Department of Chemistry, University of North Carolina, Chapel Hill, NC 27599-3290, USA.
Proc Natl Acad Sci U S A. 2013 Apr 2;110(14):5498-503. doi: 10.1073/pnas.1219988110. Epub 2013 Mar 15.
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.
当环中的核苷酸与闭合环的螺旋之外的区域配对时,RNA 中会形成假结。假结在 RNA 中相对较少见,但在大型催化 RNA 中的功能关键基序、核酶和病毒的调控元件中高度过表达。假结通常被排除在 RNA 结构预测算法之外。当包含这些配对时,由于允许这种结构会极大地增加可能的不正确折叠的数量,并且由于难以在折叠空间中搜索最优结构,因此很难准确地对其进行建模。我们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,以及一种简单但强大的用于单假结形成熵成本的能量模型。使用动态规划算法通过迭代细化来预测结构。这种融合的实验和热力学能量函数预测了一组 21 个具有挑战性的已知结构的 RNA 的二级结构和假结,这些 RNA 的大小从 34 到 530 个核苷酸不等。平均而言,预测出了 93%的已知碱基对,并且所有折叠良好的 RNA 中的假结都被识别出来。