Exploring the Aggregation Propensity of γS-Crystallin Protein Variants Using Two-Dimensional Spectroscopic Tools

被引:10
作者
Jiang, Jun [1 ,2 ]
Golchert, Kory J. [2 ]
Kingsley, Carolyn N. [2 ]
Brubaker, William D. [3 ]
Martin, Rachel W. [2 ,3 ]
Mukamel, Shaul [2 ]
机构
[1] Univ Sci & Technol China, Dept Chem Phys, Hefei 230026, Peoples R China
[2] Univ Calif Irvine, Dept Chem, Irvine, CA 92717 USA
[3] Univ Calif Irvine, Dept Mol Biol & Biochem, Irvine, CA 92717 USA
基金
美国国家科学基金会; 美国国家卫生研究院; 中国国家自然科学基金;
关键词
AMYLOID STRUCTURE; DYNAMICS; ENTROPY; NMR; PROTEOLYSIS; COUPLINGS; DENSITY;
D O I
10.1021/jp408000k
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The formation of amyloid fibrils is associated with many serious diseases as well as diverse biological functions. Despite the importance of these aggregates, predicting the aggregation propensity of a particular sequence is a major challenge. We report a joint 2D nuclear magnetic resonance (NMR) and ultraviolet (2DUV) study of fibrillization in the wild-type and two aggregation-prone mutants of the eye lens protein gamma S-crystallin. Simulations show that the complexity of 2DLTV signals as measured by their "approximate entropy" is a good indicator for the conformational entropy and in turn is strongly correlated with its aggregation propensity. These findings are in agreement with high-resolution NMR experiments and are corroborated for amyloid fibrils. The 2DUV technique is complementary to highresolution structural methods and has the potential to make the evaluation of the aggregation propensity for protein variant propensity of protein structure more accessible to both theory and experiment. The approximate entropy of experimental 2DUV signals can be used for fast screening, enabling identification of variants with high fibrillization propensity for the much more time-consuming NMR structural studies, potentially expediting the characterization of protein variants associated with cataract and other protein aggregation diseases.
引用
收藏
页码:14294 / 14301
页数:8
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