From: Jerome Henin (heninj_at_gmail.com)
Date: Thu Jan 22 2009 - 11:35:39 CST
Oops, sorry S¨¦bastien, I don't know why I thought it had made it into
Chris: having NAMD handle "lambda-lists" would be convenient, but it
fairly easy to script them in Tcl already - that is still true with
double-wide sampling. If implementing it takes you a long time or
increases the complexity of the code, I won't be pushing for it.
2009/1/22 Chris Harrison <charris5_at_nd.edu>:
> I've implemented doublewide with both a forward and reverse work lambda.
> This is not in the CVS yet, but should be available there in several weeks.
> But in reading Floris' comment I'm thinking it does make more sense to
> implement doublewide's forward and reverse work lambda's as lists to
> accomodate very non-linear perturbation paths ... to allow one to match
> exactly the set of lambda's composing the perturbation path. Any holes in
> this logic?
> Chris Harrison, Ph.D.
> Theoretical and Computational Biophysics Group
> NIH Resource for Macromolecular Modeling and Bioinformatics
> Beckman Institute for Advanced Science and Technology
> University of Illinois, 405 N. Mathews Ave., Urbana, IL 61801
> char_at_ks.uiuc.edu Voice: 217-244-1733
> http://www.ks.uiuc.edu/~char Fax: 217-244-6078
> On Thu, Jan 22, 2009 at 4:58 AM, Floris Buelens <floris_buelens_at_yahoo.com>
>> > No, formally this is correct. Numerically though, samples of dE are
>> > correlated, so you get pretty much the same statistics by storing it
>> > every 10 timesteps or so. You could try it - downsampling dE data from
>> > a calculation, and seeing how far you can go without changing the
>> > result.
>> I agree with Jerome - with linear potential scaling you can trivially
>> extrapolate at any timestep the potential energy for any value of lambda,
>> but as I think you already realised, you don't benefit from the cumulative
>> averaging of the FEP dG that NAMD performs for the comparison value lamda2.
>> You can do this yourself by post-processing; you could sample less
>> frequently than every step, in which case you have to weigh up discarding
>> lots of your data against the fact that the intervening values will be
>> highly correlated. And as you imply, this approach is anyway no longer
>> applicable when using soft core vdW.
>> > Again, you are right: actually this is now implemented. The problem
>> > is, I think, that the user's guide in CVS has not yet been updated to
>> > document this. There is some work being done on that side...
>> Actualy there's no provision for a second comparison lambda (a 'lambda3')
>> yet, and to my knowledge all the key functionality is already documented in
>> I agree that double-wide sampling / Bennett acceptance ratio estimatation
>> needs two independent comparison lambdas: the 'forward' work to the 'next'
>> point in the transformation and the 'reverse' work to the 'previous' point
>> in the transformation. A scheme that only calculates work from ¦Ë to ¦Ë+¦Ä¦Ë and
>> ¦Ë to ¦Ë-¦Ä¦Ë appears to me to assume linear spacing of intermediates in the
>> transformation, which for the work I do is never true...
>> best regards,
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