Risk alleles for complex diseases are widely spread throughout human populations. However, little is known about the geographic distribution and frequencies of risk alleles, which may contribute to differences in disease susceptibility and prevalence among populations. Here, we focus on Crohn's disease (CD) as a model for the evolutionary study of complex disease alleles. Recent genome-wide association studies and classical linkage analyses have identified more than 70 susceptible genomic regions for CD in Europeans, but only a few have been confirmed in non-European populations. Our analysis of eight European-specific susceptibility genes using HapMap data shows that at the NOD2 locus the CD-risk alleles are linked with a haplotype specific to CEU at a frequency that is significantly higher compared with the entire genome. We subsequently examined nine global populations and found that the CD-risk alleles spread through hitchhiking with a high-frequency haplotype (H1) exclusive to Europeans. To examine the neutrality of NOD2, we performed phylogenetic network analyses, coalescent simulation, protein structural prediction, characterization of mutation patterns, and estimations of population growth and time to most recent common ancestor (TMRCA). We found that while H1 was significantly prevalent in European populations, the H1 TMRCA predated human migration out of Africa. H1 is likely to have undergone negative selection because 1) the root of H1 genealogy is defined by a preexisting amino acid substitution that causes serious conformational changes to the NOD2 protein, 2) the haplotype has almost become extinct in Africa, and 3) the haplotype has not been affected by the recent European expansion reflected in the other haplotypes. Nevertheless, H1 has survived in European populations, suggesting that the haplotype is advantageous to this group. We propose that several CD-risk alleles, which destabilize and disrupt the NOD2 protein, have been maintained by natural selection on standing variation because the deleterious haplotype of NOD2 is advantageous in diploid individuals due to heterozygote advantage and/or intergenic interactions.
Crohn's disease; NOD2; hitchhiking effect; natural selection; standing variation; mildly deleterious mutation
QA-RecombineIt provides a web interface to assess the quality of protein 3D structure models and to improve the accuracy of models by merging fragments of multiple input models. QA-RecombineIt has been developed for protein modelers who are working on difficult problems, have a set of different homology models and/or de novo models (from methods such as I-TASSER or ROSETTA) and would like to obtain one consensus model that incorporates the best parts into one structure that is internally coherent. An advanced mode is also available, in which one can modify the operation of the fragment recombination algorithm by manually identifying individual fragments or entire models to recombine. Our method produces up to 100 models that are expected to be on the average more accurate than the starting models. Therefore, our server may be useful for crystallographic protein structure determination, where protein models are used for Molecular Replacement to solve the phase problem. To address the latter possibility, a special feature was added to the QA-RecombineIt server. The QA-RecombineIt server can be freely accessed at http://iimcb.genesilico.pl/qarecombineit/.
The continuously increasing amount of RNA sequence and experimentally determined 3D structure data drives the development of computational methods supporting exploration of these data. Contemporary functional analysis of RNA molecules, such as ribozymes or riboswitches, covers various issues, among which tertiary structure modeling becomes more and more important. A growing number of tools to model and predict RNA structure calls for an evaluation of these tools and the quality of outcomes their produce. Thus, the development of reliable methods designed to meet this need is relevant in the context of RNA tertiary structure analysis and can highly influence the quality and usefulness of RNA tertiary structure prediction in the nearest future. Here, we present RNAlyzer—a computational method for comparison of RNA 3D models with the reference structure and for discrimination between the correct and incorrect models. Our approach is based on the idea of local neighborhood, defined as a set of atoms included in the sphere centered around a user-defined atom. A unique feature of the RNAlyzer is the simultaneous visualization of the model-reference structure distance at different levels of detail, from the individual residues to the entire molecules.
We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks.
A key step in proliferation of retroviruses is the conversion of their RNA genome to double-stranded DNA, a process catalysed by multifunctional reverse transcriptases (RTs). Dimeric and monomeric RTs have been described, the latter exemplified by the enzyme of Moloney murine leukaemia virus. However, structural information is lacking that describes the substrate binding mechanism for a monomeric RT. We report here the first crystal structure of a complex between an RNA/DNA hybrid substrate and polymerase-connection fragment of the single-subunit RT from xenotropic murine leukaemia virus-related virus, a close relative of Moloney murine leukaemia virus. A comparison with p66/p51 human immunodeficiency virus-1 RT shows that substrate binding around the polymerase active site is conserved but differs in the thumb and connection subdomains. Small-angle X-ray scattering was used to model full-length xenotropic murine leukaemia virus-related virus RT, demonstrating that its mobile RNase H domain becomes ordered in the presence of a substrate—a key difference between monomeric and dimeric RTs.
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
Computational models of protein structures were proved to be useful as search models in Molecular Replacement (MR), a common method to solve the phase problem faced by macromolecular crystallography. The success of MR depends on the accuracy of a search model. Unfortunately, this parameter remains unknown until the final structure of the target protein is determined. During the last few years, several Model Quality Assessment Programs (MQAPs) that predict the local accuracy of theoretical models have been developed. In this article, we analyze whether the application of MQAPs improves the utility of theoretical models in MR.
For our dataset of 615 search models, the real local accuracy of a model increases the MR success ratio by 101% compared to corresponding polyalanine templates. On the contrary, when local model quality is not utilized in MR, the computational models solved only 4.5% more MR searches than polyalanine templates. For the same dataset of the 615 models, a workflow combining MR with predicted local accuracy of a model found 45% more correct solution than polyalanine templates. To predict such accuracy MetaMQAPclust, a “clustering MQAP” was used.
Using comparative models only marginally increases the MR success ratio in comparison to polyalanine structures of templates. However, the situation changes dramatically once comparative models are used together with their predicted local accuracy. A new functionality was added to the GeneSilico Fold Prediction Metaserver in order to build models that are more useful for MR searches. Additionally, we have developed a simple method, AmIgoMR (Am I good for MR?), to predict if an MR search with a template-based model for a given template is likely to find the correct solution.
Molecular replacement; MR; MQAP; Model quality assessment; Protein structure prediction
MODOMICS is a database of RNA modifications that provides comprehensive information concerning the chemical structures of modified ribonucleosides, their biosynthetic pathways, RNA-modifying enzymes and location of modified residues in RNA sequences. In the current database version, accessible at http://modomics.genesilico.pl, we included new features: a census of human and yeast snoRNAs involved in RNA-guided RNA modification, a new section covering the 5′-end capping process, and a catalogue of ‘building blocks’ for chemical synthesis of a large variety of modified nucleosides. The MODOMICS collections of RNA modifications, RNA-modifying enzymes and modified RNAs have been also updated. A number of newly identified modified ribonucleosides and more than one hundred functionally and structurally characterized proteins from various organisms have been added. In the RNA sequences section, snRNAs and snoRNAs with experimentally mapped modified nucleosides have been added and the current collection of rRNA and tRNA sequences has been substantially enlarged. To facilitate literature searches, each record in MODOMICS has been cross-referenced to other databases and to selected key publications. New options for database searching and querying have been implemented, including a BLAST search of protein sequences and a PARALIGN search of the collected nucleic acid sequences.
Cytoplasmic initiator tRNAs from plants and fungi are excluded from participating in translational elongation by the presence of a unique 2′-phosphoribosyl modification of purine 64, introduced posttranscriptionally by the enzyme Rit1p. Members of the Rit1p family show no obvious similarity to other proteins or domains, there is no structural information available to guide experimental analyses, and the mechanism of action of this enzyme remains a mystery. Using protein fold recognition, we identified a phosphatase-like domain in the C-terminal part of Rit1p. A comparative model of the C-terminal domain was constructed and used to predict the function of conserved residues and to propose the mechanism of action of Rit1p. The model will facilitate experimental analyses of Rit1p and its interactions with the initiator tRNA substrate.
fold recognition; homology modeling; tRNA modification; Rit1p; bioinformatics
Ribonucleases (RNases) are valuable tools applied in the analysis of RNA sequence, structure and function. Their substrate specificity is limited to recognition of single bases or distinct secondary structures in the substrate. Currently, there are no RNases available for purely sequence-dependent fragmentation of RNA. Here, we report the development of a new enzyme that cleaves the RNA strand in DNA–RNA hybrids 5 nt from a nonanucleotide recognition sequence. The enzyme was constructed by fusing two functionally independent domains, a RNase HI, that hydrolyzes RNA in DNA–RNA hybrids in processive and sequence-independent manner, and a zinc finger that recognizes a sequence in DNA–RNA hybrids. The optimization of the fusion enzyme’s specificity was guided by a structural model of the protein-substrate complex and involved a number of steps, including site-directed mutagenesis of the RNase moiety and optimization of the interdomain linker length. Methods for engineering zinc finger domains with new sequence specificities are readily available, making it feasible to acquire a library of RNases that recognize and cleave a variety of sequences, much like the commercially available assortment of restriction enzymes. Potentially, zinc finger-RNase HI fusions may, in addition to in vitro applications, be used in vivo for targeted RNA degradation.
The spliceosome is a molecular machine that performs the excision of introns from eukaryotic pre-mRNAs. This macromolecular complex comprises in human cells five RNAs and over one hundred proteins. In recent years, many spliceosomal proteins have been found to exhibit intrinsic disorder, that is to lack stable native three-dimensional structure in solution. Building on the previous body of proteomic, structural and functional data, we have carried out a systematic bioinformatics analysis of intrinsic disorder in the proteome of the human spliceosome. We discovered that almost a half of the combined sequence of proteins abundant in the spliceosome is predicted to be intrinsically disordered, at least when the individual proteins are considered in isolation. The distribution of intrinsic order and disorder throughout the spliceosome is uneven, and is related to the various functions performed by the intrinsic disorder of the spliceosomal proteins in the complex. In particular, proteins involved in the secondary functions of the spliceosome, such as mRNA recognition, intron/exon definition and spliceosomal assembly and dynamics, are more disordered than proteins directly involved in assisting splicing catalysis. Conserved disordered regions in spliceosomal proteins are evolutionarily younger and less widespread than ordered domains of essential spliceosomal proteins at the core of the spliceosome, suggesting that disordered regions were added to a preexistent ordered functional core. Finally, the spliceosomal proteome contains a much higher amount of intrinsic disorder predicted to lack secondary structure than the proteome of the ribosome, another large RNP machine. This result agrees with the currently recognized different functions of proteins in these two complexes.
In eukaryotic cells, introns are spliced out of proteincoding mRNAs by a highly dynamic and extraordinarily plastic molecular machine called the spliceosome. In recent years, multiple regions of intrinsic structural disorder were found in spliceosomal proteins. Intrinsically disordered regions lack stable native three-dimensional structure in solutions, which makes them structurally flexible and/or able to switch between different conformations. Hence, intrinsically disordered regions are the ideal candidate responsible for the spliceosome's plasticity. Intrinsically disordered regions are also frequently the sites of post-translational modifications, which were also proven to be important in spliceosome dynamics. In this article, we describe the results of a structural bioinformatics analysis focused on intrinsic disorder in the spliceosomal proteome. We systematically analyzed all known human spliceosomal proteins with regards to the presence and type of intrinsic disorder. Almost a half of the combined sequence of these spliceosomal proteins is predicted to be intrinsically disordered, and the type of intrinsic disorder in a protein varies with its function and its location in the spliceosome. The parts of the spliceosome that act earlier in the process are more disordered, which corresponds to their role in establishing a network of interactions, while the parts that act later are more ordered.
Dihydrouridine (D) is a modified base found in conserved positions in the
D-loop of tRNA in Bacteria, Eukaryota, and some Archaea. Despite the
abundant occurrence of D, little is known about its biochemical roles in
mediating tRNA function. It is assumed that D may destabilize the structure
of tRNA and thus enhance its conformational flexibility. D is generated
post-transcriptionally by the reduction of the 5,6-double bond of a uridine
residue in RNA transcripts. The reaction is carried out by dihydrouridine
synthases (DUS). DUS constitute a conserved family of enzymes encoded by the
orthologous gene family COG0042. In protein sequence databases, members of
COG0042 are typically annotated as “predicted TIM-barrel enzymes,
possibly dehydrogenases, nifR3 family”.
To elucidate sequence-structure-function relationships in the DUS family, a
comprehensive bioinformatic analysis was carried out. We performed extensive
database searches to identify all members of the currently known DUS family,
followed by clustering analysis to subdivide it into subfamilies of closely
related sequences. We analyzed phylogenetic distributions of all members of
the DUS family and inferred the evolutionary tree, which suggested a
scenario for the evolutionary origin of dihydrouridine-forming enzymes. For
a human representative of the DUS family, the hDus2 protein suggested as a
potential drug target in cancer, we generated a homology model. While this
article was under review, a crystal structure of a DUS representative has
been published, giving us an opportunity to validate the model.
We compared sequences and phylogenetic distributions of all members of the
DUS family and inferred the phylogenetic tree, which provides a framework to
study the functional differences among these proteins and suggests a
scenario for the evolutionary origin of dihydrouridine formation. Our
evolutionary and structural classification of the DUS family provides a
background to study functional differences among these proteins that will
guide experimental analyses.
Dihydrouridine synthases; Protein structure prediction; Fold recognition; Remote homology; RNA modification; Molecular evolution; Enzymes acting on RNA
Exonuclease VII (ExoVII) is a bacterial nuclease involved in DNA repair and recombination that hydrolyses single-stranded DNA. ExoVII is composed of two subunits: large XseA and small XseB. Thus far, little was known about the molecular structure of ExoVII, the interactions between XseA and XseB, the architecture of the nuclease active site or its mechanism of action. We used bioinformatics methods to predict the structure of XseA, which revealed four domains: an N-terminal OB-fold domain, a middle putatively catalytic domain, a coiled-coil domain and a short C-terminal segment. By series of deletion and site-directed mutagenesis experiments on XseA from Escherichia coli, we determined that the OB-fold domain is responsible for DNA binding, the coiled-coil domain is involved in binding multiple copies of the XseB subunit and residues D155, R205, H238 and D241 of the middle domain are important for the catalytic activity but not for DNA binding. Altogether, we propose a model of sequence–structure–function relationships in ExoVII.
DNA methylation-dependent restriction enzymes have many applications in genetic engineering and in the analysis of the epigenetic state of eukaryotic genomes. Nevertheless, high-resolution structures have not yet been reported, and therefore mechanisms of DNA methylation-dependent cleavage are not understood. Here, we present a biochemical analysis and high-resolution DNA co-crystal structure of the N6-methyladenine (m6A)-dependent restriction enzyme R.DpnI. Our data show that R.DpnI consists of an N-terminal catalytic PD-(D/E)XK domain and a C-terminal winged helix (wH) domain. Surprisingly, both domains bind DNA in a sequence- and methylation-sensitive manner. The crystal contains R.DpnI with fully methylated target DNA bound to the wH domain, but distant from the catalytic domain. Independent readout of DNA sequence and methylation by the two domains might contribute to R.DpnI specificity or could help the monomeric enzyme to cut the second strand after introducing a nick.
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.
In this work, we describe the results of a comprehensive structural bioinformatics analysis of the spliceosomal proteome. We used fold recognition analysis to complement prior data on the ordered domains of 252 human splicing proteins. Examples of newly identified domains include a PWI domain in the U5 snRNP protein 200K (hBrr2, residues 258–338), while examples of previously known domains with a newly determined fold include the DUF1115 domain of the U4/U6 di-snRNP protein 90K (hPrp3, residues 540–683). We also established a non-redundant set of experimental models of spliceosomal proteins, as well as constructed in silico models for regions without an experimental structure. The combined set of structural models is available for download. Altogether, over 90% of the ordered regions of the spliceosomal proteome can be represented structurally with a high degree of confidence. We analyzed the reduced spliceosomal proteome of the intron-poor organism Giardia lamblia, and as a result, we proposed a candidate set of ordered structural regions necessary for a functional spliceosome. The results of this work will aid experimental and structural analyses of the spliceosomal proteins and complexes, and can serve as a starting point for multiscale modeling of the structure of the entire spliceosome.
We previously defined a family of restriction endonucleases (REases) from Thermus sp., which share common biochemical and biophysical features, such as the fusion of both the nuclease and methyltransferase (MTase) activities in a single polypeptide, cleavage at a distance from the recognition site, large molecular size, modulation of activity by S-adenosylmethionine (SAM), and incomplete cleavage of the substrate DNA. Members include related thermophilic REases with five distinct specificities: TspGWI, TaqII, Tth111II/TthHB27I, TspDTI and TsoI.
TspDTI, TsoI and isoschizomers Tth111II/TthHB27I recognize different, but related sequences: 5'-ATGAA-3', 5'-TARCCA-3' and 5'-CAARCA-3' respectively. Their amino acid sequences are similar, which is unusual among REases of different specificity. To gain insight into this group of REases, TspDTI, the prototype member of the Thermus sp. enzyme family, was cloned and characterized using a recently developed method for partially cleaving REases.
TspDTI, TsoI and isoschizomers Tth111II/TthHB27I are closely related bifunctional enzymes. They comprise a tandem arrangement of Type I-like domains, like other Type IIC enzymes (those with a fusion of a REase and MTase domains), e.g. TspGWI, TaqII and MmeI, but their sequences are only remotely similar to these previously characterized enzymes. The characterization of TspDTI, a prototype member of this group, extends our understanding of sequence-function relationships among multifunctional restriction-modification enzymes.
Statins, HMG-CoA reductase inhibitors, are used in the prevention and treatment of cardiovascular diseases owing to their lipid-lowering effects. Previous studies revealed that, by modulating membrane cholesterol content, statins could induce conformational changes in cluster of differentiation 20 (CD20) tetraspanin. The aim of the presented study was to investigate the influence of statins on glucose transporter 1 (GLUT1)-mediated glucose uptake in tumor cells. We observed a significant concentration- and time-dependent decrease in glucose analogs' uptake in several tumor cell lines incubated with statins. This effect was reversible with restitution of cholesterol synthesis pathway with mevalonic acid as well as with supplementation of plasma membrane with exogenous cholesterol. Statins did not change overall GLUT1 expression at either transcriptional or protein levels. An exploratory clinical trial revealed that statin treatment decreased glucose uptake in peripheral blood leukocytes and lowered 18F-fluorodeoxyglucose (18F-FDG) uptake by tumor masses in a mantle cell lymphoma patient. A bioinformatics analysis was used to predict the structure of human GLUT1 and to identify putative cholesterol-binding motifs in its juxtamembrane fragment. Altogether, the influence of statins on glucose uptake seems to be of clinical significance. By inhibiting 18F-FDG uptake, statins can negatively affect the sensitivity of positron emission tomography, a diagnostic procedure frequently used in oncology.
Methyltransferases (MTases) form a major class of tRNA-modifying enzymes needed for the proper functioning of tRNA. Recently, RNA MTases from the TrmN/Trm14 family that are present in Archaea, Bacteria and Eukaryota have been shown to specifically modify tRNAPhe at guanosine 6 in the tRNA acceptor stem. Here, we report the first X-ray crystal structures of the tRNA m2G6 (N2-methylguanosine) MTase TTCTrmN from Thermus thermophilus and its ortholog PfTrm14 from Pyrococcus furiosus. Structures of PfTrm14 were solved in complex with the methyl donor S-adenosyl-l-methionine (SAM or AdoMet), as well as the reaction product S-adenosyl-homocysteine (SAH or AdoHcy) and the inhibitor sinefungin. TTCTrmN and PfTrm14 consist of an N-terminal THUMP domain fused to a catalytic Rossmann-fold MTase (RFM) domain. These results represent the first crystallographic structure analysis of proteins containing both THUMP and RFM domain, and hence provide further insight in the contribution of the THUMP domain in tRNA recognition and catalysis. Electrostatics and conservation calculations suggest a main tRNA binding surface in a groove between the THUMP domain and the MTase domain. This is further supported by a docking model of TrmN in complex with tRNAPhe of T. thermophilus and via site-directed mutagenesis.
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.
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.
Motivation: Metal ions are essential for the folding of RNA molecules into stable tertiary structures and are often involved in the catalytic activity of ribozymes. However, the positions of metal ions in RNA 3D structures are difficult to determine experimentally. This motivated us to develop a computational predictor of metal ion sites for RNA structures.
Results: We developed a statistical potential for predicting positions of metal ions (magnesium, sodium and potassium), based on the analysis of binding sites in experimentally solved RNA structures. The MetalionRNA program is available as a web server that predicts metal ions for RNA structures submitted by the user.
Availability: The MetalionRNA web server is accessible at http://metalionrna.genesilico.pl/.
Supplementary information: Supplementary data are available at Bioinformatics online.
The mom gene of bacteriophage Mu encodes an enzyme that converts adenine to N6-(1-acetamido)-adenine in the phage DNA and thereby protects the viral genome from cleavage by a wide variety of restriction endonucleases. Mu-like prophage sequences present in Haemophilus influenzae Rd (FluMu), Neisseria meningitidis type A strain Z2491 (Pnme1) and H. influenzae biotype aegyptius ATCC 11116 do not possess a Mom-encoding gene. Instead, at the position occupied by mom in Mu they carry an unrelated gene that encodes a protein with homology to DNA adenine N6-methyltransferases (hin1523, nma1821, hia5, respectively). Products of the hin1523, hia5 and nma1821 genes modify adenine residues to N6-methyladenine, both in vitro and in vivo. All of these enzymes catalyzed extensive DNA methylation; most notably the Hia5 protein caused the methylation of 61% of the adenines in λ DNA. Kinetic analysis of oligonucleotide methylation suggests that all adenine residues in DNA, with the possible exception of poly(A)-tracts, constitute substrates for the Hia5 and Hin1523 enzymes. Their potential ‘sequence specificity’ could be summarized as AB or BA (where B = C, G or T). Plasmid DNA isolated from Escherichia coli cells overexpressing these novel DNA methyltransferases was resistant to cleavage by many restriction enzymes sensitive to adenine methylation.