Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8562, Japan and Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan.
Bioinformatics. 2013 Oct 15;29(20):2524-8. doi: 10.1093/bioinformatics/btt453. Epub 2013 Aug 9.
Understanding the details of protein-RNA interactions is important to reveal the functions of both the RNAs and the proteins. In these interactions, the secondary structures of the RNAs play an important role. Because RNA secondary structures in protein-RNA complexes are variable, considering the ensemble of RNA secondary structures is a useful approach. In particular, recent studies have supported the idea that, in the analysis of RNA secondary structures, the base-pairing probabilities (BPPs) of RNAs (i.e. the probabilities of forming a base pair in the ensemble of RNA secondary structures) provide richer and more robust information about the structures than a single RNA secondary structure, for example, the minimum free energy structure or a snapshot of structures in the Protein Data Bank. However, there has been no investigation of the BPPs in protein-RNA interactions.
In this study, we analyzed BPPs of RNA molecules involved in known protein-RNA complexes in the Protein Data Bank. Our analysis suggests that, in the tertiary structures, the BPPs (which are computed using only sequence information) for unpaired nucleotides with intermolecular hydrogen bonds (hbonds) to amino acids were significantly lower than those for unpaired nucleotides without hbonds. On the other hand, no difference was found between the BPPs for paired nucleotides with and without intermolecular hbonds. Those findings were commonly supported by three probabilistic models, which provide the ensemble of RNA secondary structures, including the McCaskill model based on Turner's free energy of secondary structures.
了解蛋白质 - RNA 相互作用的细节对于揭示 RNA 和蛋白质的功能非常重要。在这些相互作用中，RNA 的二级结构起着重要作用。由于蛋白质 - RNA 复合物中的 RNA 二级结构是可变的，因此考虑 RNA 二级结构的整体是一种有用的方法。特别是，最近的研究支持了这样一种观点，即在 RNA 二级结构的分析中，RNA 的碱基配对概率（BPP）（即在 RNA 二级结构整体中形成碱基对的概率）比单个 RNA 二级结构提供了更丰富和更稳健的结构信息，例如最小自由能结构或蛋白质数据银行中结构的快照。然而，目前还没有对蛋白质 - RNA 相互作用中的 BPP 进行研究。
在这项研究中，我们分析了蛋白质数据银行中已知蛋白质 - RNA 复合物中涉及的 RNA 分子的 BPP。我们的分析表明，在三级结构中，与氨基酸具有分子间氢键（hbonds）的未配对核苷酸的 BPP（仅使用序列信息计算）显着低于没有 hbonds 的未配对核苷酸的 BPP。另一方面，具有和不具有分子间 hbonds 的配对核苷酸的 BPP 之间没有差异。这三个概率模型普遍支持这些发现，这些模型提供了 RNA 二级结构的整体，包括基于 Turner 二级结构自由能的 McCaskill 模型。
