Department of Physics, Williams College, Williamstown, Massachusetts 01257, USA.
RNA. 2010 Jul;16(7):1350-5. doi: 10.1261/rna.1831710. Epub 2010 May 26.
The reliability of RNA secondary structure predictions is subject to the accuracy of the underlying free energy model. Mfold and other RNA folding algorithms are based on the Turner model, whose weakest part is its formulation of loop free energies, particularly for multibranch loops. RNA loops contain single-strand and helix-crossing segments, so we develop an enhanced two-length freely jointed chain theory and revise it for self-avoidance. Our resulting universal formula for RNA loop entropy has fewer parameters than the Turner/Mfold model, and yet simulations show that the standard errors for multibranch loop free energies are reduced by an order of magnitude. We further note that coaxial stacking decreases the effective length of multibranch loops and provides, surprisingly, an entropic stabilization of the ordered configuration in addition to the enthalpic contribution of helix stacking. Our formula is in good agreement with measured hairpin free energies. We find that it also improves the accuracy of folding predictions.
RNA 二级结构预测的可靠性取决于基础自由能模型的准确性。Mfold 和其他 RNA 折叠算法基于 Turner 模型,该模型的最薄弱环节在于其环自由能的表述,特别是对于多分支环。RNA 环包含单链和螺旋交叉片段,因此我们开发了一种增强的双长度自由连接链理论,并对其进行了自我回避修正。我们得到的 RNA 环熵通用公式比 Turner/Mfold 模型具有更少的参数,但模拟表明,多分支环自由能的标准误差降低了一个数量级。我们进一步指出,同轴堆积减少了多分支环的有效长度,并出人意料地提供了有序构象的熵稳定,除了螺旋堆积的焓贡献之外。我们的公式与测量的发夹自由能吻合良好。我们发现它还可以提高折叠预测的准确性。