SimRNAweb v2.0: a web server for RNA folding simulations and 3D structure modeling, with optional restraints and enhanced analysis of folding trajectories.

Research on ribonucleic acid (RNA) structures and functions benefits from easy-to-use tools for computational prediction and analyses of RNA three-dimensional (3D) structure. The SimRNAweb server version 2.0 offers an enhanced, user-friendly platform for RNA 3D structure prediction and analysis of RNA folding trajectories based on the SimRNA method. SimRNA employs a coarse-grained model, Monte Carlo sampling and statistical potentials to explore RNA conformational space, optionally guided by spatial restraints. Recognized for its accuracy in RNA 3D structure prediction in RNA-Puzzles and CASP competitions, SimRNA is particularly useful for incorporating restraints based on experimental data. The new server version introduces performance optimizations and extends user control over simulations and the processing of results. It allows the application of various hard and soft restraints, accommodating alternative structures involving canonical and noncanonical base pairs and unpaired residues, while also integrating data from chemical probing methods. Enhanced features include an improved analysis of folding trajectories, offering advanced clustering options and multiple analyses of the generated trajectories. These updates provide comprehensive tools for detailed RNA structure analysis. SimRNAweb v2.0 significantly broadens the scope of RNA modeling, emphasizing flexibility and user-defined parameter control. The web server is available at https://genesilico.pl/SimRNAweb.

The Legionella kinase LegK7 exploits the Hippo pathway scaffold protein MOB1A for allostery and substrate phosphorylation.

During infection, the bacterial pathogen Legionella pneumophila manipulates a variety of host cell signaling pathways, including the Hippo pathway which controls cell proliferation and differentiation in eukaryotes. Our previous studies revealed that L. pneumophila encodes the effector kinase LegK7 which phosphorylates MOB1A, a highly conserved scaffold protein of the Hippo pathway. Here, we show that MOB1A, in addition to being a substrate of LegK7, also functions as an allosteric activator of its kinase activity. A crystallographic analysis of the LegK7-MOB1A complex revealed that the N-terminal half of LegK7 is structurally similar to eukaryotic protein kinases, and that MOB1A directly binds to the LegK7 kinase domain. Substitution of interface residues critical for complex formation abrogated allosteric activation of LegK7 both in vitro and within cells and diminished MOB1A phosphorylation. Importantly, the N-terminal extension (NTE) of MOB1A not only regulated complex formation with LegK7 but also served as a docking site for downstream substrates such as the transcriptional coregulator YAP1. Deletion of the NTE from MOB1A or addition of NTE peptides as binding competitors attenuated YAP1 recruitment to and phosphorylation by LegK7. By providing mechanistic insight into the formation and regulation of the LegK7-MOB1A complex, our study unravels a sophisticated molecular mimicry strategy that is used by L. pneumophila to take control of the host cell Hippo pathway.

RNA-Puzzles Round IV: 3D structure predictions of four ribozymes and two aptamers.

RNA-Puzzles is a collective endeavor dedicated to the advancement and improvement of RNA 3D structure prediction. With agreement from crystallographers, the RNA structures are predicted by various groups before the publication of the crystal structures. We now report the prediction of 3D structures for six RNA sequences: four nucleolytic ribozymes and two riboswitches. Systematic protocols for comparing models and crystal structures are described and analyzed. In these six puzzles, we discuss (i) the comparison between the automated web servers and human experts; (ii) the prediction of coaxial stacking; (iii) the prediction of structural details and ligand binding; (iv) the development of novel prediction methods; and (v) the potential improvements to be made. We show that correct prediction of coaxial stacking and tertiary contacts is essential for the prediction of RNA architecture, while ligand binding modes can only be predicted with low resolution and simultaneous prediction of RNA structure with accurate ligand binding still remains out of reach. All the predicted models are available for the future development of force field parameters and the improvement of comparison and assessment tools.

RNAProbe: a web server for normalization and analysis of RNA structure probing data.

RNA molecules play key roles in all living cells. Knowledge of the structural characteristics of RNA molecules allows for a better understanding of the mechanisms of their action. RNA chemical probing allows us to study the susceptibility of nucleotides to chemical modification, and the information obtained can be used to guide secondary structure prediction. These experimental results can be analyzed using various computational tools, which, however, requires additional, tedious steps (e.g., further normalization of the reactivities and visualization of the results), for which there are no fully automated methods. Here, we introduce RNAProbe, a web server that facilitates normalization, analysis, and visualization of the low-pass SHAPE, DMS and CMCT probing results with the modification sites detected by capillary electrophoresis. RNAProbe automatically analyzes chemical probing output data and turns tedious manual work into a one-minute assignment. RNAProbe performs normalization based on a well-established protocol, utilizes recognized secondary structure prediction methods, and generates high-quality images with structure representations and reactivity heatmaps. It summarizes the results in the form of a spreadsheet, which can be used for comparative analyses between experiments. Results of predictions with normalized reactivities are also collected in text files, providing interoperability with bioinformatics workflows. RNAProbe is available at https://rnaprobe.genesilico.pl.

RNArchitecture: a database and a classification system of RNA families, with a focus on structural information.

RNArchitecture is a database that provides a comprehensive description of relationships between known families of structured non-coding RNAs, with a focus on structural similarities. The classification is hierarchical and similar to the system used in the SCOP and CATH databases of protein structures. Its central level is Family, which builds on the Rfam catalog and gathers closely related RNAs. Consensus structures of Families are described with a reduced secondary structure representation. Evolutionarily related Families are grouped into Superfamilies. Similar structures are further grouped into Architectures. The highest level, Class, organizes families into very broad structural categories, such as simple or complex structured RNAs. Some groups at different levels of the hierarchy are currently labeled as 'unclassified'. The classification is expected to evolve as new data become available. For each Family with an experimentally determined three-diemsional (3D) structure(s), a representative one is provided. RNArchitecture also presents theoretical models of RNA 3D structure and is open for submission of structural models by users. Compared to other databases, RNArchitecture is unique in its focus on structure-based RNA classification, and in providing a platform for storing RNA 3D structure predictions. RNArchitecture can be accessed at http://iimcb.genesilico.pl/RNArchitecture/.

RNA-Puzzles Round III: 3D RNA structure prediction of five riboswitches and one ribozyme.

RNA-Puzzles is a collective experiment in blind 3D RNA structure prediction. We report here a third round of RNA-Puzzles. Five puzzles, 4, 8, 12, 13, 14, all structures of riboswitch aptamers and puzzle 7, a ribozyme structure, are included in this round of the experiment. The riboswitch structures include biological binding sites for small molecules (S-adenosyl methionine, cyclic diadenosine monophosphate, 5-amino 4-imidazole carboxamide riboside 5'-triphosphate, glutamine) and proteins (YbxF), and one set describes large conformational changes between ligand-free and ligand-bound states. The Varkud satellite ribozyme is the most recently solved structure of a known large ribozyme. All puzzles have established biological functions and require structural understanding to appreciate their molecular mechanisms. Through the use of fast-track experimental data, including multidimensional chemical mapping, and accurate prediction of RNA secondary structure, a large portion of the contacts in 3D have been predicted correctly leading to similar topologies for the top ranking predictions. Template-based and homology-derived predictions could predict structures to particularly high accuracies. However, achieving biological insights from de novo prediction of RNA 3D structures still depends on the size and complexity of the RNA. Blind computational predictions of RNA structures already appear to provide useful structural information in many cases. Similar to the previous RNA-Puzzles Round II experiment, the prediction of non-Watson-Crick interactions and the observed high atomic clash scores reveal a notable need for an algorithm of improvement. All prediction models and assessment results are available at http://ahsoka.u-strasbg.fr/rnapuzzles/.

Molecular basis for the binding and modulation of V-ATPase by a bacterial effector protein.

Intracellular pathogenic bacteria evade the immune response by replicating within host cells. Legionella pneumophila, the causative agent of Legionnaires' Disease, makes use of numerous effector proteins to construct a niche supportive of its replication within phagocytic cells. The L. pneumophila effector SidK was identified in a screen for proteins that reduce the activity of the proton pumping vacuolar-type ATPases (V-ATPases) when expressed in the yeast Saccharomyces cerevisae. SidK is secreted by L. pneumophila in the early stages of infection and by binding to and inhibiting the V-ATPase, SidK reduces phagosomal acidification and promotes survival of the bacterium inside macrophages. We determined crystal structures of the N-terminal region of SidK at 2.3 Å resolution and used single particle electron cryomicroscopy (cryo-EM) to determine structures of V-ATPase:SidK complexes at ~6.8 Å resolution. SidK is a flexible and elongated protein composed of an α-helical region that interacts with subunit A of the V-ATPase and a second region of unknown function that is flexibly-tethered to the first. SidK binds V-ATPase strongly by interacting via two α-helical bundles at its N terminus with subunit A. In vitro activity assays show that SidK does not inhibit the V-ATPase completely, but reduces its activity by ~40%, consistent with the partial V-ATPase deficiency phenotype its expression causes in yeast. The cryo-EM analysis shows that SidK reduces the flexibility of the A-subunit that is in the 'open' conformation. Fluorescence experiments indicate that SidK binding decreases the affinity of V-ATPase for a fluorescent analogue of ATP. Together, these results reveal the structural basis for the fine-tuning of V-ATPase activity by SidK.

SimRNAweb: a web server for RNA 3D structure modeling with optional restraints.

RNA function in many biological processes depends on the formation of three-dimensional (3D) structures. However, RNA structure is difficult to determine experimentally, which has prompted the development of predictive computational methods. Here, we introduce a user-friendly online interface for modeling RNA 3D structures using SimRNA, a method that uses a coarse-grained representation of RNA molecules, utilizes the Monte Carlo method to sample the conformational space, and relies on a statistical potential to describe the interactions in the folding process. SimRNAweb makes SimRNA accessible to users who do not normally use high performance computational facilities or are unfamiliar with using the command line tools. The simplest input consists of an RNA sequence to fold RNA de novo. Alternatively, a user can provide a 3D structure in the PDB format, for instance a preliminary model built with some other technique, to jump-start the modeling close to the expected final outcome. The user can optionally provide secondary structure and distance restraints, and can freeze a part of the starting 3D structure. SimRNAweb can be used to model single RNA sequences and RNA-RNA complexes (up to 52 chains). The webserver is available at http://genesilico.pl/SimRNAweb.

SimRNA: a coarse-grained method for RNA folding simulations and 3D structure prediction.

RNA molecules play fundamental roles in cellular processes. Their function and interactions with other biomolecules are dependent on the ability to form complex three-dimensional (3D) structures. However, experimental determination of RNA 3D structures is laborious and challenging, and therefore, the majority of known RNAs remain structurally uncharacterized. Here, we present SimRNA: a new method for computational RNA 3D structure prediction, which uses a coarse-grained representation, relies on the Monte Carlo method for sampling the conformational space, and employs a statistical potential to approximate the energy and identify conformations that correspond to biologically relevant structures. SimRNA can fold RNA molecules using only sequence information, and, on established test sequences, it recapitulates secondary structure with high accuracy, including correct prediction of pseudoknots. For modeling of complex 3D structures, it can use additional restraints, derived from experimental or computational analyses, including information about secondary structure and/or long-range contacts. SimRNA also can be used to analyze conformational landscapes and identify potential alternative structures.

Structural and Functional Investigations of the Effector Protein LpiR1 from Legionella pneumophila.

Legionella pneumophila is a causative agent of a severe pneumonia, known as Legionnaires' disease. Legionella pathogenicity is mediated by specific virulence factors, called bacterial effectors, which are injected into the invaded host cell by the bacterial type IV secretion system. Bacterial effectors are involved in complex interactions with the components of the host cell immune and signaling pathways, which eventually lead to bacterial survival and replication inside the mammalian cell. Structural and functional studies of bacterial effectors are, therefore, crucial for elucidating the mechanisms of Legionella virulence. Here we describe the crystal structure of the LpiR1 (Lpg0634) effector protein and investigate the effects of its overexpression in mammalian cells. LpiR1 is an α-helical protein that consists of two similar domains aligned in an antiparallel fashion. The hydrophilic cleft between the domains might serve as a binding site for a potential host cell interaction partner. LpiR1 binds the phosphate group at a conserved site and is stabilized by Mn(2+), Ca(2+), or Mg(2+) ions. When overexpressed in mammalian cells, a GFP-LpiR1 fusion protein is localized in the cytoplasm. Intracellular signaling antibody array analysis revealed small changes in the phosphorylation state of several components of the Akt signaling pathway in HEK293T cells overexpressing LpiR1.

RNA-Puzzles Round II: assessment of RNA structure prediction programs applied to three large RNA structures.

This paper is a report of a second round of RNA-Puzzles, a collective and blind experiment in three-dimensional (3D) RNA structure prediction. Three puzzles, Puzzles 5, 6, and 10, represented sequences of three large RNA structures with limited or no homology with previously solved RNA molecules. A lariat-capping ribozyme, as well as riboswitches complexed to adenosylcobalamin and tRNA, were predicted by seven groups using RNAComposer, ModeRNA/SimRNA, Vfold, Rosetta, DMD, MC-Fold, 3dRNA, and AMBER refinement. Some groups derived models using data from state-of-the-art chemical-mapping methods (SHAPE, DMS, CMCT, and mutate-and-map). The comparisons between the predictions and the three subsequently released crystallographic structures, solved at diffraction resolutions of 2.5-3.2 Å, were carried out automatically using various sets of quality indicators. The comparisons clearly demonstrate the state of present-day de novo prediction abilities as well as the limitations of these state-of-the-art methods. All of the best prediction models have similar topologies to the native structures, which suggests that computational methods for RNA structure prediction can already provide useful structural information for biological problems. However, the prediction accuracy for non-Watson-Crick interactions, key to proper folding of RNAs, is low and some predicted models had high Clash Scores. These two difficulties point to some of the continuing bottlenecks in RNA structure prediction. All submitted models are available for download at http://ahsoka.u-strasbg.fr/rnapuzzles/.

Leucyl-tRNA synthetase editing domain functions as a molecular rheostat to control codon ambiguity in Mycoplasma pathogens.

Mycoplasma leucyl-tRNA synthetases (LeuRSs) have been identified in which the connective polypeptide 1 (CP1) amino acid editing domain that clears mischarged tRNAs are missing (Mycoplasma mobile) or highly degenerate (Mycoplasma synoviae). Thus, these enzymes rely on a clearance pathway called pretransfer editing, which hydrolyzes misactivated aminoacyl-adenylate intermediate via a nebulous mechanism that has been controversial for decades. Even as the sole fidelity pathway for clearing amino acid selection errors in the pathogenic M. mobile, pretransfer editing is not robust enough to completely block mischarging of tRNA(Leu), resulting in codon ambiguity and statistical proteins. A high-resolution X-ray crystal structure shows that M. mobile LeuRS structurally overlaps with other LeuRS cores. However, when CP1 domains from different aminoacyl-tRNA synthetases and origins were fused to this common LeuRS core, surprisingly, pretransfer editing was enhanced. It is hypothesized that the CP1 domain evolved as a molecular rheostat to balance multiple functions. These include distal control of specificity and enzyme activity in the ancient canonical core, as well as providing a separate hydrolytic active site for clearing mischarged tRNA.

S6:S18 ribosomal protein complex interacts with a structural motif present in its own mRNA.

Prokaryotic ribosomal protein genes are typically grouped within highly conserved operons. In many cases, one or more of the encoded proteins not only bind to a specific site in the ribosomal RNA, but also to a motif localized within their own mRNA, and thereby regulate expression of the operon. In this study, we computationally predicted an RNA motif present in many bacterial phyla within the 5' untranslated region of operons encoding ribosomal proteins S6 and S18. We demonstrated that the S6:S18 complex binds to this motif, which we hereafter refer to as the S6:S18 complex-binding motif (S6S18CBM). This motif is a conserved CCG sequence presented in a bulge flanked by a stem and a hairpin structure. A similar structure containing a CCG trinucleotide forms the S6:S18 complex binding site in 16S ribosomal RNA. We have constructed a 3D structural model of a S6:S18 complex with S6S18CBM, which suggests that the CCG trinucleotide in a specific structural context may be specifically recognized by the S18 protein. This prediction was supported by site-directed mutagenesis of both RNA and protein components. These results provide a molecular basis for understanding protein-RNA recognition and suggest that the S6S18CBM is involved in an auto-regulatory mechanism.

Solution conformation of adenovirus virus associated RNA-I and its interaction with PKR.

Adenovirus virus-associated RNA (VAI) provides protection against the host antiviral response in part by inhibiting the interferon-induced double stranded RNA-activated protein kinase (PKR). VAI consists of three base-paired regions; the apical stem responsible for the interaction with double-stranded RNA binding motifs (dsRBMs) of PKR, the central stem required for inhibition, and the terminal stem. The solution conformation of VAI and VAI lacking the terminal stem were determined using SAXS that suggested extended conformations that are in agreement with their secondary structures. Solution conformations of VAI lacking the terminal stem in complex with the dsRBMs of PKR indicated that the apical stem interacts with both dsRNA-binding motifs whereas the central stem does not. Hydrodynamic properties calculated from ab initio models were compared to experimentally determined parameters for model validation. Furthermore, SAXS envelopes were used as a constraint for the in silico modeling of tertiary structure for RNA and RNA-protein complex. Finally, full-length PKR was also studied, but concentration-dependent changes in hydrodynamic parameters prevented ab initio shape determination. Taken together, results provide an improved structural framework that further our understanding of the role VAI plays in evading host innate immune responses.

RNA-Puzzles: a CASP-like evaluation of RNA three-dimensional structure prediction.

We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises.

Computational modeling of RNA 3D structures, with the aid of experimental restraints.

In addition to mRNAs whose primary function is transmission of genetic information from DNA to proteins, numerous other classes of RNA molecules exist, which are involved in a variety of functions, such as catalyzing biochemical reactions or performing regulatory roles. In analogy to proteins, the function of RNAs depends on their structure and dynamics, which are largely determined by the ribonucleotide sequence. Experimental determination of high-resolution RNA structures is both laborious and difficult, and therefore, the majority of known RNAs remain structurally uncharacterized. To address this problem, computational structure prediction methods were developed that simulate either the physical process of RNA structure formation ("Greek science" approach) or utilize information derived from known structures of other RNA molecules ("Babylonian science" approach). All computational methods suffer from various limitations that make them generally unreliable for structure prediction of long RNA sequences. However, in many cases, the limitations of computational and experimental methods can be overcome by combining these two complementary approaches with each other. In this work, we review computational approaches for RNA structure prediction, with emphasis on implementations (particular programs) that can utilize restraints derived from experimental analyses. We also list experimental approaches, whose results can be relatively easily used by computational methods. Finally, we describe case studies where computational and experimental analyses were successfully combined to determine RNA structures that would remain out of reach for each of these approaches applied separately.

Rational engineering of sequence specificity in R.MwoI restriction endonuclease.

R.MwoI is a Type II restriction endonucleases enzyme (REase), which specifically recognizes a palindromic interrupted DNA sequence 5'-GCNNNNNNNGC-3' (where N indicates any nucleotide), and hydrolyzes the phosphodiester bond in the DNA between the 7th and 8th base in both strands. R.MwoI exhibits remote sequence similarity to R.BglI, a REase with known structure, which recognizes an interrupted palindromic target 5'-GCCNNNNNGGC-3'. A homology model of R.MwoI in complex with DNA was constructed and used to predict functionally important amino acid residues that were subsequently targeted by mutagenesis. The model, together with the supporting experimental data, revealed regions important for recognition of the common bases in DNA sequences recognized by R.BglI and R.MwoI. Based on the bioinformatics analysis, we designed substitutions of the S310 residue in R.MwoI to arginine or glutamic acid, which led to enzyme variants with altered sequence selectivity compared with the wild-type enzyme. The S310R variant of R.MwoI preferred the 5'-GCCNNNNNGGC-3' sequence as a target, similarly to R.BglI, whereas the S310E variant preferentially cleaved a subset of the MwoI sites, depending on the identity of the 3rd and 9th nucleotide residues. Our results represent a case study of a REase sequence specificity alteration by a single amino acid substitution, based on a theoretical model in the absence of a crystal structure.

Naturally occurring aminoacyl-tRNA synthetases editing-domain mutations that cause mistranslation in Mycoplasma parasites.

Mycoplasma parasites escape host immune responses via mechanisms that depend on remarkable phenotypic plasticity. Identification of these mechanisms is of great current interest. The aminoacyl-tRNA synthetases (AARSs) attach amino acids to their cognate tRNAs, but occasionally make errors that substitute closely similar amino acids. AARS editing pathways clear errors to avoid mistranslation during protein synthesis. We show here that AARSs in Mycoplasma parasites have point mutations and deletions in their respective editing domains. The deleterious effect on editing was confirmed with a specific example studied in vitro. In vivo mistranslation was determined by mass spectrometric analysis of proteins produced in the parasite. These mistranslations are uniform cases where the predicted closely similar amino acid replaced the correct one. Thus, natural AARS editing-domain mutations in Mycoplasma parasites cause mistranslation. We raise the possibility that these mutations evolved as a mechanism for antigen diversity to escape host defense systems.

Helicobacter pylori FlgN binds its substrate FlgK and the flagellum ATPase FliI in a similar manner observed for the FliT chaperone.

In bacterial flagellum biogenesis, secretion of the hook-filament junction proteins FlgK and FlgL and completion of the flagellum requires the FlgN chaperone. Similarly, the related FliT chaperone is necessary for the secretion of the filament cap protein FliD and binds the flagellar export gate protein FlhA and the flagellum ATPase FliI. FlgN and FliT require FliJ for effective substrate secretion. In Helicobacter pylori, neither FlgN, FliT, nor FliJ have been annotated. We demonstrate that the genome location of HP1120 is identical to that of flgN in other flagellated bacteria and that HP1120 is the homolog of Campylobacter jejuni FlgN. A modeled HP1120 structure contains three α-helices and resembles the FliT chaperone, sharing a similar substrate-binding pocket. Using pulldowns and thermophoresis, we show that both HP1120 and a HP1120Δ126-144 deletion mutant bind to FlgK with nanomolar affinity, but not to the filament cap protein FliD, confirming that HP1120 is FlgN. Based on size-exclusion chromatography and multi-angle light scattering, H. pylori FlgN binds to FlgK with 1:1 stoichiometry. Overall structural similarities between FlgN and FliT suggest that substrate recognition on FlgN primarily involves an antiparallel coiled-coil interface between the third helix of FlgN and the C-terminal helix of the substrate. A FlgNΔ126-144 N100A, Y103A, S111I triple mutant targeting this interface significantly impairs the binding of FlgK. Finally, we demonstrate that FlgNΔ126-144 , like FliT, binds with sub-micromolar affinity to the flagellum ATPase FliI or its N-terminal domain. Hence FlgN and FliT likely couple delivery of low-abundance export substrates to the flagellum ATPase FliI.

MEMO1 binds iron and modulates iron homeostasis in cancer cells.

Mediator of ERBB2-driven cell motility 1 (MEMO1) is an evolutionary conserved protein implicated in many biological processes; however, its primary molecular function remains unknown. Importantly, MEMO1 is overexpressed in many types of cancer and was shown to modulate breast cancer metastasis through altered cell motility. To better understand the function of MEMO1 in cancer cells, we analyzed genetic interactions of MEMO1 using gene essentiality data from 1028 cancer cell lines and found multiple iron-related genes exhibiting genetic relationships with MEMO1. We experimentally confirmed several interactions between MEMO1 and iron-related proteins in living cells, most notably, transferrin receptor 2 (TFR2), mitoferrin-2 (SLC25A28), and the global iron response regulator IRP1 (ACO1). These interactions indicate that cells with high-MEMO1 expression levels are hypersensitive to the disruptions in iron distribution. Our data also indicate that MEMO1 is involved in ferroptosis and is linked to iron supply to mitochondria. We have found that purified MEMO1 binds iron with high affinity under redox conditions mimicking intracellular environment and solved MEMO1 structures in complex with iron and copper. Our work reveals that the iron coordination mode in MEMO1 is very similar to that of iron-containing extradiol dioxygenases, which also display a similar structural fold. We conclude that MEMO1 is an iron-binding protein that modulates iron homeostasis in cancer cells.