Kim Oanh T P, Yura Kei, Go Nobuhiro
Quantum Bioinformatics Team, Center for Computational Science and Engineering, Japan Atomic Energy Agency, Kizu-cho, Souraku-gun, Kyoto 619-0215, Japan.
Nucleic Acids Res. 2006;34(22):6450-60. doi: 10.1093/nar/gkl819. Epub 2006 Nov 27.
Protein-RNA interactions play essential roles in a number of regulatory mechanisms for gene expression such as RNA splicing, transport, translation and post-transcriptional control. As the number of available protein-RNA complex 3D structures has increased, it is now possible to statistically examine protein-RNA interactions based on 3D structures. We performed computational analyses of 86 representative protein-RNA complexes retrieved from the Protein Data Bank. Interface residue propensity, a measure of the relative importance of different amino acid residues in the RNA interface, was calculated for each amino acid residue type (residue singlet interface propensity). In addition to the residue singlet propensity, we introduce a new residue-based propensity, which gives a measure of residue pairing preferences in the RNA interface of a protein (residue doublet interface propensity). The residue doublet interface propensity contains much more information than the sum of two singlet propensities alone. The prediction of the RNA interface using the two types of propensities plus a position-specific multiple sequence profile can achieve a specificity of about 80%. The prediction method was then applied to the 3D structure of two mRNA export factors, TAP (Mex67) and UAP56 (Sub2). The prediction enables us to point out candidate RNA interfaces, part of which are consistent with previous experimental studies and may contribute to elucidation of atomic mechanisms of mRNA export.
蛋白质 - RNA相互作用在基因表达的多种调控机制中发挥着重要作用,如RNA剪接、转运、翻译和转录后调控。随着可用的蛋白质 - RNA复合物三维结构数量的增加,现在有可能基于三维结构对蛋白质 - RNA相互作用进行统计学研究。我们对从蛋白质数据库中检索到的86个代表性蛋白质 - RNA复合物进行了计算分析。计算了每种氨基酸残基类型的界面残基倾向(一种衡量RNA界面中不同氨基酸残基相对重要性的指标,即残基单重态界面倾向)。除了残基单重态倾向外,我们还引入了一种新的基于残基的倾向,它衡量了蛋白质RNA界面中残基配对偏好(残基双重态界面倾向)。残基双重态界面倾向所包含的信息比仅两个单重态倾向的总和要多得多。使用这两种倾向加上位置特异性多序列谱来预测RNA界面,特异性可达约80%。然后将该预测方法应用于两种mRNA输出因子TAP(Mex67)和UAP56(Sub2)的三维结构。该预测使我们能够指出候选RNA界面,其中部分与先前的实验研究一致,可能有助于阐明mRNA输出的原子机制。