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Template-based prediction of RNA tertiary structure

Publication at Faculty of Mathematics and Physics |
2016

Abstract

RNA tertiary structure prediction approaches can be divided into two groups: de novo methods and template-based modeling. We present here a methodology for prediction of RNA three dimensional structure (target) utilizing a known structure of a related RNA molecule (template).

First, target and template sequences are aligned. Next, sequentially similar regions in the alignment are identified and corresponding substructures are transferred from template to target.

The remaining parts of the target structures are predicted using an external tool. This phase includes correct treatment of indels and valid linking of the transferred and predicted portions of the target structure.

Our proposed method is able to predict even large ribosomal RNA structures when sufficiently similar template is available. The experiments have shown that the main impact on the quality of prediction has the sequence similarity of the template and target and number of indels.

For structures with size of hundreds of nucleotides with sequence similarity with template over 50\% and ratio of indels up to 50\% the method is able to generate target structures up to ten RMSD with respect to the reference structure.