Structure Prediction of RNA Loops with a Probabilistic Approach.
Structure Prediction of RNA Loops with a Probabilistic Approach.
复制标题
用概率方法预测 RNA 环的结构
DOI：
10.1371/journal.pcbi.1005032
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发表时间：
2016-08
影响因子：
4.3
通讯作者：
Wang W
中科院分区：
文献类型：
--
作者：
Li J;Zhang J;Wang J;Li W;Wang W
了解RNA环的三级结构对于理解它们的功能非常重要。在这项工作中，我们开发了一种名为RNApps的有效方法，专门用于预测RNA环的三级结构，包括发夹环，内环和多路连接环。它包括一个概率粗粒度RNA模型，一个全原子的统计能量函数，一个连续的蒙特卡罗增长算法，和一个模拟退火过程。该方法是测试与数据集，包括9个RNA环，23 S核糖体RNA，和一个大的数据集包含876个RNA。的性能进行了评估，并与同源建模为基础的预测和从头算预测。结果表明，RNApps具有与前者相当的性能，并在结构预测方面优于后者。该方法具有很大的希望，准确和有效的RNA三级结构预测。
The knowledge of the tertiary structure of RNA loops is important for understanding their functions. In this work we develop an efficient approach named RNApps, specifically designed for predicting the tertiary structure of RNA loops, including hairpin loops, internal loops, and multi-way junction loops. It includes a probabilistic coarse-grained RNA model, an all-atom statistical energy function, a sequential Monte Carlo growth algorithm, and a simulated annealing procedure. The approach is tested with a dataset including nine RNA loops, a 23S ribosomal RNA, and a large dataset containing 876 RNAs. The performance is evaluated and compared with a homology modeling based predictor and an ab initio predictor. It is found that RNApps has comparable performance with the former one and outdoes the latter in terms of structure predictions. The approach holds great promise for accurate and efficient RNA tertiary structure prediction.