Smit S, Knight R, Heringa J
Centre for Integrative Bioinformatics VU (IBIVU), Vrije Universiteit, 1081 HV Amsterdam, The Netherlands.
Nucleic Acids Res. 2009 Apr;37(5):1378-86. doi: 10.1093/nar/gkn987. Epub 2009 Jan 7.
Structural elements in RNA molecules have a distinct nucleotide composition, which changes gradually over evolutionary time. We discovered certain features of these compositional patterns that are shared between all RNA families. Based on this information, we developed a structure prediction method that evaluates candidate structures for a set of homologous RNAs on their ability to reproduce the patterns exhibited by biological structures. The method is named SPuNC for 'Structure Prediction using Nucleotide Composition'. In a performance test on a diverse set of RNA families we demonstrate that the SPuNC algorithm succeeds in selecting the most realistic structures in an ensemble. The average accuracy of top-scoring structures is significantly higher than the average accuracy of all ensemble members (improvements of more than 20% observed). In addition, a consensus structure that includes the most reliable base pairs gleaned from a set of top-scoring structures is generally more accurate than a consensus derived from the full structural ensemble. Our method achieves better accuracy than existing methods on several RNA families, including novel riboswitches and ribozymes. The results clearly show that nucleotide composition can be used to reveal the quality of RNA structures and thus the presented technique should be added to the set of prediction tools.
RNA分子中的结构元件具有独特的核苷酸组成，这种组成在进化过程中会逐渐变化。我们发现了所有RNA家族共有的这些组成模式的某些特征。基于这些信息，我们开发了一种结构预测方法，该方法根据一组同源RNA的候选结构重现生物结构所呈现模式的能力来评估它们。该方法名为SPuNC，即“利用核苷酸组成进行结构预测”。在对各种RNA家族进行的性能测试中，我们证明SPuNC算法成功地从一组结构中选择了最符合实际的结构。得分最高的结构的平均准确率显著高于所有结构成员的平均准确率（观察到提高了20%以上）。此外，包含从一组得分最高的结构中收集的最可靠碱基对的共有结构通常比从整个结构集合得出的共有结构更准确。我们的方法在包括新型核糖开关和核酶在内的几个RNA家族上比现有方法具有更高的准确率。结果清楚地表明，核苷酸组成可用于揭示RNA结构的质量，因此应将所提出的技术添加到预测工具集中。
