Piai Alessandro, Gonnelli Leonardo, Felli Isabella C, Pierattelli Roberta, Kazimierczuk Krzysztof, Grudziąż Katarzyna, Koźmiński Wiktor, Zawadzka-Kazimierczuk Anna
CERM and Department of Chemistry Ugo Schiff, University of Florence, Via Luigi Sacconi 6, Sesto Fiorentino, 50019, Florence, Italy.
Centre of New Technologies, University of Warsaw, Banacha 2C, 02-097, Warsaw, Poland.
J Biomol NMR. 2016 Mar;64(3):239-53. doi: 10.1007/s10858-016-0024-2. Epub 2016 Feb 18.
Resonance assignment is a prerequisite for almost any NMR-based study of proteins. It can be very challenging in some cases, however, due to the nature of the protein under investigation. This is the case with intrinsically disordered proteins, for example, whose NMR spectra suffer from low chemical shifts dispersion and generally low resolution. For these systems, sequence specific assignment is highly time-consuming, so the prospect of using automatic strategies for their assignment is very attractive. In this article we present a new version of the automatic assignment program TSAR dedicated to intrinsically disordered proteins. In particular, we demonstrate how the automatic procedure can be improved by incorporating methods for amino acid recognition and information on chemical shifts in selected amino acids. The approach was tested in silico on 16 disordered proteins and experimentally on α-synuclein, with remarkably good results.
共振归属是几乎所有基于核磁共振的蛋白质研究的先决条件。然而,由于所研究蛋白质的性质,在某些情况下这可能极具挑战性。例如,对于内在无序蛋白质就是这种情况,其核磁共振谱存在化学位移分散度低和分辨率普遍较低的问题。对于这些系统,序列特异性归属非常耗时,因此使用自动策略进行归属的前景非常有吸引力。在本文中,我们展示了一个专门用于内在无序蛋白质的自动归属程序TSAR的新版本。特别是,我们展示了如何通过纳入氨基酸识别方法和选定氨基酸的化学位移信息来改进自动程序。该方法在计算机上对16种无序蛋白质进行了测试,并在实验上对α-突触核蛋白进行了测试,结果非常好。