[Chimera-users] Seeking guidance on Volume-volume fitting

[ingvar]

Hi Tom,

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.

/Ingvar


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.
> 
>   Tom
> 
> 
> 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 
>> available.
>> 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")
>> saveReplyLog(r'/Users/ingvar/chimera/log/fit5500_5501_loc.txt')
>> 
>> 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
>> 
>> 
>> 
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