Theory of Computer Aided Interpretation of Sedimentation Data

The theory described here focuses on the interpretation of sedimentation data for purified proteins, glycoproteins or lipoproteins exhibiting relatively simple behavior in aqueous buffers. Proper interpretation of analytical sedimentation data can provide estimates of molecular weight, subunit stoichiometries, association constants, thermodynamic nonideality, molecular sizes and relative structural asymmetry for a wide variety of macromolecules. Estimates of the reduced apparent molecular weight (σ, sigma) or the apparent sedimentation coefficient (s*, S star) only require knowledge of the concentration distribution, rotor speed and the time from the start of the experiment. (Ref. 3 8 9 10 11 12) However, full interpretation of sedimentation data requires knowledge of ancillary information such as the solution density and viscosity, as well as the protein's partial specific volume. Such data may be entered into Sednterp directly (and temperature corrections computed) or the program may use various methods to interpolate estimates of this essential ancillary information from simpler information when explicit data are not available. In this help file (mainly in part II Theory..), the equations used for interpretation, interpolation, and the limitations of these computations are described.

Naturally, proper data interpretation requires good data acquisition. Many practical suggestions are available in books (Ref. 8 10), operating manuals (Ref. 11 12) or reviews (Ref. 9) that describe the acquisition of sedimentation velocity (Ref. 9 10 11), sedimentation equilibrium (Ref. 9 10 11 12 13 14) and diffusion data (Ref. 9 10). The approaches implemented by Sednterp are appropriate starting points for interpreting data from these experiments, but the interpretations computed by Sednterp are not comprehensive enough to deal with the sedimentation of non-proteins or complex chemical systems (Ref. 15 16 17).