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Accurate SHAPE-directed RNA secondary structure modeling including pseudoknots

机译:精确的SHAPE导向RNA二级结构建模包括假结

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摘要

A pseudoknot forms in an RNA when nucleotides in a loop pair with a region outside the helices that close the loop. Pseudoknots occur relatively rarely in RNA but are highly overrepresented in functionally critical motifs in large catalytic RNAs, in riboswitches, and in regulatory elements of viruses. Pseudoknots are usually excluded from RNA structure prediction algorithms. When included, these pairings are difficult to model accurately, especially in large RNAs, because allowing this structure dramatically increases the number of possible incorrect folds and because it is difficult to search the fold space for an optimal structure. We have developed a concise secondary structure modeling approach that combines SHAPE (selective 2′-hydroxyl acylation analyzed by primer extension) experimental chemical probing information and a simple, but robust, energy model for the entropic cost of single pseudoknot formation. Structures are predicted with iterative refinement, using a dynamic programming algorithm. This melded experimental and thermodynamic energy function predicted the secondary structures and the pseudoknots for a set of 21 challenging RNAs of known structure ranging in size from 34 to 530 nt. On average, 93% of known base pairs were predicted, and all pseudoknots in well-folded RNAs were identified.
机译:当环中的核苷酸与封闭环的螺旋外区域配对时,RNA中会形成假结。假结在RNA中相对很少出现,但在大型催化RNA,核糖开关和病毒的调控元件中的功能关键性基序中高度过量表达。假结通常从RNA结构预测算法中排除。如果包含这些配对,则很难准确建模,尤其是在大型RNA中,这是因为允许这种结构极大地增加了可能的不正确折叠的数量,并且因为很难在折叠空间中寻找最佳结构。我们已经开发了一种简洁的二级结构建模方法,该方法结合了SHAPE(通过引物延伸分析的选择性2'-羟基酰化)实验化学探测信息和简单但可靠的能量模型,可用于单个假结形成的熵成本。使用动态编程算法,通过迭代精炼来预测结构。这种融合的实验和热力学能量函数预测了已知结构的21个具有挑战性的RNA的集合的二级结构和假结,其大小从34到530 nt不等。平均而言,可以预测93%的已知碱基对,并且可以识别折叠良好的RNA中的所有假结。

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