Conformational heterogeneity of UCAAUC RNA oligonucleotide from molecular dynamics simulations, SAXS, and NMR experiments

Can We Ever Develop an Ideal RNA Force Field? Lessons Learned from Simulations of the UUCG RNA Tetraloop and Other Systems

Molecular dynamics (MD) simulations are an important and well-established tool for investigating RNA structural dynamics, but their accuracy relies heavily on the quality of the employed force field (ff). In this work, we present a comprehensive evaluation of widely used pair-additive and polarizable RNA ffs using the challenging UUCG tetraloop (TL) benchmark system. Extensive standard MD simulations, initiated from the NMR structure of the 14-mer UUCG TL, revealed that most ffs did not maintain the native state, instead favoring alternative loop conformations. Notably, three very recent variants of pair-additive ffs, OL3CP-gHBfix21, DES-Amber, and OL3R2.7, successfully preserved the native structure over a 10 × 20 μs time scale. To further assess these ffs, we performed enhanced sampling folding simulations of the shorter 8-mer UUCG TL, starting from the single-stranded conformation. Estimated folding free energies (ΔG°fold) varied significantly among these three ffs, with values of 0.0 ± 0.6, 2.4 ± 0.8, and 7.4 ± 0.2 kcal/mol for OL3CP-gHBfix21, DES-Amber, and OL3R2.7, respectively. The ΔG°fold value predicted by the OL3CP-gHBfix21 ff was closest to experimental estimates, ranging from -1.6 to -0.7 kcal/mol. In contrast, the higher ΔG°fold values obtained using DES-Amber and OL3R2.7 were unexpected, suggesting that key interactions are inaccurately described in the folded, unfolded, or misfolded ensembles. These discrepancies led us to further test DES-Amber and OL3R2.7 ffs on additional RNA and DNA systems, where further performance issues were observed. Our results emphasize the complexity of accurately modeling RNA dynamics and suggest that creating an RNA ff capable of reliably performing across a wide range of RNA systems remains extremely challenging. In conclusion, our study provides valuable insights into the capabilities of current RNA ffs and highlights key areas for future ff development.

Coarse-Grained Model of Disordered RNA for Simulations of Biomolecular Condensates

Protein-RNA condensates are involved in a range of cellular activities. Coarse-grained molecular models of intrinsically disordered proteins have been developed to shed light on and predict single-chain properties and phase separation. An RNA model compatible with such models for disordered proteins would enable the study of complex biomolecular mixtures involving RNA. Here, we present a sequence-independent coarse-grained, two-beads-per-nucleotide model of disordered, flexible RNA based on a hydropathy scale. We parametrize the model, which we term CALVADOS-RNA, using a combination of bottom-up and top-down approaches to reproduce local RNA geometry and intramolecular interactions based on atomistic simulations and in vitro experiments. The model semiquantitatively captures several aspects of RNA-RNA and RNA-protein interactions. We examined RNA-RNA interactions by comparing calculated and experimental virial coefficients and nonspecific RNA-protein interaction by studying the reentrant phase behavior of protein-RNA mixtures. We demonstrate the utility of the model by simulating the formation of mixed condensates consisting of the disordered region of MED1 and RNA chains and the selective partitioning of disordered regions from transcription factors into these and compare the results to experiments. Despite the simplicity of our model, we show that it captures several key aspects of protein-RNA interactions and may therefore be used as a baseline model to study several aspects of the biophysics and biology of protein-RNA condensates.

Sequence-dependent conformational preferences of disordered single-stranded RNA

Disordered single-stranded RNA (ssRNA) molecules, like their well-folded counterparts, have crucial functions that depend on their structures. However, since native ssRNAs constitute a highly heterogeneous conformer population, their structural characterization poses challenges. One important question regards the role of sequence in influencing ssRNA structure. Here, we adopt an integrated approach that combines solution-based measurements, including small-angle X-ray scattering (SAXS) and Förster resonance energy transfer (FRET), with experimentally guided all-atom molecular dynamics (MD) simulations, to construct structural ensembles of a 30-nucleotide RNA homopolymer (rU30) and a 30-nucleotide RNA heteropolymer with an A-/C-rich sequence. We compare the size, shape, and flexibility of the two different ssRNAs. While the average properties align with polymer-physics descriptions of flexible polymers, we discern distinct, sequence-dependent conformations at the molecular level that demand a more detailed representation than provided by polymer models. These findings emphasize the role of sequence in shaping the overall properties of ssRNA.

mRNA Fragmentation Pattern Detected by SHAPE

The success of messenger RNA (mRNA) vaccines in controlling COVID-19 has warranted further developments in new technology. Currently, their quality control process largely relies on low-resolution electrophoresis for detecting chain breaks. Here, we present an approach using multi-primer reverse transcription sequencing (MPRT-seq) to identify degradation fragments in mRNA products. Using this in-house-made mRNA containing two antigens and untranslated regions (UTRs), we analyzed the mRNA completeness and degradation pattern at a nucleotide resolution. We then analyzed the sensitive base sequence and its correlation with the secondary structure. Our MPRT-seq mapping shows that certain sequences on the 5' of bulge-stem-loop structures can result in preferential chain breaks. Our results agree with commonly used capillary electrophoresis (CE) integrity analysis but at a much higher resolution, and can improve mRNA stability by providing information to remove sensitive structures or sequences in the mRNA sequence design.

Sampling globally and locally correct RNA 3D structures using Ernwin, SPQR and experimental SAXS data

The determination of the three-dimensional structure of large RNA macromolecules in solution is a challenging task that often requires the use of several experimental and computational techniques. Small-angle X-ray scattering can provide insight into some geometrical properties of the probed molecule, but this data must be properly interpreted in order to generate a three-dimensional model. Here, we propose a multiscale pipeline which introduces SAXS data into modelling the global shape of RNA in solution, which can be hierarchically refined until reaching atomistic precision in explicit solvent. The low-resolution helix model (Ernwin) deals with the exploration of the huge conformational space making use of the SAXS data, while a nucleotide-level model (SPQR) removes clashes and disentangles the proposed structures, leading the structure to an all-atom representation in explicit water. We apply the procedure on four different known pdb structures up to 159 nucleotides with promising results. Additionally, we predict an all-atom structure for the Plasmodium falceparum signal recognition particle ALU RNA based on SAXS data deposited in the SASBDB, which has an alternate conformation and better fit to the SAXS data than the previously published structure based on the same data but other modelling methods.

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.

Hierarchical Assembly of Single-Stranded RNA

Single-stranded RNA (ssRNA) plays a major role in the flow of genetic information-most notably, in the form of messenger RNA (mRNA)-and in the regulation of biological processes. The highly dynamic nature of chains of unpaired nucleobases challenges structural characterizations of ssRNA by experiments or molecular dynamics (MD) simulations alike. Here, we use hierarchical chain growth (HCG) to construct ensembles of ssRNA chains. HCG assembles the structures of protein and nucleic acid chains from fragment libraries created by MD simulations. Applied to homo- and heteropolymeric ssRNAs of different lengths, we find that HCG produces structural ensembles that overall are in good agreement with diverse experiments, including nuclear magnetic resonance (NMR), small-angle X-ray scattering (SAXS), and single-molecule Förster resonance energy transfer (FRET). The agreement can be further improved by ensemble refinement using Bayesian inference of ensembles (BioEn). HCG can also be used to assemble RNA structures that combine base-paired and base-unpaired regions, as illustrated for the 5' untranslated region (UTR) of SARS-CoV-2 RNA.

Simple Adjustment of Intranucleotide Base-Phosphate Interaction in the OL3 AMBER Force Field Improves RNA Simulations

Molecular dynamics (MD) simulations represent an established tool to study RNA molecules. The outcome of MD studies depends, however, on the quality of the force field (ff). Here we suggest a correction for the widely used AMBER OL3 ff by adding a simple adjustment of the nonbonded parameters. The reparameterization of the Lennard-Jones potential for the -H8···O5'- and -H6···O5'- atom pairs addresses an intranucleotide steric clash occurring in the type 0 base-phosphate interaction (0BPh). The nonbonded fix (NBfix) modification of 0BPh interactions (NBfix0BPh modification) was tuned via a reweighting approach and subsequently tested using an extensive set of standard and enhanced sampling simulations of both unstructured and folded RNA motifs. The modification corrects minor but visible intranucleotide clash for the anti nucleobase conformation. We observed that structural ensembles of small RNA benchmark motifs simulated with the NBfix0BPh modification provide better agreement with experiments. No side effects of the modification were observed in standard simulations of larger structured RNA motifs. We suggest that the combination of OL3 RNA ff and NBfix0BPh modification is a viable option to improve RNA MD simulations.

Advances, Applications, and Perspectives in Small-Angle X-ray Scattering of RNA

RNAs exhibit a plethora of functions far beyond transmitting genetic information. Often, RNA functions are entailed in their structure, be it as a regulatory switch, protein binding site, or providing catalytic activity. Structural information is a prerequisite for a full understanding of RNA-regulatory mechanisms. Owing to the inherent dynamics, size, and instability of RNA, its structure determination remains challenging. Methods such as NMR spectroscopy, X-ray crystallography, and cryo-electron microscopy can provide high-resolution structures; however, their limitations make structure determination, even for small RNAs, cumbersome, if at all possible. Although at a low resolution, small-angle X-ray scattering (SAXS) has proven valuable in advancing structure determination of RNAs as a complementary method, which is also applicable to large-sized RNAs. Here, we review the technological and methodological advancements of RNA SAXS. We provide examples of the powerful inclusion of SAXS in structural biology and discuss possible future applications to large RNAs.

Internal Normal Mode Analysis Applied to RNA Flexibility and Conformational Changes

We investigated the capability of internal normal modes to reproduce RNA flexibility and predict observed RNA conformational changes and, notably, those induced by the formation of RNA-protein and RNA-ligand complexes. Here, we extended our iNMA approach developed for proteins to study RNA molecules using a simplified representation of the RNA structure and its potential energy. Three data sets were also created to investigate different aspects. Despite all the approximations, our study shows that iNMA is a suitable method to take into account RNA flexibility and describe its conformational changes opening the route to its applicability in any integrative approach where these properties are crucial.

Integrating experimental data with molecular simulations to investigate RNA structural dynamics

Conformational dynamics is crucial for ribonucleic acid (RNA) function. Techniques such as nuclear magnetic resonance, cryo-electron microscopy, small- and wide-angle X-ray scattering, chemical probing, single-molecule Förster resonance energy transfer, or even thermal or mechanical denaturation experiments probe RNA dynamics at different time and space resolutions. Their combination with accurate atomistic molecular dynamics (MD) simulations paves the way for quantitative and detailed studies of RNA dynamics. First, experiments provide a quantitative validation tool for MD simulations. Second, available data can be used to refine simulated structural ensembles to match experiments. Finally, comparison with experiments allows for improving MD force fields that are transferable to new systems for which data is not available. Here we review the recent literature and provide our perspective on this field.