All-atom knowledge-based potential for RNA structure prediction and assessment
All-atom knowledge-based potential for RNA structure prediction and assessment
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DOI：
10.1093/bioinformatics/btr093
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发表时间：
2011-04-15
期刊：
影响因子：
5.8
通讯作者：
Melo, Francisco
中科院分区：
文献类型：
--
作者：
Capriotti, Emidio;Norambuena, Tomas;Melo, Francisco
动机：近年来，RNA仅仅作为信息传递分子的观点已经发生了巨大的变化。RNA的序列/结构/功能关系的研究变得越来越重要。作为一个直接的结果，实验解决的RNA结构的总数急剧增加，新的计算机工具预测RNA结构的序列正在迅速出现。因此，新的和准确的方法来评估RNA结构models.Results的准确性：在这里，我们引入了一个全原子的知识为基础的潜在的RNA三维（3D）结构的评估。我们已经对我们的新潜力进行了基准测试，称为核糖核酸统计潜力（RASP），具有由近天然RNA结构组成的两种不同的诱饵数据集。在其中一个基准测试中，RASP能够将最接近X射线结构的模型评为最佳模型，并分别将93%和95%的诱饵模型评为前10名模型。模型准确度（计算为C3'原子的均方根偏差和全局距离测试-总得分（GDT-TS）测量）与RASP得分之间的平均相关系数分别为0.85和0.89。基于最近发布的基准数据集，该数据集包含32个具有非规范碱基对的RNA基序的数百个3D模型，RASP评分函数在选择准确模型方面优于ROSETTA FARFAR力场。最后，使用丙型肝炎病毒内部核糖体进入位点的自剪接I组内含子和茎环IIIc作为测试案例，我们表明RASP能够区分已知的结构不稳定突变和补偿突变。
Motivation: Over the recent years, the vision that RNA simply serves as information transfer molecule has dramatically changed. The study of the sequence/structure/function relationships in RNA is becoming more important. As a direct consequence, the total number of experimentally solved RNA structures has dramatically increased and new computer tools for predicting RNA structure from sequence are rapidly emerging. Therefore, new and accurate methods for assessing the accuracy of RNA structure models are clearly needed.Results: Here, we introduce an all-atom knowledge-based potential for the assessment of RNA three-dimensional (3D) structures. We have benchmarked our new potential, called Ribonucleic Acids Statistical Potential (RASP), with two different decoy datasets composed of near-native RNA structures. In one of the benchmark sets, RASP was able to rank the closest model to the X-ray structure as the best and within the top 10 models for similar to 93 and similar to 95% of decoys, respectively. The average correlation coefficient between model accuracy, calculated as the root mean square deviation and global distance test-total score (GDT-TS) measures of C3' atoms, and the RASP score was 0.85 and 0.89, respectively. Based on a recently released benchmark dataset that contains hundreds of 3D models for 32 RNA motifs with non-canonical base pairs, RASP scoring function compared favorably to ROSETTA FARFAR force field in the selection of accurate models. Finally, using the self-splicing group I intron and the stem-loop IIIc from hepatitis C virus internal ribosome entry site as test cases, we show that RASP is able to discriminate between known structure-destabilizing mutations and compensatory mutations.