MicroRNA Target Prediction Based Upon Metastable RNA Secondary Structures

摘要

In this work, we present RNAStrucTar, a miRNA target prediction tool that analyses putative mRNA binding sites within 3'UTR secondary structures representing metastable conformations. The first stage consists of generating conformations that can be classified as deep local minima. The second stage incorporates duplex structure prediction through sequence alignment and energy computation. Target site accessibility related to different sets of metastable conformations is also taken into account. An overall interaction score computed from multiple binding sites is returned. The approach is discussed in the context of single nucleotide polymorphisms (SNPs). We selected 20 instances of type [mRNA;SNP;miRNAj reported in recent literature where methods such as PCR and/or luciferase reporter assays are utilised. If the two main scores returned by RNAStrucTar are combined, 16 instances are correctly classified according to experimental findings from the literature, with two false classifications and two indifferent outcomes. When additionally combined with STarMir results (14 correct, but partly on different instances), then at least one of both methods supports the experimental findings on 18 instances, with one indifferent outcome and one prediction in favour of the experimentally established weaker binding.