Phan Ethan N H, Mak Chi H
Department of Chemistry.
Departments of Chemistry and Quantitative and Computational Biology, and Center of Applied Mathematical Sciences, University of Southern California, Los Angeles, California 90089, USA
RNA. 2024 Dec 16;31(1):14-31. doi: 10.1261/rna.080216.124.
Using a graph representation of RNA structures, we have studied the ensembles of secondary and tertiary graphs of two sets of RNA with Monte Carlo simulations. The first consisted of 91 target ribozyme and riboswitch sequences of moderate lengths (<150 nt) having a variety of secondary, H-type pseudoknots and kissing loop interactions. The second set consisted of 71 more diverse sequences across many RNA families. Using a simple empirical energy model for tertiary interactions and only sequence information for each target as input, the simulations examined how tertiary interactions impact the statistical mechanics of the fold ensembles. The results show that the graphs proliferate enormously when tertiary interactions are possible, producing an entropic driving force for the ensemble to access folds having tertiary structures even though they are overall energetically unfavorable in the energy model. For each of the targets in the two test sets, we assessed the quality of the model and the simulations by examining how well the simulated structures were able to predict the native fold, and compared the results to fold predictions from ViennaRNA. Our model generated good or excellent predictions in a large majority of the targets. Overall, this method was able to produce predictions of comparable quality to Vienna, but it outperformed Vienna for structures with H-type pseudoknots. The results suggest that while tertiary interactions are predicated on real-space contacts, their impacts on the folded structure of RNA can be captured by graph space information for sequences of moderate lengths, using a simple tertiary energy model for the loops, the base pairs, and base stacks.
利用RNA结构的图形表示，我们通过蒙特卡罗模拟研究了两组RNA的二级和三级图形集合。第一组由91个中等长度（<150个核苷酸）的靶标核酶和核糖开关序列组成，具有多种二级结构、H型假结和亲吻环相互作用。第二组由来自许多RNA家族的71个更多样化的序列组成。使用一个简单的三级相互作用经验能量模型，仅将每个靶标的序列信息作为输入，模拟研究了三级相互作用如何影响折叠集合的统计力学。结果表明，当三级相互作用可能时，图形会大量增殖，为集合产生一种熵驱动力，使其能够进入具有三级结构的折叠，尽管在能量模型中它们总体上在能量上是不利的。对于两个测试集中的每个靶标，我们通过检查模拟结构预测天然折叠的能力来评估模型和模拟的质量，并将结果与ViennaRNA的折叠预测进行比较。我们的模型在大多数靶标中产生了良好或优异的预测。总体而言，该方法能够产生与Vienna质量相当的预测，但对于具有H型假结的结构，它的表现优于Vienna。结果表明，虽然三级相互作用基于实空间接触，但对于中等长度的序列，使用一个简单的环、碱基对和碱基堆积的三级能量模型，它们对RNA折叠结构的影响可以通过图形空间信息来捕捉。
