Re: Determining Transition State from an Unfolding Simulation

From: Neelanjana Sengupta (senguptan_at_gmail.com)
Date: Wed Sep 26 2007 - 10:44:58 CDT

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 random
coil 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 characterized
is 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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