Center for Computational Natural Sciences and Bioinformatics, International Institute of Information Technology, Gachibowli, Hyderabad, Telangana 500032, India.
Computational Biochemistry Laboratory, Department of Chemistry and Centre for Advanced Studies in Chemistry, Panjab University, Chandigarh 160014, India.
J Chem Inf Model. 2021 Mar 22;61(3):1470-1480. doi: 10.1021/acs.jcim.0c01225. Epub 2021 Feb 11.
The astonishing diversity in folding patterns of RNA three-dimensional (3D) structures is crafted by myriads of noncovalent contacts, of which base pairing and stacking are the most prominent. A systematic and comprehensive classification and annotation of these interactions is necessary for a molecular-level understanding of their roles. However, unlike in the case of base pairing, where a widely accepted nomenclature and classification scheme exists in the public domain, currently available classification schemes for base-base stacking need major enhancements to comprehensively capture the necessary features underlying the rich stacking diversity in RNA. Here, we extend the previous stacking classification based on nucleobase interacting faces by introducing a structurally intuitive geometry-cum topology-based scheme. Specifically, a stack is first classified in terms of the geometry described by the relative orientation of the glycosidic bonds, which generates eight basic stacking geometric families for heterodimeric stacks and six of those for homodimeric stacks. Further annotation in terms of the identity of the bases and the region of involvement of purines (five-membered, six-membered, or both rings) leads to the enumeration of 384 distinct RNA base stacks. Based on our classification scheme, we present an algorithm for automated identification of stacks in RNA crystal structures and analyze the stacking context in selected RNA structures. Overall, the work described here is expected to greatly facilitate the structure-based RNA research.
RNA 三维（3D）结构折叠模式的惊人多样性是由无数非共价相互作用形成的，其中碱基配对和堆积是最突出的。为了从分子水平理解这些相互作用的作用，对这些相互作用进行系统和全面的分类和注释是必要的。然而，与碱基配对不同，碱基配对在公共领域存在广泛接受的命名法和分类方案，目前可用的碱基堆积分类方案需要进行重大改进，以全面捕捉 RNA 中丰富堆积多样性所必需的特征。在这里，我们通过引入基于结构直观的几何形状和拓扑的方案，扩展了以前基于核碱基相互作用面的堆积分类。具体来说，首先根据糖苷键的相对取向描述的几何形状对堆积进行分类，这为杂二聚体堆积生成了八个基本堆积几何家族，为同二聚体堆积生成了其中六个。进一步根据碱基的身份和嘌呤（五元环、六元环或两者都有）的参与区域进行注释，导致枚举了 384 种不同的 RNA 碱基堆积。基于我们的分类方案，我们提出了一种用于自动识别 RNA 晶体结构中堆积的算法，并分析了选定 RNA 结构中的堆积上下文。总的来说，这里描述的工作有望极大地促进基于结构的 RNA 研究。
