Limits in accuracy and a strategy of RNA structure prediction using experimental information.

RNA structural complexity and flexibility present a challenge for computational modeling efforts. Experimental information and bioinformatics data can be used as restraints to improve the accuracy of RNA tertiary structure prediction. Regarding utilization of restraints, the fundamental questions are: (i) What is the limit in prediction accuracy that one can achieve with arbitrary number of restraints? (ii) Is there a strategy for selection of the minimal number of restraints that would result in the best structural model? We address the first question by testing the limits in prediction accuracy using native contacts as restraints. To address the second question, we develop an algorithm based on the distance variation allowed by secondary structure (DVASS), which ranks restraints according to their importance to RNA tertiary structure prediction. We find that due to kinetic traps, the greatest improvement in the structure prediction accuracy is achieved when we utilize only 40-60% of the total number of native contacts as restraints. When the restraints are sorted by DVASS algorithm, using only the first 20% ranked restraints can greatly improve the prediction accuracy. Our findings suggest that only a limited number of strategically selected distance restraints can significantly assist in RNA structure modeling.

High-speed atomic force microscopy reveals structural dynamics of α-synuclein monomers and dimers.

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 ß-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 ß-rich segment. Moreover, NAC-regions are located in the hydrophobic core of the dimer.

Structure modeling of RNA using sparse NMR constraints.

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.

Molecular Mechanisms of the R61T Mutation in Apolipoprotein E4: A Dynamic Rescue.

The apolipoprotein E4 (ApoE4) gene is the strongest genetic risk factor for Alzheimer's disease (AD). With respect to the other common isoforms of this protein (ApoE2 and ApoE3), ApoE4 is characterized by lower stability that underlies the formation of a stable interaction between the protein's N- and C-terminal domains. AD-related cellular dysfunctions have been linked to this ApoE4 misfolded state. In this regard, it has been reported that the mutation R61T is able to rescue the deleterious cellular effects of ApoE4 by preventing the formation of the misfolded intermediate state. However, a clear description of the structural features at the basis of the R61T-ApoE4 mutant's protective effect is still missing. Recently, using extensive molecular dynamics simulations, we have identified a structural model of an ApoE4 misfolded intermediate state. Building on our previous work, here we explore the dynamical changes induced by the R61T mutation in the ApoE4 native and misfolded states. Notably, we do not observe any local changes in the domains in the R61T-ApoE4 system, rather a general loss of correlated movements in the entire protein structure. More specifically, we detect increased dynamics in the hinge region, which is essential for ApoE4 domain-domain interaction. Consistent with previously reported data on altered phospholipid and receptor binding, we hypothesize that mutations destabilizing the ApoE4 intermediate state change hinge region dynamics, which propagates to distal functional regions of the protein and modifies ApoE4's functional properties. This unique behavior of the ApoE4 hinge region provides, to our knowledge, a novel understanding of ApoE4's role in AD.

An excited state underlies gene regulation of a transcriptional riboswitch.

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, which activates 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 responses 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.

Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo.

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 ß-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.

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/.

ApoE4-specific Misfolded Intermediate Identified by Molecular Dynamics Simulations.

The increased risk of developing Alzheimer's disease (AD) is associated with the APOE gene, which encodes for three variants of Apolipoprotein E, namely E2, E3, E4, differing only by two amino acids at positions 112 and 158. ApoE4 is known to be the strongest risk factor for AD onset, while ApoE3 and ApoE2 are considered to be the AD-neutral and AD-protective isoforms, respectively. It has been hypothesized that the ApoE isoforms may contribute to the development of AD by modifying the homeostasis of ApoE physiological partners and AD-related proteins in an isoform-specific fashion. Here we find that, despite the high sequence similarity among the three ApoE variants, only ApoE4 exhibits a misfolded intermediate state characterized by isoform-specific domain-domain interactions in molecular dynamics simulations. The existence of an ApoE4-specific intermediate state can contribute to the onset of AD by altering multiple cellular pathways involved in ApoE-dependent lipid transport efficiency or in AD-related protein aggregation and clearance. We present what we believe to be the first structural model of an ApoE4 misfolded intermediate state, which may serve to elucidate the molecular mechanism underlying the role of ApoE4 in AD pathogenesis. The knowledge of the structure for the ApoE4 folding intermediate provides a new platform for the rational design of alternative therapeutic strategies to fight AD.