Summary: Automatic methods for macromolecular structure prediction (fold recognition, de novo folding and docking programs) produce large sets of alternative models. These large model sets often include many native-like structures, which are often scored as false positives. Such native-like models can be more easily identified based on data from experimental analyses used as structural restraints (e.g. identification of nearby residues by cross-linking, chemical modification, site-directed mutagenesis, deuterium exchange coupled with mass spectrometry, etc.). We present a simple server for scoring and ranking of models according to their agreement with user-defined restraints.
Availability: FILTREST3D is freely available for users as a web server and standalone software at: http://filtrest3d.genesilico.pl/
Supplementary information: Supplementary data are available at Bioinformatics online.
Rigorous assessments of protein structure prediction have demonstrated that fold recognition methods can identify remote similarities between proteins when standard sequence search methods fail. It has been shown that the accuracy of predictions is improved when refined multiple sequence alignments are used instead of single sequences and if different methods are combined to generate a consensus model. There are several meta-servers available that integrate protein structure predictions performed by various methods, but they do not allow for submission of user-defined multiple sequence alignments and they seldom offer confidentiality of the results. We developed a novel WWW gateway for protein structure prediction, which combines the useful features of other meta-servers available, but with much greater flexibility of the input. The user may submit an amino acid sequence or a multiple sequence alignment to a set of methods for primary, secondary and tertiary structure prediction. Fold-recognition results (target-template alignments) are converted into full-atom 3D models and the quality of these models is uniformly assessed. A consensus between different FR methods is also inferred. The results are conveniently presented on-line on a single web page over a secure, password-protected connection. The GeneSilico protein structure prediction meta-server is freely available for academic users at http://genesilico.pl/meta.
Predatory sea snails from the Conus family produce a variety of venomous small helical peptides called conantokins that are rich in γ-carboxyglutamic acid (Gla) residues. As potent and selective antagonists of the N-methyl-d-aspartate receptor, these peptides are potential therapeutic agents for a variety of neurological conditions. The two most studied members of this family of peptides are con-G and con-T. Con-G has Gla residues at sequence positions 3, 4, 7, 10, and 14, and requires divalent cation binding to adopt a helical conformation. Although both Ca2+ and Mg2+ can fulfill this role, Ca2+ induces dimerization of con-G, whereas the Mg2+-complexed peptide remains monomeric. A variant of con-T, con-T[K7γ] (γ is Gla), contains Gla residues at the same five positions as in con-G and behaves very similarly with respect to metal ion binding and dimerization; each peptide binds two Ca2+ ions and two Mg2+ ions per helix. To understand the difference in metal ion selectivity, affinity, and the dependence on Ca2+ for dimer formation, we report here the structure of the monomeric Cd2+/Mg2+–con-T[K7γ] complex, and, by comparison with the previously published con-T[K7γ]/Ca2+ dimer structure, we suggest explanations for both metal ion binding site specificity and metalion-dependent dimerization.
Crystallography; Conantokins; γ-Carboxyglutamic acid; Peptide α-helix
Metal ions are essential cofactors for various ribozymes. Here we dissect the roles of metal ions in an aminoacyl-tRNA synthetase-like ribozyme (ARS ribozyme), which was evolved in vitro. This ribozyme can charge phenylalanine on tRNA in cis, where it is covalently attached to the 5′-end of tRNA (i.e. a form of precursor tRNA), as well as in trans, where it can act as a catalyst. The presence of magnesium ion is essential for this ribozyme to exhibit full catalytic activity. Metal-dependent kinetics, as well as structural mappings using Tb3+ in competition with Mg2+ or Co(NH3)63+, identified two potential metal-binding sites which are embedded near the tRNA-binding site. The high affinity metal-binding site can be filled with either Mg2+ or Co(NH3)63+ and thus the activity relies on a metal ion that is fully coordinated with water or ammonium ions. This site also overlaps with the amino acid-binding site, suggesting that the metal ion plays a role in constituting the catalytic core. The weak metal-binding site is occupied only by a metal ion(s) that can form innersphere contacts with ligands in the ribozyme and, hence, Mg2+ can enhance ribozyme activity, but Co(NH3)63+ cannot. The experiments described in this work establish the roles of metal ions that have distinct coordination properties in the ARS ribozyme.
Summary: Co-crystallization experiments of proteins with nucleic acids do not guarantee that both components are present in the crystal. We have previously developed DIBER to predict crystal content when protein and DNA are present in the crystallization mix. Here, we present RIBER, which should be used when protein and RNA are in the crystallization drop. The combined RIBER/DIBER suite builds on machine learning techniques to make reliable, quantitative predictions of crystal content for non-expert users and high-throughput crystallography.
Availability: The program source code, Linux binaries and a web server are available at http://diber.iimcb.gov.pl/ RIBER/DIBER requires diffraction data to at least 3.0 Å resolution in MTZ or CIF (web server only) format. The RIBER/DIBER code is subject to the GNU Public License.
Supplementary data are available at Bioinformatics online.
Motivation: Specific non-covalent binding of metal ions and ligands, such as nucleotides and cofactors, is essential for the function of many proteins. Computational methods are useful for predicting the location of such binding sites when experimental information is lacking. Methods that use structural information, when available, are particularly promising since they can potentially identify non-contiguous binding motifs that cannot be found using only the amino acid sequence. Furthermore, a prediction method that can utilize low-resolution models is advantageous because high-resolution structures are available for only a relatively small fraction of proteins.
Results: SitePredict is a machine learning-based method for predicting binding sites in protein structures for specific metal ions or small molecules. The method uses Random Forest classifiers trained on diverse residue-based site properties including spatial clustering of residue types and evolutionary conservation. SitePredict was tested by cross-validation on a set of known binding sites for six different metal ions and five different small molecules in a non-redundant set of protein–ligand complex structures. The prediction performance was good for all ligands considered, as reflected by AUC values of at least 0.8. Furthermore, a more realistic test on unbound structures showed only a slight decrease in the accuracy. The properties that contribute the most to the prediction accuracy of each ligand were also examined. Finally, examples of predicted binding sites in homology models and uncharacterized proteins are discussed.
Availability: Binding site prediction results for all PDB protein structures and human protein homology models are available at http://sitepredict.org/.
Supplementary information: Supplementary data are available at Bioinformatics online.
We have captured a pre-insertion ternary complex of RB69 DNA polymerase (RB69pol) containing the 3’ hydroxyl group at the terminus of an extendable primer (ptO3’) and a non-hydrolyzable 2’-deoxyuridine 5’-α,β-substituted trisphosphate, dUpXpp, where X is either NH or CH2, opposite a complementary templating dA nucleotide residue. Here we report four structures of these complexes formed by three different RB69pol variants with catalytically inert Ca2+ and other four structures with catalytically competent Mn2+ or Mg2+. These structures provide new insights into why the complete divalent metal-ion coordination complexes at the A and B sites are required for nucleotidyl transfer. They show that the metal ion in the A site brings ptO3’ close to the α-phosphorus atom (Pα) of the incoming dNTP to enable phosphodiester bond formation through simultaneous coordination of both ptO3’ and the non-bridging Sp oxygen of the dNTP’s α-phosphate. The coordination bond length of metal-ion A as well as its ionic radius determines how close ptO3’ can approach Pα. These variables are expected to affect the rate of bond formation. The metal ion in the B site brings the pyrophosphate product close enough to Pα enabling pyrophosphorolysis as well as assisting in the departure of the pyrophosphate. In these dUpXpp-containing complexes, ptO3’ occupies the vertex of a distorted metalion A coordination octahedron. When ptO3’ is placed into the vertex of a non-distorted, idealized metalion A octahedron, it is within bond formation distance to Pα. This geometric relationship appears to be conserved among DNA polymerases of known structure.
The M-box riboswitch couples intracellular magnesium levels to expression of bacterial metal transport genes. Structural analyses of other riboswitch RNA classes, which typically respond to a small organic metabolite, have revealed that ligand recognition occurs through a combination of base stacking, electrostatic, and hydrogen bonding interactions. In contrast, the M-box RNA triggers a change in gene expression upon association with an undefined population of metals, rather than responding to only a single ligand. Prior biophysical experimentation suggested that divalent ions associate with the M-box RNA to promote a compacted tertiary conformation, resulting in sequestration of a short sequence tract otherwise required for downstream gene expression. Electrostatic shielding from loosely associated metals is undoubtedly an important influence during this metal-mediated compaction pathway. However, it is also likely that a subset of divalent ions specifically occupies cation-binding sites and promotes proper positioning of functional groups for tertiary structure stabilization. To better elucidate the role of these metal-binding sites a manganese-chelated M-box RNA complex was resolved to 1.86 angstroms by X-ray crystallography. These data support the presence of at least 8 well-ordered cation binding pockets, including several sites that had been predicted by biochemical studies but were not observed in prior structural analysis. Overall, these data support the presence of three metal binding cores within the M-box RNA that facilitate a network of long range interactions within the metal-bound, compacted conformation.
riboswitch; magnesium-RNA interaction; RNA folding; RNA structure; manganese; X-ray crystallography
The RNA Bricks database (http://iimcb.genesilico.pl/rnabricks), stores information about recurrent RNA 3D motifs and their interactions, found in experimentally determined RNA structures and in RNA–protein complexes. In contrast to other similar tools (RNA 3D Motif Atlas, RNA Frabase, Rloom) RNA motifs, i.e. ‘RNA bricks’ are presented in the molecular environment, in which they were determined, including RNA, protein, metal ions, water molecules and ligands. All nucleotide residues in RNA bricks are annotated with structural quality scores that describe real-space correlation coefficients with the electron density data (if available), backbone geometry and possible steric conflicts, which can be used to identify poorly modeled residues. The database is also equipped with an algorithm for 3D motif search and comparison. The algorithm compares spatial positions of backbone atoms of the user-provided query structure and of stored RNA motifs, without relying on sequence or secondary structure information. This enables the identification of local structural similarities among evolutionarily related and unrelated RNA molecules. Besides, the search utility enables searching ‘RNA bricks’ according to sequence similarity, and makes it possible to identify motifs with modified ribonucleotide residues at specific positions.
The rapid accumulation of gene sequences, many of which are hypothetical proteins with unknown function, has stimulated the development of accurate computational tools for protein function prediction with evolution/structure-based approaches showing considerable promise. In this paper, we present FINDSITE-metal, a new threading-based method designed specifically to detect metal binding sites in modeled protein structures. Comprehensive benchmarks using different quality protein structures show that weakly homologous protein models provide sufficient structural information for quite accurate annotation by FINDSITE-metal. Combining structure/evolutionary information with machine learning results in highly accurate metal binding annotations; for protein models constructed by TASSER, whose average Cα RMSD from the native structure is 8.9 Å, 59.5% (71.9%) of the best of top five predicted metal locations are within 4 Å (8 Å) from a bound metal in the crystal structure. For most of the targets, multiple metal binding sites are detected with the best predicted binding site at rank 1 and within the top 2 ranks in 65.6% and 83.1% of the cases, respectively. Furthermore, for iron, copper, zinc, calcium and magnesium ions, the binding metal can be predicted with high, typically 70-90%, accuracy. FINDSITE-metal also provides a set of confidence indexes that help assess the reliability of predictions. Finally, we describe the proteome-wide application of FINDSITE-metal that quantifies the metal binding complement of the human proteome. FINDSITE-metal is freely available to the academic community at http://cssb.biology.gatech.edu/findsite-metal/.
metalloproteins; metal binding residue prediction; protein threading; protein structure prediction; human proteome; machine learning
The hepatitis delta virus (HDV) ribozyme uses both metal ion and nucleobase catalysis in its cleavage mechanism. A reverse G•U wobble was observed in a recent crystal structure of the precleaved state. This unusual base pair positions a Mg2+ ion to participate in catalysis. Herein, we used molecular dynamics (MD) and X-ray crystallography to characterize the conformation and metal binding characteristics of this base pair in product and precleaved forms. Beginning with a crystal structure of the product form, we observed formation of the reverse G•U wobble during MD trajectories. We also demonstrated that this base pair is compatible with the diffraction data for the product-bound state. During MD trajectories of the product form, Na+ ions interacted with the reverse G•U wobble in the RNA active site, and a Mg2+ ion, introduced in certain trajectories, remained bound at this site. Beginning with a crystal structure of the precleaved form, the reverse G•U wobble with bound Mg2+ remained intact during MD simulations. When we removed Mg2+ from the starting precleaved structure, Na+ ions interacted with the reverse G•U wobble. In support of the computational results, we observed competition between Na+ and Mg2+ in the precleaved ribozyme crystallographically. Non-linear Poisson-Boltzmann calculations revealed a negatively charged patch near the reverse G•U wobble. This anionic pocket likely serves to bind metal ions and to help shift the pKa of the catalytic nucleobase, C75. Thus, the reverse G•U wobble motif serves to organize two catalytic elements, a metal ion and catalytic nucleobase, within the active site of the HDV ribozyme.
The structure of a protein determines its function and its interactions with other factors. Regions of proteins that interact with ligands, substrates, and/or other proteins, tend to be conserved both in sequence and structure, and the residues involved are usually in close spatial proximity. More than 70,000 protein structures are currently found in the Protein Data Bank, and approximately one-third contain metal ions essential for function. Identifying and characterizing metal ion–binding sites experimentally is time-consuming and costly. Many computational methods have been developed to identify metal ion–binding sites, and most use only sequence information. For the work reported herein, we developed a method that uses sequence and structural information to predict the residues in metal ion–binding sites. Six types of metal ion–binding templates– those involving Ca2+, Cu2+, Fe3+, Mg2+, Mn2+, and Zn2+–were constructed using the residues within 3.5 Å of the center of the metal ion. Using the fragment transformation method, we then compared known metal ion–binding sites with the templates to assess the accuracy of our method. Our method achieved an overall 94.6 % accuracy with a true positive rate of 60.5 % at a 5 % false positive rate and therefore constitutes a significant improvement in metal-binding site prediction.
The structures of biological macromolecules provide a framework for studying their biological functions. Three-dimensional structures of proteins, nucleic acids, or their complexes, are difficult to visualize in detail on flat surfaces, and algorithms for their spatial superposition and comparison are computationally costly. Molecular structures, however, can be represented as 2D maps of interactions between the individual residues, which are easier to visualize and compare, and which can be reconverted to 3D structures with reasonable precision. There are many visualization tools for maps of protein structures, but few for nucleic acids.
We developed RNAmap2D, a platform-independent software tool for calculation, visualization and analysis of contact and distance maps for nucleic acid molecules and their complexes with proteins or ligands. The program addresses the problem of paucity of bioinformatics tools dedicated to analyzing RNA 2D maps, given the growing number of experimentally solved RNA structures in the Protein Data Bank (PDB) repository, as well as the growing number of tools for RNA 2D and 3D structure prediction. RNAmap2D allows for calculation and analysis of contacts and distances between various classes of atoms in nucleic acid, protein, and small ligand molecules. It also discriminates between different types of base pairing and stacking.
RNAmap2D is an easy to use method to visualize, analyze and compare structures of nucleic acid molecules and their complexes with other molecules, such as proteins or ligands and metal ions. Its special features make it a very useful tool for analysis of tertiary structures of RNAs. RNAmap2D for Windows/Linux/MacOSX is freely available for academic users at http://iimcb.genesilico.pl/rnamap2d.html
Contact maps; Distance maps; RNA secondary structure; RNA base pairing; RNA stacking; Protein-RNA complex; Docking
Metal ions are essential for the folding of RNA into stable tertiary structures and for the catalytic activity of some RNA enzymes. To aid in the study of the roles of metal ions in RNA structural biology, we have created MeRNA (Metals in RNA), a comprehensive compilation of all metal binding sites identified in RNA 3D structures available from the PDB and Nucleic Acid Database. Currently, our database contains information relating to binding of 9764 metal ions corresponding to 23 distinct elements, in 256 RNA structures. The metal ion locations were confirmed and ligands characterized using original literature references. MeRNA includes eight manually identified metal-ion binding motifs, which are described in the literature. MeRNA is searchable by PDB identifier, metal ion, method of structure determination, resolution and R-values for X-ray structure and distance from metal to any RNA atom or to water. New structures with their respective binding motifs will be added to the database as they become available. The MeRNA database will further our understanding of the roles of metal ions in RNA folding and catalysis and have applications in structural and functional analysis, RNA design and engineering. The MeRNA database is accessible at .
Motivation: Ions are essential component of the cell and frequently are found bound to various macromolecules, in particular to proteins. A binding of an ion to a protein greatly affects protein’s biophysical characteristics and needs to be taken into account in any modeling approach. However, ion’s bounded positions cannot be easily revealed experimentally, especially if they are loosely bound to macromolecular surface.
Results: Here, we report a web server, the BION web server, which addresses the demand for tools of predicting surface bound ions, for which specific interactions are not crucial; thus, they are difficult to predict. The BION is easy to use web server that requires only coordinate file to be inputted, and the user is provided with various, but easy to navigate, options. The coordinate file with predicted bound ions is displayed on the output and is available for download.
Supplementary data are available at Bioinformatics online.
Metal ion binding domains are found in proteins that mediate transport, buffering or detoxification of metal ions. The objective of the study is to
design and analyze metal binding motifs against the genes involved in phytoremediation. This is being done on the basis of certain pre-requisite
amino-acid residues known to bind metal ions/metal complexes in medicinal and aromatic plants (MAP's). Earlier work on MAP's have shown
that heavy metals accumulated by aromatic and medicinal plants do not appear in the essential oil and that some of these species are able to grow
in metal contaminated sites. A pattern search against the UniProtKB/Swiss-Prot and UniProtKB/TrEMBL databases yielded true positives in
each case showing the high specificity of the motifs designed for the ions of nickel, lead, molybdenum, manganese, cadmium, zinc, iron, cobalt
and xenobiotic compounds. Motifs were also studied against PDB structures. Results of the study suggested the presence of binding sites on the
surface of protein molecules involved. PDB structures of proteins were finally predicted for the binding sites functionality in their respective
phytoremediation usage. This was further validated through CASTp server to study its physico-chemical properties. Bioinformatics implications
would help in designing strategy for developing transgenic plants with increased metal binding capacity. These metal binding factors can be used
to restrict metal update by plants. This helps in reducing the possibility of metal movement into the food chain.
Phytoremediation; medicinal and aromatic plants (MAPs); putative metal binding sites
The upstream site of cleavage of all group I self-splicing introns is identified by an absolutely conserved U.G base pair. Although a wobble C.A pair can substitute the U.G pair, all other combinations of nucleotides at this position abolish splicing, suggesting that it is an unusual RNA structure, rather than sequence, that is recognized by the catalytic intron core. RNA enzymes are metalloenzymes, and divalent metal ion binding may be an important requirement for splice site recognition and catalysis. The paramagnetic broadening of NMR resonances upon manganese binding at specific sites was used to probe the interaction between divalent metal ions and an oligonucleotide model of a group I intron ribozyme substrate. Unlike previous studies in which only imino proton resonances were monitored, we have used isotopically labelled RNA and a set of complete spectral assignments to identify the location of the divalent metal binding site with much greater detail than previously possible. Two independent metal binding sites were identified for this oligonucleotide. A first metal binding site is located in the major groove of the three consecutive G.C base pairs at the end of double helical stem. A second site is found in the major groove of the RNA double helix in the vicinity of the U.G base pair. These results suggest that metal ion coordination (or a metal bridge) and tertiary interactions identified biochemically, may be used by group I intron ribozymes for substrate recognition.
Molecular dynamics simulations have been performed to investigate the role of Mg2+ in the full-length hammerhead ribozyme cleavage reaction. In particular, the aim of this work is to characterize the binding mode and conformational events that give rise to catalytically active conformations and stabilization of the transition state. Toward this end, a series of eight 12 ns molecular dynamics simulations have been performed with different divalent metal binding occupations for the reactant, early and late transition state using recently developed force field parameters for metal ions and reactive intermediates in RNA catalysis. In addition, hybrid QM/MM calculations of the early and late transition state were performed to study the proton-transfer step in general acid catalysis that is facilitated by the catalytic Mg2+ ion. The simulations suggest that Mg2+ is profoundly involved in the hammerhead ribozyme mechanism both at structural and catalytic levels. Binding of Mg2+ in the active site plays a key structural role in the stabilization of stem I and II and to facilitate formation of near attack conformations and interactions between the nucleophile and G12, the implicated general base catalyst. In the transition state, Mg2+ binds in a bridging position where it stabilizes the accumulated charge of the leaving group while interacting with the 2′OH of G8, the implicated general acid catalyst. The QM/MM simulations provide support that, in the late transition state, the 2′OH of G8 can transfer a proton to the leaving group while directly coordinating the bridging Mg2+ ion. The present study provides evidence for the role of Mg2+ in hammerhead ribozyme catalysis. The proposed simulation model reconciles the interpretation of available experimental structural and biochemical data, and provides a starting point for more detailed investigation of the chemical reaction path with combined QM/MM methods.
COLORADO3D is a World Wide Web server for the visual presentation of three-dimensional (3D) protein structures. COLORADO3D indicates the presence of potential errors (detected by ANOLEA, PROSAII, PROVE or VERIFY3D), identifies buried residues and depicts sequence conservations. As input, the server takes a file of Protein Data Bank (PDB) coordinates and, optionally, a multiple sequence alignment. As output, the server returns a PDB-formatted file, replacing the B-factor column with values of the chosen parameter (structure quality, residue burial or conservation). Thus, the coordinates of the analyzed protein ‘colored’ by COLORADO3D can be conveniently displayed with structure viewers such as RASMOL in order to visualize the 3D clusters of regions with common features, which may not necessarily be adjacent to each other at the amino acid sequence level. In particular, COLORADO3D may serve as a tool to judge a structure's quality at various stages of the modeling and refinement (during both experimental structure determination and homology modeling). The GeneSilico group used COLORADO3D in the fifth Critical Assessment of Techniques for Protein Structure Prediction (CASP5) to successfully identify well-folded parts of preliminary homology models and to guide the refinement of misthreaded protein sequences. COLORADO3D is freely available for academic use at http://asia.genesilico.pl/colorado3d/.
The Chlorella virus RNA triphosphatase (cvRTPase) is involved in the formation of the RNA cap structure found at the 5′-end of the viral mRNAs and requires magnesium ions to mediate its catalytic activity. To extend our studies on the role of metal ions in phosphohydrolysis, we have used a combination of fluorescence spectroscopy, circular dichroism, denaturation studies and thermodynamic analyses to monitor the binding of magnesium ions to the cvRTPase. Using these techniques, the thermodynamic forces responsible for the interaction of metal ions with an RNA triphosphatase were also evaluated for the first time. Our thermodynamic analyses indicate that the initial association of magnesium with the cvRTPase is dominated by a favorable entropic effect and is accompanied by the release of eight water molecules from the enzyme. Moreover, both fluorescence spectroscopy and circular dichroism assays indicated that minor conformational changes were occurring upon magnesium binding. Mutational studies were also performed and confirmed the importance of three specific glutamate residues located in the active site of the enzyme for the binding of magnesium ions. Finally, in contrast to the yeast RNA triphosphatase, we demonstrate that the binding of magnesium ions to the cvRTPase does not lead to the stabilization of the ground state binding of the RNA substrate. Based on the results of the present study, we hypothesize that the binding of magnesium ions induces local conformational perturbations in the active site residues that ultimately positions the lateral chains of critical amino acids involved in catalysis. Our results highlight fundamental differences in the role of magnesium ions in the phosphohydrolase reactions catalyzed by the cvRTPase and the closely related yeast RNA triphosphatase.
Ribozymes are small catalytic RNAs that possess the dual functions of sequence-specific RNA recognition and site-specific cleavage. Trans-cleaving ribozymes can inhibit translation of genes at the messenger RNA (mRNA) level in both eukaryotic and prokaryotic systems and are thus useful tools for studies of gene function. However, identification of target sites for efficient cleavage poses a challenge. Here, we have considered a number of structural and thermodynamic parameters that can affect the efficiency of target cleavage, in an attempt to identify rules for the selection of functional ribozymes.
We employed the Sfold program for RNA secondary structure prediction, to account for the likely population of target structures that co-exist in dynamic equilibrium for a specific mRNA molecule. We designed and prepared 15 hammerhead ribozymes to target GUC cleavage sites in the mRNA of the breast cancer resistance protein (BCRP). These ribozymes were tested, and their catalytic activities were measured in vitro. We found that target disruption energy owing to the alteration of the local target structure necessary for ribozyme binding, and the total energy change of the ribozyme-target hybridization, are two significant parameters for prediction of ribozyme activity. Importantly, target disruption energy is the major contributor to the predictability of ribozyme activity by the total energy change. Furthermore, for a target-site specific ribozyme, incorrect folding of the catalytic core, or interactions involving the two binding arms and the end sequences of the catalytic core, can have detrimental effects on ribozyme activity.
The findings from this study suggest rules for structure-based rational design of trans-cleaving hammerhead ribozymes in gene knockdown studies. Tools implementing these rules are available from the Sribo module and the Srna module of the Sfold program available through Web server at .
cations represent key elements of RNA structure and function.
In the Neurospora VS ribozyme, metal cations play
diverse roles; they are important for substrate recognition, formation
of the active site, and shifting the pKa’s of two key nucleobases that contribute to the general acid–base
mechanism. Recently, we determined the NMR structure of the A730 loop
of the VS ribozyme active site (SLVI) that contributes the general
acid (A756) in the enzymatic mechanism of the cleavage
reaction. Our studies showed that magnesium (Mg2+) ions
are essential to stabilize the formation of the S-turn motif within
the A730 loop that exposes the A756 nucleobase for catalysis.
In this article, we extend these NMR investigations by precisely mapping
the Mg2+-ion binding sites using manganese-induced paramagnetic
relaxation enhancement and cadmium-induced chemical-shift perturbation
of phosphorothioate RNAs. These experiments identify five Mg2+-ion binding sites within SLVI. Four Mg2+ ions in SLVI
are associated with known RNA structural motifs, including the G–U
wobble pair and the GNRA tetraloop, and our studies reveal novel insights
about Mg2+ ion binding to these RNA motifs. Interestingly,
one Mg2+ ion is specifically associated with the S-turn
motif, confirming its structural role in the folding of the A730 loop.
This Mg2+ ion is likely important for formation of the
active site and may play an indirect role in catalysis.
Metal ion and nucleobase catalysis are important for ribozyme mechanism, but the extent to which they cooperate is unclear. A crystal structure of the hepatitis delta virus (HDV) ribozyme suggested that the pro-RP oxygen at the scissile phosphate directly coordinates a catalytic Mg2+ ion and is within hydrogen bonding distance of the amine of the general acid C75. Prior studies on the genomic HDV ribozyme, however, showed neither a thio effect nor metal ion rescue using Mn2+. Here, we combine experiment and theory to explore phosphorothioate substitutions at the scissile phosphate. We report significant thio effects at the scissile phosphate and metal ion rescue with Cd2+. Reaction profiles with an SP-phosphorothioate substitution are indistinguishable from those of the unmodified substrate in the presence of Mg2+ or Cd2+, supporting that the pro-SP oxygen does not coordinate metal ions. The RP-phosphorothioate substitution, however, exhibits biphasic kinetics, with the fast-reacting phase displaying a thio effect of up to 5-fold effect and the slow-reacting phase displaying a thio effect of ~1,000-fold. Moreover, the fast- and slow-reacting phases give metal ion rescues in Cd2+ of up to 10- and 330-fold, respectively. The metal ion rescues are unconventional in that they arise from Cd2+ inhibiting the oxo substrate but not the RP substrate. This metal ion rescue suggests a direct interaction of the catalytic metal ion with the pro-RP oxygen, in line with experiments on the antigenomic HDV ribozyme. Experiments without divalent ions, with mutants that interfere with Mg2+ binding, or with C75 deleted suggest that the pro-RP oxygen plays at most a redundant role in positioning C75. Quantum mechanical/molecular mechanical (QM/MM) studies indicate that the metal ion contributes to catalysis by interacting with both the pro-RP oxygen and the nucleophilic 2’- hydroxyl, supporting the experimental findings.
Intrinsically unstructured proteins (IUPs) lack a well-defined three-dimensional structure. Some of them may assume a locally stable structure under specific conditions, e.g. upon interaction with another molecule, while others function in a permanently unstructured state. The discovery of IUPs challenged the traditional protein structure paradigm, which stated that a specific well-defined structure defines the function of the protein. As of December 2011, approximately 60 methods for computational prediction of protein disorder from sequence have been made publicly available. They are based on different approaches, such as utilizing evolutionary information, energy functions, and various statistical and machine learning methods.
Given the diversity of existing intrinsic disorder prediction methods, we decided to test whether it is possible to combine them into a more accurate meta-prediction method. We developed a method based on arbitrarily chosen 13 disorder predictors, in which the final consensus was weighted by the accuracy of the methods. We have also developed a disorder predictor GSmetaDisorder3D that used no third-party disorder predictors, but alignments to known protein structures, reported by the protein fold-recognition methods, to infer the potentially structured and unstructured regions. Following the success of our disorder predictors in the CASP8 benchmark, we combined them into a meta-meta predictor called GSmetaDisorderMD, which was the top scoring method in the subsequent CASP9 benchmark.
A series of disorder predictors described in this article is available as a MetaDisorder web server at http://iimcb.genesilico.pl/metadisorder/. Results are presented both in an easily interpretable, interactive mode and in a simple text format suitable for machine processing.
The hepatitis delta virus (HDV) ribozyme and related RNAs are widely dispersed in nature. This RNA is a small nucleolytic ribozyme that self-cleaves to generate products with a 2’3’-cyclic phosphate and a free 5’-hydroxyl. Although small ribozymes are dependent on divalent metal ions under biologically-relevant buffer conditions, they function in the absence of divalent metal ions at high ionic strength. This characteristic suggests that a functional group within the covalent structure of small ribozymes is facilitating catalysis. Structural and mechanistic analyses have demonstrated that the HDV ribozyme active site contains a cytosine with a perturbed pKa which serves as a general acid to protonate the leaving group. The reaction of the HDV ribozyme in monovalent cations alone never approaches the velocity of the Mg2+-dependent reaction and there is significant biochemical evidence that a Mg2+ ion participates directly in catalysis. A recent crystal structure of the HDV ribozyme revealed that there is a metal binding pocket in the HDV ribozyme active site. Modeling of the cleavage site into the structure suggested that this metal ion can interact directly with the scissile phosphate and the nucleophile. In this manner, the Mg2+ ion can serve as a Lewis acid, facilitating deprotonation of the nucleophile and stabilizing the conformation of the cleavage site for in-line attack of the nucleophile at the scissile phosphate. This catalytic strategy had previously only been observed in much larger ribozymes. Thus, in contrast to most large and small ribozymes, the HDV ribozyme uses two distinct catalytic strategies in its cleavage reaction.