff99bsc0χ_OL3 and ff99bsc0χ_OL3 with the recent εζ_OL1 and β_OL1 corrections for DNA. Although some α/γ substates were stable with seemingly well-described equilibria, many were unstable in our simulations. Notably, the most frequent noncanonical conformer α/γ = t/t was unstable in both tested force fields. Possible reasons for this instability are discussed. Our work reveals a potentially important artifact in RNA force fields and highlights a need for further force field refinement.