DSSR: an integrated software tool for dissecting the spatial structure of RNA

By Xiang-Jun Lu, Harmen J. Bussemaker, Wilma K. Olson. Nucleic Acids Research, 2015

320 citations recorded by the source corpus.

Insight into the three-dimensional architecture of RNA is essential for understanding its cellular functions. However, even the classic transfer RNA structure contains features that are overlooked by existing bioinformatics tools. Here we present DSSR (Dissecting the Spatial Structure of RNA), an integrated and automated tool for analyzing and annotating RNA tertiary structures. The software identifies canonical and noncanonical base pairs, including those with modified nucleotides, in any tautomeric or protonation state. DSSR detects higher-order coplanar base associations, termed multiplets. It finds arrays of stacked pairs, classifies them by base-pair identity and backbone connectivity, and distinguishes a stem of covalently connected canonical pairs from a helix of stacked pairs of arbitrary type/linkage. DSSR identifies coaxial stacking of multiple stems within a single helix and lists isolated canonical pairs that lie outside of a stem. The program characterizes ‘closed’ loops of various types (hairpin, bulge, internal, and junction loops) and pseudoknots of arbitrary complexity. Notably, DSSR employs isolated pairs and the ends of stems, whether pseudoknotted or not, to define junction loops. This new, inclusive definition provides a novel perspective on the spatial organization of RNA. Tests on all nucleic acid structures in the Protein Data Bank confirm the efficiency and robustness of the software, and applications to representative RNA molecules illustrate its unique features. DSSR and related materials are freely available at http://x3dna.org/.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/34559129674dd79c60389908e4c4091096928446

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In Molecular Biology

1. Xiang-Jun Lu
2. Wilma K. Olson
3. Shuxiang Li
4. Padideh Danaee
5. M. Wiley
6. Liang Huang
7. Yanzhao Huang
8. Jun Wang

Citations in the corpus

• Integrating end-to-end learning with deep geometrical potentials for ab initio RNA structure prediction (2022, unknown): “Out of the 40 test targets, 15 contain pseudoknots as assigned by DSSR 31 .”
• 3dRNA v2.0: An Updated Web Server for RNA 3D Structure Prediction (2019, methodology): “The predicted structures are built from the sequence and secondary structure, while the former is obtained from their native structures fetched from PDB (https: // www.rcsb.org / ), and the latter is calculated from DSSR (Dissecting the Spatial Structure of RNA) [39].”
• bpRNA: large-scale automated annotation and analysis of RNA secondary structure (2018, background): “Previous work to parse RNA structural topology from base pairs does not handle pseudoknots (5) or only analyze tertiary structures (6).”
• Web 3DNA 2.0 for the analysis, visualization, and modeling of 3D nucleic acid structures (2019, methodology): “Over the years, we have continuously revised the algorithm for the identification of modified nucleotides and the list is no longer necessary (21).”