Brown Patrick H, Balbo Andrea, Schuck Peter
Dynamics of Macromolecular Assembly, Laboratory of Bioengineering and Physical Science, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD 20892-5766, USA.
Eur Biophys J. 2009 Oct;38(8):1079-99. doi: 10.1007/s00249-009-0514-1. Epub 2009 Jul 31.
Sedimentation velocity analytical ultracentrifugation has experienced a significant transformation, precipitated by the possibility of efficiently fitting Lamm equation solutions to the experimental data. The precision of this approach depends on the ability to account for the imperfections of the experiment, both regarding the sample and the instrument. In the present work, we explore in more detail the relationship between the sedimentation process, its detection, and the model used in the mathematical data analysis. We focus on configurations that produce steep and fast-moving sedimentation boundaries, such as frequently encountered when studying large multi-protein complexes. First, as a computational tool facilitating the analysis of heterogeneous samples, we introduce the strategy of partial boundary modeling. It can simplify the modeling by restricting the direct boundary analysis to species with sedimentation coefficients in a predefined range. Next, we examine factors related to the experimental detection, including the magnitude of optical aberrations generated by out-of-focus solution columns at high protein concentrations, the relationship between the experimentally recorded signature of the meniscus and the meniscus parameter in the data analysis, and the consequences of the limited radial and temporal resolution of the absorbance optical scanning system. Surprisingly, we find that large errors can be caused by the finite scanning speed of the commercial absorbance optics, exceeding the statistical errors in the measured sedimentation coefficients by more than an order of magnitude. We describe how these effects can be computationally accounted for in SEDFIT and SEDPHAT.
沉降速度分析型超速离心法已经历了重大变革，这是由能够有效地将Lamm方程解拟合到实验数据的可能性所促成的。这种方法的精度取决于考虑实验缺陷的能力，包括样品和仪器方面的缺陷。在本工作中，我们更详细地探讨沉降过程、其检测以及数学数据分析中使用的模型之间的关系。我们关注产生陡峭且快速移动的沉降边界的配置，例如在研究大型多蛋白复合物时经常遇到的情况。首先，作为一种有助于分析异质样品的计算工具，我们引入了部分边界建模策略。它可以通过将直接边界分析限制在预定义范围内具有沉降系数的物种来简化建模。接下来，我们研究与实验检测相关的因素，包括高蛋白质浓度下失焦溶液柱产生的光学像差的大小、数据分析中实验记录的弯月面特征与弯月面参数之间的关系，以及吸光度光学扫描系统有限的径向和时间分辨率的后果。令人惊讶的是，我们发现商业吸光度光学器件的有限扫描速度可能会导致很大的误差，超过测量沉降系数中的统计误差一个数量级以上。我们描述了如何在SEDFIT和SEDPHAT中通过计算来考虑这些影响。
