Poster abstracts
Poster number 5 submitted by Sri Appasamy
Choosing representatives for Equivalence Classes of RNA structures and development of new visualization features for RNA 3D structure annotation and analysis
Sri D. Appasamy (Department of Biological Sciences, Bowling Green State University), Blake Sweeney (European Bioinformatics Institute), Jamie J. Cannone (Center for Computational Biology and Bioinformatics, University of Texas at Austin), Craig L. Zirbel (Department of Mathematics and Statistics, Bowling Green State University), Neocles B. Leontis (Department of Chemistry, Bowling Green State University)
Abstract:
The number and diversity of new RNA structures deposited in the Protein Data Bank (PDB) is rapidly increasing in response to interest generated by discoveries of new functional roles for RNA molecules. Mining the new structures for novel RNA folds, 3D motifs, and protein interactions requires identifying the best structures for each distinct RNA, but presently PDB provides no filtering mechanism to help users. In collaboration with Nucleic Acid Database (NDB), we have developed an automated, weekly pipeline to compare all RNA chains from each PDB file, group them by sequence and geometry in “Equivalence Classes” (EC), and select high-quality representatives for each EC to populate reduced-redundancy “representative” sets of RNA 3D structures (http://rna.bgsu.edu/rna3dhub/nrlist), useful for searching and RNA 3D motif extraction. We have improved the selection methods to provide greater stability and take advantage of multiple quality data, including structure completeness, resolution, clash scores, and Real Space Refinement (RSR) statistics.
We are integrating new visualizations on our website (http://rna.bgsu.edu). Heat maps have been added to display structural similarity within each EC group. Annotated pairwise interactions and RSR values can be visualized on 2D structures for selected molecules. Several new features will be made available to the interactive molecule viewer in our web applications; i) displaying steric clashes in the 3D motifs, ii) displaying variable extent of neighboring regions based on distance entered by the user, and iii) coloring 3D motifs by different criteria (e.g. chain, CPK, structure quality indicators such as Real Space Refinement statistics). Specific examples will be given to show the utility of the different visualization features for facilitating the annotation and analysis of RNA 3D motifs.
Keywords: Equivalence classes, RNA 3D motifs