Demeler B, Saber H
Department of Biochemistry, University of Texas Health Sciences Center at San Antonio, 78284-7760, USA.
Biophys J. 1998 Jan;74(1):444-54. doi: 10.1016/S0006-3495(98)77802-6.
A method for fitting experimental sedimentation velocity data to finite-element solutions of various models based on the Lamm equation is presented. The method provides initial parameter estimates and guides the user in choosing an appropriate model for the analysis by preprocessing the data with the G(s) method by van Holde and Weischet. For a mixture of multiple solutes in a sample, the method returns the concentrations, the sedimentation (s) and diffusion coefficients (D), and thus the molecular weights (MW) for all solutes, provided the partial specific volumes (v) are known. For nonideal samples displaying concentration-dependent solution behavior, concentration dependency parameters for s(sigma) and D(delta) can be determined. The finite-element solution of the Lamm equation used for this study provides a numerical solution to the differential equation, and does not require empirically adjusted correction terms or any assumptions such as infinitely long cells. Consequently, experimental data from samples that neither clear the meniscus nor exhibit clearly defined plateau absorbances, as well as data from approach-to-equilibrium experiments, can be analyzed with this method with enhanced accuracy when compared to other available methods. The nonlinear least-squares fitting process was accomplished by the use of an adapted version of the "Doesn't Use Derivatives" nonlinear least-squares fitting routine. The effectiveness of the approach is illustrated with experimental data obtained from protein and DNA samples. Where applicable, results are compared to methods utilizing analytical solutions of approximated Lamm equations.
本文提出了一种将实验沉降速度数据与基于Lamm方程的各种模型的有限元解进行拟合的方法。该方法通过使用van Holde和Weischet的G(s)方法对数据进行预处理,提供初始参数估计,并指导用户选择合适的模型进行分析。对于样品中多种溶质的混合物,若已知偏比容(v),该方法可返回所有溶质的浓度、沉降系数(s)和扩散系数(D),进而得到分子量(MW)。对于显示浓度依赖性溶液行为的非理想样品,可确定s(σ)和D(δ)的浓度依赖性参数。本研究中使用的Lamm方程的有限元解为微分方程提供了数值解,不需要经验调整的校正项或任何假设,如无限长的样品池。因此,与其他现有方法相比,该方法能够更准确地分析来自既未清除弯月面也未表现出明确界定的平台吸光度的样品的实验数据,以及接近平衡实验的数据。非线性最小二乘拟合过程通过使用“不使用导数”非线性最小二乘拟合程序的改编版本来完成。通过从蛋白质和DNA样品获得的实验数据说明了该方法的有效性。在适用的情况下,将结果与使用近似Lamm方程解析解的方法进行比较。