Department of Physics, University of Missouri, Columbia, MO 65211, USA.
Nucleic Acids Res. 2012 May;40(10):4681-90. doi: 10.1093/nar/gks052. Epub 2012 Feb 3.
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.
微小 RNA（miRNAs）是一类短 RNA 分子，在转录后基因调控中发挥着重要作用。计算预测 mRNA 中的 miRNA 靶位点对于理解 miRNA-mRNA 相互作用的机制至关重要。我们在这里开发了一种新的计算模型，该模型允许我们处理各种 miRNA-mRNA 亲吻相互作用，这些相互作用在当前现有的 miRNA 靶标预测算法中被忽略了。通过包括所有不同的分子内和分子间碱基对，这个新模型可以预测靶位点的结构可及性和结合亲和力（自由能）。该模型应用于 105 个 miRNA-基因系统的测试集，成功率显著提高，达到 83/105。我们发现，尽管单独的结合亲和力以 73/105 的高成功率预测了 miRNA 的抑制效率，但种子区域的结构可以显著影响 miRNA 的活性。该方法还允许我们从给定基因靶标的 miRNA 候选物池中有效地搜索有效 miRNA。此外，该方法的扩展可能能够预测 miRNA/mRNA 复合物的三维（3D）结构。
