From: Peter Freddolino (petefred_at_ks.uiuc.edu)
Date: Wed Sep 26 2007 - 23:12:43 CDT
Richard,
If you define a transition state as a local maximum in free energy along
a reaction coordinate (as discussed elsewhere in the thread, eg by
Lewyn), there will be a finite number of transition states on any
reasonable pathway. This picture is almost certainly overly simplistic
for (say) protein folding/unfolding due to the presence of multiple
distinct pathways and low-lying intermediates, but in principle can be a
useful way of looking at things, and is the truest (as far as I can
tell) to the usual definition of "transition state".
Peter
Richard Wood wrote:
> Looking at it this way, then between EVERY step is a "transition"
> state, and that is not correct. Thus, a process would have an
> infinite number of transitions states.
>
> 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: Lewyn Li <lewynli_at_gmail.com>
> To: Richard Wood <rwoodphd_at_yahoo.com>
> Sent: Wednesday, September 26, 2007 4:32:33 PM
> Subject: Re: namd-l: Determining Transition State from an Unfolding
> Simulation
>
> Hi all,
>
> A transition state (ensemble), in a simple 2-state reaction,
> refers to the state(s) at the top of the free energy barrier. In this
> case, it would have ~0.5 probability of falling into either stable
> state basins.
>
> If you break a multi-step reaction into a series of 2-state
> reactions, that the number of "arrows" would equal (in a simplistic
> way) the number of transition state (ensembles).
>
> If we understand Prabhu's comment in this way, then he is right.
>
> I think a (perhaps more) important question is: is the transition
> state picture applicable to a complex system such as proteins?
>
>
> LEWYN
>
> On 9/26/07, * Richard Wood* <rwoodphd_at_yahoo.com
> <mailto:rwoodphd_at_yahoo.com>> wrote:
>
> 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 <mailto:rwoodphd_at_yahoo.com>
>
> ----- Original Message ----
> From: E. Prabhu Raman <eraman_at_gmu.edu <mailto:eraman_at_gmu.edu>>
> To: Neelanjana Sengupta < senguptan_at_gmail.com
> <mailto:senguptan_at_gmail.com>>
> Cc: Arun Krishnan <krishnan_at_ttck.keio.ac.jp
> <mailto:krishnan_at_ttck.keio.ac.jp>>; namd-l_at_ks.uiuc.edu
> <mailto: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
> <mailto: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
> <mailto: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
> <mailto: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
> <mailto: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
> <mailto: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
> <mailto: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
> <mailto:krishnan_at_ttck.keio.ac.jp>
> > > > URL: http://www.iab.keio.ac.jp/~krishnan
> <http://www.iab.keio.ac.jp/%7Ekrishnan>
> > > > **********************************************
> > > >
> > >
> >
> >
> >
> > --
> >
>
>
>
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