Re: Alchemical FEP simulation

From: Daipayan Sarkar (
Date: Thu Nov 17 2022 - 07:02:39 CST

Hi Anirvinya,

You should look at the underlying probability distribution for the forward and backward alchemical transformation. This can be achieved using the FEP output (files with .fepout extension) in the ParseFEP plugin in VMD ( Also, very important to look at is the BAR estimator.

Now the range of lambda is from 0 to 1 and dlambda is how gradually you want your alchemical transformation to occur. This also depends on the atom selection the transformation is applied to, because the change in free energy (A -> B) is exponentially weighted for that selection. So yes, if you are choosing a coarse grid for lambda (such as dlambda = 0.1), especially at the end points of the transformation, it is highly likely that you will get erroneous results for the net free energy change. I recommend that you use a fine grid for lambda such as 0.01, especially at the end points of the transformation. Now, if you want the same grid spacing over lambda, you will need 100 windows in each direction. This can be computationally expensive, but the FEP calculation implemented in NAMD3 performs well for applications I have worked on recently. Are you using NAMD3 to perform the FEP calculations? Also, you can try increasing the grid spacing to 0.02 and compare the results, as this would cut the number of windows by half.

This is an empirical approach, and I am not aware if there is any theoretical framework that would provide insight into what our optimal lambda grid spacing should be.

Hope this helps,

From: "" <> on behalf of Anirvinya Gururajan <>
Reply-To: "" <>, Anirvinya Gururajan <>
Date: Thursday, November 17, 2022 at 1:01 AM
To: "" <>
Subject: namd-l: Alchemical FEP simulation

Hi all,

I am trying to carry out an alchemical free energy perturbation simulation and I observe very high values of dG (99999999999.9999 throughout) for all steps and all \lambda values (d\lambda = 0.1) even though the energy values seem reasonable. If I perform the same simulation but at a different d\lambda = 0.01, dG values are in a reasonable range. Theoretically, how does the choice of d\lambda affect dG given d\lambda is reasonably small and how should one go about choosing an optimal d\lambda? Is there any plausible way to circumvent this and make it work for d\lambda = 0.1?

Anirvinya G

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