Thank you very much Prof. David Case for the valuable insight. But I should
also ask wouldn't performing an equilibration even for a longer period of
time does actually samples conformational changes? And on visualizing a
rmsd its always increasing or decreasing after a certain conformational
change? So then how would one argue that the system has attained equilibria
rather than "an equilibria"?
Regards,
On Mon, Jun 18, 2018 at 6:18 PM, David A Case <david.case.rutgers.edu>
wrote:
> On Mon, Jun 18, 2018, senal dinuka wrote:
> >
> > I am writing here hoping for a clarification. I understand that doing
> > minimization is to reduce bad contacts. And equilibration is mainly to
> give
> > velocities given that system is per-heated to a certain temperature. So
> is
> > it appropriate only to run few ns of equilibration so that the density is
> > converged and move on to about 100-150ns of production phase?
>
> Equilibration also allows the system to relax from its starting
> configuration into the ensemble of configurations favored by the force
> field. Depending on the size and floppiness of your system, and on the
> quality of your starting configuration, this can take a long time. A
> key parameter is the height of the free energy barriers that separate
> various parts of conformational space.
>
> How long to "equilibrate" is a complex function of the nature of your
> system, how important it is that you are sampling at equilibrium, how
> you are planning to use the results, and how much computing power you
> have available.
>
> I recognize that this is all rather vague, but the answer really depends
> on your system. A small and fairly rigid molecule in water should reach
> equilibrium in tens of nanoseconds or less. I have seen (folded) proteins
> where the average structure was still drifting after several hundred
> nanoseconds. But be aware the "equilibration" is not the only goal in
> most simulations: in "production" (almost?) no biomolecular simulations
> every done actually sample the full equilibrium configuration space.
>
> So, one should try to design simualtions that can provide useful
> information within the constraints of available computational power.
> I like emphasize the goal of making it likely that one could learn
> something new, that is, to get more information out of the simulation than
> goes into it.
>
> ....dac
>
>
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--
D L Senal Dinuka
Grad.Chem., A.I.Chem.C.
Research Assistant
College of Chemical Sciences
Institute of Chemistry Ceylon
Rajagiriya
Sri Lanka
+94 77 627 4678
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Received on Mon Jun 18 2018 - 09:00:02 PDT
