[gmx-users] g_rotacf
rams rams
rams.crux at gmail.com
Fri Sep 5 16:27:21 CEST 2008
Dear Xavier,
Thank you very much for your valuable inputs. I am extremely sorry for
troubling you quite often.
You are absolutely right and I am using the second order legendre
polynomials to obtain the correlation function only (am not using this to
fit the correlation function data). The correlation function vs time curve I
obtained is an exponentially decaying function. I am integrating this data
(variation of correlation functions with time) for obtaining the correlation
time. Probably I am making mistake here but am not sure.
""For an NH vector of the backbone there are several motion model that one
has to decide
which one is best""
You mean to say that, I need to use any of the model to fit the correlation
function vs time data to obtain the relaxation time for N-H curve.
Thanks and Regards,
Ram.
On Fri, Sep 5, 2008 at 4:08 AM, Xavier Periole <X.Periole at rug.nl> wrote:
> On Thu, 4 Sep 2008 21:13:39 -0400
> "rams rams" <rams.crux at gmail.com> wrote:
>
>> Hi Xavier,
>>
>> I have a question about the accuracy of the correlation times obtained
>> using
>> gromacs tools. (I am getting these by integrating the output .xvg file of
>> g_rotacf using g_analyze). Since the experimental values are not available
>> to compare, I am not so sure about the correlation times I am getting.
>> They
>> are of the order of 0.4 to 0.8ns for various N-H vectors. I believe the
>> values depends upon the range of time frames we use to fit with the
>> legendre
>> polynomials. I am using second order legendre polynomial to fit the
>> frames.
>> Can you give me any general suggestions to follow to obtain the reasonable
>> correlation time values with MD simulations.
>>
> The range of values depend on the molecule you look at and the solvent
> viscosity. A protein with 50-100 AA would have an experimental rotational
> correlation time around 3-5 ns. In MD you find in general faster motion
> (1-3
> ns may be) which is due to the solvent and may be solvent-protein
> interactions
> that are a bit too weak, but this is not completely understood.
I am more concerned about the procedure you actually use to obtain your
value.
> The Legendre polynomial should be of the order 2 if you compare to NMR
> relaxation data, this is ok, but you do not use to fit the data! You use it
> to build the correlation function. Then you fit the correlation function
> with a function that would describe the motion you look at! For an NH
> vector
> of the backbone there are several motion model that one has to decide
> which one is best. Have a look at that paper. I did not read it but it
> talks about model to fit NMR data and should contain a lot of reference
> for you to begin with. DOI: 10.1021/jp8038576.
>
> Then you should have look at your correlation functions. Are they converged
> (reached a plateau)? How do they look?
>
> You can also use the g_dipole to get the auto correlation function of the
> molecule dipole ...
>
> Ram.
>>
>> On Thu, Sep 4, 2008 at 11:02 AM, Xavier Periole <X.Periole at rug.nl> wrote:
>>
>> On Thu, 4 Sep 2008 09:45:34 -0400
>>> "rams rams" <rams.crux at gmail.com> wrote:
>>>
>>> Hi Xavier,
>>>>
>>>> I am extremely sorry for incomplete information. But this is a follow up
>>>> to
>>>> my previous two emails. Unfortunately I havent received any suggestions
>>>> for
>>>> them and it appears like you too missed them. For more clarity I am
>>>> pasting
>>>> them here again:
>>>>
>>>> Well if you do not get an answer that is probably that your post is not
>>> really asking a quick "answerable" question and you might want to
>>> re-formulate your post or dig a bit to make things easier.
>>>
>>> To calculate the rotational auto correlation functions, the command
>>>> mentioned in the maual is:
>>>>
>>>> g_rotacf -P 1 -nparm 2 -fft -n index -o .xvg -fa -beginfit -endfit
>>>>
>>>> what are the -nparm and -fa options are meant for ?
>>>>
>>>> This is an old exemple ... a bad one! Those options do not seem to
>>> exist
>>> anymore! Never knew they existed!
>>> you can grep "\-nparm" and "\-fa" in tools/*.c and you'll see they
>>> only appear in gmx_rotacf.c
>>> anyways These things are probably taken care of more invisibly.
>>> -nparm seems to give the number of parameters in the function to fit
>>> -fa the function to fit
>>>
>>> now: -nparm do not exist and -fa is -fitfn, most likely!
>>>
>>> This exemple should be removed and replaced! Just look at the
>>> options\listed when you type g_rotacf -h.
>>>
>>> Also do we need to use -fitfn option to obtain the rotational auto
>>>> correlation functions ??
>>>>
>>>> No, -fitfn defines the type of function you'd use to fit the
>>> correlation
>>> function, which itself is written cause -o rotacf.xvg ...
>>>
>>> XAvier.
>>>
>>>
>>> Ram.
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> Dear users,
>>>>
>>>> I have given a command like the following to calculate the rotational
>>>> auto
>>>> correlation function:
>>>>
>>>> g_rotacf -f .trr -s .tpr -P 2 -fft -o .xvg -b 0000 -e 10000 -n .ndx -d
>>>>
>>>> I want to use the second order Legendre polynomial to fit. I integrated
>>>> the
>>>> resulting .xvg file, to obtain the correlation time using:
>>>>
>>>> g_analyze -f .xvg -integrate
>>>>
>>>> The output is the following. Could some one help me in understanding it
>>>> betterly.
>>>>
>>>> Calculating the integral using the trapezium rule
>>>> Integral 1 120.92840 +/- 0.00000
>>>> std. dev. relative deviation of
>>>> standard --------- cumulants from those of
>>>> set average deviation sqrt(n-1) a Gaussian
>>>> distribition
>>>> cum. 3 cum. 4
>>>> SS1 2.428352e-02 2.972849e-02 4.204243e-04 9.301 120.228
>>>>
>>>>
>>>> Which value corresponds to correlation time and in which units (its in
>>>> ps
>>>> I
>>>> suppose) ?
>>>>
>>>> Thanks in advance.
>>>>
>>>> Ram.
>>>>
>>>>
>>>> On Thu, Sep 4, 2008 at 2:32 AM, Xavier Periole <X.Periole at rug.nl>
>>>> wrote:
>>>>
>>>> On Wed, 3 Sep 2008 23:40:14 -0400
>>>>
>>>>> "rams rams" <rams.crux at gmail.com> wrote:
>>>>>
>>>>> Hi,
>>>>>
>>>>>>
>>>>>> I am so surprised for not finding any one who have better experience
>>>>>> with
>>>>>> g_rotacf. I have been playing around with it and the time correlation
>>>>>> value
>>>>>> I got by g_rotacf is so small in comparison to the time correlation
>>>>>> value
>>>>>> I
>>>>>> calcualted using the hydrodynamic radius of the protein. The value is
>>>>>> nearly
>>>>>> 10 times less. Can some one give me a better idea about g_rotacf.
>>>>>>
>>>>>> Many people have certainly used g_rotacf to get ACFs of different
>>>>>>
>>>>> observables.
>>>>>
>>>>> Anyways the way you describe your system, command line and your problem
>>>>> does
>>>>> does not help anyone to help you. Read your message above and think
>>>>> about
>>>>> what
>>>>> you would answer! You've played around with g_rotacf therefore you know
>>>>> it
>>>>> is not straightforward to give you the magic command.
>>>>>
>>>>> XAvier.
>>>>>
>>>>>
>>>>> Ram.
>>>>>>
>>>>>>
>>>>>> -----------------------------------------------------
>>>>> XAvier Periole - PhD
>>>>>
>>>>> Molecular Dynamics Group / NMR and Computation
>>>>> University of Groningen
>>>>> The Netherlands
>>>>> -----------------------------------------------------
>>>>> _______________________________________________
>>>>> gmx-users mailing list gmx-users at gromacs.org
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>>>>>
>>>>>
>>>>> -----------------------------------------------------
>>> XAvier Periole - PhD
>>>
>>> Molecular Dynamics Group / NMR and Computation
>>> University of Groningen
>>> The Netherlands
>>> -----------------------------------------------------
>>> _______________________________________________
>>> gmx-users mailing list gmx-users at gromacs.org
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>>>
> -----------------------------------------------------
> XAvier Periole - PhD
>
> Molecular Dynamics Group / NMR and Computation
> University of Groningen
> The Netherlands
> -----------------------------------------------------
> _______________________________________________
> gmx-users mailing list gmx-users at gromacs.org
> http://www.gromacs.org/mailman/listinfo/gmx-users
> Please search the archive at http://www.gromacs.org/search before posting!
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