Suppr超能文献

非均匀采样相似 NMR 谱及其在研究α-突触核蛋白与脂质体相互作用中的应用。

Non-uniform sampling of similar NMR spectra and its application to studies of the interaction between alpha-synuclein and liposomes.

机构信息

Faculty of Chemistry, University of Warsaw, Pasteura 1, 02-093, Warsaw, Poland.

Department of Structural and Computational Biology, Max Perutz Labs, University of Vienna, Vienna BioCenter Campus 5, 1030, Vienna, Austria.

出版信息

J Biomol NMR. 2023 Aug;77(4):149-163. doi: 10.1007/s10858-023-00418-3. Epub 2023 May 26.

Abstract

The accelerated acquisition of multidimensional NMR spectra using sparse non-uniform sampling (NUS) has been widely adopted in recent years. The key concept in NUS is that a major part of the data is omitted during measurement, and then reconstructed using, for example, compressed sensing (CS) methods. CS requires spectra to be compressible, that is, they should contain relatively few "significant" points. The more compressible the spectrum, the fewer experimental NUS points needed in order for it to be accurately reconstructed. In this paper we show that the CS processing of similar spectra can be enhanced by reconstructing only the differences between them. Accurate reconstruction can be obtained at lower sampling levels as the difference is sparser than the spectrum itself. In many situations this method is superior to "conventional" compressed sensing. We exemplify the concept of "difference CS" with one such case-the study of alpha-synuclein binding to liposomes and its dependence on temperature. To obtain information on temperature-dependent transitions between different states, we need to acquire several dozen spectra at various temperatures, with and without the presence of liposomes. Our detailed investigation reveals that changes in the binding modes of the alpha-synuclein ensemble are not only temperature-dependent but also show non-linear behavior in their transitions. Our proposed CS processing approach dramatically reduces the number of NUS points required and thus significantly shortens the experimental time.

摘要

近年来,稀疏非均匀采样(NUS)在多维 NMR 谱的快速获取中得到了广泛应用。NUS 的关键概念是在测量过程中省略大部分数据,然后使用压缩感知(CS)方法等进行重建。CS 要求谱是可压缩的,也就是说,它们应该包含相对较少的“显著”点。谱越可压缩,为了准确重建,所需的实验 NUS 点就越少。本文表明,通过仅重建它们之间的差异,可以增强类似谱的 CS 处理。由于差异比谱本身更稀疏,因此可以在较低的采样水平上获得准确的重建。在许多情况下,这种方法优于“传统”压缩感知。我们用一个例子来说明“差分 CS”的概念——研究α-突触核蛋白与脂质体的结合及其对温度的依赖性。为了获得不同状态之间温度依赖性转变的信息,我们需要在有和没有脂质体存在的情况下,在不同温度下获取几十张光谱。我们的详细研究表明,α-突触核蛋白集合物的结合模式变化不仅依赖于温度,而且在它们的转变中还表现出非线性行为。我们提出的 CS 处理方法大大减少了所需的 NUS 点数,从而显著缩短了实验时间。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/19e1/10406685/9d63d1c03f2a/10858_2023_418_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验