On 2/14/13 10:21 AM, Sebastien Cote wrote:

Dear Justin,
I am not sure to follow you. You essentially say that it is better to avoid 
using implicit solvent i.e. the generalized Born-formalism implemented in 
GROMACS?
For the case of optimizing and relaxing a system (expecting short MD), I agree 
that it might be preferable to use explicit solvent.
But for some systems, such as the oligomerization of a protein from a random 
state, explicit solvent can make this problem intractable in MD (inefficient 
sampling of conformational space due to too many degrees of freedom from the 
solvent) or REMD (too many processors to use due to too many degrees of 
freedom).
I saw some tutorials and workshops suggesting larger cutoffs when using 
implicit solvent as the non-bonded function do tend to zero at long range. 
Then, domain decomposition can be used over particle decomposition.
Could you clarify your point please? Especially, your statement saying that : "you 
can only run on 1-2 processors in implicit solvent".

There is an existing limitation in Gromacs, related to constraints, that causes the implicit solvent code to fail when run on CPU if you try to use more than 2 processors. It is my understanding that someone (probably Berk) is working on a better fix than what is in place now. DD does not work with nonperiodic unit cells and simple grid searches; you have to use particle decomposition. Therein lies another limitation. I have found that only infinite cutoffs (i.e. rlist=rcoulomb=rvdw=0) lead to stable simulations, while any finite cutoff (even several nm in length) leads to poor energy conservation and unstable trajectories.

You can use GPU acceleration for implicit solvent simulations via OpenMM, but support for this feature is minimal, at best, at the present time.

Please do not take my comments as a criticism of implicit solvent methods; they are perfectly useful for a number of cases.

-Justin

--
========================================

Justin A. Lemkul, Ph.D.
Research Scientist
Department of Biochemistry
Virginia Tech
Blacksburg, VA
jalemkul[at]vt.edu | (540) 231-9080
http://www.bevanlab.biochem.vt.edu/Pages/Personal/justin

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