[gmx-users] Umbrella sampling
gmelaugh01 at qub.ac.uk
Thu Mar 31 13:35:45 CEST 2011
Sorry I am not sure that I follow. Will the window with r0 =0.80 giving
the distribution centred around 0.78nm not drive my free energy profile
up. If I remove this window prior to running g_wham the free energy goes
down. Should I increase the force constant so that the mean of the
window is 0.80nm (bearing in mind that this is near the barrier region).
XAvier Periole wrote:
> You can present the data differently:
> you have two windows at 0.78 nm giving different distribution.
> That indicates these windows are not converged. Does not mean
> that the others (0.80 nm) are converged :))
> On Mar 31, 2011, at 12:20 PM, Gavin Melaugh wrote:
>> Hi Xavier
>> Thanks for the reply. With respect to your answer of my first query.
>> What if you had two windows practically on top of each other, but one
>> was not supposed to be there. e.g A window with r0 of 0.80 nm and
>> centred at 0.78 nm and a window with r0 of 0.78 nm centred at 0.78nm.
>> XAvier Periole wrote:
>>> On Mar 31, 2011, at 11:53 AM, Gavin Melaugh wrote:
>>>> Hi All
>>>> I have generated several PMF curves for the one system using umbrella
>>>> sampling. In the first part of the curve (barrier region) I use a high
>>>> force constant with small intervals between the windows. The latter
>>>> of the curve I use a lower force constant with larger window spacing.
>>>> Anyway I have a few issues that I need clarifying:
>>>> 1 - Can you have too much overlap between windows?
>>> no, there no such a thing of too much overlap :)) You could even put
>>> two identical windows with same 100% overlap ... no problem.
>>>> 2 - Does the distribution at each window have to centered around the
>>>> desired r0? (If not does this affect the free energy?)
>>> The deviation of the distribution from the r0 is what dictates the
>>> profile. The more away from the disired r0 the higher the free energy
>>> of the system.
>>>> 3- If you over sample one particular window, will it affect the curve?
>>> There is no such a thing of over sampling ... the only thing you can
>>> have is not enough sampling.
>>>> Many thanks
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