Size-distribution analysis of proteins by analytical ultracentrifugation: Strategies and application to model systems
Size-distribution analysis of proteins by analytical ultracentrifugation: Strategies and application to model systems
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DOI：
10.1016/s0006-3495(02)75469-6
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发表时间：
2002-02-01
影响因子：
3.4
通讯作者：
Schubert, D
中科院分区：
文献类型：
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作者：
Schuck, P;Perugini, MA;Schubert, D
研究和开发了在由沉积速度实验确定粒度分布时的扩散去卷积策略。在四种不同模型体系的基础上，研究了时间导数法g(S)和最小二乘直接边界模拟l-g*(S)的微分视沉降系数分布，van Holde-Weischet法的积分沉积系数分布G(S)，以及前面介绍的拉姆方程解的微分分布c(S)。结果表明，通过将区域划分类似于van Holde-Weischet方法中的边界划分，最小二乘方法ls-g*(S)可以外推到无限时间，从而允许将干涉光学数据转化为积分的沉降系数分布G(S)。然而，尽管G(S)的无模型方法，对于所考虑的系统，具有分布的拉姆方程解c(S)的直接边界模拟显示出最高的分辨率和灵敏度。C(S)方法需要估计依赖于尺寸的扩散系数D(S)，它通常以所有物种的加权平均摩擦比的形式并入，或者以主要物种的摩尔质量的先验知识的形式并入。我们研究了重均摩擦比对拟合质量的影响，发现这是由数据很好地决定的。作为直接边界模型，计算的c(S)分布可以与非线性回归相结合来优化分布参数，如准确的半月面位置和权平均摩阻比。虽然c(S)在计算上是最复杂的，但它有可能达到所述方法的最高分辨率和灵敏度。
Strategies for the deconvolution of diffusion in the determination of size-distributions from sedimentation velocity experiments were examined and developed. On the basis of four different model systems, we studied the differential apparent sedimentation coefficient distributions by the time-derivative method, g(s*), and by least-squares direct boundary modeling, ls-g*(s), the integral sedimentation coefficient distribution by the van Holde-Weischet method, G(s), and the previously introduced differential distribution of Lamm equation solutions, c(s). It is shown that the least-squares approach ls-g*(s) can be extrapolated to infinite time by considering area divisions analogous to boundary divisions in the van Holde-Weischet method, thus allowing the transformation of interference optical data into an integral sedimentation coefficient distribution G(s). However, despite the model-free approach of G(s), for the systems considered, the direct boundary modeling with a distribution of Lamm equation solutions c(s) exhibited the highest resolution and sensitivity. The c(s) approach requires an estimate for the size-dependent diffusion coefficients D(s), which is usually incorporated in the form of a weight-average frictional ratio of all species, or in the form of prior knowledge of the molar mass of the main species. We studied the influence of the weight-average frictional ratio on the quality of the fit, and found that it is well-determined by the data. As a direct boundary model, the calculated c(s) distribution can be combined with a nonlinear regression to optimize distribution parameters, such as the exact meniscus position, and the weight-average frictional ratio. Although c(s) is computationally the most complex, it has the potential for the highest resolution and sensitivity of the methods described.