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

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

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/.

Blind tests of RNA nearest-neighbor energy prediction.

The predictive modeling and design of biologically active RNA molecules requires understanding the energetic balance among their basic components. Rapid developments in computer simulation promise increasingly accurate recovery of RNA's nearest-neighbor (NN) free-energy parameters, but these methods have not been tested in predictive trials or on nonstandard nucleotides. Here, we present, to our knowledge, the first such tests through a RECCES-Rosetta (reweighting of energy-function collection with conformational ensemble sampling in Rosetta) framework that rigorously models conformational entropy, predicts previously unmeasured NN parameters, and estimates these values' systematic uncertainties. RECCES-Rosetta recovers the 10 NN parameters for Watson-Crick stacked base pairs and 32 single-nucleotide dangling-end parameters with unprecedented accuracies: rmsd of 0.28 kcal/mol and 0.41 kcal/mol, respectively. For set-aside test sets, RECCES-Rosetta gives rmsd values of 0.32 kcal/mol on eight stacked pairs involving G-U wobble pairs and 0.99 kcal/mol on seven stacked pairs involving nonstandard isocytidine-isoguanosine pairs. To more rigorously assess RECCES-Rosetta, we carried out four blind predictions for stacked pairs involving 2,6-diaminopurine-U pairs, which achieved 0.64 kcal/mol rmsd accuracy when tested by subsequent experiments. Overall, these results establish that computational methods can now blindly predict energetics of basic RNA motifs, including chemically modified variants, with consistently better than 1 kcal/mol accuracy. Systematic tests indicate that resolving the remaining discrepancies will require energy function improvements beyond simply reweighting component terms, and we propose further blind trials to test such efforts.

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/.

Double-stranded RNA under force and torque: similarities to and striking differences from double-stranded DNA.

RNA plays myriad roles in the transmission and regulation of genetic information that are fundamentally constrained by its mechanical properties, including the elasticity and conformational transitions of the double-stranded (dsRNA) form. Although double-stranded DNA (dsDNA) mechanics have been dissected with exquisite precision, much less is known about dsRNA. Here we present a comprehensive characterization of dsRNA under external forces and torques using magnetic tweezers. We find that dsRNA has a force-torque phase diagram similar to that of dsDNA, including plectoneme formation, melting of the double helix induced by torque, a highly overwound state termed "P-RNA," and a highly underwound, left-handed state denoted "L-RNA." Beyond these similarities, our experiments reveal two unexpected behaviors of dsRNA: Unlike dsDNA, dsRNA shortens upon overwinding, and its characteristic transition rate at the plectonemic buckling transition is two orders of magnitude slower than for dsDNA. Our results challenge current models of nucleic acid mechanics, provide a baseline for modeling RNAs in biological contexts, and pave the way for new classes of magnetic tweezers experiments to dissect the role of twist and torque for RNA-protein interactions at the single-molecule level.

Correcting pervasive errors in RNA crystallography through enumerative structure prediction.

Three-dimensional RNA models fitted into crystallographic density maps exhibit pervasive conformational ambiguities, geometric errors and steric clashes. To address these problems, we present enumerative real-space refinement assisted by electron density under Rosetta (ERRASER), coupled to Python-based hierarchical environment for integrated 'xtallography' (PHENIX) diffraction-based refinement. On 24 data sets, ERRASER automatically corrects the majority of MolProbity-assessed errors, improves the average R(free) factor, resolves functionally important discrepancies in noncanonical structure and refines low-resolution models to better match higher-resolution models.

Blind predictions of DNA and RNA tweezers experiments with force and torque.

Single-molecule tweezers measurements of double-stranded nucleic acids (dsDNA and dsRNA) provide unprecedented opportunities to dissect how these fundamental molecules respond to forces and torques analogous to those applied by topoisomerases, viral capsids, and other biological partners. However, tweezers data are still most commonly interpreted post facto in the framework of simple analytical models. Testing falsifiable predictions of state-of-the-art nucleic acid models would be more illuminating but has not been performed. Here we describe a blind challenge in which numerical predictions of nucleic acid mechanical properties were compared to experimental data obtained recently for dsRNA under applied force and torque. The predictions were enabled by the HelixMC package, first presented in this paper. HelixMC advances crystallography-derived base-pair level models (BPLMs) to simulate kilobase-length dsDNAs and dsRNAs under external forces and torques, including their global linking numbers. These calculations recovered the experimental bending persistence length of dsRNA within the error of the simulations and accurately predicted that dsRNA's "spring-like" conformation would give a two-fold decrease of stretch modulus relative to dsDNA. Further blind predictions of helix torsional properties, however, exposed inaccuracies in current BPLM theory, including three-fold discrepancies in torsional persistence length at the high force limit and the incorrect sign of dsRNA link-extension (twist-stretch) coupling. Beyond these experiments, HelixMC predicted that 'nucleosome-excluding' poly(A)/poly(T) is at least two-fold stiffer than random-sequence dsDNA in bending, stretching, and torsional behaviors; Z-DNA to be at least three-fold stiffer than random-sequence dsDNA, with a near-zero link-extension coupling; and non-negligible effects from base pair step correlations. We propose that experimentally testing these predictions should be powerful next steps for understanding the flexibility of dsDNA and dsRNA in sequence contexts and under mechanical stresses relevant to their biology.

Automated RNA structure prediction uncovers a kink-turn linker in double glycine riboswitches.

The tertiary structures of functional RNA molecules remain difficult to decipher. A new generation of automated RNA structure prediction methods may help address these challenges but have not yet been experimentally validated. Here we apply four prediction tools to a class of double glycine riboswitches that can bind two ligands cooperatively. A novel method (BPPalign), RMdetect, JAR3D, and Rosetta 3D modeling give consistent predictions for a new stem P0 and a kink-turn motif. These elements structure the linker between the RNAs' double aptamers. Chemical mapping on the Fusobacterium nucleatum riboswitch with N-methylisatoic anhydride, dimethyl sulfate and 1-cyclohexyl-3-(2-morpholinoethyl)carbodiimide metho-p-toluenesulfonate probing, mutate-and-map studies, and mutation/rescue experiments all provide strong evidence for the structured linker. Under solution conditions that permit rigorous thermodynamic analysis, disrupting this helix-junction-helix structure gives 120- and 6-30-fold poorer dissociation constants for the RNA's two glycine-binding transitions, corresponding to an overall energetic impact of 4.3 ± 0.5 kcal/mol. Prior biochemical and crystallography studies did not include this critical element due to over-truncation of the RNA. We speculate that several further undiscovered elements are likely to exist in the flanking regions of this and other functional RNAs, and automated prediction tools can play a useful role in their detection and dissection.

Steric zipper formed by hydrophobic peptide fragment of Syrian hamster prion protein.

Steric zippers, where the residues of two neighboring ß-sheet layers are tightly interdigitated, have been proposed as fundamental structural units of amyloid fibrils by Eisenberg and co-workers. The steric zipper formed by polypeptides containing the palindromic sequence AGAAAAGA has a distinctive feature that the distance between two interdigitated ß-sheet layers is comparable to the interstrand distance of the individual ß-sheet. This structural motif is of great interest in the study of prion disease because the AGAAAAGA sequence is highly conserved in prion proteins of different species. In this work, the amyloid fibrils formed by the polypeptides of PrP(113-127), viz. Ac-AGAAAAGAVVGGLGG-NH(2), are taken as the model compound to investigate the biophysical principles governing the steric zipper formation. The target fibrils adopt the structural motif of class 7 steric zipper, which is formed by stacking of antiparallel ß-sheet layers with residue 117 + k forming backbone hydrogen bonds to residue 120 - k. Implication of our results in the infectivity of scrapie prion is briefly discussed.

Molecular structure of amyloid fibrils formed by residues 127 to 147 of the human prion protein.

Amyloid fibrils are filamentous and insoluble forms of peptides or proteins. Proline has long been considered to be incompatible with the cross-beta structural motif of amyloid fibrils. On the basis of solid-state NMR spectroscopy data, we present a structural model of an in-register parallel beta sheet for the amyloid fibrils formed from a human prion protein fragment, huPrP(127-47). We have developed a simple solid-state NMR spectroscopy technique to identify solvent-protected backbone amide protons in a H/D exchange experiment without disaggregating the amyloid fibrils, from which we find that proline residue P(137) does not disrupt the beta-sheet structure from G(127) to G(142). We suggest that the resultant kink at P(137) generates a twist between adjacent peptide strands to maintain hydrogen bonding in the beta-sheet regions flanking the P(137) residue. Although proline can be well integrated into the cross-beta structure of amyloid fibrils, the kink formed at the position of the proline residue will considerably weaken the hydrogen bonding between the neighboring strands, especially when the mutation site is near the central region of a beta sheet.

Solid-state P-31 NMR study of octacalcium phosphate incorporated with succinate.

Octacalcium phosphate (OCP) is an important model compound in the study of biomineralization. The octacalcium phosphate-succinate (OCPS) compound is prepared and characterized by (31)P solid-state NMR spectroscopy. Taking advantage of the fact that the crystal structures of OCP and OCPS are very similar, an NMR strategy based on the (31)P homonuclear double-quantum spectroscopy is developed to assign all the peaks observed in the (31)P magic-angle spinning spectrum of OCPS. On the basis of our experimental data, the molecular formula of OCPS is determined to be Ca(7.81)(HPO(4))(1.82)(PO(4))(3.61)(succinate)(0.56).zH(2)O, where z

Internal symmetry of basic elements in symmetry-based recoupling sequences under magic-angle spinning.

In solid-state NMR, many powerful pulse sequences under the condition of magic-angle spinning can be analyzed on the basis of the C- and R-sequences developed by Levitt and co-workers. It has been speculated for some years that the basic elements commonly used in symmetry-based recoupling pulse sequences have certain kind of internal symmetries. We show by a detailed analysis that a set of internal selection rules does exist for many basic elements. These internal selection rules may allow a more versatile design of CN(n)(ν) or RN(n)(ν) sequences when n is an integer or half-integer multiple of N. As an illustration, we have derived the symmetry arguments to rationalize the observation that the C-REDOR pulse sequence can suppress homonuclear dipole-dipole interaction, leading to the design of new windowed basic elements usable for heteronuclear dipolar recoupling with active suppression of homonuclear dipole-dipole interaction. Numerical simulations and experiments measured for [U-(13)C,(15)N]-L-alanine have been used to validate our approach. On a more general note, the symmetry rules discussed in this work can also be applied for the design of supercycles.

Rotational echo double resonance without proton decoupling under fast spinning condition.

We show that rotational echo double resonance (REDOR) experiments can be carried out without proton decoupling under the conditions of fast spinning and strong rf field. Numerical simulations on a five-spin systems show that no significant attenuation of the reference signal (S(0)) is observed at a spin rate of 25 kHz, provided that the rf power is larger than 100 kHz. This approach has been validated by (31)P{(13)C} REDOR measurements on isotopically labeled glyphosate. The obtained van Vleck's second moment is in favorable agreement with the value calculated based on the crystal structure.

Compensated DRAMA sequence for homonuclear dipolar recoupling under magic-angle spinning.

The DRAMA sequence has been considered as the milestone in the development of homonuclear dipolar recoupling. Although it has a high efficiency for double-quantum excitation in spin 1/2 systems, it is seldom used today for real applications because of its susceptibility to the deteriorating effects of chemical shift anisotropy and resonance offsets. We show in this work that the practicability of DRAMA can be greatly enhanced by incorporating four pi pulses with XY-4 phases into the basic DRAMA cycles. Average Hamiltonian theory is used to evaluate the performance of the resulting pulse sequence with respect to the compensation of chemical shift anisotropy. Numerical simulations and experimental measurements on hydroxyapatite indeed show that the performance of DRAMA-XY4 is very satisfying for 31P DQ excitation, provided that the resonance offset is within the range of [-4, 4]kHz.

RNA Structure Refinement Using the ERRASER-Phenix Pipeline.

The final step of RNA crystallography involves the fitting of coordinates into electron density maps. The large number of backbone atoms in RNA presents a difficult and tedious challenge, particularly when experimental density is poor. The ERRASER-Phenix pipeline can improve an initial set of RNA coordinates automatically based on a physically realistic model of atomic-level RNA interactions. The pipeline couples diffraction-based refinement in Phenix with the Rosetta-based real-space refinement protocol ERRASER (Enumerative Real-Space Refinement ASsisted by Electron density under Rosetta). The combination of ERRASER and Phenix can improve the geometrical quality of RNA crystallographic models while maintaining or improving the fit to the diffraction data (as measured by R free). Here we present a complete tutorial for running ERRASER-Phenix through the Phenix GUI, from the command-line, and via an application in the Rosetta On-line Server that Includes Everyone (ROSIE).

Modeling complex RNA tertiary folds with Rosetta.

Reliable modeling of RNA tertiary structures is key to both understanding these structures' roles in complex biological machines and to eventually facilitating their design for molecular computing and robotics. In recent years, a concerted effort to improve computational prediction of RNA structure through the RNA-Puzzles blind prediction trials has accelerated advances in the field. Among other approaches, the versatile and expanding Rosetta molecular modeling software now permits modeling of RNAs in the 100-300 nucleotide size range at consistent subhelical (~1 nm) resolution. Our laboratory's current state-of-the-art methods for RNAs in this size range involve Fragment Assembly of RNA with Full-Atom Refinement (FARFAR), which optimizes RNA conformations in the context of a physically realistic energy function, as well as hybrid techniques that leverage experimental data to inform computational modeling. In this chapter, we give a practical guide to our current workflow for modeling RNA three-dimensional structures using FARFAR, including strategies for using data from multidimensional chemical mapping experiments to focus sampling and select accurate conformations.

Consistent global structures of complex RNA states through multidimensional chemical mapping.

Accelerating discoveries of non-coding RNA (ncRNA) in myriad biological processes pose major challenges to structural and functional analysis. Despite progress in secondary structure modeling, high-throughput methods have generally failed to determine ncRNA tertiary structures, even at the 1-nm resolution that enables visualization of how helices and functional motifs are positioned in three dimensions. We report that integrating a new method called MOHCA-seq (Multiplexed •OH Cleavage Analysis with paired-end sequencing) with mutate-and-map secondary structure inference guides Rosetta 3D modeling to consistent 1-nm accuracy for intricately folded ncRNAs with lengths up to 188 nucleotides, including a blind RNA-puzzle challenge, the lariat-capping ribozyme. This multidimensional chemical mapping (MCM) pipeline resolves unexpected tertiary proximities for cyclic-di-GMP, glycine, and adenosylcobalamin riboswitch aptamers without their ligands and a loose structure for the recently discovered human HoxA9D internal ribosome entry site regulon. MCM offers a sequencing-based route to uncovering ncRNA 3D structure, applicable to functionally important but potentially heterogeneous states.

Serverification of molecular modeling applications: the Rosetta Online Server that Includes Everyone (ROSIE).

The Rosetta molecular modeling software package provides experimentally tested and rapidly evolving tools for the 3D structure prediction and high-resolution design of proteins, nucleic acids, and a growing number of non-natural polymers. Despite its free availability to academic users and improving documentation, use of Rosetta has largely remained confined to developers and their immediate collaborators due to the code's difficulty of use, the requirement for large computational resources, and the unavailability of servers for most of the Rosetta applications. Here, we present a unified web framework for Rosetta applications called ROSIE (Rosetta Online Server that Includes Everyone). ROSIE provides (a) a common user interface for Rosetta protocols, (b) a stable application programming interface for developers to add additional protocols, (c) a flexible back-end to allow leveraging of computer cluster resources shared by RosettaCommons member institutions, and (d) centralized administration by the RosettaCommons to ensure continuous maintenance. This paper describes the ROSIE server infrastructure, a step-by-step 'serverification' protocol for use by Rosetta developers, and the deployment of the first nine ROSIE applications by six separate developer teams: Docking, RNA de novo, ERRASER, Antibody, Sequence Tolerance, Supercharge, Beta peptide design, NCBB design, and VIP redesign. As illustrated by the number and diversity of these applications, ROSIE offers a general and speedy paradigm for serverification of Rosetta applications that incurs negligible cost to developers and lowers barriers to Rosetta use for the broader biological community. ROSIE is available at http://rosie.rosettacommons.org.

Adding diverse noncanonical backbones to rosetta: enabling peptidomimetic design.

Peptidomimetics are classes of molecules that mimic structural and functional attributes of polypeptides. Peptidomimetic oligomers can frequently be synthesized using efficient solid phase synthesis procedures similar to peptide synthesis. Conformationally ordered peptidomimetic oligomers are finding broad applications for molecular recognition and for inhibiting protein-protein interactions. One critical limitation is the limited set of design tools for identifying oligomer sequences that can adopt desired conformations. Here, we present expansions to the ROSETTA platform that enable structure prediction and design of five non-peptidic oligomer scaffolds (noncanonical backbones), oligooxopiperazines, oligo-peptoids, [Formula: see text]-peptides, hydrogen bond surrogate helices and oligosaccharides. This work is complementary to prior additions to model noncanonical protein side chains in ROSETTA. The main purpose of our manuscript is to give a detailed description to current and future developers of how each of these noncanonical backbones was implemented. Furthermore, we provide a general outline for implementation of new backbone types not discussed here. To illustrate the utility of this approach, we describe the first tests of the ROSETTA molecular mechanics energy function in the context of oligooxopiperazines, using quantum mechanical calculations as comparison points, scanning through backbone and side chain torsion angles for a model peptidomimetic. Finally, as an example of a novel design application, we describe the automated design of an oligooxopiperazine that inhibits the p53-MDM2 protein-protein interaction. For the general biological and bioengineering community, several noncanonical backbones have been incorporated into web applications that allow users to freely and rapidly test the presented protocols (http://rosie.rosettacommons.org). This work helps address the peptidomimetic community's need for an automated and expandable modeling tool for noncanonical backbones.

Measurements of 13C multiple-quantum coherences in amyloid fibrils under magic-angle spinning.

The excitation and detection of high-order multiple quantum coherences among (13)C nuclear spins are demonstrated in the samples of [1-(13)C]-L-alanine and (13)C labeled amyloid fibrils at a spinning frequency of 20 kHz. The technique is based on the double-quantum average Hamiltonian prepared by the DRAMA-XY4 pulse sequence. Empirically, we find that multiple supercycles are required to suppress the higher-order effects for real applications. Measurements for the fibril samples formed by the polypeptides of PrP(113-127) provide the first solid-state NMR evidence for the stacking of multiple ß-sheet layers at the structural core of amyloid fibrils.