Measuring Sedimentation, Diffusion, and Molecular Weights of Small Molecules by Direct Fitting of Sedimentation Velocity Concentration Profiles
John S. Philo
Abstract
John S. Philo
Abstract
Sedimentation velocity experiments have traditionally been used for samples with relatively high sedimentation coefficients and low diffusion. Such samples give sharp boundaries from which it is relatively easy to extract the sedimentation coefficient, and which permit the separation of multicomponent samples into distinct boundaries. However, many proteins of interest for therapeutic purposes, such as cytokines and growth factors, have molecular masses of only 10–40 kDa. Even at 60000 rpm, such small molecules give very broad boundaries which are difficult to analyze by existing techniques. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
OpenAlex reports 80 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Sedimentation velocity experiments have traditionally been used for samples with relatively high sedimentation coefficients and low diffusion. Such samples give sharp boundaries from which it is relatively easy to extract the sedimentation coefficient, and which permit the separation of multicomponent samples into distinct boundaries. However, many proteins of interest for therapeutic purposes, such as cytokines and growth factors, have molecular masses of only 10–40 kDa. Even at 60000 rpm, such small molecules give very broad boundaries which are difficult to analyze by existing techniques. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Key concepts: Sedimentation, Sedimentation coefficient, Diffusion, Small molecule, Chemistry, Materials science, Physics, Geology