CiTCOM, Cibles Thérapeutiques et conception de médicaments, UMR8038 CNRS, Université de PARIS, Paris, France.
Sanofi mRNA center of excellence 1541, Marcy-l'Etoile, France.
Methods Mol Biol. 2024;2726:85-104. doi: 10.1007/978-1-0716-3519-3_4.
The structure of RNA molecules and their complexes are crucial for understanding biology at the molecular level. Resolving these structures holds the key to understanding their manifold structure-mediated functions ranging from regulating gene expression to catalyzing biochemical processes. Predicting RNA secondary structure is a prerequisite and a key step to accurately model their three dimensional structure. Although dedicated modelling software are making fast and significant progresses, predicting an accurate secondary structure from the sequence remains a challenge. Their performance can be significantly improved by the incorporation of experimental RNA structure probing data. Many different chemical and enzymatic probes have been developed; however, only one set of quantitative data can be incorporated as constraints for computer-assisted modelling. IPANEMAP is a recent workflow based on RNAfold that can take into account several quantitative or qualitative data sets to model RNA secondary structure. This chapter details the methods for popular chemical probing (DMS, CMCT, SHAPE-CE, and SHAPE-Map) and the subsequent analysis and structure prediction using IPANEMAP.
RNA 分子及其复合物的结构对于理解分子水平的生物学至关重要。解析这些结构是理解其多种结构介导功能的关键，这些功能包括调节基因表达到催化生化过程。预测 RNA 二级结构是准确模拟其三维结构的前提和关键步骤。尽管专用建模软件正在快速取得重大进展，但从序列中准确预测二级结构仍然是一个挑战。通过纳入实验 RNA 结构探测数据，可以显著提高其性能。已经开发了许多不同的化学和酶探针，但只能将一组定量数据作为计算机辅助建模的约束条件纳入。IPANEMAP 是一种基于 RNAfold 的新工作流程，它可以考虑多个定量或定性数据集来模拟 RNA 二级结构。本章详细介绍了常用的化学探测方法（DMS、CMCT、SHAPE-CE 和 SHAPE-Map），以及使用 IPANEMAP 进行后续分析和结构预测的方法。
