Department of Chemistry and Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, NY 10012, USA.
J Phys Condens Matter. 2010 Jul 21;22(28):283101. doi: 10.1088/0953-8984/22/28/283101. Epub 2010 Jun 15.
Many exciting discoveries have recently revealed the versatility of RNA and its importance in a variety of functions within the cell. Since the structural features of RNA are of major importance to their biological function, there is much interest in predicting RNA structure, either in free form or in interaction with various ligands, including proteins, metabolites and other molecules. In recent years, an increasing number of researchers have developed novel RNA algorithms for predicting RNA secondary and tertiary structures. In this review, we describe current experimental and computational advances and discuss recent ideas that are transforming the traditional view of RNA folding. To evaluate the performance of the most recent RNA 3D folding algorithms, we provide a comparative study in order to test the performance of available 3D structure prediction algorithms for an RNA data set of 43 structures of various lengths and motifs. We find that the algorithms vary widely in terms of prediction quality across different RNA lengths and topologies; most predictions have very large root mean square deviations from the experimental structure. We conclude by outlining some suggestions for future RNA folding research.
最近，许多令人兴奋的发现揭示了 RNA 的多功能性及其在细胞内各种功能中的重要性。由于 RNA 的结构特征对其生物学功能至关重要，因此人们对预测 RNA 结构（无论是在游离形式还是与各种配体（包括蛋白质、代谢物和其他分子）相互作用的形式）非常感兴趣。近年来，越来越多的研究人员开发了用于预测 RNA 二级和三级结构的新型 RNA 算法。在这篇综述中，我们描述了当前的实验和计算进展，并讨论了正在改变 RNA 折叠传统观点的最新思路。为了评估最新 RNA 3D 折叠算法的性能，我们进行了一项比较研究，以测试针对各种长度和模体的 43 个结构的 RNA 数据集的现有 3D 结构预测算法的性能。我们发现，这些算法在不同 RNA 长度和拓扑结构的预测质量方面存在很大差异；大多数预测与实验结构的均方根偏差非常大。最后，我们概述了对未来 RNA 折叠研究的一些建议。
