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Incorporating global features of RNA motifs in predictions for an ensemble of secondary structures for encapsidated MS2 bacteriophage RNA

机译:结合RNA基序的整体特征预测衣壳化的MS2噬菌体RNA的二级结构的整体

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摘要

The secondary structure of encapsidated MS2 genomic RNA poses an interesting RNA folding challenge. Cryoelectron microscopy has demonstrated that encapsidated MS2 RNA is well-ordered. Models of MS2 assembly suggest that the RNA hairpin–protein interactions and the appropriate placement of hairpins in the MS2 RNA secondary structure can guide the formation of the correct icosahedral particle. The RNA hairpin motif that is recognized by the MS2 capsid protein dimers, however, is energetically unfavorable, and thus free energy predictions are biased against this motif. Computer programs called Crumple, Sliding Windows, and Assembly provide useful tools for prediction of viral RNA secondary structures when the traditional assumptions of RNA structure prediction by free energy minimization may not apply. These methods allow incorporation of global features of the RNA fold and motifs that are difficult to include directly in minimum free energy predictions. For example, with MS2 RNA the experimental data from SELEX experiments, crystallography, and theoretical calculations of the path for the series of hairpins can be incorporated in the RNA structure prediction, and thus the influence of free energy considerations can be modulated. This approach thoroughly explores conformational space and generates an ensemble of secondary structures. The predictions from this new approach can test hypotheses and models of viral assembly and guide construction of complete three-dimensional models of virus particles.
机译:衣壳化的MS2基因组RNA的二级结构构成了有趣的RNA折叠挑战。低温电子显微镜已证明,衣壳化的MS2 RNA是有序的。 MS2组装模型表明,RNA发夹-蛋白质相互作用以及发夹在MS2 RNA二级结构中的适当放置可以指导正确的二十面体颗粒的形成。但是,MS2衣壳蛋白二聚体识别的RNA发夹基序在能量上不利,因此自由能预测与此基序有偏差。当通过自由能最小化预测RNA结构的传统假设可能不适用时,称为Crumple,Sliding Windows和Assembly的计算机程序会提供有用的工具来预测病毒RNA二级结构。这些方法可以整合难以直接包含在最小自由能预测中的RNA折叠和基序的整体特征。例如,使用MS2 RNA,可以将来自SELEX实验,晶体学和一系列发夹路径的理论计算的实验数据纳入RNA结构预测中,从而可以调节自由能因素的影响。这种方法彻底探索了构象空间并生成了二级结构的集合。这种新方法的预测可以检验病毒装配的假设和模型,并指导构建完整的病毒颗粒三维模型。

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