From: Matthew Parker <mparker@oberon.cmc.uab.edu>
  To  : Joel Mackay <j.mackay@biochem.usyd.edu.au>
  Date: Tue, 07 Sep 1999 08:54:28 -0500

Re: significance?

Dear Joel,

	You might want to try doing a "two-species plot." This involves plotting
the Mw vs Mn (or the Mz vs Mw) values for the data points in the cell.
(There is a program, developed by Walt Stafford I believe, called BIOSPIN
that will calculate these values for you.) If the plot proceeds as a
straight line from the monomer to trimer molecular masses, then you
probably have a monomer/trimer system. If you have a monomer/dimer/tetramer
system, then you might see the line going initially from monomer toward
dimer molecular mass but then veering off in the direction of the tetramer
mass (assuming you have enough tetramer present to be detected).

	I don't have the original reference for this at hand, but we made use of
it recently when we encountered the same type of problem (Parker, M. H.,
Stafford, W. F., 3rd & Prevelige, P. E., Jr. (1997). Bacteriophage P22
scaffolding protein forms oligomers in solution. J Mol Biol 268(3),
655-65.) The reference for the original paper is in there.

	I hope this helps.

	Matt Parker


At 12:33 PM 9/7/99 +1000, you wrote:
>Dear all,
>I have a question about deciding which model describes one's data best. I
>have recorded sedimentation equilibrium data at three speeds with three
>different dilutions for a protein which undergoes some self-association. I
>have been fitting the data in NONLIN. If i fit the data by fixing sigma to
>the monomer mass, allowing delta y and lnA values to float, and permitting
>a single association constant to float, i get the best fit with a
>monomer-trimer model (both monomer-dimer and monomer-tetramer have worse
>residuals and higher chi-squared etc according to NONLIN). If I instead
>allow an extra equilibrium constant to float, and call the two associations
>monomer-dimer and monomer-tetramer, i get a slightly lower chi-squared
>(0.0138 vs 0.014 for the monomer-trimer model). My question is, how do i
>decide if the extra complexity of the model is justified. I know there is a
>thing called an F-test, and thought that might be appropriate. If so, how
>does one apply it in this case? What do you all do in these situations? It
>seems that the extra variable is pretty risky, but presumably a
>sufficiantly large reduction in the chi-squared would justify its inclusion.
>cheers and thanks in advance for any help,
>Joel Mackay
>************************************************************************
>Dr Joel Mackay			ph +61-2-9351-3906
>ARC Research Fellow			fax +61-2-9351-4726
>Department of Biochemistry
>University of Sydney
>NSW 2006 Australia
>http://www.biochem.usyd.edu.au/~joel/
>************************************************************************
>