Möglich Andreas, Krieger Florian, Kiefhaber Thomas
Biozentrum der Universität Basel, Division of Biophysical Chemistry, Klingelbergstrasse 70, CH-4056 Basel, Switzerland.
J Mol Biol. 2005 Jan 7;345(1):153-62. doi: 10.1016/j.jmb.2004.10.036.
Chemical denaturants are frequently used to unfold proteins and to characterize mechanisms and transition states of protein folding reactions. The molecular basis of the effect of urea and guanidinium chloride (GdmCl) on polypeptide chains is still not well understood. Models for denaturant--protein interaction include both direct binding and indirect changes in solvent properties. Here we report studies on the effect of urea and GdmCl on the rate constants (k(c)) of end-to-end diffusion in unstructured poly(glycine-serine) chains of different length. Urea and GdmCl both lead to a linear decrease of lnk(c) with denaturant concentration, as observed for the rate constants for protein folding. This suggests that the effect of denaturants on chain dynamics significantly contributes to the denaturant-dependence of folding rate constants for small proteins. We show that this linear dependency is the result of two additive non-linear effects, namely increased solvent viscosity and denaturant binding. The contribution from denaturant binding can be quantitatively described by Schellman's weak binding model with binding constants (K) of 0.62(+/-0.01)M(-1) for GdmCl and 0.26(+/-0.01)M(-1) for urea. In our model peptides the number of binding sites and the effect of a bound denaturant molecule on chain dynamics is identical for urea and GdmCl. The results further identify the polypeptide backbone as the major denaturant binding site and give an upper limit of a few nanoseconds for residence times of denaturant molecules on the polypeptide chain.
化学变性剂经常被用于使蛋白质解折叠,并用于表征蛋白质折叠反应的机制和过渡态。尿素和氯化胍(GdmCl)对多肽链作用的分子基础仍未被完全理解。变性剂与蛋白质相互作用的模型包括直接结合和溶剂性质的间接变化。在此,我们报告了关于尿素和GdmCl对不同长度的无规聚(甘氨酸 - 丝氨酸)链中端到端扩散速率常数(k(c))影响的研究。尿素和GdmCl都导致lnk(c)随变性剂浓度呈线性下降,这与蛋白质折叠的速率常数情况相同。这表明变性剂对链动力学的影响显著促成了小蛋白质折叠速率常数对变性剂的依赖性。我们表明这种线性依赖性是两种加和的非线性效应的结果,即溶剂粘度增加和变性剂结合。变性剂结合的贡献可以用Schellman的弱结合模型进行定量描述,其中GdmCl的结合常数(K)为0.62(±0.01)M⁻¹,尿素的结合常数为0.26(±0.01)M⁻¹。在我们的模型肽中,尿素和GdmCl的结合位点数量以及结合的变性剂分子对链动力学的影响是相同的。这些结果进一步确定多肽主链为主要的变性剂结合位点,并给出了变性剂分子在多肽链上停留时间的上限为几纳秒。