Abstract While novel deep learning and statistics-based techniques predict accurate structural models for proteins and non-coding RNA, describing their macromolecular conformations in solution is still challenging. Small-angle X-ray scattering (SAXS) in solution is an efficient technique to validate structural predictions by comparing the experimental SAXS profile with those calculated from predicted structures. There are two main challenges in comparing SAXS profiles to RNA structures: the structures often lack cations necessary for stability and charge neutralization, and a single structure inadequately represents the conformational plasticity of RNA. We introduce Solution Conformation Predictor for RNA (SCOPER) to address these challenges. This pipeline integrates kinematics-based conformational sampling with the innovative deep-learning model, IonNet, designed for predicting Mg 2+ ion binding sites. Validated through benchmarking against fourteen experimental datasets, SCOPER significantly improved the quality of SAXS profile fits by including Mg 2+ ions and sampling of conformational plasticity. We observe that an increased content of monovalent and bivalent ions leads to decreased RNA plasticity. Therefore, carefully adjusting the plasticity and ion density is crucial to avoid overfitting experimental SAXS data. SCOPER is an efficient tool for accurately predicting the solution state of RNAs and providing atomistic models of their structures. The method is available from: https://github.com/dina-lab3d/IonNet Our pipeline is available for use as a web server: https://bilbomd.bl1231.als.lbl.gov/ 

pdf/predicting-rna-structure-and-dynamics-with-deep-learning-and-1nv69ko2j0.pdf

Predicting RNA Structure and Dynamics with Deep Learning and Solution Scattering

ABSTRACT 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 towards 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 in TDP-43 function and pathology, a comprehensive characterization of the effect of RNA-binding on conformational dynamics, interdomain interactions and intradomain stability of the tandem RRMs has not yet been conducted. 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. Our simulations reveal a high intrinsic conformational plasticity of the tandem RRMs in the absence of RNA which surprisingly, is accompanied by a tendency of RRM1 to adopt partially-unfolded conformations. While binding to RNA limits the overall conformational space of the tandem RRMs and promotes intradomain stability, several RRM-RNA contacts mediated by highly conserved residues are observed to be far more dynamic than previously inferred from NMR structural ensemble. Overall, our simulations reveal how RNA dynamically tunes the structural and conformational landscape of TDP-43 tandem RRMs, contributing to physiological function and mitigating pathological aggregation. SIGNIFICANCE The cytoplasmic mislocalization and aggregation of TDP-43 due to loss of its RNA-binding capability is associated with the onset and progression of neurodegenerative diseases such as Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Due to the flexible nature of RNA and the presence of a disordered linker between RRM domains, characterizing the dynamic interactions between RRMs-RNA and/or RRM1-RRM2 by experiments alone has remained challenging. In this study, we performed all-atom simulations initiated from the NMR conformers of RNA-bound tandem RRMs of TDP-43 to investigate their underlying structural and conformational dynamics. Our findings indicate that RNA binding effectively reduces conformational heterogeneity in the tandem RRMs and acts as a protective factor for the unfolding and aggregation of RRM1. These effects are achieved through a combination of stable and dynamic protein-RNA interactions which involve highly conserved amino acids. 

pdf/rna-binding-tunes-the-conformational-plasticity-and-2iaa64iirx.pdf

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

How the interactions with RNA influences iron homeostasis. 

pdf/influencing-iron-homeostasis-by-a-transition-metal-complex-cmom5pjwwsy8.pdf

Influencing iron homeostasis by a transition metal complex interacting with a messenger-RNA stem loop in the iron regulating element

We investigated the capability of internal normal modes to reproduce RNA dynamics 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 RNA structure and its potential energy. Three datasets 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.

Internal Normal Mode Analysis applied to RNA flexibility and conformational changes

Facing the current challenges raised by human health diseases requires the un-derstanding 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 com-plexes 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 and the structural waters involved in the binding. Based on our analysis, the interfaces rearranged during the simulation time showing alternative and stable residue-residue contacts with respect to the experimental structure.

The dynamics of protein-RNA interfaces using all-atom molecular dynamics simulations

Plasticity and Co-Factor-Dependent Structural Changes in the RecA Nucleoprotein Filament Studied by Small-Angle X-Ray Scattering (SAXS) Measurements and Molecular Modeling

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.

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

BPS2025 - Investigating the mechanosensitivity of RecA nucleoprotein filaments: Influence of DNA length in recombination

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