Peterson Jake M, O'Leary Collin A, Coppenbarger Evelyn C, Tompkins Van S, Moss Walter N
Roy J. Carver Department of Biophysics, Biochemistry and Molecular Biology, Iowa State University, Ames, IA 50011, USA.
MethodsX. 2023 Jun 29;11:102275. doi: 10.1016/j.mex.2023.102275. eCollection 2023 Dec.
Major advances in RNA secondary structural motif prediction have been achieved in the last few years; however, few methods harness the predictive power of multiple approaches to deliver in-depth characterizations of local RNA motifs and their potential functionality. Additionally, most available methods do not predict RNA pseudoknots. This work combines complementary bioinformatic systems into one robust discovery pipeline where: •RNA sequences are folded to search for thermodynamically favorable motifs utilizing ScanFold.•Motifs are expanded and refolded into alternate pseudoknot conformations by Knotty/Iterative HFold.•All conformations are evaluated for covariance via the cm-builder pipeline (Infernal and R-scape).
在过去几年中，RNA二级结构基序预测取得了重大进展；然而，很少有方法利用多种方法的预测能力来深入表征局部RNA基序及其潜在功能。此外，大多数现有方法都无法预测RNA假结。这项工作将互补的生物信息学系统整合到一个强大的发现流程中，其中：•利用ScanFold对RNA序列进行折叠，以搜索热力学上有利的基序。•通过Knotty/迭代HFold将基序扩展并重新折叠成交替的假结构象。•通过cm-builder流程（Infernal和R-scape）对所有构象进行协方差评估。
