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/.

Riboswitches control gene expression through ligand-dependent structural rearrangements of the sensing aptamer domain. However, we found that the Bacillus cereus fluoride riboswitch aptamer adopts identical tertiary structures in solution with and without ligand. Using chemical exchange saturation transfer (CEST) NMR spectroscopy, we revealed that the structured ligand-free aptamer transiently accesses a low-populated (~1%) and short-lived (~3 ms) excited conformational state that unravels a conserved ‘linchpin’ base pair to signal transcription termination. Upon fluoride binding, this highly localized fleeting process is allosterically suppressed to activate transcription. We demonstrated that this mechanism confers effective fluoride-dependent gene activation over a wide range of transcription rates, which is essential for robust toxicity response across diverse cellular conditions. These results unveil a novel switching mechanism that employs ligand-dependent suppression of an aptamer excited state to coordinate regulatory conformational transitions rather than adopting distinct aptamer ground-state tertiary architectures, exemplifying a new mode of ligand-dependent RNA regulation.

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Natural recombination combines pieces of pre-existing proteins to create new tertiary structures and functions. We describe a computational protocol, called SEWING, which is inspired by this process and builds new proteins from connected or disconnected pieces of existing structures. Helical proteins designed with SEWING contain structural features absent from other de novo designed proteins and in some cases remain folded to over 100 °C. High resolution structures of the designed proteins CA01 and DA05R1 were solved by X-ray crystallography (2.2 Å resolution) and NMR respectively, and there was excellent agreement with the design models. This method provides a new strategy to rapidly create large numbers of diverse and designable protein scaffolds.

α-Synuclein (α-syn) is the major component of the intraneuronal inclusions called Lewy bodies, which are the pathological hallmark of Parkinson's disease. α-Syn is capable of self-assembly into many different species, such as soluble oligomers and fibrils. Even though attempts to resolve the structures of the protein have been made, detailed understanding about the structures and their relationship with the different aggregation steps is lacking, which is of interest to provide insights into the pathogenic mechanism of Parkinson's disease. Here we report the structural flexibility of α-syn monomers and dimers in an aqueous solution environment as probed by single-molecule time-lapse high-speed AFM. In addition, we present the molecular basis for the structural transitions using discrete molecular dynamics (DMD) simulations. α-Syn monomers assume a globular conformation, which is capable of forming tail-like protrusions over dozens of seconds. Importantly, a globular monomer can adopt fully extended conformations. Dimers, on the other hand, are less dynamic and show a dumbbell conformation that experiences morphological changes over time. DMD simulations revealed that the α-syn monomer consists of several tightly packed small helices. The tail-like protrusions are also helical with a small β-sheet, acting as a "hinge". Monomers within dimers have a large interfacial interaction area and are stabilized by interactions in the non-amyloid central (NAC) regions. Furthermore, the dimer NAC-region of each α-syn monomer forms a β-rich segment. Moreover, NAC-regions are located in the hydrophobic core of the dimer.

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When a ribonucleic acid (RNA) molecule folds, it often does not adopt a single, well-defined conformation. The folding energy landscape of an RNA is highly dependent on its nucleotide sequence and molecular environment. Cellular molecules sometimes alter the energy landscape, thereby changing the ensemble of likely low-energy conformations. The effects of these energy landscape changes on the conformational ensemble are particularly challenging to visualize for large RNAs. We have created a robust approach for visualizing the conformational ensemble of RNAs that is well suited for in vitro versus in vivo comparisons. Our method creates a stable map of conformational space for a given RNA sequence. We first identify single point mutations in the RNA that maximally sample suboptimal conformational space based on the ensemble’s partition function. Then, we cluster these diverse ensembles to identify the most diverse partition functions for Boltzmann stochastic sampling. By using, to our knowledge, a novel nestedness distance metric, we iteratively add mutant suboptimal ensembles to converge on a stable 2D map of conformational space. We then compute the selective 2′ hydroxyl acylation by primer extension (SHAPE)-directed ensemble for the RNA folding under different conditions, and we project these ensembles on the map to visualize. To validate our approach, we established a conformational map of the Vibrio vulnificus add adenine riboswitch that reveals five classes of structures. In the presence of adenine, projection of the SHAPE-directed sampling correctly identified the on-conformation; without the ligand, only off-conformations were visualized. We also collected the whole-transcript in vitro and in vivo SHAPE-MaP for human β-actin messenger RNA that revealed similar global folds in both conditions. Nonetheless, a comparison of in vitro and in vivo data revealed that specific regions exhibited significantly different SHAPE-MaP profiles indicative of structural rearrangements, including rearrangement consistent with binding of the zipcode protein in a region distal to the stop codon.

RNAs fold into distinct molecular conformations that are often essential for their functions. Accurate structure modeling of complex RNA motifs, including ubiquitous non-canonical base pairs and pseudoknots, remains a challenge. Here, we present an NMR-guided all-atom discrete molecular dynamics (DMD) platform, iFoldNMR, for rapid and accurate structure modeling of complex RNAs. We show that sparse distance constraints from imino resonances, which can be readily obtained from routine NMR experiments and easier to compile than laborious assignments of non-solvent-exchangeable protons, are sufficient to direct a DMD search for low-energy RNA conformers. Benchmarking on a set of RNAs with complex folds spanning up to 56 nucleotides in length yields structural models that recapitulate experimentally determined structures with all-heavy-atom RMSDs ranging from 2.4 to 6.5 Å. This platform represents an efficient approach for high-throughput RNA structure modeling and will facilitate analysis of diverse, newly discovered functional RNAs.