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Hi Marina and Walter ,<br>
<br>
<blockquote cite="mid:BF9B6304-C298-4343-84C1-4C6C26D03584@bbri.org"
type="cite">
<div>Second SEDFIT does not have a monomer-hexamer model that can be
used for direct fitting to a monomer-hexamer model.</div>
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</blockquote>
For years now, the explicit interaction models for self-association,
binary and ternary associating systems have been moved from SEDFIT to
SEDPHAT, which can be started seamlessly from within SEDFIT, funneling
the data along from one into the other. (Only a few self-association
models remain in SEDFIT duplicating those in SEDPHAT.) This is
probably the easiest for any SEDFIT user, since SEDPHAT has a very
similar user interface and is based on the same principles. I think
nobody will have a problem finding the monomer-hexamer model as a
special case of the monomer-n-mer model with n = 6.<br>
<blockquote cite="mid:BF9B6304-C298-4343-84C1-4C6C26D03584@bbri.org"
type="cite">
<div>If the material is pure and exhibits no concentration dependence
you can use SEDFIT c(s) and C(M) to get the molecular weight.</div>
<div><br class="webkit-block-placeholder">
</div>
<div>However if it is reversibly associating/dissociating, you will
need to use other software, like SEDANAL, in which you can specify a
model of your choice.</div>
</blockquote>
<blockquote cite="mid:BF9B6304-C298-4343-84C1-4C6C26D03584@bbri.org"
type="cite">
<div>Of course, you can use SEDANAL also to get the molar mass of
non-interacting species as well without making any assumptions about
frictional ratios.</div>
<div><span class="Apple-tab-span" style="white-space: pre;"> </span><br
class="webkit-block-placeholder">
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</blockquote>
Sorry for everybody remembering this discussion, I know this is tedious
because it has been said many times before: What one needs for c(M) to
get good molecular weight estimates (usually within 5-10% of the true
molar mass or better, assuming that vbar and buffer density are known)
is not that the sample is pure - but only that the species of interest
is the main peak. If that's not the case, one may use,
for example, the bimodal frictional ratio model. Second, it does still
work well (certainly sufficient to distinguish trimer from hexamer) for
reacting systems if the species of interest is
kinetically stable because of either a slow off-rate constant (koff
< 1e-4) or because it is kept populated via mass action law by
having a concentration >> Kd or << Kd. Both conditions can
be checked by
confirming that the c(s) peak of interest does not show a concentration
dependence (when trying, for example, 3fold higher and 3fold lower
concentrations). <br>
<br>
An essential criterion for any c(s) or c(M) analysis, or any other
analysis for that matter, is that the model actually fits the raw data.<br>
<br>
What Walter proposes to do in his last sentence is modeling with a
discrete Lamm equation solution or variation of that. Note that
'without making any assumptions about frictional ratios' in SEDANAL
means without diffusional deconvolution. As is well-published,
attempting to determine molar masses without resolving possible
heterogeneity contributions to the boundary spread can give very poor
results, frequently vastly underestimating the molar mass, even in the
absence of chemical reactions. The discrete approach actually requires
much higher purity than the c(M) approach. This can be easily tested
within SEDFIT or SEDPHAT, which incorporates both approaches and
hybrids thereof. Usually the discrete Lamm equation solutions give too
low Mw's, much higher rmsd and clearly systematic residual bitmaps.<br>
<br>
To come back to Marina's data - I don't know where the discrepancy in
the obtained molar mass from the expected values comes from, but I
don't think it can be fixed by using a discrete Lamm equation
solution. I would suggest to double-check in a concentration series
that the c(s) peak does not change position with concentration.
Studying this problem with sedimentation equilibrium will have the same
requirement of using a concentration series making sure that the
highest species remains sufficiently populated (via mass action law),
otherwise the result will also be an average over the populations seen
in the radial range of data analysis.<br>
<br>
Also, more basic, I think it is important to look carefully at the
temperature equilibration (in particular with the run being done at 8
C), and the effect of temperature and buffer composition on density and
viscosity. And as I said above, it is essential that the fit is good,
otherwise this indicates that something is wrong and one can't trust
very much the numbers coming from the fit.<br>
<br>
Best regards,<br>
Peter Schuck<br>
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