Accounting for Solvent Signal Offsets in the Analysis of Interferometric Sedimentation Velocity Data
Accounting for Solvent Signal Offsets in the Analysis of Interferometric Sedimentation Velocity Data
复制标题
DOI：
10.1002/mabi.200900456
复制
发表时间：
2010-07-07
影响因子：
4.6
通讯作者：
Schuck, Peter
中科院分区：
文献类型：
--
作者：
Zhao, Huaying;Brown, Patrick H.;Schuck, Peter
沉降速度 (SV) 分析超速离心已重新成为生物大分子和纳米颗粒表征的重要工具。大分子浓度分布演变的计算分析可以表征大分子的许多流体力学和热力学性质及其相互作用。瑞利干涉光学系统通常是首选的检测方法，因为它通常具有卓越的数据质量和折射率敏感检测的广泛适用性。然而，干涉光学系统对共溶剂分子的重新分布也很敏感，这不是主要的实验兴趣。原则上，可以通过样品溶液和参考溶液的精确几何和成分匹配来消除它们的贡献，从而实现不需要的缓冲信号的完全光学减去。不幸的是，在实践中，由于各种原因，这通常无法完美实现，从而导致由于溶剂成分的不匹配沉降而产生信号偏移。如果不认识到这一点，这可能会导致严重的失配，并伴有大分子沉降参数的严重错误。在目前的工作中，我们描述了一种通过使用 Lamm 方程解对信号的重新分布进行显式建模来计算沉降缓冲区组件信号的方法，并在软件 SEDFIT 中实现。我们演示了如何恢复 SV 分析以产生高质量的数据拟合并提供正确的大分子沉降参数。
Sedimentation velocity (SV) analytical ultracentrifugation has re-emerged as an important tool in the characterization of biological macromolecules and nanoparticles. The computational analysis of the evolution of the macromolecular concentration profile allows the characterization of many hydrodynamic and thermodynamic properties of the macromolecules and their interactions. The Rayleigh interference optical system is often the detection method of choice, for its usually superior data quality and the wide applicability of refractive index sensitive detection. However, the interference optical system is also sensitive to the redistribution of co-solvent molecules, which are not of primary experimental interest. In principle, their contribution can be eliminated by an exact geometric and compositional match of the sample solution and the reference solution, achieving the complete optical subtraction of unwanted buffer signals. Unfortunately, in practice, this can often not be perfectly achieved for various reasons, leading to signal offsets arising from unmatched sedimentation of solvent components. If unrecognized, this can lead to significant misfit, accompanied by significant errors in the macromolecular sedimentation parameters. In the present work, we describe an approach of computationally accounting for signals from sedimenting buffer components through explicitly modeling their redistribution with Lamm Equation solutions, implemented in the software SEDFIT. We demonstrate how this can restore the SV analysis to yield a high quality fit of the data and to provide correct macromolecular sedimentation parameters.