From: Vermaas, Joshua (Joshua.Vermaas_at_nrel.gov)
Date: Fri Jul 27 2018 - 14:43:26 CDT
No, I mean figure out what parts of the variables are actually relevant to the transition you are trying to describe and make it 1-D. The pathCV is just useful if you can't entirely get a handle on what *specifically* is changing, but you know that something is, since RMSD to a target hides a multitude of sins. Multidimensional sampling, while technically doable, is expensive to do properly, since the amount of sampling required for convergence is polynomial in the number of dimensions. So 1D is ideal, 2D is doable, and anything beyond is unheard of.
If it were me, I'd use a regular distanceZ on the parts away from the histidines, and just focus sampling on the transition like crazy. This sounds like a selectivity filter for the channel, where the ions tend to dehydrate quite substantially, and you get a hard-to-sample region of your PMF. How long did you run your 1D stuff again? Di Maio et a. (10.1371/journal.pone.0140258) ran for 20ns a window, and while their sodium PMF closes (equal free energies in solution), their chloride PMF does not, and seems to "remember" being dragged across the membrane to start the simulation.
-Josh
On 2018-07-27 12:07:57-06:00 McGuire, Kelly wrote:
Thanks Josh, just to be clear when you say project down from 5D to 1D you do mean a vector projection from the 5D output values to a 1D vector?
Kelly L. McGuire
PhD Scholar
Biophysics
Department of Physiology and Developmental Biology
Brigham Young University
LSB 3050
Provo, UT 84602
________________________________
From: Vermaas, Joshua <Joshua.Vermaas_at_nrel.gov>
Sent: Friday, July 27, 2018 10:27:45 AM
To: McGuire, Kelly; jerome.henin_at_ibpc.fr
Cc: namd-l_at_ks.uiuc.edu
Subject: RE: namd-l: Multi-dimensional PMF
Hi Kelly,
Figure out the appropriate 1-D pmf so that other collective variables are no longer corrupting. This might involve sampling a higher dimensional space, and then projecting down from that higher dimension to make a 1-D reaction coordinate. An example of this is the "pathCV" example provided in the colvars source (https://github.com/Colvars/colvars/blob/master/examples/10_pathCV.namd -Josh
On 2018-07-27 09:57:08-06:00 owner-namd-l_at_ks.uiuc.edu wrote:
Ah ok I see. In your experience, when other degrees of freedom in your system are corrupting your 1-D PMF, what is your process to deal with them? If it requires higher dimensions because you have to use more colvars, do you stay away from those situations? It was suggested to me that I bias the other orthogonal degrees of freedom, which is how I ended up at 5D.
Kelly L. McGuire
PhD Scholar
Biophysics
Department of Physiology and Developmental Biology
Brigham Young University
LSB 3050
Provo, UT 84602
________________________________
On Fri, 27 Jul 2018 at 16:59, McGuire, Kelly <mcg05004_at_byui.edu<mailto:mcg05004_at_byui.edu>> wrote:
Kelly L. McGuire
________________________________
On Thu, 26 Jul 2018 at 23:43, McGuire, Kelly <mcg05004_at_byui.edu<mailto:mcg05004_at_byui.edu>> wrote:
So, everything seems to be working having a distanceZ colvar and 4 dihedral colvars (to bias the 4 histidine sidechains in my ion channel). But, now that means I have a 5-D .grad and .count, instead of just the 1-D .grad and .count which writes a 1-D PMF. I know how to use abf_integrate and got that to work to create a PMF. But, we are wondering how to even begin plotting data beyond 1, 2, and 3-D...
The reason I am biasing those four dihedrals is because our 1-D PMF was skewed, meaning bulk water on the c-terminus side of the ion channel is 30-50 kcal/mol higher than bulk water on the n-terminus side (they should be the same energy). We believe this energy value corruption is due to these histidines, so we are biasing them. We would like to see if this fixed the corrupted energy values on the 1-D PMF, how would we go about doing that?
Kelly L. McGuire
PhD Scholar
Biophysics
Department of Physiology and Developmental Biology
Brigham Young University
LSB 3050
Provo, UT 84602
This archive was generated by hypermail 2.1.6
: Mon Dec 31 2018 - 23:21:19 CST
From: Jérôme Hénin <jerome.henin_at_ibpc.fr>
Sent: Friday, July 27, 2018 9:16:44 AM
To: McGuire, Kelly
Cc: Namd Mailing List
Subject: Re: namd-l: Multi-dimensional PMF
What I meant between the lines is, don't do 5D PMFs.
There are no ready-made tools to do the projection - if you get into this you'll have to be ready to write your own tools, and know the corresponding theory.
Jerome
It's been a while since I've dealt with projections. Any suggestions on programs or the process you use to do that?
PhD Scholar
Biophysics
Department of Physiology and Developmental Biology
Brigham Young University
LSB 3050
Provo, UT 84602
From: Jérôme Hénin <jerome.henin_at_ibpc.fr<mailto:jerome.henin_at_ibpc.fr>>
Sent: Friday, July 27, 2018 1:45:20 AM
To: Namd Mailing List; McGuire, Kelly
Subject: Re: namd-l: Multi-dimensional PMF
Hi Kelly,
the only way to plot 5D data is to project it into lower-dimension spaces. A 5D space is also difficult to sample. Typically we'll try to make our colvar space as low-dimension as possible, to make our life simpler.
Jerome