(E) Helices are defined by stacking interactions of base pairs, regardless of pairing type (canonical or otherwise) or backbone connectivity (covalently connected or broken). Higher-order (three or more) co-planar base associations, termed multiplets, are also detected. This geometric algorithm can find canonical (Watson-Crick and G–U wobble) as well as non-canonical pairs.
(D) Base pairs are identified from the co-planarity of base rings and the occurrence of hydrogen bonds. (C) The standard base frame is derived from an idealized Watson-Crick base pair, and defines three base edges (Watson-Crick, minor groove, and Major groove) that are used to classify pairing interactions. (B) Bases are assigned a standard reference frame (25) that is independent of sequence identity: purines and pyrimidines are symmetrically placed with respect to the sugar. This method works for both the standard bases (A, C, G, T and U), and those of modified nucleotides, regardless of their tautomeric or protonation states. (A) Nucleotides are recognized using standard atom names and base planarity. It fills a gap in RNA structural bioinformatics, and is freely accessible (via the Jmol application or the JSmol-based website ).ĭefinitions of key nucleic acid structural components in DSSR. This seamless combination of DSSR and Jmol/JSmol brings the molecular graphics of 3D RNA structures to a similar level as that for proteins, and enables a much deeper analysis of structural characteristics. The DSSR web service accepts 3D coordinate files (in mmCIF or PDB format) initiated from a Jmol or JSmol session and returns DSSR-derived structural features in JSON format. The DSSR-Jmol integration presented here makes salient features of DSSR readily accessible, either via the Java-based Jmol application itself, or its HTML5-based equivalent, JSmol. JSmol, its reincarnation based on native JavaScript, has a predominant position in the post Java-applet era for web-based visualization of molecular structures. Jmol is a widely used, open-source Java viewer for 3D structures, with a powerful scripting language. It calculates a comprehensive and unique set of features for characterizing RNA, as well as DNA structures. DSSR (Dissecting the Spatial Structure of RNA) is an integrated and automated command-line tool for the analysis and annotation of RNA tertiary structures. However, the field of RNA structural bioinformatics is still lagging behind for example, current molecular graphics tools lack built-in support even for base pairs, double helices, or hairpin loops. For proteins, secondary structural components are routinely featured in molecular graphics visualizations. Sophisticated and interactive visualizations are essential for making sense of the intricate 3D structures of macromolecules.
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