González Àlex L, Teixidó Jordi, Borrell José I, Estrada-Tejedor Roger
Grup d'Enginyeria Molecular (GEM), Institut Químic de Sarrià (IQS) - Universitat Ramon Llull (URL), Barcelona, Catalonia, 08017, Spain.
PLoS One. 2016 Mar 24;11(3):e0152049. doi: 10.1371/journal.pone.0152049. eCollection 2016.
Non-coding RNAs play a pivotal role in a number of diseases promoting an aberrant sequestration of nuclear RNA-binding proteins. In the particular case of myotonic dystrophy type 1 (DM1), a multisystemic autosomal dominant disease, the formation of large non-coding CUG repeats set up long-tract hairpins able to bind muscleblind-like proteins (MBNL), which trigger the deregulation of several splicing events such as cardiac troponin T (cTNT) and insulin receptor's, among others. Evidence suggests that conformational changes in RNA are determinant for the recognition and binding of splicing proteins, molecular modeling simulations can attempt to shed light on the structural diversity of CUG repeats and to understand their pathogenic mechanisms. Molecular dynamics (MD) are widely used to obtain accurate results at atomistic level, despite being very time consuming, and they contrast with fast but simplified coarse-grained methods such as Elastic Network Model (ENM). In this paper, we assess the application of ENM (traditionally applied on proteins) for studying the conformational space of CUG repeats and compare it to conventional and accelerated MD conformational sampling. Overall, the results provided here reveal that ANM can provide useful insights into dynamic rCUG structures at a global level, and that their dynamics depend on both backbone and nucleobase fluctuations. On the other hand, ANM fail to describe local U-U dynamics of the rCUG system, which require more computationally expensive methods such as MD. Given that several limitations are inherent to both methods, we discuss here the usefulness of the current theoretical approaches for studying highly dynamic RNA systems such as CUG trinucleotide repeat overexpansions.
非编码RNA在许多疾病中发挥着关键作用，促进了核RNA结合蛋白的异常隔离。在1型强直性肌营养不良症（DM1）这种多系统常染色体显性疾病的特殊情况下，大量非编码CUG重复序列的形成产生了能够结合肌肉盲样蛋白（MBNL）的长链发夹结构，这引发了多种剪接事件的失调，如心肌肌钙蛋白T（cTNT）和胰岛素受体等的剪接失调。有证据表明，RNA的构象变化对于剪接蛋白的识别和结合至关重要，分子建模模拟可以尝试阐明CUG重复序列的结构多样性并了解其致病机制。分子动力学（MD）尽管非常耗时，但被广泛用于在原子水平上获得准确结果，并且与快速但简化的粗粒度方法如弹性网络模型（ENM）形成对比。在本文中，我们评估了ENM（传统上应用于蛋白质）在研究CUG重复序列构象空间方面的应用，并将其与传统和加速的MD构象采样进行比较。总体而言，此处提供的结果表明，ANM可以在全局水平上为动态rCUG结构提供有用的见解，并且它们的动力学取决于主链和核碱基的波动。另一方面，ANM无法描述rCUG系统的局部U-U动力学，这需要更计算昂贵的方法如MD。鉴于这两种方法都存在一些固有的局限性，我们在此讨论当前理论方法对于研究高度动态的RNA系统如CUG三核苷酸重复序列过度扩增的有用性。
