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使用分子力学技术对大型RNA和核糖核蛋白颗粒进行建模。

Modeling large RNAs and ribonucleoprotein particles using molecular mechanics techniques.

作者信息

Malhotra A, Tan R K, Harvey S C

机构信息

Department of Biochemistry and Molecular Genetics, University of Alabama at Birmingham 35294.

出版信息

Biophys J. 1994 Jun;66(6):1777-95. doi: 10.1016/S0006-3495(94)80972-5.

Abstract

There is a growing body of low-resolution structural data that can be utilized to devise structural models for large RNAs and ribonucleoproteins. These models are routinely built manually. We introduce an automated refinement protocol to utilize such data for building low-resolution three-dimensional models using the tools of molecular mechanics. In addition to specifying the positions of each nucleotide, the protocol provides quantitative estimates of the uncertainties in those positions, i.e., the resolution of the model. In typical applications, the resolution of the models is about 10-20 A. Our method uses reduced representations and allows us to refine three-dimensional structures of systems as big as the 16S and 23S ribosomal RNAs, which are about one to two orders of magnitude larger than nucleic acids that can be examined by traditional all-atom modeling methods. Nonatomic resolution structural data--secondary structure, chemical cross-links, chemical and enzymatic footprinting patterns, protein positions, solvent accessibility, and so on--are combined with known motifs in RNA structure to predict low-resolution models of large RNAs. These structural constraints are imposed on the RNA chain using molecular mechanics-type potential functions with parameters based on the quality of experimental data. Surface potential functions are used to incorporate shape and positional data from electron microscopy image reconstruction experiments into our models. The structures are optimized using techniques of energy refinement to get RNA folding patterns. In addition to providing a consensus model, the method finds the range of models consistent with the data, which allows quantitative evaluation of the resolution of the model. The method also identifies conflicts in the experimental data. Although our protocol is aimed at much larger RNAs, we illustrate these techniques using the tRNA structure as an example and test-bed.

摘要

越来越多的低分辨率结构数据可用于构建大型RNA和核糖核蛋白的结构模型。这些模型通常是手动构建的。我们引入了一种自动优化协议,利用这些数据,借助分子力学工具构建低分辨率三维模型。除了指定每个核苷酸的位置外,该协议还提供这些位置不确定性的定量估计,即模型的分辨率。在典型应用中,模型的分辨率约为10 - 20埃。我们的方法使用简化表示,使我们能够优化像16S和23S核糖体RNA那么大的系统的三维结构,这些结构比传统全原子建模方法可研究的核酸大约大一个到两个数量级。非原子分辨率的结构数据——二级结构、化学交联、化学和酶足迹模式、蛋白质位置、溶剂可及性等等——与RNA结构中的已知基序相结合,以预测大型RNA的低分辨率模型。利用基于实验数据质量的参数的分子力学型势函数,将这些结构约束施加于RNA链上。表面势函数用于将电子显微镜图像重建实验中的形状和位置数据纳入我们的模型。通过能量优化技术对结构进行优化,以获得RNA折叠模式。除了提供一个共识模型外,该方法还能找到与数据一致的模型范围,从而对模型的分辨率进行定量评估。该方法还能识别实验数据中的冲突。尽管我们的协议针对的是大得多的RNA,但我们以tRNA结构为例并作为试验台来说明这些技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5290/1275904/dce624d57be7/biophysj00074-0056-a.jpg

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