Routledge Katy E, Tartaglia Gian Gaetano, Platt Geoffrey W, Vendruscolo Michele, Radford Sheena E
Astbury Centre for Structural Molecular Biology, Institute of Molecular and Cellular Biology, University of Leeds, Leeds LS2 9JT, UK.
J Mol Biol. 2009 Jun 19;389(4):776-86. doi: 10.1016/j.jmb.2009.04.042. Epub 2009 Apr 23.
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.
尽管在理解蛋白质折叠和聚集过程方面取得了很大进展,但定义它们相互作用的规则尚未完全明确。这个问题尤为重要,因为许多疾病是由蛋白质解折叠引发的,因此聚集倾向与分子内折叠和其他折叠事件相互竞争。在这里,我们描述了分子内和分子间相互作用在定义滞后时间长度和100个残基的人β2-微球蛋白在pH 2.5时的表观伸长率中的作用,该过程从缺乏持久结构但包含显著非随机疏水相互作用的酸变性状态开始。通过结合定点诱变、定量动力学分析和计算方法,我们表明,尽管其他区域表现出显著的内在聚集倾向,但只有一个长度约为10个残基的单一区域决定了原纤维形成的速率。我们通过将核磁共振光谱测量的酸解折叠β2-微球蛋白及其变体在pH 2.5时的构象性质纳入Zyggregator聚集预测算法来分析这些结果,从而对这些结果进行了合理化解释。这些结果表明,前体状态下的残余结构调节了多肽链聚集的内在倾向,并且这里开发的算法允许更清楚地识别聚集的关键区域并预测它们的自组装速率。鉴于未折叠链作为单体形成非随机分子内相互作用并随后自组装成淀粉样原纤维的常见倾向,所开发的方法应该在预测淀粉样形成中重要的区域及其自组装速率方面具有广泛的用途。