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具有选择性碳(C)和氮(N)同位素标记的自组装肽的固态核磁共振结构表征

Solid-State NMR Structural Characterization of Self-Assembled Peptides with Selective C and N Isotopic Labels.

作者信息

Huang Danting, Hudson Benjamin C, Gao Yuan, Roberts Evan K, Paravastu Anant K

机构信息

School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA.

出版信息

Methods Mol Biol. 2018;1777:23-68. doi: 10.1007/978-1-4939-7811-3_2.

Abstract

For the structural characterization methods discussed here, information on molecular conformation and intermolecular organization within nanostructured peptide assemblies is discerned through analysis of solid-state NMR spectral features. This chapter reviews general NMR methodologies, requirements for sample preparation, and specific descriptions of key experiments. An attempt is made to explain choices of solid-state NMR experiments and interpretation of results in a way that is approachable to a nonspecialist. Measurements are designed to determine precise NMR peak positions and line widths, which are correlated with secondary structures, and probe nuclear spin-spin interactions that report on three-dimensional organization of atoms. The formulation of molecular structural models requires rationalization of data sets obtained from multiple NMR experiments on samples with carefully chosen C and N isotopic labels. The information content of solid-state NMR data has been illustrated mostly through the use of simulated data sets and references to recent structural work on amyloid fibril-forming peptides and designer self-assembling peptides.

摘要

对于此处讨论的结构表征方法,通过对固态核磁共振光谱特征的分析,可识别纳米结构肽组装体中的分子构象和分子间组织信息。本章回顾了一般的核磁共振方法、样品制备要求以及关键实验的具体描述。我们试图以非专业人士易于理解的方式解释固态核磁共振实验的选择和结果的解读。测量旨在确定精确的核磁共振峰位置和线宽,这些与二级结构相关,并探测报告原子三维组织的核自旋 - 自旋相互作用。分子结构模型的构建需要对从多个核磁共振实验获得的数据集进行合理化处理,这些实验针对的是带有精心选择的碳和氮同位素标记的样品。固态核磁共振数据的信息内容大多通过使用模拟数据集以及参考近期关于淀粉样纤维形成肽和设计自组装肽的结构研究来说明。

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Physical and structural basis for polymorphism in amyloid fibrils.淀粉样纤维多态性的物理和结构基础。
Protein Sci. 2014 Nov;23(11):1528-39. doi: 10.1002/pro.2544. Epub 2014 Sep 13.

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