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<DIV><FONT face=新細明體 size=2>Dear Prof. Philo and Prof. Correia,</FONT></DIV>
<DIV><FONT face=新細明體 size=2></FONT> </DIV>
<DIV><FONT face=新細明體 size=2>After calculating the sw by the second moment
integration (by SEDFIT), I found sw is 6.4 at 0.15 mg/ml, 6.9 at 0.50 mg/ml and
7.2 at 1.00 mg/ml. Another isoform showed s = 5.5-5.8 at the same
concentration range. If I set s = 10.0 as the middle line, the c(s) curve area
larger than s = 10.0 is 9% at 0.15 mg/ml and that is 20% at 1.00 mg/ml.
Differently, another isoform didn't have this feature (14% at 0.15 mg/ml and 11%
at 1.00 mg/ml). I'm trying to use ultrascan II for the g(s) model
analysis ( although my free-trial has been out of date...). I attached a
pdf file including the results of ls-g*(s) model. Seems like no obvious
difference at the two concentration. However, the area larger than s = 10.0
is also higher (22%) at 1.00 mg/ml, compared with 14% at 0.15
mg/ml.</FONT></DIV>
<DIV><FONT face=新細明體 size=2></FONT> </DIV>
<DIV><FONT face=新細明體 size=2>I think it is truly a aggregating system. The
aggregating isoform didn't have any cysteine and the buffer didn't contain
any reducing agent like DTT or Beta mercaptoethanol. My buffer is PBS containing
150 mM NaCl, 20 mM phosphate and pH is 7.3.</FONT></DIV>
<DIV><FONT face=新細明體 size=2></FONT> </DIV>
<DIV><FONT face=新細明體 size=2>I've already give up trying to calculate the
individual "peaks". The difference of sw and the percentage of "pretty large"
aggregating species (s > 10.0) may be enough to make a conclusion about
the tendency. This structural feature can partial explain why one isoform is
pathgenic and the other is normal isoform.</FONT></DIV>
<DIV><FONT face=新細明體 size=2></FONT> </DIV>
<DIV><FONT face=新細明體 size=2>Recently, I've learned a lot from RASMB and think
this club is full of treasure ^^. Once again, thanks, everyone.</FONT></DIV>
<DIV><FONT face=新細明體 size=2></FONT> </DIV>
<DIV><FONT face=新細明體 size=2>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></FONT></DIV>
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style="PADDING-RIGHT: 0px; PADDING-LEFT: 5px; MARGIN-LEFT: 5px; BORDER-LEFT: #000000 2px solid; MARGIN-RIGHT: 0px">
<DIV style="FONT: 10pt 新細明體">----- Original Message ----- </DIV>
<DIV
style="BACKGROUND: #e4e4e4; FONT: 10pt 新細明體; font-color: black"><B>From:</B>
<A title=jcorreia@biochem.umsmed.edu
href="mailto:jcorreia@biochem.umsmed.edu">John Correia</A> </DIV>
<DIV style="FONT: 10pt 新細明體"><B>To:</B> <A title=ls890067@ndmctsgh.edu.tw
href="mailto:ls890067@ndmctsgh.edu.tw">ls890067@ndmctsgh.edu.tw</A> ; <A
title=rasmb@rasmb-email.bbri.org
href="mailto:rasmb@rasmb-email.bbri.org">rasmb@rasmb-email.bbri.org</A> </DIV>
<DIV style="FONT: 10pt 新細明體"><B>Sent:</B> Thursday, July 15, 2004 11:11
PM</DIV>
<DIV style="FONT: 10pt 新細明體"><B>Subject:</B> Re: [RASMB] Re: RASMB digest, Vol
1 #319 - 5 msgs</DIV>
<DIV><BR></DIV>
<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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--------------------------------------------------------------------------<BR>--------<BR>><BR>>
> 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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