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Default nightshift: A Python program for plotting simulated NMR spectra from assigned chemical shifts from the Biological Magnetic Resonance Data Bank

nightshift: A Python program for plotting simulated NMR spectra from assigned chemical shifts from the Biological Magnetic Resonance Data Bank

Abstract

Nuclear magnetic resonance (NMR) provides site specific information on local environments through chemical shifts. NMR is widely used in the study of proteins, ranging from determination of three-dimensional structures to characterizing dynamics and binding of small molecules and other proteins or ligands. Assigned chemical shift data for the atoms within proteins is a treasure trove of information that can facilitate a broad range of biochemical and biophysical studies. The Biological Magnetic Resonance Data Bank (BMRB) is a publicly accessible database that contains a large number of assigned chemical shifts; however, translating this wealth of knowledge into a practical application is not straightforward. Herein we present nightshift: a Python command line utility and library for plotting simulated 2D and 3D NMR spectra from assigned chemical shifts in the BMRB. This tool allows users to simulate routinely collected amide and methyl fingerprint spectra, backbone triple-resonance assignment spectra, and user-defined custom correlations, including ones that do not necessarily correspond to published experiments. This tool enables experienced NMR spectroscopists, those learning the craft, and interested scientists seeking to utilize NMR the ability to preview or examine a wide range of spectra for proteins whose assignments are deposited in the BMRB, irrespective of whether those experiments have been executed or reported. The tool applies equally to folded and intrinsically disordered proteins, limited only by the existence of a BMRB deposition. The features of nightshift are described along with applications that illustrate the ease with which complicated correlation spectra and binding events can be simulated.

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