A new way to see RNA

The Nucleic Acid Knowledgebase: a new portal for 3D structural information about nucleic acids

The Nucleic Acid Knowledgebase (nakb.org) is a new data resource, updated weekly, for experimentally determined 3D structures containing DNA and/or RNA nucleic acid polymers and their biological assemblies. NAKB indexes nucleic acid-containing structures derived from all major structure determination methods (X-ray, NMR and EM), including all held by the Protein Data Bank (PDB). As the planned successor to the Nucleic Acid Database (NDB), NAKB's design preserves all functionality of the NDB and provides novel nucleic acid-centric content, including structural and functional annotations, as well as annotations from and links to external resources. A variety of custom interactive tools have been developed to enable rapid exploration and drill-down of NAKB's content.

The pseudotorsional space of RNA

The characterization of the conformational landscape of the RNA backbone is rather complex due to the ability of RNA to assume a large variety of conformations. These backbone conformations can be depicted by pseudotorsional angles linking RNA backbone atoms, from which Ramachandran-like plots can be built. We explore here different definitions of these pseudotorsional angles, finding that the most accurate ones are the traditional η (eta) and θ (theta) angles, which represent the relative position of RNA backbone atoms P and C4'. We explore the distribution of η - θ in known experimental structures, comparing the pseudotorsional space generated with structures determined exclusively by one experimental technique. We found that the complete picture only appears when combining data from different sources. The maps provide a quite comprehensive representation of the RNA accessible space, which can be used in RNA-structural predictions. Finally, our results highlight that protein interactions lead to significant changes in the population of the η - θ space, pointing toward the role of induced-fit mechanisms in protein-RNA recognition.

lociPARSE: a locality-aware invariant point attention model for scoring RNA 3D structures

A scoring function that can reliably assess the accuracy of a 3D RNA structural model in the absence of experimental structure is not only important for model evaluation and selection but also useful for scoring-guided conformational sampling. However, high-fidelity RNA scoring has proven to be difficult using conventional knowledge-based statistical potentials and currently-available machine learning-based approaches. Here we present lociPARSE, a locality-aware invariant point attention architecture for scoring RNA 3D structures. Unlike existing machine learning methods that estimate superposition-based root mean square deviation (RMSD), lociPARSE estimates Local Distance Difference Test (lDDT) scores capturing the accuracy of each nucleotide and its surrounding local atomic environment in a superposition-free manner, before aggregating information to predict global structural accuracy. Tested on multiple datasets including CASP15, lociPARSE significantly outperforms existing statistical potentials (rsRNASP, cgRNASP, DFIRE-RNA, and RASP) and machine learning methods (ARES and RNA3DCNN) across complementary assessment metrics. lociPARSE is freely available at https://github.com/Bhattacharya-Lab/lociPARSE.

Sarcin/Ricin Domain RNA Retains Its Structure Better Than A-RNA in Adaptively Biased Molecular Dynamics Simulations

Less than one in thirty of the RNA sequences transcribed in humans are translated into protein. The noncoding RNA (ncRNA) functions in catalysis, structure, regulation, and more. However, for the most part, these functions are poorly characterized. RNA is modular and described by motifs that include helical A-RNA with canonical Watson-Crick base-pairing as well as structures with only noncanonical base pairs. Understanding the structure and dynamics of motifs will aid in deciphering functions of specific ncRNAs. We present computational studies on a standard sarcin/ricin domain (SRD), citrus bark cracking viroid SRD, as well as A-RNA. We have applied enhanced molecular dynamics techniques that construct an inverse free-energy surface (iFES) determined by collective variables that monitor base-pairing and backbone conformation. Each SRD RNA is flanked on each side by A-RNA, allowing comparison of the behavior of these motifs in the same molecule. The RNA iFESs have single peaks, indicating that the combined motifs should denature as a single cohesive unit, rather than by regional melting. Local root-mean-square deviation (RMSD) analysis and communication propensity (CProp, variance in distances between residue pairs) reveal distinct motif properties. Our analysis indicates that the standard SRD is more stable than the viroid SRD, which is more stable than A-RNA. Base pairs at SRD to A-RNA transitions have limited flexibility. Application of CProp reveals extraordinary stiffness of the SRD, allowing residues on opposite sides of the motif to sense each other's motions.

RNANet: an automatically built dual-source dataset integrating homologous sequences and RNA structures

MOTIVATION

Applied research in machine learning progresses faster when a clean dataset is available and ready to use. Several datasets have been proposed and released over the years for specific tasks such as image classification, speech-recognition and more recently for protein structure prediction. However, for the fundamental problem of RNA structure prediction, information is spread between several databases depending on the level we are interested in: sequence, secondary structure, 3D structure or interactions with other macromolecules. In order to speed-up advances in machine-learning based approaches for RNA secondary and/or 3D structure prediction, a dataset integrating all this information is required, to avoid spending time on data gathering and cleaning.

RESULTS

Here, we propose the first attempt of a standardized and automatically generated dataset dedicated to RNA combining together: RNA sequences, homology information (under the form of position-specific scoring matrices) and information derived by annotation of available 3D structures (including secondary structure, canonical and non-canonical interactions and backbone torsion angles). The data are retrieved from public databases PDB, Rfam and SILVA. The paper describes the procedure to build such dataset and the RNA structure descriptors we provide. Some statistical descriptions of the resulting dataset are also provided.

AVAILABILITY AND IMPLEMENTATION

The dataset is updated every month and available online (in flat-text file format) on the EvryRNA software platform (https://evryrna.ibisc.univ-evry.fr/evryrna/rnanet). An efficient parallel pipeline to build the dataset is also provided for easy reproduction or modification.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

BioCommons: a robust Java library for RNA structural bioinformatics

Motivation

Biomolecular structures come in multiple representations and diverse data formats. Their incompatibility with the requirements of data analysis programs significantly hinders the analytics and the creation of new structure-oriented bioinformatic tools. Therefore, the need for robust libraries of data processing functions is still growing.

Results

BioCommons is an open-source, Java library for structural bioinformatics. It contains many functions working with the 2D and 3D structures of biomolecules, with a particular emphasis on RNA.

Availability and implementation

The library is available in Maven Central Repository and its source code is hosted on GitHub: https://github.com/tzok/BioCommons

Supplementary information

Supplementary data are available at Bioinformatics online.

Understanding the binding specificities of mRNA targets by the mammalian Quaking protein

Mammalian Quaking (QKI) protein, a member of STAR family of proteins is a mRNA-binding protein, which post-transcriptionally modulates the target RNA. QKI protein possesses a maxi-KH domain composed of single heterogeneous nuclear ribonucleoprotein K homology (KH) domain and C-terminal QUA2 domain, that binds a sequence-specific QKI RNA recognition element (QRE), CUAAC. To understand the binding specificities for different mRNA sequences of the KH-QUA2 domain of QKI protein, we introduced point mutations at different positions in the QRE resulting in twelve different mRNA sequences with single nucleotide change. We carried out long unbiased molecular dynamics simulations using two different sets of recently updated forcefield parameters: AMBERff14SB+RNAχOL3 and CHARMM36 (with CMAP correction). We analyzed the changes in intermolecular dynamics as a result of mutation. Our results show that AMBER forcefields performed better to model the interactions between mRNA and protein. We also calculated the binding affinities of different mRNA sequences and found that the relative order correlates to the reported experimental studies. Our study shows that the favorable binding with the formation of stable complex will occur when there is an increase of the total intermolecular contacts between mRNA and protein, but without the loss of native contacts within the KH-QUA domain.

Web 3DNA 2.0 for the analysis, visualization, and modeling of 3D nucleic acid structures

Web 3DNA (w3DNA) 2.0 is a significantly enhanced version of the widely used w3DNA server for the analysis, visualization, and modeling of 3D nucleic-acid-containing structures. Since its initial release in 2009, the w3DNA server has continuously served the community by making commonly-used features of the 3DNA suite of command-line programs readily accessible. However, due to the lack of updates, w3DNA has clearly shown its age in terms of modern web technologies and it has long lagged behind further developments of 3DNA per se. The w3DNA 2.0 server presented here overcomes all known shortcomings of w3DNA while maintaining its battle-tested characteristics. Technically, w3DNA 2.0 implements a simple and intuitive interface (with sensible defaults) for increased usability, and it complies with HTML5 web standards for broad accessibility. Featurewise, w3DNA 2.0 employs the most recent version of 3DNA, enhanced with many new functionalities, including: the automatic handling of modified nucleotides; a set of 'simple' base-pair and step parameters for qualitative characterization of non-Watson-Crick double-helical structures; new structural parameters that integrate the rigid base plane and the backbone phosphate group, the two nucleic acid components most reliably determined with X-ray crystallography; in silico base mutations that preserve the backbone geometry; and a notably improved module for building models of single-stranded RNA, double-helical DNA, Pauling triplex, G-quadruplex, or DNA structures 'decorated' with proteins. The w3DNA 2.0 server is freely available, without registration, at http://web.x3dna.org.

Structural basis for IL-1α recognition by a modified DNA aptamer that specifically inhibits IL-1α signaling

IL-1α is an essential cytokine that contributes to inflammatory responses and is implicated in various forms of pathogenesis and cancer. Here we report a naphthyl modified DNA aptamer that specifically binds IL-1α and inhibits its signaling pathway. By solving the crystal structure of the IL-1α/aptamer, we provide a high-resolution structure of this critical cytokine and we reveal its functional interaction interface with high-affinity ligands. The non-helical aptamer, which represents a highly compact nucleic acid structure, contains a wealth of new conformational features, including an unknown form of G-quadruplex. The IL-1α/aptamer interface is composed of unusual polar and hydrophobic elements, along with an elaborate hydrogen bonding network that is mediated by sodium ion. IL-1α uses the same interface to interact with both the aptamer and its cognate receptor IL-1RI, thereby suggesting a novel route to immunomodulatory therapeutics.

The cytokine interleukin 1α (IL-1α) plays an important role in inflammatory processes. Here the authors use SELEX to generate a modified DNA aptamer which specifically binds IL-1α, present the structure of the IL-1α/aptamer complex and show that this aptamer inhibits the IL-1α signaling pathway.

Mechanism of mRNA-STAR domain interaction: Molecular dynamics simulations of Mammalian Quaking STAR protein

STAR proteins are evolutionary conserved mRNA-binding proteins that post-transcriptionally regulate gene expression at all stages of RNA metabolism. These proteins possess conserved STAR domain that recognizes identical RNA regulatory elements as YUAAY. Recently reported crystal structures show that STAR domain is composed of N-terminal QUA1, K-homology domain (KH) and C-terminal QUA2, and mRNA binding is mediated by KH-QUA2 domain. Here, we present simulation studies done to investigate binding of mRNA to STAR protein, mammalian Quaking protein (QKI). We carried out conventional MD simulations of STAR domain in presence and absence of mRNA, and studied the impact of mRNA on the stability, dynamics and underlying allosteric mechanism of STAR domain. Our unbiased simulations results show that presence of mRNA stabilizes the overall STAR domain by reducing the structural deviations, correlating the ‘within-domain’ motions, and maintaining the native contacts information. Absence of mRNA not only influenced the essential modes of motion of STAR domain, but also affected the connectivity of networks within STAR domain. We further explored the dissociation of mRNA from STAR domain using umbrella sampling simulations, and the results suggest that mRNA binding to STAR domain occurs in multi-step: first conformational selection of mRNA backbone conformations, followed by induced fit mechanism as nucleobases interact with STAR domain.

Identification of possible siRNA molecules for TDP43 mutants causing amyotrophic lateral sclerosis: In silico design and molecular dynamics study

The DNA binding protein, TDP43 is a major protein involved in amyotrophic lateral sclerosis and other neurological disorders such as frontotemporal dementia, Alzheimer disease, etc. In the present study, we have designed possible siRNAs for the glycine rich region of tardbp mutants causing ALS disorder based on a systematic theoretical approach including (i) identification of respective codons for all mutants (reported at the protein level) based on both minimum free energy and probabilistic approaches, (ii) rational design of siRNA, (iii) secondary structure analysis for the target accessibility of siRNA, (iii) determination of the ability of siRNA to interact with mRNA and the formation/stability of duplex via molecular dynamics study for a period of 15ns and (iv) characterization of mRNA-siRNA duplex stability based on thermo-physical analysis. The stable GC-rich siRNA expressed strong binding affinity towards mRNA and forms stable duplex in A-form. The linear dependence between the thermo-physical parameters such as Tm, GC content and binding free energy revealed the ability of the identified siRNAs to interact with mRNA in comparable to that of the experimentally reported siRNAs. Hence, this present study proposes few siRNAs as the possible gene silencing agents in RNAi therapy based on the in silico approach.

Crystal structure of group II intron domain 1 reveals a template for RNA assembly

Although the importance of large noncoding RNAs is increasingly appreciated, our understanding of their structures and architectural dynamics remains limited. In particular, we know little about RNA folding intermediates and how they facilitate the productive assembly of RNA tertiary structures. Here, we report the crystal structure of an obligate intermediate that is required during the earliest stages of group II intron folding. Composed of domain 1 from the Oceanobacillus iheyensis group II intron (266 nucleotides), this intermediate retains native-like features but adopts a compact conformation in which the active site cleft is closed. Transition between this closed and the open (native) conformation is achieved through discrete rotations of hinge motifs in two regions of the molecule. The open state is then stabilized by sequential docking of downstream intron domains, suggesting a 'first come, first folded' strategy that may represent a generalizable pathway for assembly of large RNA and ribonucleoprotein structures.

ESI-MS Investigation of an Equilibrium between a Bimolecular Quadruplex DNA and a Duplex DNA/RNA Hybrid

Electrospray ionization mass spectrometry (ESI-MS) conditions were optimized for simultaneous observation of a bimolecular qDNA and a Watson-Crick base-paired duplex DNA/RNA hybrid. The DNA sequence used was telomeric DNA, and the RNA contained the template for telomerase-mediated telomeric DNA synthesis. Addition of RNA to the quadruplex DNA (qDNA) resulted in formation of the duplex DNA/RNA hybrid. Melting profiles obtained using circular dichroism spectroscopy confirmed that the DNA/RNA hybrid exhibited greater thermal stability than the bimolecular qDNA in solution. Binding of a 13-substituted berberine (1) derivative to the bimolecular qDNA stabilized its structure as evidenced by an increase in its stability in the mass spectrometer, and an increase in its circular dichroism (CD) melting temperature of 10°C. The DNA/RNA hybrid did not bind the ligand extensively and its thermal stability was unchanged in the presence of (1). The qDNA-ligand complex resisted unfolding in the presence of excess RNA, limiting the formation of the DNA/RNA hybrid. Previously, it has been proposed that DNA secondary structures, such as qDNA, may be involved in the telomerase mechanism. DNA/RNA hybrid structures occur at the active site of telomerase. The results presented in the current work show that if telomeric DNA was folded into a qDNA structure, it is possible for a DNA/RNA hybrid to form as is required during template alignment. The discrimination of ligand (1) for binding to the bimolecular qDNA over the DNA/RNA hybrid positions it as a useful compound for probing the role(s), if any, of antiparallel qDNA in the telomerase mechanism.

Structural snapshots of actively translating human ribosomes

Macromolecular machines, such as the ribosome, undergo large-scale conformational changes during their functional cycles. Although their mode of action is often compared to that of mechanical machines, a crucial difference is that, at the molecular dimension, thermodynamic effects dominate functional cycles, with proteins fluctuating stochastically between functional states defined by energetic minima on an energy landscape. Here, we have used cryo-electron microscopy to image ex-vivo-derived human polysomes as a source of actively translating ribosomes. Multiparticle refinement and 3D variability analysis allowed us to visualize a variety of native translation intermediates. Significantly populated states include not only elongation cycle intermediates in pre- and post-translocational states, but also eEF1A-containing decoding and termination/recycling complexes. Focusing on the post-translocational state, we extended this assessment to the single-residue level, uncovering striking details of ribosome-ligand interactions and identifying both static and functionally important dynamic elements.

Visualizing the ai5γ group IIB intron

It has become apparent that much of cellular metabolism is controlled by large well-folded noncoding RNA molecules. In addition to crystallographic approaches, computational methods are needed for visualizing the 3D structure of large RNAs. Here, we modeled the molecular structure of the ai5γ group IIB intron from yeast using the crystal structure of a bacterial group IIC homolog. This was accomplished by adapting strategies for homology and de novo modeling, and creating a new computational tool for RNA refinement. The resulting model was validated experimentally using a combination of structure-guided mutagenesis and RNA structure probing. The model provides major insights into the mechanism and regulation of splicing, such as the position of the branch-site before and after the second step of splicing, and the location of subdomains that control target specificity, underscoring the feasibility of modeling large functional RNA molecules.

Mapping L1 ligase ribozyme conformational switch

L1 ligase (L1L) molecular switch is an in vitro optimized synthetic allosteric ribozyme that catalyzes the regioselective formation of a 5'-to-3' phosphodiester bond, a reaction for which there is no known naturally occurring RNA catalyst. L1L serves as a proof of principle that RNA can catalyze a critical reaction for prebiotic RNA self-replication according to the RNA world hypothesis. L1L crystal structure captures two distinct conformations that differ by a reorientation of one of the stems by around 80Å and are presumed to correspond to the active and inactive state, respectively. It is of great interest to understand the nature of these two states in solution and the pathway for their interconversion. In this study, we use explicit solvent molecular simulation together with a novel enhanced sampling method that utilizes concepts from network theory to map out the conformational transition between active and inactive states of L1L. We find that the overall switching mechanism can be described as a three-state/two-step process. The first step involves a large-amplitude swing that reorients stem C. The second step involves the allosteric activation of the catalytic site through distant contacts with stem C. Using a conformational space network representation of the L1L switch transition, it is shown that the connection between the three states follows different topographical patterns: the stem C swing step passes through a narrow region of the conformational space network, whereas the allosteric activation step covers a much wider region and a more diverse set of pathways through the network.

Discrete RNA libraries from pseudo-torsional space

The discovery that RNA molecules can fold into complex structures and carry out diverse cellular roles has led to interest in developing tools for modeling RNA tertiary structure. While significant progress has been made in establishing that the RNA backbone is rotameric, few libraries of discrete conformations specifically for use in RNA modeling have been validated. Here, we present six libraries of discrete RNA conformations based on a simplified pseudo-torsional notation of the RNA backbone, comparable to phi and psi in the protein backbone. We evaluate the ability of each library to represent single nucleotide backbone conformations, and we show how individual library fragments can be assembled into dinucleotides that are consistent with established RNA backbone descriptors spanning from sugar to sugar. We then use each library to build all-atom models of 20 test folds, and we show how the composition of a fragment library can limit model quality. Despite the limitations inherent in using discretized libraries, we find that several hundred discrete fragments can rebuild RNA folds up to 174 nucleotides in length with atomic-level accuracy (<1.5 Å RMSD). We anticipate that the libraries presented here could easily be incorporated into RNA structural modeling, analysis, or refinement tools.