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Abstract：
The rapid spread of COVID-19 is motivating development of antivirals targeting conserved SARS-CoV-2 molecular machinery. The SARS-CoV-2 genome includes conserved RNA elements that offer potential small-molecule drug targets, but most of their 3D structures have not been experimentally characterized. Here, we provide a compilation of chemical mapping data from our and other labs, secondary structure models, and 3D model ensembles based on Rosetta\'s FARFAR2 algorithm for SARS-CoV-2 RNA regions including the individual stems SL1-8 in the extended 5\' UTR; the reverse complement of the 5\' UTR SL1-4; the frameshift stimulating element (FSE); and the extended pseudoknot, hypervariable region, and s2m of the 3\' UTR. For eleven of these elements (the stems in SL1-8, reverse complement of SL1-4, FSE, s2m and 3\' UTR pseudoknot), modeling convergence supports the accuracy of predicted low energy states; subsequent cryo-EM characterization of the FSE confirms modeling accuracy. To aid efforts to discover small molecule RNA binders guided by computational models, we provide a second set of similarly prepared models for RNA riboswitches that bind small molecules. Both datasets (\'FARFAR2-SARS-CoV-2\', https://github.com/DasLab/FARFAR2-SARS-CoV-2; and \'FARFAR2-Apo-Riboswitch\', at https://github.com/DasLab/FARFAR2-Apo-Riboswitch\') include up to 400 models for each RNA element, which may facilitate drug discovery approaches targeting dynamic ensembles of RNA molecules.
摘要：
COVID-19的迅速传播正在推动靶向保守SARS-CoV-2分子机制的抗病毒药物的发展。SARS-CoV-2基因组包括保守的RNA元件，提供潜在的小分子药物靶标，但是他们的大部分3D结构还没有被实验表征。这里,我们提供了来自我们和其他实验室的化学绘图数据的汇编，二级结构模型，和基于Rosetta的FARFAR2算法的SARS-CoV-2RNA区域的3D模型集合，包括扩展的5'UTR中的单个茎SL1-8；5'UTRSL1-4的反向互补；移码刺激元件（FSE）；和扩展的假结，高变区，和3'UTR的s2m。对于这些元素中的11个(SL1-8中的茎，SL1-4的反向互补，FSE，s2m和3'UTR假结)，建模收敛支持预测的低能量状态的准确性;FSE的后续低温EM表征证实了建模的准确性。为了帮助努力发现由计算模型指导的小分子RNA结合剂，我们为结合小分子的RNA核糖开关提供了第二组类似制备的模型.两个数据集(“FARFAR2-SARS-CoV-2”，https://github.com/DasLab/FARFAR2-SARS-CoV-2;和\'FARFAR2-Apo-Riboswitch\',在https://github.com/DasLab/FARFAR2-Apo-Riboswitch\')为每个RNA元件包含多达400个模型，这可能有助于靶向RNA分子动态集合的药物发现方法。
