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 homologyderived 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.ustrasbg.fr/rnapuzzles/.

In addition to continuous rapid progress in RNA structure determination, probing, and biophysical studies, the past decade has seen remarkable advances in the development of a new generation of RNA folding theories and models. Here, we review RNA structure prediction models and models for ion-RNA and ligand-RNA interactions. These new models are becoming increasingly important for mechanistic understanding of RNA function and quantitative design of RNA nanotechnology. We focus on new methods for physics-based, knowledge-based, and experimental data-directed modeling for RNA structures, and explore the new theories for the predictions of metal ion and ligand binding sites and metal ion-dependent RNA stabilities. The integration of these new methods with theories for the cellular environment effects, such as molecular crowding and cotranscriptional folding, may ultimately lead to an all-encompassing RNA folding model.

Nanostructured polyaniline (PANI)-WO 3 hybrid thin films were synthesized via a molecular assembling route in a solution of aniline using peroxotungstic acid (PTA) as the dopant and ammonium persulfate as the oxidant. The films show a porous morphology with nanorod arrays on the surface, and WO 3 is uniformly incorporated into the polymer network. Electrochemical and electrochromic tests including cyclic voltammetry, chronoamperometry and corresponding in situ transmittance of PANI-WO 3 hybrid films compared with neat PANI film and sol-gel WO 3 film were conducted in 0.5 M sulfuric acid solution. The hybrid films, being a dual electrochromic material, varied from royal purple to green, pale yellow and finally dark blue as the applied potential was scanned from 0.8 V to À0.5 V. Compared to sulfate doped PANI film, high colouration efficiency and comparable durability are obtained in the PANI-WO 3 hybrid films. The PANI-WO 3 hybrid films also show faster switching speed and better durability than WO 3 film. The enhanced electrochromic properties such as faster switching speed and better durability are mainly attributed to the combining of advantages of both materials and the formation of the donor-acceptor system.

Coarse-grained RNA folding models promise great potential for RNA structure prediction. A key component in a coarse-grained folding model is the force field. One of the challenges in the coarse-grained force field calculation is how to treat the correlation between the different degrees of freedoms. Here, we describe a new approach (IsRNA) to extract the correlated energy functions from the known structures. Through iterative molecular dynamics simulations, we build the correlation effects into the reference states, from which we extract the energy functions. The validity of IsRNA is supported by the close agreement between the simulated Boltzmann-like probability distributions for all the structure parameters and those observed from the experimentally determined structures. The correlated energy functions derived here may provide a new tool for RNA 3D structure prediction.

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Modeling structures and functions of large ribonucleic acid (RNAs) especially with complicated topologies is highly challenging due to the inefficiency of large conformational sampling and the presence of complicated tertiary interactions. To address this problem, one highly promising approach is coarse-grained modeling. Here, following an iterative simulated reference state approach to decipher the correlations between different structural parameters, we developed a potent coarse-grained RNA model named as IsRNA1 for RNA studies. Molecular dynamics simulations in the IsRNA1 can predict the native structures of small RNAs from a sequence and fold medium-sized RNAs into near-native tertiary structures with the assistance of secondary structure constraints. A large-scale benchmark test on RNA 3D structure prediction shows that IsRNA1 exhibits improved performance for relatively large RNAs of complicated topologies, such as large stem-loop structures and structures containing long-range tertiary interactions. The advantages of IsRNA1 include the consideration of the correlations between the different structural variables, the appropriate characterization of canonical base-pairing and base-stacking interactions, and the better sampling for the backbone conformations. Moreover, a blind screening protocol was developed based on IsRNA1 to identify good structural models from a pool of candidates without prior knowledge of the native structures.

While CRISPR/Cas9 is a powerful tool in genome engineering, the ontarget activity and off-target effects of the system widely vary because of the differences in guide RNA (gRNA) sequences and genomic environments. Traditional approaches rely on separate models and parameters to treat on-and off-target cleavage activities.Here, we demonstrate that a free-energy scheme dominates the Cas9 editing efficacy and delineate a method that simultaneously considers on-target activities and off-target effects. While data-driven machinelearning approaches learn rules to model particular datasets, they may not be as transferrable to new systems or capable of producing new mechanistic insights as principled physical approaches. By integrating the energetics of R-loop formation under Cas9 binding, the effect of the protospacer adjacent motif sequence, and the folding stability of the whole single guide RNA, we devised a unified, physical model that can apply to any cleavage-activity dataset. This unified framework improves predictions for both on-target activities and offtarget efficiencies of spCas9 and may be readily transferred to other systems with different guide RNAs or Cas9 ortholog proteins.RNA folding | free-energy landscape | folding stability | CRISPR | Cas9

Shanshanosaurus huoyanshanensis from the Subashi Formation (Upper Cretaceous) of Xinjiang in northwestern China has long been thought of as a distinctive genus of small theropod. Although usually assigned to its own family, it has generally been included in the tyrannosaurid subfamily Aublysodontinae in recent years. Restudy and description of the only known specimen reveal that it is not a small species, but is a juvenile tyrannosaurine, possibly Tarbosaurus. With a total estimated length of 2.3 m, it is the smallest tyrannosaurid skeleton known. Shanshanosaurus provides the best information available on ontogenetic changes in these enormous carnivores and reveals that young tyrannosaurids had long, low skulls, huge pubic boots, and well-developed limb joints. Evidence suggesting that young tyrannosaurs had relatively longer forelimbs than the adults is not supported by Shanshanosaurus.