The role of nucleobase interactions in RNA structure and dynamics.
The role of nucleobase interactions in RNA structure and dynamics.
复制标题
DOI：
10.1093/nar/gku972
复制
发表时间：
2014-12-01
影响因子：
14.9
通讯作者：
Bussi G
中科院分区：
文献类型：
--
作者：
Bottaro S;Di Palma F;Bussi G
RNA 三维结构中观察到的复杂相互作用网络通常用多种几何特性来描述，包括螺旋参数、碱基配对/堆积、氢键和主链构象。我们证明，由每个核苷酸一个定向珠组成的简单分子表示可以解释 RNA 的基本结构特性。在此框架中，可以在明确定义的交互外壳内明确识别规范的 Watson-Crick、非 Watson-Crick 碱基配对和碱基堆叠相互作用。我们通过执行两个独立的、互补的测试来验证这种表示。首先，我们使用它构建了一个与序列无关、基于知识的 RNA 结构预测评分函数，该函数与完全原子论的最先进技术相比具有优势。其次，我们定义了一个度量来测量 RNA 结构之间的偏差，该偏差直接报告碱基-碱基相互作用网络的差异。该指标的有效性是针对区分结构和动力学上遥远的 RNA 构象的能力进行测试的，与标准技术相比，性能更好。总而言之，我们的结果表明，这种以核碱基为中心的极简表示捕获了与描述 RNA 结构和动力学相关的主要相互作用。
The intricate network of interactions observed in RNA three-dimensional structures is often described in terms of a multitude of geometrical properties, including helical parameters, base pairing/stacking, hydrogen bonding and backbone conformation. We show that a simple molecular representation consisting in one oriented bead per nucleotide can account for the fundamental structural properties of RNA. In this framework, canonical Watson-Crick, non-Watson-Crick base-pairing and base-stacking interactions can be unambiguously identified within a well-defined interaction shell. We validate this representation by performing two independent, complementary tests. First, we use it to construct a sequence-independent, knowledge-based scoring function for RNA structural prediction, which compares favorably to fully atomistic, state-of-the-art techniques. Second, we define a metric to measure deviation between RNA structures that directly reports on the differences in the base–base interaction network. The effectiveness of this metric is tested with respect to the ability to discriminate between structurally and kinetically distant RNA conformations, performing better compared to standard techniques. Taken together, our results suggest that this minimalist, nucleobase-centric representation captures the main interactions that are relevant for describing RNA structure and dynamics.
登录
查看更多内容
影响因子：
14.9
作者：
Apostolico A;Ciriello G;Guerra C;Heitsch CE;Hsiao C;Williams LD
通讯作者：
Williams LD
DOI：
10.1093/bioinformatics/btp250
发表时间：
2009-08-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Darty K;Denise A;Ponty Y
通讯作者：
Ponty Y
影响因子：
3.4
作者：
Fogolari, F;Esposito, G;Cattarinussi, S
通讯作者：
Cattarinussi, S
影响因子：
4.5
作者：
Ding, Feng;Sharma, Shantanu;Dokholyan, Nikolay V.
通讯作者：
Dokholyan, Nikolay V.
影响因子：
3.3
作者：
Denesyuk, Natalia A.;Thirumalai, D.
通讯作者：
Thirumalai, D.