From: James Starlight (jmsstarlight_at_gmail.com)
Date: Thu Jul 24 2014 - 01:13:09 CDT
Thomas, many thanks for the suggestion!
So Rosetta in comparison to modeller could be used for i) prediction of ss
eleents in *long* loops ii) performing clustering of generated models based
on chosen criterium (e.g conformation of loop, or % of SS in its), couldn't
it?
Regarding the general workflow of the modelling and refirement based on
your assumptions I guess it would be more correct to do:
1) homology modelling by modeller/posetta-> clustering -> selection of
model from bigeest cluster
2) short cmd simulation in membrane to relax the system
3)loop refirement w/o membrane with applied position restraints (yes, I
dont like to kill this idea :-) )
James
2014-07-24 1:37 GMT+04:00 Thomas Evangelidis <tevang3_at_gmail.com>:
>
>
>
> On 23 July 2014 23:32, James Starlight <jmsstarlight_at_gmail.com> wrote:
>
>> Hi Thomas,
>>
>> this is some receptor from the GPCR family but with no known experimental
>> structure available at this moment. The reason of the refirement of the
>> extracellular loops is that I need very good model for further md
>> simulation to study initial ligand binding (which happens initially in
>> these extracellular loops) with the receptor (like in this paper
>> http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3156183/ ). In case of this
>> receptor modeller never predicted some secondary structure elements in the
>> region of second extracellular loop (which always looks like very long coil
>> (~30 aa) althought 2 disulphide bridges are located here as the possible
>> constraints) although we changes templates (in other GPCRs for instance in
>> Beta-adrenergic receptor) there are short helix in this region for instance
>> which is the vestibule to the ligand-binding pocket.
>>
>>
> In the paper you cited the authors ran multiple simulations, each one
> lasting several microsecond, to see the binding events. So unless you have
> access to Anton, the chances to see a binding event and transport are very
> low with unbiased MD on conventional computer clusters. Even with
> accelerated MD it is still difficult and you also have the complication
> that you cannot reweight such big systems to get accurate unbiased
> observables. I am working on a similar case of ligand binding and transport
> across the membrane. I have run more that 1 microsecond aMD with distance
> restraints between the ligands (5 copies of the same molecule) and the
> protein and still haven't seen binding. Your best bet is to use a more
> sophisticated method, like funnel metadynamics, which can give you all
> binding sites (including the allosteric) on the extracellular surface.
> However, this method is much more convoluted than aMD and hence I wouldn't
> recommend pursuing it without the guidance of an expert.
>
> As for the initial loop conformation, from what you say I wouldn't worry
> that much and rather let it assume the hypothetical helical conformation
> during the production run. However, freezing the transmembrane part of the
> protein while doing loop prediction with MD is wrong. Transmembrane
> proteins are crystallized in detergent, not in native conditions. There are
> also crystal contacts effects that need to be corrected. Consequently, you
> have to let them relax first before freezing them, especially in your case
> that you start from a homology model.
>
>
>
>> On other hand we never do *MANY* models. From your suggestion it seems
>> that I need to generate many models (e.g 1000 pdbs) which will be with the
>> same bundle but differ only in one extracellular loopin which I most
>> interested. Than I need to cluster my 1000 pdbs according to the
>> conformation of extracellulalar loop and chose some shared conformation
>> which will be in most populated cluster. Could you provide me with the
>> ideas of some soft which will be good for this which will have i)python
>> interface ii) tutorial :-)?
>>
>>
> No I mean, at least 10,000 loop models for the big one. Modeller have a
> python API and can run in parallel, so than won't take much to finish. I
> lately do these kind of tasks with Rosetta which provides more options
> specifically for transmembrane proteins and does also run in parallel. Both
> software have plenty of tutorials on their websites or source bundles.
> Rosetta tends to give more loop models with helical structures (due to
> fragment-based assembly) as in your case, yet their validity is
> questionable. In fact, I am not aware of any loop modeling method that can
> give accurate predictions for loops longer than 12 aa.
>
>
>
>>
>> Many thanks for suggestions,
>>
>>
>> James
>>
>>
>> 2014-07-24 0:02 GMT+04:00 Thomas Evangelidis <tevang3_at_gmail.com>:
>>
>>
>>>
>>>
>>> On 23 July 2014 22:24, James Starlight <jmsstarlight_at_gmail.com> wrote:
>>>
>>>> Dear NAMD users,
>>>> I'm very appologise, this question was adressed to both forums :-)
>>>> My question is refirement of loops predicted by modeller
>>>> the goal is
>>>> 1- just refine loops but not refine rest of the protein (freezing it)
>>>> 2- avoid to use the membrane, because I'd like to refine water expoised
>>>> regions of the membrane protein only
>>>> 3- enhansing sampling engine to refine it quickly
>>>> 4- do several refirement simulation, use PCA to test coverage (found
>>>> shared regions in PC projections of the loops conformations predicted by
>>>> such refirement from seveal simulations)
>>>>
>>>>
>>> Do you realize how much time this protocol needs to reach convergence on
>>> the eigenvectors of the accumulated trajectory (if that ever happens at
>>> all)? Why not just create tens of thousands of loop models, cluster them
>>> and start a simulation from the representative conformation of the
>>> predominant cluster?
>>>
>>> On another note, are these extracellular and intracellular loops so
>>> important to invest that amount of labour on them? What kind of protein is
>>> this? Can you upload some pictures on Dropbox to show us the protein with
>>> the loops coloured differently?
>>>
>>>
>>>
>>>> 2014-07-23 23:14 GMT+04:00 Pino, James Christopher <
>>>> james.c.pino_at_vanderbilt.edu>:
>>>>
>>>>> Your greeting implies this went to the wrong forum.
>>>>>
>>>>> However, I am using aMD through amber also.
>>>>>
>>>>> I am curious what your goal is? Loop refinement of de novo models?
>>>>>
>>>>>
>>>>> James
>>>>> Vanderbilt University
>>>>>
>>>>> ________________________________________
>>>>> From: owner-namd-l_at_ks.uiuc.edu [owner-namd-l_at_ks.uiuc.edu] on behalf
>>>>> of James Starlight [jmsstarlight_at_gmail.com]
>>>>> Sent: Wednesday, July 23, 2014 6:30 AM
>>>>> To: Namd Mailing List
>>>>> Subject: [External] namd-l: Boost value in aMD simulation
>>>>>
>>>>>
>>>>> Dear Amber users!
>>>>>
>>>>> In this topic I would like to talk about information obtained from the
>>>>> amd.log concerning the reasonability of the values of boost potentials
>>>>> applied to my system. For my case I'm simulating protein in explicit water
>>>>> with the task to refine its loops appling position restraints on part of
>>>>> the protein (which I'd like to keep unchanged). Firstly I've performed cMD
>>>>> with no restraints to obtain all values needed to compute boost and alpha
>>>>> according to the impirical formuli presented in manual. Then I run 2 boost
>>>>> aMD with applied of the position restraints on the bigger part of the
>>>>> protein and see amd.log. According to themd.log the value of dihedral
>>>>> boost added to my system per step during amd simulation has been ~ 10
>>>>> Kcal/mol on each step. I wounder if the dihe boost of this value have been
>>>>> applied to the whole protein (including its restrained parts) or only to
>>>>> its unrestrained (in my case loops) parts? What the reasonable dUdihe
>>>>> should be expected in principle for the simulation of protein consisted of
>>>>> ~ 300 amino acids? I guess that this value should be nuch biger than
>>>>> several Kcal/ mol to obtain better sampling.
>>>>>
>>>>>
>>>>>
>>>>>
>>>>> Thanks for suggestions,
>>>>>
>>>>>
>>>>> James
>>>>>
>>>>
>>>>
>>>
>>>
>>> --
>>>
>>> ======================================================================
>>>
>>> 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/
>>>
>>>
>>>
>>
>
>
> --
>
> ======================================================================
>
> 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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