ClaRNA: a classifier of contacts in RNA 3D structures based on a comparative analysis of various classification schemes

By Tomasz Waleń, Grzegorz Chojnowski, Przemysław Gierski, Janusz M. Bujnicki. 2014

48 citations recorded by the source corpus.

The understanding of folding and function of RNA molecules depends on the identification and classification of interactions between ribonucleotide residues. We developed a new method named ClaRNA for computational classification of contacts in RNA 3D structures. Unique features of the program are the ability to identify imperfect contacts and to process coarse-grained models. Each doublet of spatially close ribonucleotide residues in a query structure is compared to clusters of reference doublets obtained by analysis of a large number of experimentally determined RNA structures, and assigned a score that describes its similarity to one or more known types of contacts, including pairing, stacking, base–phosphate and base–ribose interactions. The accuracy of ClaRNA is 0.997 for canonical base pairs, 0.983 for non-canonical pairs and 0.961 for stacking interactions. The generalized squared correlation coefficient (GC2) for ClaRNA is 0.969 for canonical base pairs, 0.638 for non-canonical pairs and 0.824 for stacking interactions. The classifier can be easily extended to include new types of spatial relationships between pairs or larger assemblies of nucleotide residues. ClaRNA is freely available via a web server that includes an extensive set of tools for processing and visualizing structural information about RNA molecules.

Subfields: Molecular Biology

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Citations in the corpus

Assessment of three-dimensional RNA structure prediction in CASP15 (2023, positive): “INF scores were calculated from interaction predictions dependent on ClaRNA 34 ; (4) OpenStructure, 35,36 a framework used to find lDDT, a metric that measures structural similarity (unlike for proteins, our implementation of lDDT for RNA did not penalize for stereochemical violations); and (5)…”
RNA-Puzzles toolkit: a computational resource of RNA 3D structure benchmark datasets, structure manipulation, and evaluation tools (2019, methodology): “First, to perform contact classifications, we provide two wrappers, that are ClaRNA (28) and 3DNA / DSSR (57).”
New prediction categories in CASP15 (2023, methodology): “This is done using 2D structure annotators such as RNAView, 21 MC-Annotate, 22 ClaRNA 23 or FR3D, 24 which provide base pairs and their classification.”