From: Richard Wood (rwoodphd_at_yahoo.com)
Date: Wed Sep 26 2007 - 15:30:58 CDT
Hi all,
I think the two of you are confused.
Let's say I have a process D->M1->M2->N. In this process, the arrows represent TRANSITIONS and the M1 and M2 represent states of the system. Thus, there are THREE TRANSITIONS, but only TWO TRANSITION STATES (caps for emphasis).
HTH,
Richard
Richard L. Wood, Ph. D.
University of Minnesota
Dept. of Medicinal Chemistry,
College of Pharmacy
717 Delaware St. SE
Minneapolis, MN
55414-2959
rwoodphd_at_yahoo.com
----- Original Message ----
From: E. Prabhu Raman <eraman_at_gmu.edu>
To: Neelanjana Sengupta <senguptan_at_gmail.com>
Cc: Arun Krishnan <krishnan_at_ttck.keio.ac.jp>; namd-l_at_ks.uiuc.edu
Sent: Wednesday, September 26, 2007 1:24:03 PM
Subject: Re: namd-l: Determining Transition State from an Unfolding Simulation
Neelanjana: As per my understanding, Transition states are defined as short lived states that the system passes, when going from a stable (or matastable) state to another. For example: If a system posseses a denatured, two metastable and a native state. Then you end up having 3 transition states denoted by arrows here: (D->M1->M2->N).
I think the difference between what we both are suggesting is simply that I call the transition states as the arrows(->) wheras you call them as M1 and M2(This I gather from your suggestion of 'catching' the metastable states by looking at stabilized quantities during the kinetics run).
Thanks for sharing your thoughts.It would be interesting if others can comment too.
-Prabhu
E.Prabhu Raman
Ph.D Student, Bioinformatics & Computational Biology
George Mason University
----- Original Message -----
From: Neelanjana Sengupta <senguptan_at_gmail.com>
Date: Wednesday, September 26, 2007 11:44 am
Subject: Re: namd-l: Determining Transition State from an Unfolding Simulation
> On 9/26/07, E. Prabhu Raman <eraman_at_gmu.edu> wrote:
> >
> > Neelanjana:
> > >see if it is stable over an extended period of time.
> > > If you
> > > find that the energy is stable too, then you "may" think that
> you have
> > > encountered a transition state. However, a lot of caution is
> > > required in
> > > your treatment...
>
>
> Hi,
>
> Lets say the protein traverses along its folding pathway (from the
> randomcoil to the natively folded form). If you look at the protein
> folding'funnel', the conformer goes through multiple 'metastable'
> conformers,before finding its way to the most stable form. These
> states could also be
> 'transition states', right? (One such state that has been well
> characterizedis the molten globule form). They are metastable. They
> are trapped in local
> minima before they get enough energy to jump the barrier to move to
> a more
> stable state. These were the states I was referring to... please
> let me
> know your thoughts.
>
> Best,
> Neelanjana
>
>
> I do not understand your point of finding a stable state. During a
> constant> temperature run, the transition state will be populated
> for a "short" time
> > right? (as by definition the transition state is the maximum of
> Free energy
> > as a function of the reaction coordinate) Then why are we
> detecting a stable
> > state? (I think by this, we will end up detecting the equilibrium
> state at
> > the simulation temperature and not the transition state)
> >
> > Arun: You have complete unfolding trajectory right? i.e you start
> from a
> > fairly folded state and end at a unfolded state where most native
> contacts> are lost ? Because if the trajectory is not complete,
> then detecting the
> > transition state(s) using snapshots showing steep buildup of
> reaction> coordinate might not be right.
> >
> > -Prabhu
> >
> > E.Prabhu Raman
> > Ph.D Student, Bioinformatics & Computational Biology
> > George Mason University
> >
> > ----- Original Message -----
> > From: Arun Krishnan <krishnan_at_ttck.keio.ac.jp>
> > Date: Wednesday, September 26, 2007 0:56 am
> > Subject: Re: namd-l: Determining Transition State from an Unfolding
> > Simulation
> >
> > > Hi Prabhu and Neelanjana,
> > >
> > > Thanks for your inputs... Shall try them out and let you know what
> > > I get. To
> > > answer Neelanjana's point, yes, my unfolding simulation does seem
> > > to follow
> > > the same pathway as has been shown in literature... so am fairly
> > > confidentabout it being right.
> > >
> > > Cheers,
> > >
> > > Arun
> > >
> > > On 9/24/07, E. Prabhu Raman <eraman_at_gmu.edu> wrote:
> > > >
> > > > Using Snapshots of a trajectory of Kinetics simulation at a
> constant> > > temperature, a method called Progress Variable
> Cluster has been
> > > used to
> > > > pin-point the structures of the transition state ensemble(TSE).
> > > > REF : Chemical Physics Volume 307, Issues 2-3, 27 December 2004,
> > > Pages> 251-258
> > > > The basic idea being that the passage through the transition
> > > state can be
> > > > identified by the time-point(s) that record a maximal change in
> > > a suitable
> > > > reaction coordinate (example Rg, or number of native contacts)
> > > > However,I WOULD CAUTION that this approach,to my best knowledge
> > > has been
> > > > tried for Coarse Grained Model folding studies and more
> importantly> > > lots(~100) of independent trajectories were used
> to get a
> > > picture of the
> > > > TSE.
> > > > I assume that you might not have too many unfolding
> > > trajectories. But
> > > > since this procedure is easy to apply, you can try it out and
> > > compare your
> > > > TSE from any experimental available data(phi-values).
> > > > The reference given above uses a clustering algorithm to cluster
> > > similar> structures. A first pass at TSE determination could be
> > > not to cluster, but
> > > > simply pick out the structures that record the steepest
> > > buildup(or down) of
> > > > the reaction coordinate and look at the structures to see if it
> > > is any
> > > > meaningful at all.
> > > >
> > > > Best
> > > > Prabhu
> > > >
> > > > E.Prabhu Raman
> > > > Ph.D Student, Bioinformatics & Computational Biology
> > > > George Mason University
> > > >
> > > > ----- Original Message -----
> > > > From: Neelanjana Sengupta <senguptan_at_gmail.com>
> > > > Date: Sunday, September 23, 2007 7:33 pm
> > > > Subject: Re: namd-l: Determining Transition State from an
> Unfolding> > > Simulation
> > > >
> > > > > Hi,
> > > > >
> > > > > This would work (if at all) assuming your unfolding pathway
> > > > > retraces the
> > > > > protein folding pathway. If you figure out a way to
> determine if
> > > > > this is
> > > > > what is going on (figuring this out would indeed be non-
> trivial),> > > > you may
> > > > > then closely examine the timeline of a unfolding parameter
> > > (Rg, for
> > > > > instance) and see if it is stable over an extended period
> of time.
> > > > > If you
> > > > > find that the energy is stable too, then you "may" think that
> > > you have
> > > > > encountered a transition state. However, a lot of caution is
> > > > > required in
> > > > > your treatment...
> > > > >
> > > > > Would be great if others share their thought too!
> > > > >
> > > > > Cheers,
> > > > > Neelanjana
> > > > >
> > > > > On 9/23/07, Arun Krishnan <krishnan_at_ttck.keio.ac.jp> wrote:
> > > > > >
> > > > > > Hi All,
> > > > > >
> > > > > > Is there a way to calculate the transition state
> structure from
> > > > > Unfolding> data? From the plot of RMSD vs time maybe?
> > > > > > Or is there some other way? Any pointers would be much
> > > appreciated.> > >
> > > > > > Cheers,
> > > > > >
> > > > > > Arun
> > > > > >
> > > > > >
> > > > > >
> > > > >
> > > > >
> > > > > --
> > > > >
> > > >
> > >
> > >
> > >
> > > --
> > > ***********************************************
> > > Arun Krishnan, Ph.D,
> > > Assistant Professor,
> > > Institute for Advanced Biosciences,
> > > Keio University,
> > > Center Building,
> > > Tsuruoka, Yamagata 997-0035
> > > Japan
> > > Phone: +81 (0)235-29-0824
> > > Email: krishnan_at_ttck.keio.ac.jp
> > > URL: http://www.iab.keio.ac.jp/~krishnan
> > > **********************************************
> > >
> >
>
>
>
> --
>
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