Brautigam Chad A
Department of Biophysics, The University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Methods Enzymol. 2015;562:109-33. doi: 10.1016/bs.mie.2015.05.001. Epub 2015 Jun 16.
The analysis of analytical ultracentrifugation (AUC) data has been greatly facilitated by the advances accumulated in recent years. These improvements include refinements in AUC-based binding isotherms, advances in the fitting of both sedimentation velocity (SV) and sedimentation equilibrium (SE) data, and innovations in calculations related to posttranslationally modified proteins and to proteins with a large amount of associated cosolute, e.g., detergents. To capitalize on these advances, the experimenter often must prepare and collate multiple data sets and parameters for subsequent analyses; these tasks can be cumbersome and unclear, especially for new users. Examples are the sorting of concentration-profile scans for SE data, the integration of sedimentation velocity distributions (c(s)) to arrive at weighted-average binding isotherms, and the calculations to determine the oligomeric state of glycoproteins and membrane proteins. The significant organizational and logistical hurdles presented by these approaches are streamlined by the software described herein, called GUSSI. GUSSI also creates publication-quality graphics for documenting and illustrating AUC and other biophysical experiments with minimal effort on the user's part. The program contains three main modules, allowing for plotting and calculations on c(s) distributions, SV signal versus radius data, and general data/fit/residual plots.
近年来积累的进展极大地促进了分析超速离心(AUC)数据的分析。这些改进包括基于AUC的结合等温线的优化、沉降速度(SV)和沉降平衡(SE)数据拟合方面的进展,以及与翻译后修饰蛋白和具有大量相关共溶质(如去污剂)的蛋白相关计算的创新。为了利用这些进展,实验者通常必须准备和整理多个数据集和参数以供后续分析;这些任务可能既繁琐又不明确,尤其是对于新用户而言。例如,对SE数据的浓度分布扫描进行排序、对沉降速度分布(c(s))进行积分以得出加权平均结合等温线,以及确定糖蛋白和膜蛋白寡聚状态的计算。本文所述的名为GUSSI的软件简化了这些方法所带来的重大组织和后勤障碍。GUSSI还能以最小的用户工作量创建用于记录和说明AUC及其他生物物理实验的高质量出版物图形。该程序包含三个主要模块,可用于对c(s)分布、SV信号与半径数据以及一般数据/拟合/残差图进行绘图和计算。