Department of Computer Science, University of Central Florida, Orlando, FL 32816, USA.
Nucleic Acids Res. 2021 Jun 21;49(11):e61. doi: 10.1093/nar/gkab131.
Understanding the 3D structural properties of RNAs will play a critical role in identifying their functional characteristics and designing new RNAs for RNA-based therapeutics and nanotechnology. While several existing computational methods can help in the analysis of RNA properties by recognizing structural motifs, they do not provide the means to compare and contrast those motifs extensively. We have developed a new method, RNAMotifContrast, which focuses on analyzing the similarities and variations of RNA structural motif characteristics. In this method, a graph is formed to represent the similarities among motifs, and a new traversal algorithm is applied to generate visualizations of their structural properties. Analyzing the structural features among motifs, we have recognized and generalized the concept of motif subfamilies. To asses its effectiveness, we have applied RNAMotifContrast on a dataset of known RNA structural motif families. From the results, we observed that the derived subfamilies possess unique structural variations while holding standard features of the families. Overall, the visualization approach of this method presents a new perspective to observe the relation among motifs more closely, and the discovered subfamilies provide opportunities to achieve valuable insights into RNA's diverse roles.
理解 RNA 的 3D 结构特性将在识别其功能特征和设计基于 RNA 的治疗和纳米技术的新 RNA 方面发挥关键作用。虽然现有的几种计算方法可以通过识别结构基序帮助分析 RNA 特性，但它们不能提供广泛比较和对比这些基序的手段。我们开发了一种新方法 RNAMotifContrast，它专注于分析 RNA 结构基序特征的相似性和变化。在这种方法中，形成一个图形来表示基序之间的相似性，并且应用新的遍历算法来生成它们结构属性的可视化。通过分析基序之间的结构特征，我们已经识别并概括了基序子家族的概念。为了评估其有效性，我们将 RNAMotifContrast 应用于已知 RNA 结构基序家族的数据集。从结果中，我们观察到衍生的子家族具有独特的结构变化，同时保持家族的标准特征。总的来说，该方法的可视化方法提供了一种新的视角来更密切地观察基序之间的关系，并且发现的子家族为深入了解 RNA 的多种作用提供了机会。
