[gmx-users] pca-based MD

Thomas Evangelidis tevang3 at gmail.com
Sun Sep 23 13:51:41 CEST 2012

I presume you are referring to Essential Dynamics Sampling, described in
section 3.14 of the manual (v4.5.4). There is also a great tool that finds
the few PCs that are maximally correlated to a functional quantity (e.g.
the volume of the active site). The technique is coined Functional Mode
Analysis (FMA) and you can find more information at:


I have used FMA and worked pretty well in my case. I am wondering if anyone
thought of using that technique to find the PCs that are maximally
correlated to a functional quantity and then perform Essential Dynamics
sampling  on these PCs to explore the conformational space that affects the
most that functional quantity.

I.e. I am studying a kinase in the wt and mutant form. Although the
mutation is not near the active site there is a lot of discussion in the
literature about the effect of the mutation on the opening of the catalytic
cleft. Some people claim that one possible explanation of the over-activity
of the mutant is the greater opening of the active site, which facilitates
substrate binding and thus leads to enhanced reaction turn-over. In order
to test this hypothesis with unbiased MD one would need tremendous computer
resources and a lot of time (the kinase is gigantic). On the other hand one
could run short simulations of the wt and mutant, do FMA to find the 10-20
PCs that are maximally correlated to the volume of the active site, and
then perform Essential Dynamics Sampling on these PCs to explore the
conformational space that is highly correlated to the volume of the active
site. After that, one could safely claim that the Hypothesis was true or

I would be interested to read your comments on this.


On 23 September 2012 11:19, James Starlight <jmsstarlight at gmail.com> wrote:

> Dear Gromacs Users!
> There are many publications about implementation of the pca-based MD
> simulations for the investigation of the functional-relevant motions.
> In that cases the eigenvectors are extracted from the relatively short
> MD simulation of the investigated protein and than the biassed MD
> simulation is started along chosen principal component which used as
> the reaction coordinate.
> I'd like to know more about implementation of that technique in
> Gromacs. E.g if I've performed some PCA and extracted eigenvectors how
> I can run further simulation along one of the chosen PC ?
> Thanks for help
> James
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Thomas Evangelidis

PhD student
University of Athens
Faculty of Pharmacy
Department of Pharmaceutical Chemistry
157 71 Athens

email: tevang at pharm.uoa.gr

          tevang3 at gmail.com

website: https://sites.google.com/site/thomasevangelidishomepage/

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