[Chimera-users] Seeking guidance on Volume-volume fitting
ingvar at ebi.ac.uk
Wed Apr 24 05:10:31 PDT 2013
Thank you for explaining the inner workings of the volume-volume
fitting in Chimera.
The long term goal is to set up a searchable database with what volumes
fit in each other, not necessarily limited to EM, and also provide a
service where a user can upload a volume and see if it fits in any
existing volume in the archive.
It sounds like I am used a good set options. I will try some other
examples to see if I have better luck in finding the best fit there, may
be a set of 70 S ribosomes.
On 2013-04-24 06:09, Tom Goddard wrote:
> Hi Ingvar,
> It sounds like you want to automate the fitting of one EMDB
> ribosome map to another, and probably other structures too. Probably
> you are aiming to have it find the best fit as often as possible
> without taking too long. It is not easy to guarantee you have the
> best fit, even using an exhaustive search can miss it unless you take
> very fine rotational and translation steps. Here are answers to some
> of your questions.
> Should one map be resampled before fitting in the other map? No, I
> don't see any advantage to doing that. The fit is done on the grid
> points of the first map within the displayed contour level, and the
> second map is interpolated at those grid points.
> Could aligning principle inertia axes help get the best fit. Yes,
> in some cases that will work. And if you only optimize that initial
> it will be very fast (less than a second typically). But unless you
> search lots of other possible orientations you will miss the best fit
> in some percentage of cases. So it doesn't seem particularly useful
> if reliability of automated fitting is your goal.
> Does it matter if grid sizes are different? No. Trilinear
> interpolation is being used, so there is no advantage of the grid
> sizes or spacings matching.
> Should any correction be done for fitting different resolution maps
> to each other? I don't think there would be much advantage to say
> smoothing the higher resolution map to match the lower resolution map.
> I don't think that will improve convergence to the best fit. And I
> don't think it will change the best fit -- although maybe it is
> theoretically possible.
> If you are using the correlation about mean metric then shifting
> the density values will have no effect, because the mean is subtracted
> from the density of both maps. But if you are using correlation or
> overlap a shift may be needed.
> I am unpleasantly surprised by your low success rate getting the
> best fit in 5000 or 50000 searched positions. My experience has been
> that it is found in a few hundred positions. I will need to try your
> examples. I'll report in a later email what I find.
> On Apr 22, 2013, at 3:37 AM, ingvar wrote:
>> Dear Chimera,
>> I am seeking guidance on what would be best practice in doing
>> volume-volume fitting, and what expectations should I have on number
>> of trial conformations. For instance would it be beneficial to
>> resample one of the volumes to the same grid as the other volume.
>> What about volumes with different resolutions, do this require any
>> special handling.
>> In the case below it would probably be more efficient to just align
>> the principal moments of inertia of the envelopes above the contour
>> level and then do a search from there, though this will only work well
>> if the volumes are very similar.
>> In an initial study I used 3 EM volumes from EMDB, (EMD-5500,
>> EMD-5501, and EMD-2017). They are all 30S E. coli ribosomes of
>> similar resolution (12.9, 14.0, 13.5 Å). I thought that this would be
>> a relatively easy starting point, with the intent to then go on to fit
>> 30S subunit in some of the many E. coli 70S EM volumes that are
>> The volumes EMD-5500 and EMD-5501 are in similar orientation, while
>> EMD-2017 is in a completely different orientation.
>> The grids are similar but not identical, 125^3 vs 128^3. I adjusted
>> the contour levels from the EMDB recommended values to make the
>> enclosed volumes more similar in size.
>> Contour levels used:
>> EMD-5500 -2.8 -> -2.5
>> EMD-5501 -2.8
>> EMD-2017 39 -> 32
>> I am using scripts like the one shown here:
>> from chimera import runCommand as rc
>> from chimera.tkgui import saveReplyLog
>> rc("open data/EMD-5500.map")
>> rc("volume #0 level -2.5 transparency 0.5")
>> rc("open data/EMD-5501.map")
>> rc("volume #1 level -2.8 transparency 0.5")
>> rc("fitmap #1 #0 search 50000 metric cam envelope true inside 0.2")
>> It seems correlation about mean is the best metric for volume-volume
>> fitting, and that it is best to only use points inside the envelope.
>> The maps EMD-5500, and EMD-5501 have the unusual feature that the
>> density range is shifted downwards so that the average is well below
>> 0. I was concerned about that and moved the density range, but with
>> the fitmap parameters above that did not seem to have any significant
>> impact (with other sets of parameters the density range appears to be
>> an issue).
>> In this case, it is relatively easy to see when you have found the
>> "good" fit, all other fits have clearly worse statistics.
>> What I was surprised about was the number of trial conformations
>> needed to be reasonable certain to find the "good" fit.
>> 5500 in 5501 7 times in 5000
>> 5501 in 5500 2 times in 5000
>> 5500 in 2017 0 times in 5000
>> 5500 in 2017 8 times in 50000
>> 2017 in 5501 0 times in 5000
>> Many Thanks,
>> Ingvar Lagerstedt
>> Chimera-users mailing list
>> Chimera-users at cgl.ucsf.edu
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