Optimization of a novel biophysical model using large scale in vivo antisense hybridization data displays improved prediction capabilities of structurally accessible RNA regions.

Abstract:

:Current approaches to design efficient antisense RNAs (asRNAs) rely primarily on a thermodynamic understanding of RNA-RNA interactions. However, these approaches depend on structure predictions and have limited accuracy, arguably due to overlooking important cellular environment factors. In this work, we develop a biophysical model to describe asRNA-RNA hybridization that incorporates in vivo factors using large-scale experimental hybridization data for three model RNAs: a group I intron, CsrB and a tRNA. A unique element of our model is the estimation of the availability of the target region to interact with a given asRNA using a differential entropic consideration of suboptimal structures. We showcase the utility of this model by evaluating its prediction capabilities in four additional RNAs: a group II intron, Spinach II, 2-MS2 binding domain and glgC 5΄ UTR. Additionally, we demonstrate the applicability of this approach to other bacterial species by predicting sRNA-mRNA binding regions in two newly discovered, though uncharacterized, regulatory RNAs.

journal_name

Nucleic Acids Res

journal_title

Nucleic acids research

authors

Vazquez-Anderson J,Mihailovic MK,Baldridge KC,Reyes KG,Haning K,Cho SH,Amador P,Powell WB,Contreras LM

doi

10.1093/nar/gkx115

subject

Has Abstract

pub_date

2017-05-19 00:00:00

pages

5523-5538

issue

9

eissn

0305-1048

issn

1362-4962

pii

3038235

journal_volume

45

pub_type

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