**From:** Jrme Hnin (*jhenin_at_ifr88.cnrs-mrs.fr*)

**Date:** Fri Jan 27 2012 - 09:10:44 CST

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Dear Ajasja,

2012/1/27 Ajasja Ljubetič <ajasja.ljubetic_at_gmail.com>:

*>> If you model the unbiased process as 2D diffusion on an effective
*

*>> potential (i.e. the PMF), then ABF will (in time) erase the barriers, but
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*>> not change the intrinsic diffusion properties.
*

*>
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*> Actually what I would like to do now is to model the (unbiased) dynamic
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*> behaviour of my colvars.
*

That is an intrinsically difficult question. A couple of colleagues

have been thinking hard about it for a while now, and they still don't

have a clear answer. For now, I would say that using ABF (and the

whole family of biased methods) essentially means that you give up on

getting dynamical information.

*> I would like to know how far my colvars move in 10
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*> ns. I plan to preform a random walk on the obtained PMF, where each step
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*> will be accepted according to the Metropolis criterion (ie the probability
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*> of accepting the step is min(1,exp(dE/(kT)))). Since such simulations are
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*> computationaly extremely cheap I could get excellent sampling.
*

Sampling, certainly, but you already have that from ABF. And those

simulations would not give you access to any kind of accurate

dynamics. You might think of a kind of diffusive dynamics, using

diffusion coefficients to be determined (see below).

*> The only
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*> thing I have to figure out is what is the (real) time of one step is. Am I
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*> correct in guessing that it is proportional to
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*> the autocorrelation time obtained from the colvars trajectory?
*

In a sense, yes, since that would be related to the diffusion

coefficient. There are several ways to access that, but I have to warn

you to be wary of the suitability of the dynamical model to begin

with.

The only serious attempt I have made to go back to dynamics based on

ABF results was in the glycerol-in-GlpF work:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2186255/

There is an attempt at predicting a mean first passage time, and

hence, the channel conductance - I am not really convinced about that

particular result. The method we used to get position-dependent

diffusion coefficients is from Gerhard Hummer, it is particularly

simple and effective.

If at all possible, I'd recommend getting dynamical data from unbiased

simulations.

Cheers,

Jérôme

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