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RNAfitme: a webserver for modeling nucleobase and nucleoside residue conformation in fixed-backbone RNA structures

Authors :
Maciej Antczak
Tomasz Zok
Maciej Osowiecki
Mariusz Popenda
Ryszard W. Adamiak
Marta Szachniuk
Source :
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-11 (2018)
Publication Year :
2018
Publisher :
BMC, 2018.

Abstract

Abstract Background Computational RNA 3D structure prediction and modeling are rising as complementary approaches to high-resolution experimental techniques for structure determination. They often apply to substitute or complement them. Recently, researchers’ interests have directed towards in silico methods to fit, remodel and refine RNA tertiary structure models. Their power lies in a problem-specific exploration of RNA conformational space and efficient optimization procedures. The aim is to improve the accuracy of models obtained either computationally or experimentally. Results Here, we present RNAfitme, a versatile webserver tool for remodeling of nucleobase- and nucleoside residue conformations in the fixed-backbone RNA 3D structures. Our approach makes use of dedicated libraries that define RNA conformational space. They have been built upon torsional angle characteristics of PDB-deposited RNA structures. RNAfitme can be applied to reconstruct full-atom model of RNA from its backbone; remodel user-selected nucleobase/nucleoside residues in a given RNA structure; predict RNA 3D structure based on the sequence and the template of a homologous molecule of the same size; refine RNA 3D model by reducing steric clashes indicated during structure quality assessment. RNAfitme is a publicly available tool with an intuitive interface. It is freely accessible at http://rnafitme.cs.put.poznan.pl/ Conclusions RNAfitme has been applied in various RNA 3D remodeling scenarios for several types of input data. Computational experiments proved its efficiency, accuracy, and usefulness in the processing of RNAs of any size. Fidelity of RNAfitme predictions has been thoroughly tested for RNA 3D structures determined experimentally and modeled in silico.

Details

Language :
English
ISSN :
14712105
Volume :
19
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Bioinformatics
Publication Type :
Academic Journal
Accession number :
edsdoj.7477060bad8d4e9681d2bb08e0a453dc
Document Type :
article
Full Text :
https://doi.org/10.1186/s12859-018-2317-9