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      RNA‐protein interactions in an unstructured context

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          Despite their importance, our understanding of noncovalent RNA–protein interactions is incomplete. This especially concerns the binding between RNA and unstructured protein regions, a widespread class of such interactions. Here, we review the recent experimental and computational work on RNA–protein interactions in an unstructured context with a particular focus on how such interactions may be shaped by the intrinsic interaction affinities between individual nucleobases and protein side chains. Specifically, we articulate the claim that the universal genetic code reflects the binding specificity between nucleobases and protein side chains and that, in turn, the code may be seen as the Rosetta stone for understanding RNA–protein interactions in general.

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          Most cited references 110

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          ViennaRNA Package 2.0

          Background Secondary structure forms an important intermediate level of description of nucleic acids that encapsulates the dominating part of the folding energy, is often well conserved in evolution, and is routinely used as a basis to explain experimental findings. Based on carefully measured thermodynamic parameters, exact dynamic programming algorithms can be used to compute ground states, base pairing probabilities, as well as thermodynamic properties. Results The ViennaRNA Package has been a widely used compilation of RNA secondary structure related computer programs for nearly two decades. Major changes in the structure of the standard energy model, the Turner 2004 parameters, the pervasive use of multi-core CPUs, and an increasing number of algorithmic variants prompted a major technical overhaul of both the underlying RNAlib and the interactive user programs. New features include an expanded repertoire of tools to assess RNA-RNA interactions and restricted ensembles of structures, additional output information such as centroid structures and maximum expected accuracy structures derived from base pairing probabilities, or z-scores for locally stable secondary structures, and support for input in fasta format. Updates were implemented without compromising the computational efficiency of the core algorithms and ensuring compatibility with earlier versions. Conclusions The ViennaRNA Package 2.0, supporting concurrent computations via OpenMP, can be downloaded from
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            Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure.

            An improved dynamic programming algorithm is reported for RNA secondary structure prediction by free energy minimization. Thermodynamic parameters for the stabilities of secondary structure motifs are revised to include expanded sequence dependence as revealed by recent experiments. Additional algorithmic improvements include reduced search time and storage for multibranch loop free energies and improved imposition of folding constraints. An extended database of 151,503 nt in 955 structures? determined by comparative sequence analysis was assembled to allow optimization of parameters not based on experiments and to test the accuracy of the algorithm. On average, the predicted lowest free energy structure contains 73 % of known base-pairs when domains of fewer than 700 nt are folded; this compares with 64 % accuracy for previous versions of the algorithm and parameters. For a given sequence, a set of 750 generated structures contains one structure that, on average, has 86 % of known base-pairs. Experimental constraints, derived from enzymatic and flavin mononucleotide cleavage, improve the accuracy of structure predictions. Copyright 1999 Academic Press.
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              IUPred: web server for the prediction of intrinsically unstructured regions of proteins based on estimated energy content.

              Intrinsically unstructured/disordered proteins and domains (IUPs) lack a well-defined three-dimensional structure under native conditions. The IUPred server presents a novel algorithm for predicting such regions from amino acid sequences by estimating their total pairwise interresidue interaction energy, based on the assumption that IUP sequences do not fold due to their inability to form sufficient stabilizing interresidue interactions. Optional to the prediction are built-in parameter sets optimized for predicting short or long disordered regions and structured domains.

                Author and article information

                FEBS Lett
                FEBS Lett
                Febs Letters
                John Wiley and Sons Inc. (Hoboken )
                21 June 2018
                September 2018
                : 592
                : 17 , Mirroring the multifaceted roles of RNA and its partners in gene expression ( doiID: 10.1002/feb2.2018.592.issue-17 )
                : 2901-2916
                [ 1 ] Department of Structural and Computational Biology Max F. Perutz Laboratories University of Vienna Austria
                [ 2 ] MM Shemyakin and Yu A Ovchinnikov Institute of Bioorganic Chemistry Russian Academy of Sciences Moscow Russia
                Author notes
                [* ] Correspondence

                B. Zagrovic, Department of Structural and Computational Biology, Max F. Perutz Laboratories, University of Vienna, Campus Vienna Biocenter 5, A‐1030 Vienna, Austria

                Fax: +43 1 4277 9522

                Tel: +43 1 4277 52271

                E‐mail: bojan.zagrovic@

                © 2018 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.

                This is an open access article under the terms of the License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                Page count
                Figures: 5, Tables: 0, Pages: 16, Words: 9913
                Funded by: European Research Council
                Award ID: 279408
                Funded by: Austrian Science Fund
                Award ID: 30680–B21
                Review Article
                Review Articles
                RNA biology
                Custom metadata
                September 2018
                Converter:WILEY_ML3GV2_TO_NLMPMC version:version=5.5.0 mode:remove_FC converted:08.10.2018


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