Conformational Heterogeneity of RNA Stem-Loop Hairpins Bound to FUS-RNA Recognition Motif with Disordered RGG Tail Revealed by Unbiased Molecular Dynamics Simulations

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.

RNA binding tunes the conformational plasticity and intradomain stability of TDP-43 tandem RNA recognition motifs

TAR DNA binding protein 43 (TDP-43) is a nuclear RNA/DNA-binding protein with pivotal roles in RNA-related processes such as splicing, transcription, transport, and stability. The high binding affinity and specificity of TDP-43 toward its cognate RNA sequences (GU-rich) is mediated by highly conserved residues in its tandem RNA recognition motif (RRM) domains (aa: 104-263). Importantly, the loss of RNA binding to the tandem RRMs caused by physiological stressors and chemical modifications promotes cytoplasmic mislocalization and pathological aggregation of TDP-43. Despite the substantial implications of RNA binding in TDP-43 function and pathology, its precise effects on the intradomain stability, and conformational dynamics of the tandem RRMs is not properly understood. Here, we employed all-atom molecular dynamics (MD) simulations to assess the effect of RNA binding on the conformational landscape and intradomain stability of TDP-43 tandem RRMs. RNA limits the overall conformational space of the tandem RRMs and promotes intradomain stability through a combination of specific base stacking interactions and transient electrostatic interactions. In contrast, tandem RRMs exhibit a high intrinsic conformational plasticity in the absence of RNA, which, surprisingly, is accompanied by a tendency of RRM1 to adopt partially unfolded conformations. Overall, our simulations reveal how RNA binding dynamically tunes the structural and conformational landscape of TDP-43 tandem RRMs, contributing to physiological function and mitigating pathological aggregation.

Structure and Internal Dynamics of Short RNA Duplexes Determined by a Combination of Pulsed EPR Methods and MD Simulations

We used EPR spectroscopy to characterize the structure of RNA duplexes and their internal twist, stretch and bending motions. We prepared eight 20-base-pair-long RNA duplexes containing the rigid spin-label Çm, a cytidine analogue, at two positions and acquired orientation-selective PELDOR/DEER data. By using different frequency bands (X-, Q-, G-band), detailed information about the distance and orientation of the labels was obtained and provided insights into the global conformational dynamics of the RNA duplex. We used 19F Mims ENDOR experiments on three singly Çm- and singly fluorine-labeled RNA duplexes to determine the exact position of the Çm spin label in the helix. In a quantitative comparison to MD simulations of RNA with and without Çm spin labels, we found that state-of-the-art force fields with explicit parameterization of the spin label were able to describe the conformational ensemble present in our experiments. The MD simulations further confirmed that the Çm spin labels are excellent mimics of cytidine inducing only small local changes in the RNA structure. Çm spin labels are thus ideally suited for high-precision EPR experiments to probe the structure and, in conjunction with MD simulations, motions of RNA.

RNA regulates cohesiveness and porosity of a biological condensate

Biological condensates have emerged as key elements of a biological cell function, concentrating disparate biomolecules to accomplish specific biological tasks. RNA was identified as a key ingredient of such condensates, however, its effect on the physical properties of the condensate was found to depend on the condensate's composition while its effect on the microstructure has remained elusive. Here, we characterize the physical properties and the microstructure of a protein-RNA condensate by means of large-scale coarse-grained (CG) molecular dynamics simulations. By developing a custom CG model of RNA compatible with a popular CG model of proteins, we systematically investigate the structural, thermodynamic, and kinetic properties of condensate droplets containing thousands of individual protein and RNA molecules over a range of temperatures. While we find RNA to increase the condensate's cohesiveness, its effect on the condensate's fluidity is more nuanced with longer molecules compacting the condensate and making it less fluid. We show that a biological condensate has a sponge-like morphology of interconnected channels of size that increases with temperature and decreases in the presence of RNA. Our results suggest that longer RNA form a dynamic scaffold within a condensate, regulating not only its fluidity but also permeability to intruder molecules.

Developing an Implicit Solvation Machine Learning Model for Molecular Simulations of Ionic Media

Molecular dynamics (MD) simulations of biophysical systems require accurate modeling of their native environment, i.e., aqueous ionic solution, as it critically impacts the structure and function of biomolecules. On the other hand, the models should be computationally efficient to enable simulations of large spatiotemporal scales. Here, we present the deep implicit solvation model for sodium chloride solutions that satisfies both requirements. Owing to the use of the neural network potential, the model can capture the many-body potential of mean force, while the implicit water treatment renders the model inexpensive. We demonstrate our approach first for pure ionic solutions with concentrations ranging from physiological to 2 M. We then extend the model to capture the effective ion interactions in the vicinity and far away from a DNA molecule. In both cases, the structural properties are in good agreement with all-atom MD, showcasing a general methodology for the efficient and accurate modeling of ionic media.

"Boundary residues" between the folded RNA recognition motif and disordered RGG domains are critical for FUS-RNA binding

Fused in sarcoma (FUS) is an abundant RNA-binding protein, which drives phase separation of cellular condensates and plays multiple roles in RNA regulation. The RNA-binding ability of FUS protein is crucial to its cellular function. Here, our molecular simulation study on the FUS-RNA complex provides atomic resolution insights into the observations from biochemical studies and also illuminates our understanding of molecular driving forces that mediate the structure, stability, and interaction of the RNA recognition motif (RRM) and RGG domains of FUS with a stem-loop junction RNA. We observe clear cooperativity and division of labor among the ordered (RRM) and disordered domains (RGG1 and RGG2) of FUS that leads to an organized and tighter RNA binding. Irrespective of the length of RGG2, the RGG2-RNA interaction is confined to the stem-loop junction and the proximal stem regions. On the other hand, the RGG1 interactions are primarily with the longer RNA stem. We find that the C terminus of RRM, which make up the "boundary residues" that connect the folded RRM with the long disordered RGG2 stretch of the protein, plays a critical role in FUS-RNA binding. Our study provides high-resolution molecular insights into the FUS-RNA interactions and forms the basis for understanding the molecular origins of full-length FUS interaction with RNA.

Capturing heterogeneous conformers of cobalamin riboswitch by cryo-EM

RNA conformational heterogeneity often hampers its high-resolution structure determination, especially for large and flexible RNAs devoid of stabilizing proteins or ligands. The adenosylcobalamin riboswitch exhibits heterogeneous conformations under 1 mM Mg2+ concentration and ligand binding reduces conformational flexibility. Among all conformers, we determined one apo (5.3 Å) and four holo cryo-electron microscopy structures (overall 3.0-3.5 Å, binding pocket 2.9-3.2 Å). The holo dimers exhibit global motions of helical twisting and bending around the dimer interface. A backbone comparison of the apo and holo states reveals a large structural difference in the P6 extension position. The central strand of the binding pocket, junction 6/3, changes from an 'S'- to a 'U'-shaped conformation to accommodate ligand. Furthermore, the binding pocket can partially form under 1 mM Mg2+ and fully form under 10 mM Mg2+ within the bound-like structure in the absence of ligand. Our results not only demonstrate the stabilizing ligand-induced conformational changes in and around the binding pocket but may also provide further insight into the role of the P6 extension in ligand binding and selectivity.

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.

Benchmarking Molecular Dynamics Force Fields for All-Atom Simulations of Biological Condensates

Proteins containing intrinsically disordered regions are integral parts of the cellular signaling pathways and common components of biological condensates. Point mutations in the protein sequence, genetic at birth or acquired through aging, can alter the properties of the condensates, marking the onset of neurodegenerative diseases such as ALS and dementia. While the all-atom molecular dynamics method can, in principle, elucidate the conformational changes that arise from point mutations, the applications of this method to protein condensate systems is conditioned upon the availability of molecular force fields that can accurately describe both structured and disordered regions of such proteins. Using the special-purpose Anton 2 supercomputer, we benchmarked the efficacy of nine presently available molecular force fields in describing the structure and dynamics of a Fused in sarcoma (FUS) protein. Five-microsecond simulations of the full-length FUS protein characterized the effect of the force field on the global conformation of the protein, self-interactions among its side chains, solvent accessible surface area, and the diffusion constant. Using the results of dynamic light scattering as a benchmark for the FUS radius of gyration, we identified several force fields that produced FUS conformations within the experimental range. Next, we used these force fields to perform ten-microsecond simulations of two structured RNA binding domains of FUS bound to their respective RNA targets, finding the choice of the force field to affect stability of the RNA-FUS complex. Taken together, our data suggest that a combination of protein and RNA force fields sharing a common four-point water model provides an optimal description of proteins containing both disordered and structured regions and RNA-protein interactions. To make simulations of such systems available beyond the Anton 2 machines, we describe and validate implementation of the best performing force fields in a publicly available molecular dynamics program NAMD. Our NAMD implementation enables simulations of large (tens of millions of atoms) biological condensate systems and makes such simulations accessible to a broader scientific community.