Tangprasertchai Narin S, Zhang Xiaojun, Ding Yuan, Tham Kenneth, Rohs Remo, Haworth Ian S, Qin Peter Z
Department of Chemistry, University of Southern California, Los Angeles, California, USA.
Department of Chemistry, University of Southern California, Los Angeles, California, USA; Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, California, USA.
Methods Enzymol. 2015;564:427-53. doi: 10.1016/bs.mie.2015.07.007. Epub 2015 Aug 8.
The technique of site-directed spin labeling (SDSL) provides unique information on biomolecules by monitoring the behavior of a stable radical tag (i.e., spin label) using electron paramagnetic resonance (EPR) spectroscopy. In this chapter, we describe an approach in which SDSL is integrated with computational modeling to map conformations of nucleic acids. This approach builds upon a SDSL tool kit previously developed and validated, which includes three components: (i) a nucleotide-independent nitroxide probe, designated as R5, which can be efficiently attached at defined sites within arbitrary nucleic acid sequences; (ii) inter-R5 distances in the nanometer range, measured via pulsed EPR; and (iii) an efficient program, called NASNOX, that computes inter-R5 distances on given nucleic acid structures. Following a general framework of data mining, our approach uses multiple sets of measured inter-R5 distances to retrieve "correct" all-atom models from a large ensemble of models. The pool of models can be generated independently without relying on the inter-R5 distances, thus allowing a large degree of flexibility in integrating the SDSL-measured distances with a modeling approach best suited for the specific system under investigation. As such, the integrative experimental/computational approach described here represents a hybrid method for determining all-atom models based on experimentally-derived distance measurements.
定点自旋标记(SDSL)技术通过使用电子顺磁共振(EPR)光谱监测稳定自由基标签(即自旋标记)的行为,提供有关生物分子的独特信息。在本章中,我们描述了一种将SDSL与计算建模相结合以绘制核酸构象的方法。这种方法建立在先前开发和验证的SDSL工具包之上,该工具包包括三个组件:(i)一种不依赖核苷酸的氮氧化物探针,命名为R5,它可以有效地连接到任意核酸序列内的特定位点;(ii)通过脉冲EPR测量的纳米范围内的R5间距离;(iii)一个名为NASNOX的高效程序,它可以计算给定核酸结构上的R5间距离。遵循数据挖掘的一般框架,我们的方法使用多组测量的R5间距离从大量模型集合中检索“正确的”全原子模型。模型池可以独立生成,而不依赖于R5间距离,从而在将SDSL测量的距离与最适合所研究特定系统的建模方法相结合时具有很大的灵活性。因此,这里描述的综合实验/计算方法代表了一种基于实验得出的距离测量来确定全原子模型的混合方法。