Article

Predicting kissing interactions in microRNA–target complex and assessment of microRNA activity

Department of Physics, University of Missouri, Columbia, MO 65211, USA.
Nucleic Acids Research (Impact Factor: 9.11). 02/2012; 40(10):4681-90. DOI: 10.1093/nar/gks052
Source: PubMed

ABSTRACT

MicroRNAs (miRNAs) are a class of short RNA molecules that play an important role in post-transcriptional gene regulation. Computational prediction of the miRNA target sites in mRNA is crucial for understanding the mechanism of miRNA-mRNA interactions. We here develop a new computational model that allows us to treat a variety of miRNA-mRNA kissing interactions, which have been ignored in the currently existing miRNA target prediction algorithms. By including all the different inter- and intra-molecular base pairs, this new model can predict both the structural accessibility of the target sites and the binding affinity (free energy). Applications of the model to a test set of 105 miRNA-gene systems show a notably improved success rate of 83/105. We found that although the binding affinity alone predicts the miRNA repression efficiency with a high success rate of 73/105, the structure in the seed region can significantly influence the miRNA activity. The method also allows us to efficiently search for the potent miRNA from a pool of miRNA candidates for any given gene target. Furthermore, extension of the method may enable predictions of the three-dimensional (3D) structures of miRNA/mRNA complexes.

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    • "Current computational methods to identify mRNA targets of miRNAs use rules based on primary and secondary structure information. Target prediction algorithms primarily consider conservation of sequence complementarity to miRNA seeds and miRNA–target duplex hybridization energies (e.g., PicTar [Krek et al. 2005; Lall et al. 2006] and TargetScan [Friedman et al. 2009]) and may incorporate additional features of mRNAs such as target site accessibility (e.g., PITA [Kertesz et al. 2007], mirWIP [Hammell et al. 2008], and Vfold [Cao and Chen 2012]). The common element of these algorithms is the presence of base-pair matches in the seed region—a 7-nt stretch starting at the first or second position from the 5 ′ end of the miRNA (Ambros 2004)—with base pairs in the 3 ′ region playing only a minor role in target selection. "
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