Determination of the sedimentation coefficient distribution by least-squares boundary modeling.
A new method is presented for the calculation of apparent sedimentation coefficient distributions g*(s) for the size-distribution analysis of polymers in sedimentation velocity experiments. Direct linear least-squares boundary modeling by a superposition of sedimentation profiles of ideal nondiffusing particles is employed. It can be combined with algebraic noise decomposition techniques for the application to interference optical ultracentrifuge data at low loading concentrations with significant systematic noise components. Because of the use of direct boundary modeling, residuals are available for assessment of the quality of the fits and the consistency of the g*(s) distribution with the experimental data. The method can be combined with regularization techniques based on F statistics, such as used in the program CONTIN, or alternatively, the increment of s values can be adjusted empirically. The method is simple, has advantageous statistical properties, and reveals precise sedimentation coefficients. The new least-squares ls-g*(s) exhibits a very high robustness and resolution if data acquired over a large time interval are analyzed. This can result in a high resolution for large particles, and for samples with a high degree of heterogeneity. Because the method does not require a high frequency of scans, it can also be easily used in experiments with the absorbance optical scanning system. Published 2000 John Wiley & Sons, Inc.
Molecular Interactions Resource, Bioengineering and Physical Science Program, ORS, National Institutes of Health, Bethesda, Maryland 20892, USA. pschuck@helix.nih.gov
P
P
Schuck
P
P
Rossmanith
D007074:Immunoglobulin G / Q000737:chemistry; D008956:Models, Chemical; D008962:Models, Theoretical; D010316:Particle Size; D011108:Polymers / Q000737:chemistry; D012680:Sensitivity and Specificity; D014461:Ultracentrifugation / Q000295:instrumentation / Q000379:methods*
D007074:Immunoglobulin G; D011108:Polymers