[RASMB] averages from SV

[John Correia]

Holger
 
To my knowledge my review from a few years ago is the most recent
comprehensive overview of weight average.  It finishes with a mention of
other averages & who has applied them.  
 
J.J. CORREIA (2000) "The Analysis of Weight Average Sedimentation Data."
Methods in Enzymol., vol 321, 81-100.

 
Soon after I published that review John Philo published a paper
claiming typical data is too noisy for higher averages, and demonstrated
so by simulations.  As Walter mentioned these averages are also
calculated in the DCDT portion of SEDANAL.  Peter Schuck also suggests
they are too noisy.  Attached please find a test of those claims,
derived from XLA data using g(s) analysis in SEDANAL.  Clearly if done
properly they are not too noisy! (I have compared this analysis with
results from Philo's DCDTplus2 and the error bars are comparable for Sw,
Sz and Sz+1 - John doesn't report Sn.)  
 
As to claims about no theoretical meaning, moments or averages of
distributions are what they are.  One could easily write a program to
fit these moments and compare them to some model.  We have done this but
I generally only attempt such complexity when the system is very
complex.  I find it much more useful to compare weight average fitting
with direct boundary fitting.  For my self association systems the K's
derived typically agree to within 20%.  The direct boundary fitting
usually reveals what causes the disagreement, typically aggregation at
the centrifugal edge of the boundary.
 
Applying these averages to different signals has its pitfalls, but
Schachman 1st described absorbance average moments in his book, so the
use of different signals is an old idea and easy to apply as a fitter. 
We again prefer to resort to direct boundary fitting, combining
different wavelengths and extinction coefficients to different
components and species.  I strongly agree the information is in the
shape of the sedimenting boundary.  (This does not necessarily mean the
shape of the derived distribution.)  Comparisons to averages should in
principle work with the usual caveats about reversibility, degree of
aggregation, the presence of plateaus, etc.  
 
I hope you try this approach, apply your own direct statistical tests,
and convince yourself of its potential utility.  I have no doubts there
may be a system dependency.  My bias continues to be direct boundary
fitting is the most informative, although we use weight average for
model building, extrapolation to end points, and estimation of K's for
initial guesses.
 
Good luck!
 
 
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 Dr. John J. "Jack" Correia
 Department of Biochemistry
 University of Mississippi Medical Center
 2500 North State Street
 Jackson, MS  39216
 (601) 984-1522                                 
 fax (601) 984-1501                             
 email address: jcorreia at biochem.umsmed.edu     
 homepage location: http://biochemistry.umc.edu/correia.html
 dept homepage location:    http://biochemistry.umc.edu/
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