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<DIV><FONT size=2>Chi-Yuan </FONT></DIV>
<DIV><FONT size=2></FONT> </DIV>
<DIV><FONT size=2>It is always helpful to make composite plots of the c(s) or
g(s) distributions so you can directly see the presence or I think in this case
the absence of concentration dependence. Some people like to normalize the
plots by dividing by the area under the total curve. Make both those
composite plots and look at the data and tell us again what you see! The
extra stuff at larger s is most likely just a sensitivity issue, you see it
because you raised the concentration of all aggregates. This does display
the amazing ability of AUC to fractionate broad distributions.</FONT></DIV>
<DIV><FONT size=2></FONT> </DIV>
<DIV><FONT size=2>I ask again - reducing agent? cys in the sequence?
</FONT></DIV>
<DIV><FONT size=2></FONT> </DIV>
<DIV><FONT size=2>If this had really been a reversibly interacting system, why
would you expect to see peaks? c(s) has a tendency to make peaks, even for
reacting boundaries. It is the tendency to over interpret those peaks that
one must guard against. Others have pointed out the amazing ability of
c(s) to see small amounts of aggregates, something of special interest in the
biotech area. In this case the peaks in fact suggest even the major
species are aggregates.</FONT></DIV>
<DIV><FONT size=2></FONT> </DIV>
<DIV><FONT size=2>After all the discussion about how to use sedfit and analysis
of distributions, what did you expect to learn from integrating these
peaks?</FONT></DIV>
<DIV><FONT size=2></FONT> </DIV>
<DIV><FONT size=2></FONT> </DIV>
<DIV><BR><BR>>>> "medakachou" <ls890067@ndmctsgh.edu.tw> 07/14/04
10:16PM >>><BR>Dear RASMB,<BR><BR>I attached a pdf file
(distribution.pdf) containing c(s) distribution plot<BR>at high and low protein
conecentration. The parameters are included, also<BR>the rmsd, f/f0, residual
bitmap. p = 0.68 and the resolution is 250 (smin to<BR>smax is 0.1 to 25).
Thanks everyone's comments and suggestion.<BR><BR>Chi-Yuan Chou<BR>PhD student,
the Institutes of Life sciences, National Defense Medical<BR>Center, Taipei,
Taiwan<BR>e-mail: r6243023@yahoo.com.tw<BR>Lab homepage: <A
href="http://www.enzkin.org/">http://www.enzkin.org/</A><BR><BR>----- Original
Message ----- <BR>From: "John Correia"
<jcorreia@biochem.umsmed.edu><BR>To: <ls890067@ndmctsgh.edu.tw>;
<rasmb@server1.bbri.org><BR>Sent: Thursday, July 15, 2004 6:45
AM<BR>Subject: Re: [RASMB] Re: RASMB digest, Vol 1 #319 - 5 msgs<BR><BR><BR>>
Isolating the main peak, reconcentrating the sample, and generating the<BR>>
same distribution suggests reversibility, the classic test, although its<BR>>
not clear what a 10 peak pattern means? Discrete peaks suggest<BR>>
irreversible aggregates. Is there reducing agent in the buffer? Cys
in<BR>> the protein?<BR>><BR>> What optical system and how good are the
fits, rms values? c(s) can<BR>> get more peaky with very low
noise levels & apparently low p values - I<BR>> personally only do
.95. I always check c(s) distributions with g(s),<BR>> although for a
broad distribution g(s) may be hard to apply.<BR>> Alternatively what do the
Ls-g(s) distributions look like? Ultimately I<BR>> plot c(s) and g(s)
as a function of concentration to develop hypotheses<BR>> about the
data. The shape of the conc dependence of the boundaries is<BR>> often
informative, although I would never fit a c(s) or Ls-g(s)<BR>> distribution
shape to extract molecular information. Maybe a g(s) since<BR>> if
properly done its the derivative of the boundary.<BR>><BR>> Then I go to
direct boundary fitting, individually & globally - in my<BR>> case
Sedanal but sedfit/sedphat can work depending upon the model.<BR>> Years ago
(the 70's) there was a lively, but non email (didn't exist),<BR>> discussion
about fitting raw data vs smoothed data or extracted moments<BR>> - many
methods give similar answers, but if possible always fit the raw<BR>> data
directly.<BR>><BR>> So if your system is a broad but reversible
distribution what are the<BR>> options? Indefinite? You are
describing big shifts? You need to<BR>> establish endpoints, the s
value of the monomer and the endpoint of the<BR>> association, if there is
one? Integrate the entire distribution and<BR>> plot weight average S
vs concentration. Remember the behavior of a<BR>> simple titration
experiment, you need at least two orders of magnitude<BR>> to go from 10% to
90% saturation. Plot the data vs log conc. Does it<BR>> look like
a binding curve and does it saturate? To go higher in c try<BR>> the
0.3 mm path centerpieces, you can gain a factor of 5 in<BR>>
concentration. Try 230 nm or interference to go lower, or can you<BR>>
estiamte s1 from the other isoform's data?<BR>><BR>> Without seeing the
data or the actual distributions it is hard to
know!<BR>><BR>><BR>><BR>>
-------------------------------------------------------------------<BR>>
Dr. John J. "Jack" Correia<BR>> Department of
Biochemistry<BR>> University of Mississippi Medical
Center<BR>> 2500 North State Street<BR>> Jackson, MS
39216<BR>> (601) 984-1522<BR>> fax (601)
984-1501<BR>> email address: jcorreia@biochem.umsmed.edu<BR>>
homepage location: <A
href="http://biochemistry.umc.edu/correia.html">http://biochemistry.umc.edu/correia.html</A><BR>>
dept homepage location: <A
href="http://biochemistry.umc.edu/">http://biochemistry.umc.edu/</A><BR>>
-------------------------------------------------------------------<BR>><BR>><BR>><BR>>
>>> "medakachou" <ls890067@ndmctsgh.edu.tw> 07/13/04 11:38 PM
>>><BR>>
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> Date: Tue, 13 Jul 2004 10:59:00 -0500<BR>> > From: "John Correia"
<jcorreia@biochem.umsmed.edu><~!B*+R^&>> To:<BR>>
<jphilo@mailway.com>,
<r6243023@ms48.hinet.net>,<~!B*+R^&>><BR>>
<arthur.rowe@nottingham.ac.uk>,
<rasmb@server1.bbri.org><~!B*+R^&>><BR>> Subject: Re:
[RASMB] difference of p = 0.95, 0.68 and 0.55, the<BR>> > confidencelevel
in the sedfit c(s) distributi<BR>> ><BR>> > This is a MIME message.
If you are reading this text, you may want to<BR>> > consider changing to
a mail reader or gateway that understands how to<BR>> > properly handle
MIME multipart messages.<BR>> ><BR>> >
--=__Part0E2FB7D4.3__=<BR>> > Content-Type: text/plain;
charset=US-ASCII<BR>> > Content-Transfer-Encoding: 7bit<BR>>
><BR>> > One problem I have with these discussions is they are method
of<BR>> analysis<BR>> > focused and until Arthur's illustion to "know
your system" not focused<BR>> > on the molecules, the mechanism, the
interactions. Were we just<BR>> talking<BR>> > about one run and
one concentration or a series of conectrations? Why<BR>> > do you
want to integrate? Are the "peak" positions constant or do<BR>>
they<BR>> > change with concentration? Is this in fact an impure
system of<BR>> > nointeracting species or aggregates, or are these
aggregates of a<BR>> single<BR>> > component? Is there any
reversible interaction going on?<BR>> ><BR>> > The goal is to
describe your system in molecular and mechanistic terms<BR>> > and then
fit the data individually & globally to that model to prove<BR>>
the<BR>> > hypothesized mechanism. Statistics, assumptions,
simulations are all<BR>> > important. Now what is going on in your
system?<BR>><BR>> Dear John,<BR>><BR>> Yes,
I should give more information about my case. I expressed and<BR>> purified a
34 kDa protein and it's N-terminal or C-terminal truncated<BR>> fragments by
E. coli expression system. The protein purity is > 99% by<BR>>
SDS-PAGE. This protein has two isoforms. I study them in three<BR>>
different<BR>> concentration: 0.15, 0.50 and 1.00 mg/ml in PBS (pH7.3). By
using<BR>> sedimentation velocity and c(s) distribution analysis, I found
one<BR>> isoform's<BR>> N-terminal truncated fragments showed a 10 "peaks"
pattern whose s is<BR>> from 3<BR>> to 23 at 1.00 mg/ml. While at 0.15
mg/ml, only 5 peaks were found at s =<BR>> 3<BR>> to 12. It means it
should be a single component aggregation and is<BR>> concentration-dependent.
The other isoform didnot show this<BR>> characteristics.<BR>> I want to
give my paper some quantitative data about this difference, so<BR>> I<BR>>
chose "Origin peak fitting module" and analyzed the pattern of gaussian<BR>>
peaks. The reviewer thought it is overinterpretation (about the<BR>>
fused-"peaks") and suggested me lowering the cinfidence level to p =<BR>>
0.7.<BR>> I've tried and found the resolution is better (every "peaks" is
still<BR>> existed). These two days I've tried Jack Lebowitz's comment and
gained<BR>> some<BR>> quantitative data. I'm going to compare them and
hope it can make my<BR>> paper<BR>> more quantitative
sound.<BR>> By the way, while I isolated the major
"peak" species by using<BR>> gel-filtration chromatography (S-300 column) and
concentrate them (I<BR>> need<BR>> higher concentration), It just change
back to the same "multi-peaks"<BR>> situation (by sedimentation velocity). I
think it's not a<BR>> non-interacting<BR>> but a associating system,
right? Thanks your help.<BR>><BR>> Chi-Yuan Chou<BR>> PhD student, the
Institutes of Life sciences, National Defense Medical<BR>> Center, Taipei,
Taiwan<BR>> e-mail: r6243023@yahoo.com.tw<BR>><BR>><BR>><BR>>
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