1,760 research outputs found

    Modeling RNA loops using sequence homology and geometric constraints

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    Summary: RNA loop regions are essential structural elements of RNA molecules influencing both their structural and functional properties. We developed RLooM, a web application for homology-based modeling of RNA loops utilizing template structures extracted from the PDB. RLooM allows the insertion and replacement of loop structures of a desired sequence into an existing RNA structure. Furthermore, a comprehensive database of loops in RNA structures can be accessed through the web interface

    Ab initio RNA folding

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    RNA molecules are essential cellular machines performing a wide variety of functions for which a specific three-dimensional structure is required. Over the last several years, experimental determination of RNA structures through X-ray crystallography and NMR seems to have reached a plateau in the number of structures resolved each year, but as more and more RNA sequences are being discovered, need for structure prediction tools to complement experimental data is strong. Theoretical approaches to RNA folding have been developed since the late nineties when the first algorithms for secondary structure prediction appeared. Over the last 10 years a number of prediction methods for 3D structures have been developed, first based on bioinformatics and data-mining, and more recently based on a coarse-grained physical representation of the systems. In this review we are going to present the challenges of RNA structure prediction and the main ideas behind bioinformatic approaches and physics-based approaches. We will focus on the description of the more recent physics-based phenomenological models and on how they are built to include the specificity of the interactions of RNA bases, whose role is critical in folding. Through examples from different models, we will point out the strengths of physics-based approaches, which are able not only to predict equilibrium structures, but also to investigate dynamical and thermodynamical behavior, and the open challenges to include more key interactions ruling RNA folding.Comment: 28 pages, 18 figure

    3D modeling of ribosomal RNA using cryo-electron microscopy density maps

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    Ribosomes are macromolecular protein-RNA complexes translating mRNA into protein. To date, crystal structures are available for the bacterial 30S and archaeal 50S subunits, as well as the complete bacterial 70S ribosomes. Eukaryotic ribosomes are much more complex in terms of ribosomal RNA and proteins. However, to date high-resolution crystal structures of eukaryotic ribosomes or ribosomal subunits are lacking. In order to build reliable models for the eukaryotic rRNA, we developed an approach for large scale homology and de novo modeling of RNA and subsequent exible tting into high-resolution cryo-EM density maps. Using this approach we built a model of the T. aestivum and the S. cerevisiae ribosome based on available cryo-EM maps at 5.5 Å and 6.1 Å resolution, respectively. The model comprises of 98% of the eukaryotic rRNA including all 21 RNA expansion segments (ES) and structurally six variable regions. Further, we were able to localize 74/80 (92.5%) of the ribosomal proteins. The model reveals unique ES-ES and r-protein-ES interactions, providing new insight into the structure and evolution of the eukaryotic ribosome. Moreover, the model was used for analyzing functional ribosomal complexes, i.e. the characterization of dierent nascent polypeptide chains within the ribosomal tunnel, intermediates of protein translocation as well as mRNA quality control

    Accelerated probabilistic inference of RNA structure evolution

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    BACKGROUND: Pairwise stochastic context-free grammars (Pair SCFGs) are powerful tools for evolutionary analysis of RNA, including simultaneous RNA sequence alignment and secondary structure prediction, but the associated algorithms are intensive in both CPU and memory usage. The same problem is faced by other RNA alignment-and-folding algorithms based on Sankoff's 1985 algorithm. It is therefore desirable to constrain such algorithms, by pre-processing the sequences and using this first pass to limit the range of structures and/or alignments that can be considered. RESULTS: We demonstrate how flexible classes of constraint can be imposed, greatly reducing the computational costs while maintaining a high quality of structural homology prediction. Any score-attributed context-free grammar (e.g. energy-based scoring schemes, or conditionally normalized Pair SCFGs) is amenable to this treatment. It is now possible to combine independent structural and alignment constraints of unprecedented general flexibility in Pair SCFG alignment algorithms. We outline several applications to the bioinformatics of RNA sequence and structure, including Waterman-Eggert N-best alignments and progressive multiple alignment. We evaluate the performance of the algorithm on test examples from the RFAM database. CONCLUSION: A program, Stemloc, that implements these algorithms for efficient RNA sequence alignment and structure prediction is available under the GNU General Public License
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