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通过压缩感知重建的反卷积提高 NMR 谱的分辨率。

Resolution enhancement in NMR spectra by deconvolution with compressed sensing reconstruction.

机构信息

Centre of New Technologies, University of Warsaw, ul. Banacha 2C, 02-097 Warsaw, Poland.

出版信息

Chem Commun (Camb). 2020 Dec 4;56(93):14585-14588. doi: 10.1039/d0cc06188c. Epub 2020 Nov 4.

DOI:10.1039/d0cc06188c
PMID:33146166
Abstract

NMR spectroscopy is one of the basic tools for molecular structure elucidation. Unfortunately, the resolution of the spectra is often limited by inter-nuclear couplings. The existing workarounds often alleviate the problem by trading it for another deficiency, such as spectral artefacts or difficult sample preparation and, thus, are rarely used. We suggest an approach using the coupling deconvolution in the framework of compressed sensing (CS) spectra processing that leads to a major increase in resolution, sensitivity, and overall quality of NUS reconstruction. A new mathematical description of the decoupling by deconvolution explains the effects of thermal noise and reveals a relation with the underlying assumption of the CS. The gain in resolution and sensitivity for challenging molecular systems is demonstrated for the key HNCA experiment used for protein backbone assignment applied to two large proteins: intrinsically disordered 441-residue Tau and a 509-residue globular bacteriophytochrome fragment. The approach will be valuable in a multitude of chemistry applications, where NMR experiments are compromised by the homonuclear scalar coupling.

摘要

核磁共振波谱学是分子结构解析的基本工具之一。不幸的是,光谱的分辨率通常受到核间耦合的限制。现有的解决方法往往通过牺牲另一个缺陷来缓解这个问题,例如光谱伪影或难以制备的样品,因此很少被使用。我们建议在压缩感知 (CS) 谱处理的框架中使用耦合去卷积的方法,这将大大提高分辨率、灵敏度和 NUS 重建的整体质量。通过去卷积对解耦的新数学描述解释了热噪声的影响,并揭示了与 CS 基本假设的关系。该方法在应用于两个大型蛋白质的关键 HNCA 实验中,用于蛋白质骨架分配,证明了对具有挑战性的分子系统的分辨率和灵敏度的提高。该方法在许多化学应用中都将具有重要价值,在这些应用中,核磁共振实验受到同核标量耦合的影响。

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