Department of Biochemistry, The University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Drive, MC 7760, San Antonio, TX 78229-3901, USA.
Eur Biophys J. 2010 Feb;39(3):405-14. doi: 10.1007/s00249-009-0413-5. Epub 2009 Feb 27.
We report a model-independent analysis approach for fitting sedimentation velocity data which permits simultaneous determination of shape and molecular weight distributions for mono- and polydisperse solutions of macromolecules. Our approach allows for heterogeneity in the frictional domain, providing a more faithful description of the experimental data for cases where frictional ratios are not identical for all components. Because of increased accuracy in the frictional properties of each component, our method also provides more reliable molecular weight distributions in the general case. The method is based on a fine grained two-dimensional grid search over s and f/f (0), where the grid is a linear combination of whole boundary models represented by finite element solutions of the Lamm equation with sedimentation and diffusion parameters corresponding to the grid points. A Monte Carlo approach is used to characterize confidence limits for the determined solutes. Computational algorithms addressing the very large memory needs for a fine grained search are discussed. The method is suitable for globally fitting multi-speed experiments, and constraints based on prior knowledge about the experimental system can be imposed. Time- and radially invariant noise can be eliminated. Serial and parallel implementations of the method are presented. We demonstrate with simulated and experimental data of known composition that our method provides superior accuracy and lower variance fits to experimental data compared to other methods in use today, and show that it can be used to identify modes of aggregation and slow polymerization.
我们报告了一种模型独立的沉降速度数据分析方法，该方法允许同时确定单分散和多分散大分子溶液的形状和分子量分布。我们的方法允许摩擦域中的异质性，为摩擦比不为所有组分都相同的情况提供了对实验数据更真实的描述。由于每个组分的摩擦特性的准确性提高，我们的方法在一般情况下也提供了更可靠的分子量分布。该方法基于 s 和 f/f(0) 的细粒度二维网格搜索，其中网格是由 Lamm 方程的有限元解表示的整个边界模型的线性组合，具有与网格点对应的沉降和扩散参数。使用蒙特卡罗方法来描述确定溶质的置信限。讨论了满足细粒度搜索的非常大内存需求的计算算法。该方法适用于全局拟合多速度实验，并可以施加基于实验系统先验知识的约束。可以消除时间和径向不变的噪声。本文提出了串行和并行实现方法。我们用已知组成的模拟和实验数据证明，与当今使用的其他方法相比，我们的方法提供了更准确和更低方差的实验数据拟合，并且可以用于识别聚集模式和聚合缓慢。
