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[ccp4bb]: Summary: Amore Rotation Function Scoring?



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Dear CCP4 users & staff,

on September, 23rd, I've posted the following message on the CCP4BB:


"The Amore cross-rotation function basically calculates a correlation 
coefficient between the observed and calculated Patterson function (CC_P). 
However, the output of the cross-rotation search is for some dubious reason 
sorted on the correlation coefficient between calculated and observed F 
(CC_F). This doesn't make much sense to me for the following reasons:
(1) The search function is the CC_P, thus, from a methodological point of 
view, the output should be sorted on this value and not on something else.
(2) Both, the calculated F and I of the model only make sense after it has 
been correctly positioned, which is not the case in the cross-rotation 
search.
(3) Accordingly, the signal-to-noise must be much better for CC_P than for 
either CC_F or CC_I. To illustrate this, I have run a cross-rotation search 
with the refined protein-only model of the A. niger phytase (Kostrewa et al., 
NSB, 4, 185ff, 1995) against its observed data. The top 10 of the amore 
cross-rotation output looks like this (I've removed the TX,TY,TZ columns for 
better readability):

            ITAB  ALPHA    BETA   GAMMA    CC_F RF_F CC_I CC_P Icp
 SOLUTIONRC    1    3.28   85.77  237.92  27.9 55.3 42.8 26.8   1
 SOLUTIONRC    1  117.85   90.00   58.64  22.2 57.2 34.3 16.3   2
 SOLUTIONRC    1   90.57   80.41  235.17  18.2 58.3 26.3  5.6   3
 SOLUTIONRC    1   60.20   85.07  240.47  17.9 58.5 25.9  4.9   4
 SOLUTIONRC    1   22.57   57.12  223.13  17.9 58.5 26.6  4.1   5
 SOLUTIONRC    1   47.85   86.10  237.71  17.8 58.5 25.8  5.2   6
 SOLUTIONRC    1   87.65   60.22   71.67  17.8 58.4 25.9  4.4   7
 SOLUTIONRC    1   80.37   85.82  235.99   17.7 58.4 25.1  4.5   8
 SOLUTIONRC    1   44.86   24.72   48.00  17.7 58.5 26.0  5.6   9
 SOLUTIONRC    1   41.18   58.25   87.29  17.7 58.4 25.7  6.4  10

Interestingly, the correct top peak appears to be also the top peak in CC_F 
and CC_I. However, as you can clearly see, the signal-to-noise ratio is MUCH 
better for CC_P. Now, imagine that you do not have a perfect search model. In 
this case, I think, the chances to find the correct peak are much poorer if 
the output is sorted on CC_F rather than on CC_P. I don't know what you other 
users of CCP4 think about this, but I would strongly prefer a sorting on the 
real search function values rather than on something else in order to get the 
best chances to find the correct molecular replacement solution. 
Unfortunately, CCP4 Amore apparently does not give the user the choice on 
which values he/she wants to sort the output. Thus, the request from my side 
to the CCP4 developers is to give the user the choice on which values the 
output should be sorted, and to set the sorting on CC_P as the default, and 
not the sorting on CC_F."


I received three replies (excerpts in ""):

(1) from Steve Soisson:

"You can always just grep out the SOLUTIONRC lines and sort them using shell
commands:
cat amore.output | grep SOLUTIONRC | sort -r +8 > sort.list"

I think that this only works IF the true CC_P peak is really in the CC_F list. 
It does not cure the underlying problem of sorting on the wrong value in the 
first place.

(2) from David Borhani:

"I agree."

(3) from Alexandre Urzhumtsev:

"I agree with you. At my opinion, the advantage of the rot.function is that 
it uses the Pattersons and does NOT make a comparison of Fs which is 
useless for unpositioned and especially for uncomplete models."


Thus, I would like to repeat my request to the CCP4 staff to give the user the 
choice on which value Amore's rotation function output should be sorted.

Best regards,

Dirk.

-- 

***************************************************************
Dirk Kostrewa
Paul Scherrer Institut             E-mail: dirk.kostrewa@psi.ch
Life Sciences, OSRA/007             Phone: +41-56-310-4722
CH-5232 Villigen PSI                  Fax: +41-56-310-4556
Switzerland                      Internet: http://www.sb.psi.ch
***************************************************************