SLEEPY: a comprehensive Python module for simulating relaxation and dynamics in nuclear magnetic resonance.

IF 15.7 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
Albert A Smith,Kai Zumpfe
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引用次数: 0

Abstract

Nuclear magnetic resonance is a powerful method for characterizing dynamics of biological systems in a native-like environment. Accurate dynamics characterization, however, often requires simulations of complex NMR experiments. While a number of simulation programs exist for NMR simulation (SIMPSON, Spinach, SpinEvolution), none of these are focused on easy simulation of motional effects on NMR experiments. The SLEEPY Python module makes it straightforward to simulate arbitrary pulse sequences while including both relaxation and exchange processes. SLEEPY furthermore allows simulation of solid-state (static and spinning) and solution NMR experiments, using both truncated and full Hamiltonians (rotating frame/lab frame). We demonstrate its application to a wide variety of experiments, including transverse (T1ρ), and longitudinal relaxation (T1), nuclear Overhauser effect magnetization transfers, recoupling, and paramagnetic effects. We also provide an extensive online tutorial that explains how to use the various capabilities of SLEEPY. This tool can then be used for both better understanding of the impact of dynamics on NMR and in reproduction of experimental results.
一个全面的Python模块,用于模拟核磁共振中的松弛和动态。
核磁共振是一种强有力的方法来表征生物系统的动力学在原生环境。然而,准确的动力学表征往往需要模拟复杂的核磁共振实验。虽然有许多核磁共振模拟的模拟程序存在(SIMPSON,菠菜,SpinEvolution),但这些程序都没有集中在核磁共振实验中运动效果的简单模拟上。SLEEPY Python模块可以直接模拟任意脉冲序列,同时包括松弛和交换过程。SLEEPY进一步允许模拟固态(静态和旋转)和溶液核磁共振实验,使用截断和完整的哈密顿量(旋转框架/实验室框架)。我们展示了它在各种各样的实验中的应用,包括横向(T1ρ)和纵向弛豫(T1),核Overhauser效应磁化转移,重耦合和顺磁效应。我们还提供了一个广泛的在线教程,解释如何使用SLEEPY的各种功能。该工具可用于更好地理解动力学对核磁共振的影响和实验结果的再现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nature Communications
Nature Communications Biological Science Disciplines-
CiteScore
24.90
自引率
2.40%
发文量
6928
审稿时长
3.7 months
期刊介绍: Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.
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