Dynamics of Protein Assemblies by Analytical Ultracentrifugation

多信号沉降速度是研究多蛋白质复合物的一项重要技术，我们一直在继续开发这种方法。 我们设计了一种新的质量守恒约束作为贝叶斯正则化的一种形式。 我们已经从数学上证明了它可以显著地帮助组分的光谱鉴别。 在Chad Brautigam博士的合作下，这种方法的性能现在正在用模拟和实验数据集进行测试。 从沉降速度导出的一个基本量是平移的流体动力学摩擦系数，其报告蛋白质溶液构象。 特别是，这个系数与结构预测结合起来非常有用。 在与Ghirdham、Brautigam和阿拉贡博士的合作中，我们开始将基于结构的摩擦系数预测的新的高精度边界元方法的结果与沉降速度的实验数据进行比较。 从最初的数据收集，我们已经确定了关键的实验因素。 所有超浓缩实验都受到大分子浮力的影响，浮力是沉积行为的主要因素。 为了补充现有的组成和密度测定方法的测定大分子部分特定的体积，我们已经开发了一种密度对比沉降速度方法。 这在几种模型蛋白上进行了成功的测试。 最后，我们已经更新了我们的SEDFIT软件与新的工具，沉降平衡和沉降速度的研究固有的多分散大分子，如碳水化合物。

One of the techniques with major promise for the study of multi-protein complexes is multi-signal sedimentation velocity, and we have continued the development of this approach. We have devised a novel mass conservation constraint to be used as a form of Bayesian regularization. We have mathematically shown that it can significantly aid in the spectral discrimination of components. In collaboration with Dr. Chad Brautigam, the performance of this approach is now being tested with simulated and experimental data sets. A fundamental quantity derived from sedimentation velocity is the hydrodynamic frictional coefficient of translation, which reports on the protein solution conformation. In particular, this coefficieint is very informative in conjunction with structural predictions. In a collaboration with Drs. Ghirlando, Brautigam, and Aragon, we have set out to compare results from the new high-precision boundary element methods for structure-based prediction of friction coeffcients with experimental data from sedimentation velocity. From initial collection of data, we have identified key experimental factors. All ultracentrifugation experiments are subject to macromolecular buoyancy as a dominating factor of sedimentation behaviour. To complement existing compositional and densimetry approaches for the determination of macromolecular partial-specific volume, we have developed a density contrast sedimentation velocity method. This was successfully tested on several model proteins. Finally, we have updated our SEDFIT software with new tools for sedimentation equilibrium and sedimentation velocity studies of intrinsically polydisperse macromolecules, such as carbohydrates.