Re: [ccp4bb] phaser openmp

[Dr G. Bunkoczi]

Hi Ed,

in the CCP4 distribution, openmp is not enabled by default, and there
seems to be no easy way to enable it (i.e. by setting a flag at the
configure stage).

On the other hand, you can easily create a separate build for phaser
that is openmp enabled and use phaser from there. To do this, create a
new folder, say phaser-build, cd into it, and issue the following
commands (this assumes you are using bash):

$ python $CCP4/lib/cctbx/cctbx_sources/cctbx_project/libtbx/configure.py
--repository=$CCP4/src/phaser/source phaser
--build-boost-python-extensions=False --enable-openmp-if-possible=True

$ . ./setpaths.sh (source ./setpaths.csh with csh) $ libtbx.scons (if you 
have several CPUs, add -jX where X is the number of CPUs you want to use 
for compilation)


This will build phaser that is openmp-enabled. You can also try passing
the --static-exe flag (to configure.py), in which case the executable is
static and can be relocated without any headaches. This works with
certain compilers.

Let me know if there are any problems!

BW, Gabor

On Nov 8 2011, Ed Pozharski wrote:


Could anyone point me towards instructions on how to get/build
parallelized phaser binary on linux?  I searched around but so far found
nothing.  The latest updated phaser binary doesn't seem to be
parallelized.  


Apologies if this has been resolved before - just point at the relevant
thread, please.

Re: [ccp4bb] MR with ensemble containing multiple models

[Dr G. Bunkoczi]

Hi G,


Dear all,

I have several similar models which can be superimposed. (looks like NMR
solved structure) Then I made those superimposed models to be a single
ensemble in phaser.

My question is:

what would be the difference of running phaser with this kind of ensemble
and with an ensemble which include only one model? As I have B factor
information in PDB, the uncertainty in model has already been considered
even if I just provide one model. Is that right? Would that really be more
helpful to test an ensemble with multiple models superimposed?


Although I am not aware of any systematic study, there are indications that 
an ensemble can be a better model than a single model with B-factor 
weighting (check out the phaser MR tutorial with toxd). For one thing, an 
ensemble will weight up the structurally conserved parts of the model, 
while this is not guaranteed with B-factors (although both tends to weight 
up the core and weight down the surface). Also, B-factors are normally 
restricted to describe an isotropic uncertainty, but ensembles can describe 
complex motions of loops, etc.




What would happen if those superimposed models are not quite similar, or 
they can not superimposed well( some distance between them can be 
observed)?


It is possibly a good idea to do a weighted superposition, so that only the 
structurally similar parts are superposed (this is automatically done by 
the SSM algorithm). If there are still major deviations, you can consider 
trimming these residues away. This is something that can be done 
automatically with ensembler (currently in PHENIX, but eventually to be 
included in CCP4 as well).


BW, Gabor



Many thanks,
G