Institute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, Denmark.
Institute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, DenmarkInstitute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, DenmarkInstitute for Theoretical Chemistry and Research group BCB, Faculty of Computer Science, University of Vienna, Währinger Straße 17, 1090 Vienna, Austria, Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark, Department of Computer Science & IZBI & iDiv & LIFE, Härtelstraße 16-18, D-04107 University of Leipzig, Max Planck Institute for Mathematics in the Sciences and Fraunhofer Institute IZI, Leipzig, Germany, Santa Fe Institute, Santa Fe, NM 87501, USA and Department of Mathematics and Computer Science, University Of Southern Denmark, Odense, Denmark.
Bioinformatics. 2014 Jul 15;30(14):2009-17. doi: 10.1093/bioinformatics/btu156. Epub 2014 Mar 19.
RNA folding is a complicated kinetic process. The minimum free energy structure provides only a static view of the most stable conformational state of the system. It is insufficient to give detailed insights into the dynamic behavior of RNAs. A sufficiently sophisticated analysis of the folding free energy landscape, however, can provide the relevant information.
We introduce the Basin Hopping Graph (BHG) as a novel coarse-grained model of folding landscapes. Each vertex of the BHG is a local minimum, which represents the corresponding basin in the landscape. Its edges connect basins when the direct transitions between them are 'energetically favorable'. Edge weights endcode the corresponding saddle heights and thus measure the difficulties of these favorable transitions. BHGs can be approximated accurately and efficiently for RNA molecules well beyond the length range accessible to enumerative algorithms.
The algorithms described here are implemented in C++ as standalone programs. Its source code and supplemental material can be freely downloaded from http://www.tbi.univie.ac.at/bhg.html.
RNA 折叠是一个复杂的动力学过程。最小自由能结构仅提供系统最稳定构象状态的静态视图。它不足以详细了解 RNA 的动态行为。然而，对折叠自由能景观进行足够复杂的分析可以提供相关信息。
我们引入了 Basin Hopping Graph（BHG）作为一种新的折叠景观的粗粒度模型。BHG 的每个顶点都是一个局部最小值，代表景观中的相应盆地。当它们之间的直接跃迁“在能量上有利”时，其边连接盆地。边的权重编码相应的鞍点高度，从而衡量这些有利跃迁的难度。BHG 可以准确且高效地逼近 RNA 分子，超出可枚举算法可及的长度范围。
此处描述的算法用 C++实现为独立程序。其源代码和补充材料可从 http://www.tbi.univie.ac.at/bhg.html 自由下载。
