Extracting stacking interaction parameters for RNA from the data set of native structures
Extracting stacking interaction parameters for RNA from the data set of native structures
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DOI：
10.1016/j.jmb.2004.12.012
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发表时间：
2005-03-18
影响因子：
5.6
通讯作者：
Thirumalai, D
中科院分区：
文献类型：
--
作者：
Dima, RI;Hyeon, C;Thirumalai, D
确定RNA三维天然结构的关键一步是预测它们的二级结构，这些二级结构是稳定的，不依赖于三级褶皱。二级结构的准确预测需要对相互作用参数进行上下文相关的估计。我们利用蛋白质数据库（PDB）中不断增长的天然折叠RNA结构数据库，使用基于知识的方法获得堆叠相互作用参数。值得注意的是，所得统计电位（SPs）的计算值与使用小寡核苷酸测量确定的参数非常一致。我们通过使用ViennaRNA包在结构数据集中预测74%的碱基对来验证SPs。有趣的是，这个数字与使用测量的热力学参数得到的数字相似。我们还通过使用无间隙穿线测试了SP在预测二级结构方面的有效性，我们提倡使用无间隙穿线作为快速预测RNA结构的替代方法。对于少于700个核苷酸的RNA分子，大约70%的天然碱基对被正确预测。作为SPs的进一步验证，我们计算了z分数，它衡量了相对于多种更高自由能态的自然状态的相对稳定性。计算出的z分数与使用量热法测量的一些RNA分子的估计值一致。采用结构分析方法对SP和实验确定的参数的成败进行了合理化分析。首先，从原生碱基对数量与序列长度之间近乎完美的线性关系来看，我们发现近46%的核苷酸不是堆叠的。其次，通过分析在无间隙穿线中产生的次优结构，我们证明了SPs和实验确定的参数在预测以发夹结尾的堆叠方面是最成功的。这些结果表明，二级结构预测的进一步改进需要可靠地估计环路、凸起和不以发夹结尾的堆的相互作用参数。(C) 2005 Elsevier Ltd版权所有。
A crucial step in the determination of the three-dimensional native structures of RNA is the prediction of their secondary structures, which are stable independent of the tertiary fold. Accurate prediction of the secondary structure requires context-dependent estimates of the interaction parameters. We have exploited the growing database of natively folded RNA structures in the Protein Data Bank (PDB) to obtain stacking interaction parameters using a knowledge-based approach. Remarkably, the calculated values of the resulting statistical potentials (SPs) are in excellent agreement with the parameters determined using measurements in small oligonucleotides. We validate the SPs by predicting 74% of the base-pairs in a dataset of structures using the ViennaRNA package. Interestingly, this number is similar to that obtained using the measured thermodynamic parameters. We also tested the efficacy of the SP in predicting secondary structure by using gapless threading, which we advocate as an alternative method for rapidly predicting RNA structures. For RNA molecules with less than 700 nucleotides, about 70% of the native base-pairs are correctly predicted. As a further validation of the SPs we calculated Z-scores, which measure the relative stability of the native state with respect to a manifold of higher free energy states. The computed Z-scores agree with estimates made using calorimetric measurements for a few RNA molecules. Structural analysis was used to rationalize the success and failures of SP and experimentally determined parameters. First, from the near perfect linear relationship between the number of native base-pairs and sequence length, we show that nearly 46% of nucleotides are not in stacks. Second, by analyzing the suboptimal structures that are generated in gapless threading we show that the SPs and experimentally determined parameters are most successful in predicting stacks that end in hairpins. These results show that further improvement in secondary structure prediction requires reliable estimates of interaction parameters for loops, bulges, and stacks that do not end in hairpins. (C) 2005 Elsevier Ltd. All rights reserved.