Hi, 

I have been using Gromacs for my MD liquid simulations for about 2 years
now, and, of course, it has been working great!

Now, in the current part of my project, I am looking at liquid structure,
not dynamics.  Of course, one can analyze liquid structure by simply
analyzing an MD trajectory.  I have run into some difficulties with
sampling, however.  I could try some "special" sampling techniques (umbrella
sampling, replica exchange, etc.), but another thing that has been suggested
to me is to try Monte Carlo simulations.  Monte Carlo simulations, of
course, do not model dynamics, but since I'm only interested in structure at
this point, Monte Carlo might be a faster, less computationally expensive
way to do sampling of possible liquid structures/configurations.

It looks like, according to the Gromacs website, that a Monte Carlo
integrator is in the process of being implemented in Gromacs (maybe for
version 5.0 or so?).  If that is possible and will be funded, that would be
great, because I would just like to use my same force field, same parameters
as I have for my MD simulations--but just now I want to use Monte Carlo to
quickly generate (low-energy/high-probability) configurations.

But, until Monte Carlo is implemented in Gromacs, do you have any
suggestions of another package that I can use to do MC on my system?
Perhaps there is some MC package out there that is somewhat "similar" to
Gromacs, such that maybe I could write scripts to translate my system
topology from Gromacs to the MC package?  Do you have any experience or
advice on Monte Carlo simulations?

By the way, I hesitate to even ask questions like "when is this or that
feature going to be implemented in Gromacs?", because I know that the
development of Gromacs is a huge project and that many people are spending
lots of time and resources to continually add features!  I am not yet very
fluent in C/C++ and am not much of a programmer.  I am more of a
chemist/simulator.  So I just want to thank you all for all your work on
making Gromacs what it is!  

Thanks!

Andrew DeYoung
Carnegie Mellon University

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