New in silico approach to assessing RNA secondary structures with non-canonical base pairs.
BACKGROUND
The function of RNA is strongly dependent on its structure, so an appropriate recognition of this structure, on every level of organization, is of great importance. One particular concern is the assessment of base-base interactions, described as the secondary structure, the knowledge of which greatly facilitates an interpretation of RNA function and allows for structure analysis on the tertiary level. The RNA secondary structure can be predicted from a sequence using in silico methods often adjusted with experimental data, or assessed from 3D structure atom coordinates. Computational approaches typically consider only canonical, Watson-Crick and wobble base pairs. Handling of non-canonical interactions, important for a full description of RNA structure, is still very difficult.


RESULTS
We introduce our novel approach to assessing an extended RNA secondary structure, which characterizes both canonical and non-canonical base pairs, along with their type classification. It is based on predicting the RNA 3D structure from a user-provided sequence or a secondary structure that only describes canonical base pairs, and then deriving the extended secondary structure from atom coordinates. In our example implementation, this was achieved by integrating the functionality of two fully automated, high fidelity methods in a computational pipeline: RNAComposer for the 3D RNA structure prediction and RNApdbee for base-pair annotation.


CONCLUSIONS
The presented methodology ties together existing applications for RNA 3D structure prediction and base-pair annotation. The example performance, applying RNAComposer and RNApdbee, reveals better accuracy in non-canonical base pair assessment than the compared methods that directly predict RNA secondary structure.
Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965, Poznan, Poland. arybarczyk@cs.put.poznan.pl.|Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704, Poznan, Poland. arybarczyk@cs.put.poznan.pl.
Agnieszka
A
Rybarczyk
Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965, Poznan, Poland. nszostak@cs.put.poznan.pl.
Natalia
N
Szostak
Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965, Poznan, Poland. mantczak@cs.put.poznan.pl.
Maciej
M
Antczak
Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965, Poznan, Poland. tzok@cs.put.poznan.pl.
Tomasz
T
Zok
Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704, Poznan, Poland. mariusz.popenda@ibch.poznan.pl.|European Center for Bioinformatics and Genomics, Poznan University of Technology, Piotrowo 2, 60-965, Poznan, Poland. mariusz.popenda@ibch.poznan.pl.
Mariusz
M
Popenda
Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704, Poznan, Poland. ryszard.adamiak@ibch.poznan.pl.|European Center for Bioinformatics and Genomics, Poznan University of Technology, Piotrowo 2, 60-965, Poznan, Poland. ryszard.adamiak@ibch.poznan.pl.
Ryszard
R
Adamiak
Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965, Poznan, Poland. jblazewicz@cs.put.poznan.pl.|Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704, Poznan, Poland. jblazewicz@cs.put.poznan.pl.
Jacek
J
Blazewicz
Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965, Poznan, Poland. mszachniuk@cs.put.poznan.pl.|Institute of Bioorganic Chemistry, Polish Academy of Sciences, Noskowskiego 12/14, 61-704, Poznan, Poland. mszachniuk@cs.put.poznan.pl.
Marta
M
Szachniuk
D020029:Base Pairing / Q000235:genetics*; D003198:Computer Simulation / Q000639:trends*; D017433:Protein Structure, Secondary; D012313:RNA / Q000737:chemistry / Q000235:genetics*
D012313:RNA