Dear Yu,
In addition to what Dave was telling you, after to get a good
initial classically equilibrated system at each window, you can proceed
with the usual US methodology, with an initial QM/MM-MD equilibration to
relax your QM region and environment. That could be done directly using
DFT or another possibility could be with a semi-empirical trajectory
first followed by the final DFT equilibration to obtain a progressive
adaptation of your system to its environment. This initial equilibration
will depend of your system but could be from 0.5 up to 2 ps (in case of
DFT) or much more if you finally decide to go through semi-empirical
QM/MM-MD approach.
Of course ab initio DFT calculations are much more expensive than
semi-empirical PM6DH+ which will force you to produce much shorter MD
production trajectories at each windows (may be about 4-8 ps, depending
on the complexity of your QM system) but with a much better description
of your chemical interactions in the QM region. Thus it will depends
again in what you want to learn with this dynamics in order to apply one
or other approximations.
I hope that it will helps,
Juan Torras
El 13/11/18 a les 02:17, 郭昱 ha escrit:
> Dear everyone,
>
> I'm trying to run a QM/MM umbrella sampling with amber.
> In the AMBER Advanced Tutorial 17 for umbrella sampling, the author first run a 2000 step minimization then a 50ps NPT equilibration before production run.
> But my QM region include 80 atoms, 50ps NPT equilibration would cost me a long time if I use DFT method. So in a attempt I make, I only run a 1ps NPT equilibration with PM6DH+. Although I got what I want, but I do not know if I'm making mistake shorten the NPT run.
>
> So, my question is, before a QM/MM MD production run, can I just run a minimization and NPT equilibration as in http://ambermd.org/tutorials/advanced/tutorial17/section2.htm ? If I can, how long should a equilibration run take? If I can not, what procedure should I take?
> I'd be very thankful if anyone can answer my question or tell me where to look for the answers.
> Thanks for reading.
>
> best wishes,
> Yu
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Received on Mon Nov 12 2018 - 18:30:03 PST
