Competition between Intramolecular and Intermolecular Interactions in an Amyloid-Forming Protein

被引:68
作者
Routledge, Katy E. [2 ]
Tartaglia, Gian Gaetano [1 ]
Platt, Geoffrey W. [2 ]
Vendrusco, Michele [1 ]
Radford, Sheena E. [2 ]
机构
[1] Univ Cambridge, Dept Chem, Cambridge CB2 1EW, England
[2] Univ Leeds, Astbury Ctr Struct Mol Biol, Inst Mol & Cellular Biol, Leeds LS2 9JT, W Yorkshire, England
基金
英国惠康基金;
关键词
amyloid; aggregation; NMR relaxation; prediction; unfolded state; FIBRIL FORMATION; DISULFIDE BOND; IN-VITRO; AGGREGATION; BETA(2)-MICROGLOBULIN; BETA-2-MICROGLOBULIN; NMR; INSIGHTS; STATE; PREDICTION;
D O I
10.1016/j.jmb.2009.04.042
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Despite much progress in understanding the folding and the aggregation processes of proteins, the rules defining their interplay have yet to be fully defined. This problem is of particular importance since many diseases are initiated by protein unfolding and hence the propensity to aggregate competes with intramolecular collapse and other folding events. Here, we describe the roles of intramolecular and intermolecular interactions in defining the length of the lag time and the apparent rate of elongation of the 100-residue protein human beta(2)-microglobulin at pH 2.5, commencing from an acid-denatured state that lacks persistent structure but contains significant non-random hydrophobic interactions. Using a combination of site-directed mutagenesis, quantitative kinetic analysis and computational methods, we show that only a single region of about 10 residues in length, determines the rate of fibril formation, despite the fact that other regions exhibit a significant intrinsic propensity for aggregation. We rationalise these results by analysing the effect of incorporating the conformational properties of acid-unfolded beta(2)-microglobulin and its variants at pH 2.5 as measured by NMR spectroscopy into the Zyggregator aggregation prediction algorithm. These results demonstrate that residual structure in the precursor state modulates the intrinsic propensity of the polypeptide chain to aggregate and that the algorithm developed here allows the key regions for aggregation to be more clearly identified and the rates of their self-association to be predicted. Given the common propensity of unfolded chains to form non-random intramolecular interactions as monomers and to self-assemble subsequently into amyloid fibrils, the approach developed should find widespread utility for the prediction of regions important in amyloid formation and their rates of self-assembly. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:776 / 786
页数:11
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