We introduce the SPlit-and-conQueR (SPQR) model, a coarse-grained (CG) representation of RNA designed for structure prediction and refinement. In our approach, the representation of a nucleotide consists of a point particle for the phosphate group and an anisotropic particle for the nucleoside. The interactions are, in principle, knowledge-based potentials inspired by the |$\mathcal {E}$|SCORE function, a base-centered scoring function. However, a special treatment is given to base-pairing interactions and certain geometrical conformations which are lost in a raw knowledge-based model. This results in a representation able to describe planar canonical and non-canonical base pairs and base–phosphate interactions and to distinguish sugar puckers and glycosidic torsion conformations. The model is applied to the folding of several structures, including duplexes with internal loops of non-canonical base pairs, tetraloops, junctions and a pseudoknot. For the majority of these systems, experimental structures are correctly predicted at the level of individual contacts. We also propose a method for efficiently reintroducing atomistic detail from the CG representation.

中文翻译：

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以核碱基为中心的粗粒表示法，用于RNA基序的结构预测

我们介绍了SPlit-and-conQueR（SPQR）模型，它是RNA的粗粒度（CG）表示形式，旨在用于结构预测和优化。在我们的方法中，核苷酸的表示由磷酸基团的点粒子和核苷的各向异性粒子组成。原则上，相互作用是受| $ \ mathcal {E} $ |启发的基于知识的潜力。SCORE函数，一个以基数为中心的评分函数。但是，对基于原始知识的模型中丢失的碱基对相互作用和某些几何构型进行了特殊处理。这导致能够描述平面规范和非规范碱基对以及碱基-磷酸盐相互作用，并区分糖折叠和糖苷扭转构象。该模型适用于几种结构的折叠，包括带有非规范碱基对的内部环，四环，结和假结的双链体。对于大多数这些系统，可以在单个接触点的水平上正确预测实验结构。我们还提出了一种有效地从CG表示中重新引入原子细节的方法。