Abstract
BackgroundMany functional RNA molecules fold into pseudoknot structures, which are often essential for the formation of an RNA’s 3D structure. Currently the design of RNA molecules, which fold into a specific structure (known as RNA inverse folding) within biotechnological applications, is lacking the feature of incorporating pseudoknot structures into the design. Hairpin-(H)- and kissing hairpin-(K)-type pseudoknots cover a wide range of biologically functional pseudoknots and can be represented on a secondary structure level.ResultsThe RNA inverse folding program antaRNA, which takes secondary structure, target GC-content and sequence constraints as input, is extended to provide solutions for such H- and K-type pseudoknotted secondary structure constraint.We demonstrate the easy and flexible interchangeability of modules within the antaRNA framework by incorporating pKiss as structure prediction tool capable of predicting the mentioned pseudoknot types. The performance of the approach is demonstrated on a subset of the Pseudobase ++ dataset.ConclusionsThis new service is available via a standalone version and is also part of the Freiburg RNA Tools webservice. Furthermore, antaRNA is available in Galaxy and is part of the RNA-workbench Docker image.
Highlights
Many functional RNA molecules fold into pseudoknot structures, which are often essential for the formation of an RNA’s 3D structure
Aptamers against virtually any larger cellular molecule or even complete cells can be identified by SELEX RNA enrichment [1, 2]
We present the extension of antaRNA for targeting pseudoknot structures
Summary
Structural Distance dstr Compared to the approach of MODENA, antaRNA (blue in Fig. 3c) usually predicts the structure with high accuracy, exhibiting only a small variation among the structure distances within the different pseudoknot categories. The structural distances of antaRNA display the growing complexities of the respective pseudoknot categories. With increasing structure complexity (H- to K-type), the upper quartiles of the distributions escalate to a dstr value of 1.5 % for B-type, 3 % for cH-type and about 7 % in the case of K-type structures. MODENA (yellow in Fig. 3c) shows for both predictors (hotknots and IPknot) dstr-medians between 5 % and 12 %. Hotknots performs better than IPknot, especially in the case of H- and K-type structures. No correlation of structure’s pseudoknot complexity and the resulting structural distance is visible
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