Specific interaction of zinc finger protein Com with RNA and the crystal structure of a self-complementary RNA duplex recognized by Com.

The bacteriophage Mu Com is a small zinc finger protein that binds to its cognate mom mRNA and activates its translation. The Mom protein, in turn, elicits a chemical modification (momification) of the bacteriophage genome, rendering the DNA resistant to cleavage by bacterial restriction endonucleases, and thereby protecting it from defense mechanisms of the host. We examined the basis of specificity in Com-RNA interactions by in vitro selection and probing of RNA structure. We demonstrated that Com recognizes a sequence motif within a hairpin-loop structure of its target RNA. Our data support the model of Com interaction with mom mRNA, in which Com binds to the short hairpin structure proximal to the so-called translation inhibition structure. We also observed that Com binds its target motif weakly if it is within an RNA duplex. These results suggest that the RNA structure, in addition to its sequence, is crucial for Com to recognize its target and that RNA conformational changes may constitute another level of Mom regulation. We determined a crystal structure of a Com binding site variant designed to form an RNA duplex preferentially. Our crystal model forms a 19-mer self-complementary double helix composed of the canonical and non-canonical base pairs. The helical parameters of crystalized RNA indicate why Com may bind it more weakly than a monomeric hairpin form.

Isotope Effects on Nuclear Magnetic Shielding in Molecular Hydrogen.

The secondary isotope shifts of six molecular hydrogen isotopologues (H2, D2, T2, HD, HT, and DT) were measured using gas-phase nuclear magnetic resonance spectroscopy. It was found that these isotope shifts are in satisfying agreement with performed ab initio quantum chemistry computations. However, there is a small systematic discrepancy between results of experiments and computations, i.e., the magnitudes of computed shifts are approximately 10% larger than those obtained from the experiments. This indicates that computations performed using the Born-Oppenheimer approximation are not sufficient for reproducing quantitatively the experimentally determined secondary isotope shifts of molecular hydrogen.

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

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

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

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

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

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

Computational methods for prediction of RNA interactions with metal ions and small organic ligands.

In the recent years, it has become clear that a wide range of regulatory functions in bacteria are performed by riboswitches--regions of mRNA that change their structure upon external stimuli. Riboswitches are therefore attractive targets for drug design, molecular engineering, and fundamental research on regulatory circuitry of living cells. Several mechanisms are known for riboswitches controlling gene expression, but most of them perform their roles by ligand binding. As with other macromolecules, knowledge of the 3D structure of riboswitches is crucial for the understanding of their function. The development of experimental methods allowed for investigation of RNA structure and its complexes with ligands (which are either riboswitches' substrates or inhibitors) and metal cations (which stabilize the structure and are also known to be riboswitches' inhibitors). The experimental probing of different states of riboswitches is however time consuming, costly, and difficult to resolve without theoretical support. The natural consequence is the use of computational methods at least for initial research, such as the prediction of putative binding sites of ligands or metal ions. Here, we present a review on such methods, with a special focus on knowledge-based methods developed in our laboratory: LigandRNA--a scoring function for the prediction of RNA-small molecule interactions and MetalionRNA--a predictor of metal ions-binding sites in RNA structures. Both programs are available free of charge as a Web servers, LigandRNA at http://ligandrna.genesilico.pl and MetalionRNA at http://metalionrna.genesilico.pl/.

Designability landscape reveals sequence features that define axial helix rotation in four-helical homo-oligomeric antiparallel coiled-coil structures.

Coiled coils are widespread protein domains comprising α-helices wound around each other in a regular fashion. Owing to their regularity, coiled-coil structures can be fully described by parametric equations. This in turn makes them an excellent model for studying sequence-structure relationships in proteins. Here, we used computational design to identify sequence features that determine the degree of helix axial rotation in four-helical homo-oligomeric antiparallel coiled coils. We designed 135,000 artificial sequences for a repertoire of backbone models representing all theoretically possible axial rotation states. Analysis of the designed sequences revealed features that precisely define the rotation of the helices. Based on these features we implemented a bioinformatic tool, which given a coiled-coil sequence, predicts the rotation of the helices in its structure. Moreover, we showed that another structural parameter, helix axial shift, is coupled to helix axial rotation and that dependence between these two parameters narrows the number of possible axial rotation states.

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

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

LigandRNA: computational predictor of RNA-ligand interactions.

RNA molecules have recently become attractive as potential drug targets due to the increased awareness of their importance in key biological processes. The increase of the number of experimentally determined RNA 3D structures enabled structure-based searches for small molecules that can specifically bind to defined sites in RNA molecules, thereby blocking or otherwise modulating their function. However, as of yet, computational methods for structure-based docking of small molecule ligands to RNA molecules are not as well established as analogous methods for protein-ligand docking. This motivated us to create LigandRNA, a scoring function for the prediction of RNA-small molecule interactions. Our method employs a grid-based algorithm and a knowledge-based potential derived from ligand-binding sites in the experimentally solved RNA-ligand complexes. As an input, LigandRNA takes an RNA receptor file and a file with ligand poses. As an output, it returns a ranking of the poses according to their score. The predictive power of LigandRNA favorably compares to five other publicly available methods. We found that the combination of LigandRNA and Dock6 into a "meta-predictor" leads to further improvement in the identification of near-native ligand poses. The LigandRNA program is available free of charge as a web server at http://ligandrna.genesilico.pl.

MetalionRNA: computational predictor of metal-binding sites in RNA structures.

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/.

Quantum Electrodynamics Effects in Rovibrational Spectra of Molecular Hydrogen.

The dissociation energies from all rovibrational levels of H2 and D2 in the ground electronic state are calculated with high accuracy by including relativistic and quantum electrodynamics (QED) effects in the nonadiabatic treatment of the nuclear motion. For D2, the obtained energies have theoretical uncertainties of 0.001 cm(-1). For H2, similar uncertainties are for the lowest levels, while for the higher ones the uncertainty increases to 0.005 cm(-1). Very good agreement with recent high-resolution measurements of the rotational v = 0 levels of H2, including states with large angular momentum J, is achieved. This agreement would not have been possible without accurate evaluation of the relativistic and QED contributions and may be viewed as the first observation of the QED effects, mainly the electron self-energy, in a molecular spectrum. For several electric quadrupole transitions, we still observe certain disagreement with experimental results, which remains to be explained.

Effect of nicotinamide and its two derivatives on the generation of reactive oxygen species in human monocytes cooperating with platelets.

The study was designed to demonstrate the relationship between the activity of human normal monocytes and blood platelets, to determine the metabolic activity of normal monocytes and monocytes cooperating with blood platelets in respect of their generation of reactive oxygen species (ROS) and to study the response of cooperating cells to nicotinamide (NA), 1-methylnicotinamide (MNA+) and 1-methyl-N'-hydroxymethylnicotinamide (MNAF+). The ability of those potential antiinflammatory compounds to inhibit oxygen respiratory burst was also assessed. Measurements were carried out by luminol chemiluminometry. The results of the measurements were compared to the data acquired for aspirin (ASA). The results obtained showed that MNAF inhibited oxygen burst in monocytes cooperating with platelets, whereas the two other compounds, NA and MNA, did not cause inhibition of oxygen burst in vitro at a statistically significant level.

Theoretical Determination of the Dissociation Energy of Molecular Hydrogen.

The dissociation energy of molecular hydrogen is determined theoretically with a careful estimation of error bars by including nonadiabatic, relativistic, and quantum electrodynamics (QED) corrections. The relativistic and QED corrections were obtained at the adiabatic level of theory by including all contributions of the order α(2) and α(3) as well as the major (one-loop) α(4) term, where α is the fine-structure constant. The computed α(0), α(2), α(3), and α(4) components of the dissociation energy of the H2 isotopomer are 36 118.7978(2), -0.5319(3), -0.1948(2), and -0.0016(8) cm(-1), respectively, while their sum amounts to 36 118.0695(10) cm(-1), where the total uncertainty includes the estimated size (±0.0004 cm(-1)) of the neglected relativistic nonadiabatic/recoil corrections. The obtained theoretical value of the dissociation energy is in excellent agreement with the most recent experimental determination 36 118.0696(4) cm(-1) [J. Liu et al. J. Chem. Phys. 2009, 130, 174 306]. This agreement would have been impossible without inclusion of several subtle QED contributions which have not been considered, thus far, for molecules. A similarly good agreement is observed for the leading vibrational and rotational energy differences. For the D2 molecule we observe, however, a small disagreement between our value 36 748.3633(9) cm(-1) and the experimental result 36 748.343(10) cm(-1) obtained in a somewhat older and less precise experiment [Y. P. Zhang et al. Phys. Rev. Lett. 2004, 92, 203003]. The reason of this discrepancy is not known.

Radiative corrections to the polarizability of helium.

The complete alpha(3) QED correction to the helium atom polarizability is computed assuming an infinite nuclear mass and found to be equal to 0.000030666(3) a.u., with the contribution from the electric-field dependence of the Bethe logarithm amounting to 0.000000193(2) a.u. After including the alpha(2) and alpha(3) corrections for the nuclear recoil and the leading part of the alpha(4) QED correction, we find that the molar polarizability of 4He is 0.51725419(9)(4) cm(3)/mol. The first of the two error bounds is dominated by the uncertainty of alpha(4) and higher-order QED corrections and the second reflects the uncertainty of the Avogadro constant.