Shapiro B A, Bengali D, Kasprzak W, Wu J C
Laboratory of Experimental and Computational Biology, NCI Center for Cancer Research, NCI-Frederick, National Institutes of Health, Building 469, Room 150, Frederick, MD 21702, USA.
J Mol Biol. 2001 Sep 7;312(1):27-44. doi: 10.1006/jmbi.2001.4931.
The massively parallel genetic algorithm (GA) for RNA structure prediction uses the concepts of mutation, recombination, and survival of the fittest to evolve a population of thousands of possible RNA structures toward a solution structure. As described below, the properties of the algorithm are ideally suited to use in the prediction of possible folding pathways and functional intermediates of RNA molecules given their sequences. Utilizing Stem Trace, an interactive visualization tool for RNA structure comparison, analysis of not only the solution ensembles developed by the algorithm, but also the stages of development of each of these solutions, can give strong insight into these folding pathways. The GA allows the incorporation of information from biological experiments, making it possible to test the influence of particular interactions between structural elements on the dynamics of the folding pathway. These methods are used to reveal the folding pathways of the potato spindle tuber viroid (PSTVd) and the host killing mechanism of Escherichia coli plasmid R1, both of which are successfully explored through the combination of the GA and Stem Trace. We also present novel intermediate folds of each molecule, which appear to be phylogenetically supported, as determined by use of the methods described below.
用于RNA结构预测的大规模并行遗传算法（GA）利用突变、重组和适者生存的概念，使数千种可能的RNA结构群体朝着一种解决方案结构进化。如下所述，鉴于RNA分子的序列，该算法的特性非常适合用于预测其可能的折叠途径和功能中间体。利用“茎迹”（Stem Trace）这一用于RNA结构比较的交互式可视化工具，不仅对算法开发的解决方案集合进行分析，而且对这些解决方案中每一个的发展阶段进行分析，能够深入了解这些折叠途径。遗传算法允许纳入来自生物学实验的信息，从而能够测试结构元件之间特定相互作用对折叠途径动力学的影响。这些方法用于揭示马铃薯纺锤块茎类病毒（PSTVd）的折叠途径以及大肠杆菌质粒R1的宿主杀伤机制，通过遗传算法和“茎迹”的结合，这两者均得以成功探究。我们还展示了每个分子新的中间折叠形式，如下文所述方法所确定，这些折叠形式似乎得到了系统发育的支持。
