**From:** Jérôme Hénin (*jerome.henin_at_ibpc.fr*)

**Date:** Fri Aug 27 2021 - 07:05:16 CDT

**Next message:**René Hafner TUK: "Re: eABF 3D sampling using distance Colvars + X and Y: averaged PMF difference to 1D sampling"**Previous message:**Mohammad Mehdi Pirnia: "Error: psfgen) unknown atom type H"**In reply to:**René Hafner TUK: "Re: eABF 3D sampling using distance Colvars + X and Y: averaged PMF difference to 1D sampling"**Next in thread:**René Hafner TUK: "Re: eABF 3D sampling using distance Colvars + X and Y: averaged PMF difference to 1D sampling"**Reply:**René Hafner TUK: "Re: eABF 3D sampling using distance Colvars + X and Y: averaged PMF difference to 1D sampling"**Messages sorted by:**[ date ] [ thread ] [ subject ] [ author ] [ attachment ]

Hi René,

----- On Aug 26, 2021, at 8:52 PM, René Hafner TUK <hamburge_at_physik.uni-kl.de> wrote:

*> Hi Jérôme!
*

*>> The way I extract it was to run second abf instance with only the
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*>> distanceFromMembrane colvar that is **not** applied.
*

*>> Which turned out to be the same as when just weighting the zgrad(x,y,z) by the
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*>> respective counts and average over X,Y.
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*>> But we were wondering whether this is the correct way.
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I don't think that is correct, because the simulation is biased in the directions X and Y, so you are not computing an unbiased average at each z value.

*>> I even tried an easier setup with an almost flat membrane surface where I can
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*>> compare results to a simple distanceZ variable.
*

*>> Here the distanceMin 1D case returns 4.6 (+. 0.1) kcal/mol (same as distanceZ)
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*>> the 3D case returns dG = 4.3 (+- 0.1) kcal/mol (with the above assumption)
*

*>> Though what you suggest is to calculate the marginal distribution via the
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*>> following?
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Just an integral instead of an average:

*>> What I additionally needed to do in order to gain a smooth curve here was to
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*>> weight every grid point by its counts (such that "bad" guesses with low counts
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*>> get suppressed). But I am not yet the sure the scale is correct.
*

With the expression above you won't need to worry about that.

Jérôme

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