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结合预测、计算和实验对蛋白质无序状态进行表征。

Combining prediction, computation and experiment for the characterization of protein disorder.

作者信息

Bracken Clay, Iakoucheva Lilia M, Romero Pedro R, Dunker A Keith

机构信息

Department of Biochemistry, Weill Medical College of Cornell University, 1300 York Avenue, New York, NY 10021, USA.

出版信息

Curr Opin Struct Biol. 2004 Oct;14(5):570-6. doi: 10.1016/j.sbi.2004.08.003.

Abstract

Several computational and experimental methods exist for identifying disordered residues within proteins. Computational algorithms can now identify these disordered sequences and predict their occurrence within genomes with relatively high accuracy. Recent advances in NMR and mass spectroscopy permit faster and more detailed studies of disordered states at atomic resolutions. Combining prediction, computation and experimentation is proposed to accelerate and enhance the characterization of intrinsically disordered protein.

摘要

存在多种用于识别蛋白质中无序残基的计算和实验方法。现在,计算算法能够识别这些无序序列,并以相对较高的准确率预测它们在基因组中的出现情况。核磁共振(NMR)和质谱技术的最新进展使得在原子分辨率下对无序状态进行更快、更详细的研究成为可能。有人提出将预测、计算和实验相结合,以加速和加强对内在无序蛋白质的表征。

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