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.
A flow type quartz crystal microbalance (QCM) chemical sensor was developed for monitoring of heavy metal ions in aqueous solutions (that is suitable for environmental monitoring). The sensor is based upon surface chelation of the metal ions at multifunctional polymer modified gold electrodes on 9 MHz AT-cut quartz resonators, functioning as a QCM. New processes have been developed which enable to obtain surface-modified gold electrodes with high heavy metal ions complexing ability. These polymer grafted QCM sensors can selectively adsorb heavy metal ions, such as copper lead chrome and cadmium, from solution over a wide range from 0.01 to 1000 ppm concentration by complexation with functional groups in the polymers. Cations typically present in natural water did not interfere with the detection of heavy metals. X-Ray Reflectivity (XRR) and Total Reflection X-ray Fluorescence (TXRF) were carried out to characterise the unmodified and modified gold surfaces as well as to verify the possibility to selectively bond and remove metal ions.
polymer grafted quartz crystal microbalance; multifunctional polymers; heavy metal ions detection
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.
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: The web server MetalDetector classifies histidine residues in proteins into one of two states (free or metal bound) and cysteines into one of three states (free, metal bound or disulfide bridged). A decision tree integrates predictions from two previously developed methods (DISULFIND and Metal Ligand Predictor). Cross-validated performance assessment indicates that our server predicts disulfide bonding state at 88.6% precision and 85.1% recall, while it identifies cysteines and histidines in transition metal-binding sites at 79.9% precision and 76.8% recall, and at 60.8% precision and 40.7% recall, respectively.
Availability: Freely available at http://metaldetector.dsi.unifi.it
Supplementary Information: Details and data can be found at http://metaldetector.dsi.unifi.it/help.php
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 .
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.
Motivation: Identifying the location of binding sites on proteins is of fundamental importance for a wide range of applications, including molecular docking, de novo drug design, structure identification and comparison of functional sites. Here we present Erebus, a web server that searches the entire Protein Data Bank for a given substructure defined by a set of atoms of interest, such as the binding scaffolds for small molecules. The identified substructure contains atoms having the same names, belonging to same amino acids and separated by the same distances (within a given tolerance) as the atoms of the query structure. The accuracy of a match is measured by the root-mean-square deviation or by the normal weight with a given variance. Tests show that our approach can reliably locate rigid binding scaffolds of drugs and metal ions.
Availability and Implementation: We provide this service through a web server at http://erebus.dokhlab.org.
The function of non-coding RNA genes largely depends on their secondary structure and the interaction with other molecules. Thus, an accurate prediction of secondary structure and RNA–RNA interaction is essential for the understanding of biological roles and pathways associated with a specific RNA gene. We present web servers to analyze multiple RNA sequences for common RNA structure and for RNA interaction sites. The web servers are based on the recent PET (Probabilistic Evolutionary and Thermodynamic) models PETfold and PETcofold, but add user friendly features ranging from a graphical layer to interactive usage of the predictors. Additionally, the web servers provide direct access to annotated RNA alignments, such as the Rfam 10.0 database and multiple alignments of 16 vertebrate genomes with human. The web servers are freely available at: http://rth.dk/resources/petfold/
Motivation: Binding site identification is a classical problem that is important for a range of applications, including the structure-based prediction of function, the elucidation of functional relationships among proteins, protein engineering and drug design. We describe an accurate method of binding site identification, namely FTSite. This method is based on experimental evidence that ligand binding sites also bind small organic molecules of various shapes and polarity. The FTSite algorithm does not rely on any evolutionary or statistical information, but achieves near experimental accuracy: it is capable of identifying the binding sites in over 94% of apo proteins from established test sets that have been used to evaluate many other binding site prediction methods.
Availability: FTSite is freely available as a web-based server at http://ftsite.bu.edu.
Contact: email@example.com; firstname.lastname@example.org
Supplementary information: Supplementary data are available at Bioinformatics online.
Early life presumably required polymerase ribozymes capable of replicating RNA. Known polymerase ribozymes best approximating such replicases use as their catalytic engine an RNA-ligase ribozyme originally selected from random RNA sequences. Here, we report 3.15 Å crystal structures of this ligase trapped in catalytically viable pre-ligation states, with the 3′-hydroxyl nucleophile positioned for in-line attack on the 5′-triphosphate. Guided by metal and solvent-mediated interactions, the 5′-triphosphate hooks into the major groove of the adjoining RNA duplex in an unanticipated conformation. Two phosphates and the nucleophile jointly coordinate an active-site metal ion. Atomic mutagenesis experiments demonstrate that active-site nucleobase and hydroxyl groups also participate directly in catalysis, collectively playing a role that in proteinaceous polymerases is performed by a second metal ion. Thus artificial ribozymes can employ complex catalytic strategies that differ dramatically from those of analogous biological enzymes.
Computational sequence analysis, that is, prediction of local sequence properties, homologs, spatial structure and function from the sequence of a protein, offers an efficient way to obtain needed information about proteins under study. Since reliable prediction is usually based on the consensus of many computer programs, meta-severs have been developed to fit such needs. Most meta-servers focus on one aspect of sequence analysis, while others incorporate more information, such as PredictProtein for local sequence feature predictions, SMART for domain architecture and sequence motif annotation, and GeneSilico for secondary and spatial structure prediction. However, as predictions of local sequence properties, three-dimensional structure and function are usually intertwined, it is beneficial to address them together.
We developed a MEta-Server for protein Sequence Analysis (MESSA) to facilitate comprehensive protein sequence analysis and gather structural and functional predictions for a protein of interest. For an input sequence, the server exploits a number of select tools to predict local sequence properties, such as secondary structure, structurally disordered regions, coiled coils, signal peptides and transmembrane helices; detect homologous proteins and assign the query to a protein family; identify three-dimensional structure templates and generate structure models; and provide predictive statements about the protein's function, including functional annotations, Gene Ontology terms, enzyme classification and possible functionally associated proteins. We tested MESSA on the proteome of Candidatus Liberibacter asiaticus. Manual curation shows that three-dimensional structure models generated by MESSA covered around 75% of all the residues in this proteome and the function of 80% of all proteins could be predicted.
MESSA is free for non-commercial use at http://prodata.swmed.edu/MESSA/
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 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.
In vitro selection was used to isolate five classes of allosteric hammerhead ribozymes that are triggered by binding to certain divalent metal ion effectors. Each of these ribozyme classes are similarly activated by Mn2+, Fe2+, Co2+, Ni2+, Zn2+ and Cd2+, but their allosteric binding sites reject other divalent metals such as Mg2+, Ca2+ and Sr2+. Through a more comprehensive survey of cations, it was determined that some metal ions (Be2+, Fe3+, Al3+, Ru2+ and Dy2+) are extraordinarily disruptive to the RNA structure and function. Two classes of RNAs examined in greater detail make use of conserved nucleotides within the large internal bulges to form critical structures for allosteric function. One of these classes exhibits a metal-dependent increase in rate constant that indicates a requirement for the binding of two cation effectors. Additional findings suggest that, although complex allosteric functions can be exhibited by small RNAs, larger RNA molecules will probably be required to form binding pockets that are uniquely selective for individual cation effectors.
Metalloproteins are proteins capable of binding one or more metal ions, which may be required for their biological function, for regulation of their activities or for structural purposes. Metal-binding properties remain difficult to predict as well as to investigate experimentally at the whole-proteome level. Consequently, the current knowledge about metalloproteins is only partial.
The present work reports on the development of a machine learning method for the prediction of the zinc-binding state of pairs of nearby amino-acids, using predictors based on support vector machines. The predictor was trained using chains containing zinc-binding sites and non-metalloproteins in order to provide positive and negative examples. Results based on strong non-redundancy tests prove that (1) zinc-binding residues can be predicted and (2) modelling the correlation between the binding state of nearby residues significantly improves performance. The trained predictor was then applied to the human proteome. The present results were in good agreement with the outcomes of previous, highly manually curated, efforts for the identification of human zinc-binding proteins. Some unprecedented zinc-binding sites could be identified, and were further validated through structural modelling. The software implementing the predictor is freely available at:
The proposed approach constitutes a highly automated tool for the identification of metalloproteins, which provides results of comparable quality with respect to highly manually refined predictions. The ability to model correlations between pairwise residues allows it to obtain a significant improvement over standard 1D based approaches. In addition, the method permits the identification of unprecedented metal sites, providing important hints for the work of experimentalists.
Site-bound metal ions participate in the catalytic mechanisms of many ribozymes. Understanding these mechanisms therefore requires knowledge of the specific ligands on both substrate and ribozyme that coordinate these catalytic metal ions. A number of different structural and biochemical strategies have been developed and refined for identifying metal ion binding sites within ribozymes, and for assessing the catalytic contributions of the metal ions bound at those sites. We review these approaches and provide examples of their application, focusing in particular on metal ion rescue experiments and their roles in the construction of the transition state models for the Tetrahymena group I and RNase P ribozymes.
Ribonuclease (RNase) P is the universal ribozyme responsible for 5′-end tRNA processing. We report the crystal structure of the Thermotoga maritima RNase P holoenzyme in complex with tRNAPhe. The 154 kDa complex consists of a large catalytic RNA (P RNA), a small protein cofactor, and mature tRNA. The structure shows that RNA-RNA recognition occurs through shape complementarity, specific intermolecular contacts, and base pairing interactions. Soaks with a pre-tRNA 5′ leader sequence with and without metal help identify the 5′ substrate path and potential catalytic metal ions. The protein binds on top of a universally conserved structural module in P RNA and interacts with the leader, but not with mature tRNA. The active site is composed of phosphate backbone moieties, a universally conserved uridine nucleobase, and at least two catalytically important metal ions. The active site structure and conserved RNase P/tRNA contacts suggest a universal mechanism of catalysis by RNase P.
A physical model of selective “ion binding” in the L-type calcium channel is constructed, and consequences of the model are compared with experimental data. This reduced model treats only ions and the carboxylate oxygens of the EEEE locus explicitly and restricts interactions to hard-core repulsion and ion–ion and ion–dielectric electrostatic forces. The structural atoms provide a flexible environment for passing cations, thus resulting in a self-organized induced-fit model of the selectivity filter. Experimental conditions involving binary mixtures of alkali and/or alkaline earth metal ions are computed using equilibrium Monte Carlo simulations in the grand canonical ensemble. The model pore rejects alkali metal ions in the presence of biological concentrations of Ca2+ and predicts the blockade of alkali metal ion currents by micromolar Ca2+. Conductance patterns observed in varied mixtures containing Na+ and Li+, or Ba2+ and Ca2+, are predicted. Ca2+ is substantially more potent in blocking Na+ current than Ba2+. In apparent contrast to experiments using buffered Ca2+ solutions, the predicted potency of Ca2+ in blocking alkali metal ion currents depends on the species and concentration of the alkali metal ion, as is expected if these ions compete with Ca2+ for the pore. These experiments depend on the problematic estimation of Ca2+ activity in solutions buffered for Ca2+ and pH in a varying background of bulk salt. Simulations of Ca2+ distribution with the model pore bathed in solutions containing a varied amount of Li+ reveal a “barrier and well” pattern. The entry/exit barrier for Ca2+ is strongly modulated by the Li+ concentration of the bath, suggesting a physical explanation for observed kinetic phenomena. Our simulations show that the selectivity of L-type calcium channels can arise from an interplay of electrostatic and hard-core repulsion forces among ions and a few crucial channel atoms. The reduced system selects for the cation that delivers the largest charge in the smallest ion volume.
DNA and RNA polymerases use divalent metal ions for catalysis. Crystal structures of several polymerases reveal that two acidic residues are involved in coordinating two metal ions at the catalytic centre. Bacteriophage RNA polymerases contain a highly conserved C-terminus with the carboxylate positioned near the active site. We examined whether theC-terminal carboxy group of T7 RNA polymerase is important for magnesium ion-dependent catalysis. Introduction of a methyl ester or decarboxylation of the C-terminal carboxy group was achieved with an intein-based protein expression system and an elongation rate assay was developed to test the effects of the modifications. The results show that enzymes with a modified C-terminal carboxy group exhibit a magnesium ion-dependent decrease in catalytic activity.
Enolase is a dimeric metal-activated metalloenzyme, which uses two magnesium ions per subunit: the strongly bound conformational ion and the catalytic ion that binds to the enzyme-substrate complex inducing catalysis. The crystal structure of the human neuronal enolase-Mg2F2Pi complex (enolase fluoride/phosphate inhibitory complex, EFPIC) determined at 1.36 Å resolution shows that the combination of anions effectively mimics an intermediate state in catalysis. The phosphate ion binds in the same site as the phosphate group of the substrate/product, 2-phospho-D-glycerate/phosphoenolpyruvate, and induces binding of catalytic Mg2+ ion. One fluoride ion bridges the structural and catalytic magnesium ions while the other interacts with the structural magnesium ion and the ammonio groups of Lys 342 and Lys 393. These fluoride ion positions correspond closely to the positions of the oxygen atoms of the substrate's carboxylate moiety. To relate structural changes resulting from fluoride, phosphate and magnesium ions binding to those that are induced by phosphate and magnesium ions alone, we also determined the structure of the human neuronal enolase-Mg2Pi complex (enolase phosphate inhibitory complex, EPIC) at 1.92 Å resolution. It shows the closed conformation in one subunit and a mixture of open and semi-closed conformations in the other. The EPFIC dimer is essentially symmetric while EPIC dimer is asymmetric. Isothermal titration calorimetry data confirmed binding of four fluoride ions per dimer and yielded Kb values of 7.5 × 105 ± 1.3 × 105, 1.2 × 105 ± 0.2 × 105, 8.6 × 104 ± 1.6 × 104, 1.6 × 104 ± 0.7 × 104 M−1. The different binding constants indicate negative cooperativity between the subunits; the asymmetry of EPIC supports such an interpretation.
enolase; fluoride inhibition; negative cooperativity; glycolysis; crystal structure; isothermal titration calorimetry
Correctly folded into the respective native 3D structure, RNA and DNA are responsible for uncountable key functions in any viable organism. In order to exert their function, metal ion cofactors are closely involved in folding, structure formation and, e.g. in ribozymes, also the catalytic mechanism. The database MINAS, Metal Ions in Nucleic AcidS (http://www.minas.uzh.ch), compiles the detailed information on innersphere, outersphere and larger coordination environment of >70 000 metal ions of 36 elements found in >2000 structures of nucleic acids contained today in the PDB and NDB. MINAS is updated monthly with new structures and offers a multitude of search functions, e.g. the kind of metal ion, metal-ligand distance, innersphere and outersphere ligands defined by element or functional group, residue, experimental method, as well as PDB entry-related information. The results of each search can be saved individually for later use with so-called miniPDB files containing the respective metal ion together with the coordination environment within a 15 Å radius. MINAS thus offers a unique way to explore the coordination geometries and ligands of metal ions together with the respective binding pockets in nucleic acids.
The T box transcription antitermination mechanism regulates the expression of unique genes in many Gram-positive bacteria by responding, in a magnesium-dependent manner, to uncharged cognate tRNA base pairing with an antiterminator RNA element and other regions of the 5′-untranslated region. Model T box antiterminator RNA are known to bind aminoglycosides, ligands that typically bind RNA in divalent metal ion binding sites. In this study, enzymatic footprinting and spectroscopic assays were used to identify and characterize the binding site of neomycin B to an antiterminator model RNA. Neomycin B binds the antiterminator bulge nucleotides in an electrostatic-dependent manner and displaces 3–4 monovalent cations, indicating that the antiterminator likely contains a divalent metal ion-binding site. Neomycin B facilitates rather than inhibits tRNA binding indicating that bulge-targeted inhibitors that bind the antiterminator via non-electrostatic interactions may be the more optimal candidates for antiterminator-targeted ligand design.
aminoglycoside; RNA; antitermination; T box; binding; inhibition
Although the hammerhead ribozyme is regarded as a prototype for understanding RNA catalysis, the mechanistic roles of associated metal ions and water molecules in the cleavage reaction remain controversial. We have investigated the catalytic potential of observed divalent metal ions and water molecules bound to a 2 Å structure of the full-length hammerhead ribozyme by using X-ray crystallography in combination with molecular dynamics simulations. A single Mn2+ is observed to bind directly to the A9 phosphate in the active site, accompanying a hydrogen-bond network involving a well-ordered water molecule spanning N1 of G12 (the general base) and 2′-O of G8 (previously implicated in general acid catalysis) that we propose, based on molecular dynamics calculations, facilitates proton transfer in the cleavage reaction. Phosphate-bridging metal interactions and other mechanistic hypotheses are also tested with this approach.
In ribozyme catalysis, metal ions are generally known to make structural
and∕or mechanistic contributions. The catalytic activity of a previously
described Diels-Alderase ribozyme was found to depend on the concentration
of divalent metal ions, and crystallographic data revealed multiple binding
sites. Here, we elucidate the interactions of this ribozyme with divalent
metal ions in solution using electron paramagnetic resonance (EPR) spectroscopy.
Manganese ion titrations revealed five high-affinity Mn2+ binding
sites with an upper Kd of
0.6±0.2 μM. In order to characterize each binding site individually,
EPR-silent Cd2+ ions were used to saturate the
other binding sites. This cadmium-induced EPR silencing showed that the Mn2+ binding sites possess different affinities. In addition,
these binding sites could be assigned to three different types, including
innersphere, outersphere, and a Mn2+ dimer. Based
on simulations, the Mn2+-Mn2+ distance
within the dimer was found to be ∼6 Å, which is in good agreement
with crystallographic data. The EPR-spectroscopic characterization reveals
no structural changes upon addition of a Diels-Alder product, supporting the
concept of a preorganized catalytic pocket in the Diels-Alder ribozyme and
the structural role of these ions.