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The role of nucleobase interactions in RNA structure and dynamics
, 2014
"... The intricate network of interactions observed in RNA three-dimensional structures is often described in terms of a multitude of geometrical properties, including helical parameters, base pairing/stacking, hydrogen bonding and backbone conformation. We show that a simple molecular representation con ..."
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The intricate network of interactions observed in RNA three-dimensional structures is often described in terms of a multitude of geometrical properties, including helical parameters, base pairing/stacking, hydrogen bonding and backbone conformation. We show that a simple molecular representation con-sisting in one oriented bead per nucleotide can ac-count for the fundamental structural properties of RNA. In this framework, canonical Watson-Crick, non-Watson-Crick base-pairing and base-stacking interactions can be unambiguously identified within a well-defined interaction shell. We validate this rep-resentation by performing two independent, com-plementary tests. First, we use it to construct a sequence-independent, knowledge-based scoring function for RNA structural prediction, which com-pares favorably to fully atomistic, state-of-the-art techniques. Second, we define a metric to measure deviation between RNA structures that directly re-ports on the differences in the base–base interaction network. The effectiveness of this metric is tested with respect to the ability to discriminate between structurally and kinetically distant RNA conforma-tions, performing better compared to standard tech-niques. Taken together, our results suggest that this minimalist, nucleobase-centric representation cap-tures the main interactions that are relevant for de-scribing RNA structure and dynamics.
doi:10.1155/2012/103132 Research Article Computer-Based Annotation of Putative AraC/XylS-Family Transcription Factors of Known Structure but Unknown Function
"... Copyright © 2012 Andreas Schüller et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Currently, about 20 crystal structures per d ..."
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Copyright © 2012 Andreas Schüller et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Currently, about 20 crystal structures per day are released and deposited in the Protein Data Bank. A significant fraction of these structures is produced by research groups associated with the structural genomics consortium. The biological function of many of these proteins is generally unknown or not validated by experiment. Therefore, a growing need for functional prediction of protein structures has emerged. Here we present an integrated bioinformatics method that combines sequence-based relationships and three-dimensional (3D) structural similarity of transcriptional regulators with computer prediction of their cognate DNA binding sequences. We applied this method to the AraC/XylS family of transcription factors, which is a large family of transcriptional regulators found in many bacteria controlling the expression of genes involved in diverse biological functions. Three putative new members of this family with known 3D structure but unknown function were identified for which a probable functional classification is provided. Our bioinformatics analyses suggest that they could be involved in plant cell wall degradation (Lin2118 protein from Listeria innocua, PDB code 3oou), symbiotic nitrogen fixation (protein from Chromobacterium violaceum,PDBcode
3dRNAscore: a distance and torsion angle dependent evaluation function of 3D RNA structures
, 2014
"... Model evaluation is a necessary step for bet-ter prediction and design of 3D RNA structures. For proteins, this has been widely studied and the knowledge-based statistical potential has been proved to be one of effective ways to solve this problem. Currently, a few knowledge-based statis-tical poten ..."
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Model evaluation is a necessary step for bet-ter prediction and design of 3D RNA structures. For proteins, this has been widely studied and the knowledge-based statistical potential has been proved to be one of effective ways to solve this problem. Currently, a few knowledge-based statis-tical potentials have also been proposed to eval-uate predicted models of RNA tertiary structures. The benchmark tests showed that they can iden-tify the native structures effectively but further im-provements are needed to identify near-native struc-tures and those with non-canonical base pairs. Here, we present a novel knowledge-based potential, 3dR-NAscore, which combines distance-dependent and dihedral-dependent energies. The benchmarks on different testing datasets all show that 3dRNAscore are more efficient than existing evaluation methods in recognizing native state from a pool of near-native states of RNAs as well as in ranking near-native states of RNA models.
Structural bioinformatics Advance Access publication August 7, 2013 WebRASP: a server for computing energy scores to assess the accuracy and stability of RNA 3D structures
, 2013
"... Summary: The understanding of the biological role of RNA molecules has changed. Although it is widely accepted that RNAs play important regulatory roles without necessarily coding for proteins, the functions of many of these non-coding RNAs are unknown. Thus, determining or modeling the 3D structure ..."
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Summary: The understanding of the biological role of RNA molecules has changed. Although it is widely accepted that RNAs play important regulatory roles without necessarily coding for proteins, the functions of many of these non-coding RNAs are unknown. Thus, determining or modeling the 3D structure of RNA molecules as well as assessing their accuracy and stability has become of great importance for character-izing their functional activity. Here, we introduce a new web applica-tion, WebRASP, that uses knowledge-based potentials for scoring RNA structures based on distance-dependent pairwise atomic inter-actions. This web server allows the users to upload a structure in PDB format, select several options to visualize the structure and calculate the energy profile. The server contains online help, tutorials and links to other related resources. We believe this server will be a useful tool for predicting and assessing the quality of RNA 3D structures. Availability and implementation: The web server is available at
