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<div>Hi Tara,</div>
<div><x-tab> </x-tab>The
choice to use the sequence molecular weight is the correct one.
I think that if you had had significant amounts of other species
present (monomer or aggregates), the plots would have exhibited
noticeable curvature. I would say that the error you do have is
quite small given the potential sources of error. For example, an
error in v-bar gets nearly tripled in the calculation. Is your density
correct? An error in radial calibration could also contribute. Did you
run at other loading concentrations and did you get the same results
at each concentration? How many times have you repeated this run. Do
you have an idea what the run-to-run error is? You may find that 4.8%
is not too far from the error expected.</div>
<div><br></div>
<div>The value of sigma you used here looks to be about 1.2 (cm^-2);
At sigmas this low you cannot expect to get much
resolution/fractionation and, therefore, it becomes extremely
difficult to fit to a unique model. This is because, at sigmas below
about 2.0, the three parameters, simga, ln(A1) and delta are highly
cross correlated. Although you didn't fit for delta, if you force it
to a particular value, (zero for example), that is in error, the other
parameters, sigma and ln(A1), will compensate to give a very good fit.
At sigmas below 1.0 , what you get is something like, but not exactly,
a weight average for the sample.</div>
<div><br></div>
<div>My suggestion would be to run this sample at three loading
concentrations at several speeds at higher sigmas like 2,3 and 4 and
perform a global fit. The higher sigmas will give you better
fractionation/resolution between species, and the range of loading
concentrations will allow you to differentiate between reversible
interactions and heterogeneity should there be more than one species
present.</div>
<div><br></div>
<div>Walter</div>
<div><br></div>
<div>At 4:22 PM -0700 10/13/04, John Philo wrote:</div>
<blockquote type="cite" cite><font size="-1"
color="#0000FF">Tara,</font></blockquote>
<blockquote type="cite" cite> </blockquote>
<blockquote type="cite" cite><font size="-1" color="#0000FF">You are
making the graphs correctly, but your own statements about your
results show why these lines have different slopes. When you use the
sigma calculated by SEDNTERP using the sequence mass for a trimer,
then your graph will give a line corresponding to that sequence mass.
However, you said that the fit from NONLIN corresponds to a molecular
mass that is 4.8% different from the sequence mass for trimer, and
one can easily see a 4.8% difference in slope on such a graph. So
yes, of course, the line using the NONLIN result goes through the data
very well (by definition if it is a good fit), and the line using the
sequence mass won't go through the data as well because your
data don't actually correspond to the molecular mass for pure
trimer.</font></blockquote>
<blockquote type="cite" cite> </blockquote>
<blockquote type="cite" cite><font size="-1" color="#0000FF">If you
are trying to show the expected slopes that correspond to trimer,
dimer, and tetramer then you should use the values based on the known
monomer mass. But fundamentally the graph isn't coming out like the
published results because your data is telling you the sample is not
pure trimer (unless the vbar or density are way off, but presumably
you are using the same vbar as the other labs
used).</font></blockquote>
<blockquote type="cite" cite> </blockquote>
<blockquote type="cite" cite><font size="-1" color="#0000FF">You
didn't say whether the NONLIN result is above or below the
expected trimer mass. If it is below, it might simply be because
at the concentration you used there is significant reversible
dissociation to monomer (perhaps the other labs were plotting data
taken at a higher concentration, where the fraction monomer is very
low). If the concentrations are similar, and your mass is low, I'm
going to guess your sample is a mixture of trimer and some denatured
'incompetent monomer' that cannot associate to form trimers. On the
other hand, if NONLIN says the average mass is above that for trimer,
your sample probably contains some aggregate.</font></blockquote>
<blockquote type="cite" cite> </blockquote>
<blockquote type="cite" cite><font size="-1" color="#0000FF">'Hope
this helps,</font></blockquote>
<blockquote type="cite" cite> </blockquote>
<blockquote type="cite" cite><font size="-1" color="#0000FF">John
Philo</font></blockquote>
<blockquote type="cite" cite><font size="-1" color="#0000FF">Alliance
Protein Laboratories</font><br>
<blockquote><font face="Tahoma" size="-1">-----Original
Message-----<br>
<b>From:</b> rasmb-admin@server1.bbri.org
[mailto:rasmb-admin@server1.bbri.org]<b> On Behalf Of</b> Tara
Suntoke<br>
<b>Sent:</b> Wednesday, October 13, 2004 10:48 AM<br>
<b>To:</b> rasmb@server1.bbri.org</font></blockquote>
<blockquote><font face="Tahoma" size="-1"><b>Subject:</b> [RASMB]
graphing AUC data</font><br>
<font face="Tahoma" size="-1"></font></blockquote>
<blockquote>Hi all,</blockquote>
<blockquote>I am fairly new to AUC and have a question about Sednterp
and graphing AUC data.</blockquote>
<blockquote> </blockquote>
<blockquote>I spun a peptide that is a clean trimer- other people have
published the same result for the same peptide. I think the data
is good for the following reasons: the residuals are random, the
data fits best to a single species, and has a square root of variance
of 5.9 e-3. In addition, the molecular weight I get from the
experiment, (24.8kD for the trimer) is within 4.8% of the
calculated MW in Sednterp (based on composition).</blockquote>
<blockquote> </blockquote>
<blockquote>I am trying to make a graph of ln(A) vs. r^2, and show
that the peptide corresponds to a trimer and not a dimer or tetramer.
In order to graph the lines of the dimer, trimer, and
tetramer, I used the equation of a line as follows:</blockquote>
<blockquote> </blockquote>
<blockquote>ln(A) = (sigma)(r^2) + ln(A1). I obtained the
constant ln(A1) from the WinNonlin program.</blockquote>
<blockquote> </blockquote>
<blockquote>My question is about which value of sigma I should use.
I can use the value of sigma obtained from Nonlin, which is based on
the data. Alternatively, I can use the sigma that Sednterp gives
me, based on the peptide composition and buffers. When making
these graphs however, the data fits exactly to the line for a trimer
which uses the Nonlin sigma, and doesn't exactly follow the slope of
the line that uses the Sednterp sigma. I understand that the
sigma obtained from Nonlin comes from the data, and perhaps that is
why it fits to the data well. On the other hand, the sigma from
Sednterp is calculated using density and partial specific volumes that
are close estimates, but aren't exact. (at least this is my
understanding so far...) So I am wondering which value of sigma
is appropriate to use.</blockquote>
<blockquote> </blockquote>
<blockquote>I'm not sure whether you will be able to see this at all,
but I have enclosed a PDF to show you the different results I get
using the different sigma values. In all the papers that use the
same peptide, people report graphs very similar to the lower one,
which uses sigma derived from Nonlin. The data always overlaps
the line for a trimer. However, it isn't clear how they
generated those graphs.</blockquote>
<blockquote> </blockquote>
<blockquote>I would greatly appreciate any advice you
have.</blockquote>
<blockquote> </blockquote>
<blockquote>Thanks for your help,</blockquote>
<blockquote> </blockquote>
<blockquote>Tara Suntoke</blockquote>
</blockquote>
<div><br></div>
<div><br></div>
<x-sigsep><pre>--
</pre></x-sigsep>
<div><font face="Times"
color="#0000FF"
>----------------------------------------------------------</font></div
>
<div><font face="Times" color="#0000FF">Walter Stafford</font></div>
<div><font face="Times"
color="#0000FF">mailto:stafford@bbri.org</font></div>
<div><font face="Times" color="#0000FF">direct dial:
617-658-7808</font></div>
<div><font face="Times" color="#0000FF">receptionist:
617-658-7700</font></div>
<div><font face="Times"
color="#0000FF"
>----------------------------------------------------------</font></div
>
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