Dear XAvier,<br><br>Thanks for your reply and for the explanation. I am not an NMR guy so I would like to know little bit of more about the way we can calculate the rotational diffusion. The way I understood is the following and let me know if I am wrong.<br>
<br>After obtaining the rotaional correlation function using Gromacs tools (g_rotacf), I need to calculate the correlation time I suppose. <br>The obtained correlation time is related with the local diffusion constant (d) by the relation<br>
d = 1/l(l+1) t<br>t is the correlation time obtained above and l = 1 or 2 depends upon the order of the legendre polynomial we will use in the g_rotacf and the experimental results with which we are comparing. <br><br>then by solving the following relation<br>
d=n'Qn (n is a unit vector lies along the vector connecting the two spins), we can obtain "Q" which inturn is in relation with D (the diffusion tensor). <br><br>Thats the overall idea I have but I am sure I need to worry alot of finer other details while I start putting my hands into it. If the overall idea is alright I could put the things in a more detailed way.<br>
<br>Ram.<br><br><div class="gmail_quote">On Sat, Jul 5, 2008 at 12:51 PM, Xavier Periole <<a href="mailto:X.Periole@rug.nl">X.Periole@rug.nl</a>> wrote:<br><blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
<div><div></div><div class="Wj3C7c">On Sat, 5 Jul 2008 10:40:21 -0400<br>
"rams rams" <<a href="mailto:rams.crux@gmail.com" target="_blank">rams.crux@gmail.com</a>> wrote:<br>
<blockquote class="gmail_quote" style="border-left: 1px solid rgb(204, 204, 204); margin: 0pt 0pt 0pt 0.8ex; padding-left: 1ex;">
Dear users,<br>
<br>
Is it possible to evaluate the rotational diffusion of proteins using<br>
gromacs tools ??<br>
</blockquote></div></div>
No directly. However you can use g_rotacf to generate the autocorrelation<br>
function of vectors (option -d). By defining vectors representing your<br>
molecule/protein you can access the rotational correlation time of your<br>
representative vector. You can imagine different way to get a statistically<br>
significant value. One would be to define many vectors between backbone<br>
atoms and average your results. Another would be to again define many<br>
vectors but this time between the center of mass of the protein and each<br>
Ca atoms and average ...<br>
<br>
You can also hack the g_rms code to extract the rotational matrix during<br>
the overlay of your protein to a reference structure and apply it to<br>
a unit vector from whose trajectory you can again use g_rotacf to get<br>
the autocorrelation function of that vector ...<br>
<br>
An important point in the comparison of your result to experimental<br>
values is the way the rotational correlation time is extracted<br>
experimentally. They select different mode of relaxation (1 or 2) and thus<br>
you have to use the corresponding Legendre polynomial when calculating the<br>
autocorrelation function. From NMR relaxation l=2.<br>
<br>
XAvier.<br>
<br>
-----------------------------------------------------<br>
XAvier Periole - PhD<br>
<br>
Molecular Dynamics Group<br>
- NMR and Computation -<br>
University of Groningen<br>
The Netherlands<br>
-----------------------------------------------------<br>
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</blockquote></div><br>