Principles for Predicting RNA Secondary Structure Design Difficulty.
Principles for Predicting RNA Secondary Structure Design Difficulty.
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DOI：
10.1016/j.jmb.2015.11.013
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发表时间：
2016-02-27
影响因子：
5.6
通讯作者：
Eterna Players
中科院分区：
文献类型：
--
作者：
Anderson-Lee J;Fisker E;Kosaraju V;Wu M;Kong J;Lee J;Lee M;Zada M;Treuille A;Das R;Eterna Players
设计形成特定二级结构的RNA，通过RNA引导的沉默、基因组编辑和蛋白质组织，能够更好地理解和控制生命系统。然而，关于哪些RNA二级结构可能易于下游序列设计，由于低效的二级结构选择，增加了设计工作的时间和费用，目前知之甚少。在这里，我们提出了对特定结构特征的见解，这些特征增加了寻找折叠成靶RNA二级结构的序列的难度，总结了Eterna大规模开放实验室中数万名人类参与者和三种自动化算法（RNAInverse，INFO-RNA和RNA-SSD）的设计工作。随后通过三种独立的RNA设计算法（NUPACK，DSS-Opt，MODENA）进行的测试证实了几个特征在确定设计难度方面的假设重要性，包括序列长度，平均茎长，对称性和特定的难以设计的基序，如锯齿形。基于这些结果，我们编制了一个包含100个二级结构设计挑战的Eterna 100基准测试，这些挑战跨越了很大的设计难度范围，以帮助测试未来的工作。我们的计算机模拟结果提出了新的途径，用于改进计算RNA设计方法，并将这些见解扩展到评估单个RNA结构的“可设计性”以及体外和体内应用的开关。
Designing RNAs that form specific secondary structures is enabling better understanding and control of living systems through RNA-guided silencing, genome editing and protein organization. Little is known, however, about which RNA secondary structures might be tractable for downstream sequence design, increasing the time and expense of design efforts due to inefficient secondary structure choices. Here, we present insights into specific structural features that increase the difficulty of finding sequences that fold into a target RNA secondary structure, summarizing the design efforts of tens of thousands of human participants and three automated algorithms (RNAInverse, INFO-RNA and RNA-SSD) in the Eterna massive open laboratory. Subsequent tests through three independent RNA design algorithms (NUPACK, DSS-Opt, MODENA) confirmed the hypothesized importance of several features in determining design difficulty, including sequence length, mean stem length, symmetry, and specific difficult-to-design motifs like zig-zags. Based on these results, we have compiled an Eterna100 benchmark of 100 secondary structure design challenges that span a large range in design difficulty to help test future efforts. Our in silico results suggest new routes for improving computational RNA design methods and for extending these insights to assessing “designability” of single RNA structures as well as of switches for in vitro and in vivo applications.