BACKGROUND Computational models of RNA 3D structure often present various inaccuracies caused by simplifications used in structure prediction methods, such as template-based modeling or coarse-grained simulations. To obtain a high-quality model, the preliminary RNA structural model needs to be refined, taking into account atomic interactions. The goal of the refinement is not only to improve the local quality of the model but to bring it globally closer to the true structure. RESULTS We present QRNAS, a software tool for fine-grained refinement of nucleic acid structures, which is an extension of the AMBER simulation method with additional restraints. QRNAS is capable of handling RNA, DNA, chimeras, and hybrids thereof, and enables modeling of nucleic acids containing modified residues. CONCLUSIONS We demonstrate the ability of QRNAS to improve the quality of models generated with different methods. QRNAS was able to improve MolProbity scores of NMR structures, as well as of computational models generated in the course of the RNA-Puzzles experiment. The overall geometry improvement may be associated with increased model accuracy, especially on the level of correctly modeled base-pairs, but the systematic improvement of root mean square deviation to the reference structure should not be expected. The method has been integrated into a computational modeling workflow, enabling improved RNA 3D structure prediction.

中文翻译：

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QRNAS：用于精炼核酸结构的软件工具。

背景技术RNA 3D结构的计算模型经常呈现由结构预测方法（例如基于模板的建模或粗粒度模拟）中使用的简化引起的各种不准确性。为了获得高质量的模型，需要完善初步的 RNA 结构模型，同时考虑原子相互作用。细化的目标不仅是提高模型的局部质量，而且是使其在全局上更接近真实结构。结果我们提出了 QRNAS，一种用于细粒度细化核酸结构的软件工具，它是 AMBER 模拟方法的扩展，具有额外的限制。QRNAS 能够处理 RNA、DNA、嵌合体及其杂交体，并能够对含有修饰残基的核酸进行建模。结论 我们证明了 QRNAS 提高用不同方法生成的模型质量的能力。QRNAS 能够提高 NMR 结构以及 RNA-Puzzles 实验过程中生成的计算模型的 MolProbity 分数。整体几何形状的改进可能与模型精度的提高有关，特别是在正确建模的碱基对的水平上，但不应期望参考结构的均方根偏差的系统改进。该方法已集成到计算建模工作流程中，从而改进了 RNA 3D 结构预测。