A generalizable scaffold-based approach for structure determination of RNAs by cryo-EM.

The close relationship between RNA structure and function underlines the significance of accurately predicting RNA structures from sequence information. Structural topologies such as pseudoknots are of particular interest due to their ubiquity and direct involvement in RNA function, but identifying pseudoknots is a computationally challenging problem and existing heuristic approaches usually perform poorly for RNA sequences of even a few hundred bases. We survey the performance of pseudoknot prediction methods on a data set of full-length RNA sequences representing varied sequence lengths, and biological RNA classes such as RNase P RNA, Group I Intron, tmRNA and tRNA. Pseudoknot prediction methods are compared with minimum free energy and suboptimal secondary structure prediction methods in terms of correct base-pairs, stems and pseudoknots and we find that the ensemble of suboptimal structure predictions succeeds in identifying correct structural elements in RNA that are usually missed in MFE and pseudoknot predictions. We propose a strategy to identify a comprehensive set of non-redundant stems in the suboptimal structure space of a RNA molecule by applying heuristics that reduce the structural redundancy of the predicted suboptimal structures by merging slightly varying stems that are predicted to form in local sequence regions. This reduced-redundancy set of structural elements consistently outperforms more specialized approaches.in data sets. Thus, the suboptimal folding space can be used to represent the structural diversity of an RNA molecule more comprehensively than optimal structure prediction approaches alone.

Untersuchungen zum Mechanismus der katalytischen Aktivierung von Spleißosomen aus Saccharomyces Cerevisiae

Characterizing hydrogen bonds in intact RNA from MS2 bacteriophage using magic angle spinning NMR

Bulges in nucleic acids

The dramatically increasing number of new protein sequences arising from genomics and proteomics requires the need for methods to rapidly and reliably infer the molecular and cellular functions of these proteins. One such approach, structural genomics, aims to delineate the total repertoire of protein folds in nature, thereby providing three-dimensional folding patterns for all proteins and to infer molecular functions of the proteins based on the combined information of structures and sequences. The goal of obtaining protein structures on a genomic scale has motivated the development of high throughput technologies and protocols for macromolecular structure determination that have begun to produce structures at a greater rate than previously possible. These new structures have revealed many unexpected functional inferences and evolutionary relationships that were hidden at the sequence level. Here, we present samples of structures determined at Berkeley Structural Genomics Center and collaborators' laboratories to illustrate how structural information provides and complements sequence information to deduce the functional inferences of proteins with unknown molecular functions. Two of the major premises of structural genomics are to discover a complete repertoire of protein folds in nature and to find molecular functions of the proteins whose functions are not predicted from sequence comparison alone. To achieve these objectives on a genomic scale, new methods, protocols, and technologies need to be developed by multi-institutional collaborations worldwide. As part of this effort, the Protein Structure Initiative has been launched in the United States (PSI; www.nigms.nih.gov/funding/psi.html). Although infrastructure building and technology development are still the main focus of structural genomics programs, a considerable number of protein structures have already been produced, some of them coming directly out of semiautomated structure determination pipelines. The Berkeley Structural Genomics Center (BSGC) has focused on the proteins of Mycoplasma or their homologues from other organisms as its structural genomics targets because of the minimal genome size of the Mycoplasmas as well as their relevance to human and animal pathogenicity (http://www.strgen.org). Here we present several protein examples encompassing a spectrum of functional inferences obtainable from their three-dimensional structures in five situations, where the inferences are new and testable, and are not predictable from protein sequence information alone.

Most currently known molecular structures were determined by X-ray crystallography or Nuclear Magnetic Resonance (NMR). These methods generate a large amount of structure data, even for small molecules, and consist mainly of three-dimensional atomic coordinates. These are useful for analyzing molecular structure, but structure elements at higher level are also needed for a complete understanding of structure, and especially for structure prediction. Computational approaches exist for identifying secondary structural elements in proteins from atomic coordinates. However, similar methods have not been developed for RNA, due in part to the very small amount of structure data so far available, and extracting the structural elements of RNA requires substantial manual work. Since the number of three-dimensional RNA structures is increasing, a more systematic and automated method is needed. We have developed a set of algorithms for recognizing secondary and tertiary structural elements in RNA molecules and in the protein-RNA structures in protein data banks (PDB). The algorithms were implemented in to a web-based program called PairAnalyzer. The present work represents the first attempt at extracting RNA structure elements from atomic coordinates in structure databases. The regularities in the structure elements revealed by the algorithms should provide useful information for predicting the structure of RNA molecules bound to proteins. PairAnalyzer is accessible at http://wilab.inha.ac.kr/PairAnalyzer/.

‘User-friendly’ primary phosphines and an arsine: synthesis and characterization of new air-stable ligands incorporating the ferrocenyl group

Recent technological breakthroughs in single-particle cryo-electron microscopy (cryo-EM) enable rapid atomic structure determination of biological macromolecules. A major bottleneck in the current single particle cryo-EM pipeline is the preparation of good quality frozen cryo-EM grids, which is mostly a trial-and-error process. Among many issues, preferred particle orientation and sample damage by air–water interface (AWI) are common practical problems. Here we report a method of applying metallo-supramolecular branched polymer (MSBP) in the cryo-sample preparation for high-resolution single-particle cryo-EM. Our data shows that MSBP keeps a majority of particles away from air–water interface and mitigates preferred orientation as verified by the analyses of apoferritin, hemagglutinin) trimer and various sample proteins. The use of MSBP is a simple method to improve particle distribution for high-resolution structure determination in single-particle cryo-EM.

The recently described Citrus viroid V (CVd-V) induces, in Etrog citron, mild stunting and very small necrotic lesions and cracks, sometimes filled with gum. As Etrog citron plants co-infected with Citrus dwarfing viroid (CDVd) and CVd-V show synergistic interactions, these host-viroid combinations provide a convenient model to identify the pathogenicity determinant(s). The biological effects of replacing limited portions of the rod-like structure of CVd-V with the corresponding portions of CDVd are reported. Chimeric constructs were synthesized using a novel polymerase chain reaction-based approach, much more flexible than those based on restriction enzymes used in previous studies. Of the seven chimeras (Ch) tested, only one (Ch5) proved to be infectious. Plants infected with Ch5 showed no symptoms and, although this novel chimera was able to replicate to relatively high titres in singly infected plants, it was rapidly displaced by either CVd-V or CDVd in doubly infected plants. The results demonstrate that direct interaction(s) between structural elements in the viroid RNA (in this case, the terminal left domain) and as yet unidentified host factors play an important role in modulating viroid pathogenicity. This is the first pathogenic determinant mapped in species of the genus Apscaviroid.

Single particle cryo-electron microscopy (cryo-EM) has matured into a robust method for the determination of biological macromolecule structures in the past decade, complementing X-ray crystallography and nuclear magnetic resonance. Constant methodological improvements in both cryo-EM hardware and image processing software continue to contribute to an exponential growth in the number of structures solved annually. In this review, we provide a historical view of the many steps that were required to make cryo-EM a successful method for the determination of high-resolution protein complex structures. We further discuss aspects of cryo-EM methodology that are the greatest pitfalls challenging successful structure determination to date. Lastly, we highlight and propose potential future developments that would improve the method even further in the near future.

The diversity of RNA structural elements and their documented role in human diseases make RNA an attractive therapeutic target. However, progress in drug discovery and development has been hindered by challenges in the determination of high-resolution RNA structures and a limited understanding of the parameters that drive RNA recognition by small molecules, including a lack of validated quantitative structure-activity relationships (QSAR). Herein, we developed QSAR models that quantitatively predict both thermodynamic and kinetic-based binding parameters of small molecules and the HIV-1 TAR model RNA system. A set of small molecules bearing diverse scaffolds was screened against the HIV-1-TAR construct using surface plasmon resonance, which provided the binding kinetics and affinities. The data was then analyzed using multiple linear regression (MLR) combined with feature selection to afford robust models for binding of diverse RNA-targeted scaffolds. The predictivity of the model was validated on untested small molecules. The QSAR models presented herein represent the first application of validated and predictive 2D-QSAR using multiple scaffolds against an RNA target. We expect the workflow to be generally applicable to other RNA structures, ultimately providing essential insight into the small molecule descriptors that drive selective binding interactions and, consequently, providing a platform that can exponentially increase the efficiency of ligand design and optimization without the need for high-resolution RNA structures.

Structure determination of clathrin coats to subnanometer resolution by single particle cryo-electron microscopy

In this work, we present a computational screen conducted for functional RNA structures, resulting in over 100,000 conserved RNA structure elements found in alignments of mouse (mm10) against 59 other vertebrates. We explicitly included masked repeat regions to explore the potential of transposable elements and low-complexity regions to give rise to regulatory RNA elements. In our analysis pipeline, we implemented a four-step procedure: (i) we screened genome-wide alignments for potential structure elements using RNAz-2, (ii) realigned and refined candidate loci with LocARNA-P, (iii) scored candidates again with RNAz-2 in structure alignment mode, and (iv) searched for additional homologous loci in mouse genome that were not covered by genome alignments. The 3’-untranslated regions (3’-UTRs) of protein-coding genes and small noncoding RNAs are enriched for structures, while coding sequences are depleted. Repeat-associated loci make up about 95% of the homologous loci identified and are, as expected, predominantly found in intronic and intergenic regions. Nevertheless, we report the structure elements enriched in specific genome elements, such as 3’-UTRs and long noncoding RNAs (lncRNAs). We provide full access to our results via a custom UCSC genome browser trackhub freely available on our website (http://rna.tbi.univie.ac.at/trackhubs/#RNAz).

In many single-stranded (ss) RNA viruses, the cis-acting packaging signal that confers selectivity genome packaging usually encompasses short structured RNA repeats. These structural units, termed repetitive structural motifs (RSMs), potentially mediate capsid assembly by specific RNA–protein interactions. However, general knowledge of the conservation and/or the diversity of RSMs in the positive-sense ssRNA coronaviruses (CoVs) is limited. By performing structural phylogenetic analysis, we identified a variety of RSMs in nearly all CoV genomic RNAs, which are exclusively located in the 5′-untranslated regions (UTRs) and/or in the inter-domain regions of poly-protein 1ab coding sequences in a lineage-specific manner. In all alpha- and beta-CoVs, except for Embecovirus spp, two to four copies of 5′-gUUYCGUc-3′ RSMs displaying conserved hexa-loop sequences were generally identified in Stem-loop 5 (SL5) located in the 5′-UTRs of genomic RNAs. In Embecovirus spp., however, two to eight copies of 5′-agc-3′/guAAu RSMs were found in the coding regions of non-structural protein (NSP) 3 and/or NSP15 in open reading frame (ORF) 1ab. In gamma- and delta-CoVs, other types of RSMs were found in several clustered structural elements in 5′-UTRs and/or ORF1ab. The identification of RSM-encompassing structural elements in all CoVs suggests that these RNA elements play fundamental roles in the life cycle of CoVs. In the recently emerged SARS-CoV-2, beta-CoV-specific RSMs are also found in its SL5, displaying two copies of 5′-gUUUCGUc-3′ motifs. However, multiple sequence alignment reveals that the majority of SARS-CoV-2 possesses a variant RSM harboring SL5b C241U, and intriguingly, several variations in the coding sequences of viral proteins, such as Nsp12 P323L, S protein D614G, and N protein R203K-G204R, are concurrently found with such variant RSM. In conclusion, the comprehensive exploration for RSMs reveals phylogenetic insights into the RNA structural elements in CoVs as a whole and provides a new perspective on variations currently found in SARS-CoV-2.

1] Determination of a transfer RNA structure by crystallographic method