[gmx-users] pca-based MD
James Starlight
jmsstarlight at gmail.com
Sun Sep 23 16:58:44 CEST 2012
Thomas,
thanks again for explanation. Its also intresting to me is it possible
to do further biassed MD guided on that FMA modes as well as obtain
projections onto that FMA sub-spaces of X-ray datasets for instance ?
( e.g for comparison of the results from FMA of experimental data as
well as MD_data)
James
2012/9/23 Thomas Evangelidis <tevang3 at gmail.com>:
> On 23 September 2012 17:18, James Starlight <jmsstarlight at gmail.com> wrote:
>
>> Thomas,
>>
>> thank you for the explanation
>>
>> 1) Indeed ED sampling was exactly that I need. It's not quite
>> understand for me about correct chose of that parameters for biassing
>> simulation
>>
>> -linfix string Indices of eigenvectors for fixed increment
>> linear sampling
>> -linacc string Indices of eigenvectors for acceptance linear
>> sampling
>> -radfix string Indices of eigenvectors for fixed increment
>> radius expansion
>> -radacc string Indices of eigenvectors for acceptance radius
>> expansion
>> -radcon string Indices of eigenvectors for acceptance radius
>> contraction
>>
>> What exactly I need is the biasing of the new MD run along one
>> specified eigenvector which I've extracted from previous run. So it's
>> not quite understand for me what chose would be most correct e.g
>> linnear sampling along that eigenvector or rafius expansion.
>>
>>
> Unfortunately I haven't ever used ED sampling myself so someone else might
> explain what these parameters are meant for.
>
>
>
>> 2) Also I want to perform such biassing along PC mode extracted from
>> the X-ray data-set of my protein. E.g on first step I calculate PC
>> from the X-ray data-set consisted of different functional relevant
>> conformations of my protein ( for this purpose I need create
>> trajectory from that x-ray data-set firstly). Than I'm looking for one
>> PC which correspond to biological relevant motion ( e.g opening of
>> active center seen in first PC). Finally I want to perform MD from one
>> start structure ( e,g its closed form) along extracted 1 PC from x-ray
>> data-set. For that step I also must make *.edi file for further md_run
>> of the protein firslty. Does this workflow correct in general ? :)
>>
>>
>> 3) This FMA technique is very intresting indeed. As I've understood It
>> can be usefull in case where I could not find biological-relevent
>> motion along one specified PCs ( In that case the combination of the
>> PCs might represent this motion which can correspond to one
>> eigenvector made by FMA). Does it correct ?
>>
>
> It is highly unlikely that a functionally relevant motion is explained by a
> single PC. FMA gives the degree in which each PC affects (and thus is
> correlated to) the functional quantity you chose (e.g. the volume of the
> active site), it does not give you a single eigenvector. For instance you
> may have found that the opening of your active site is well explained by
> the first PC. Yet, FMA may give you that this functional quantity (volume
> of the active site) is affected from the 1st PC by 70%, from the 2nd by 5%,
> from the 3rd by 12%, and from the 4th by 7% and to the 5th by 6%. It is
> more accurate then to use PC1-5 in ED sampling.
>
>
>
>> 2012/9/23 Thomas Evangelidis <tevang3 at gmail.com>:
>> > 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:
>> >
>> > http://xray.bmc.uu.se/~jochen/fma.html
>> >
>> > 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
>> > false.
>> >
>> > I would be interested to read your comments on this.
>> >
>> > Thomas
>> >
>> >
>> > 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
>> > Panepistimioupoli-Zografou
>> > 157 71 Athens
>> > GREECE
>> >
>> > email: tevang at pharm.uoa.gr
>> >
>> > tevang3 at gmail.com
>> >
>> >
>> > website: https://sites.google.com/site/thomasevangelidishomepage/
>> > --
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>
>
>
> --
>
> ======================================================================
>
> Thomas Evangelidis
>
> PhD student
> University of Athens
> Faculty of Pharmacy
> Department of Pharmaceutical Chemistry
> Panepistimioupoli-Zografou
> 157 71 Athens
> GREECE
>
> email: tevang at pharm.uoa.gr
>
> tevang3 at gmail.com
>
>
> website: https://sites.google.com/site/thomasevangelidishomepage/
> --
> gmx-users mailing list gmx-users at gromacs.org
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