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Merging two models with combine_models
Author(s)
PurposeThis routine takes a model and finds pieces of a second model file that improve its fit to density when they replace the corresponding pieces in the first model. UsageThe main uses of phenix.combine_models are:
How combine_models works:Combine_models starts with two input models. The first model is used as the default; if nothing can be found in the second model that is better than what is in the first model, then that part of the first model is kept. The second model is used as a template for improving the first model. Fragments of the second model are considered as alternatives for corresponding segments in the first model. The fit of the models to density is used to decide which of a pair of fragments is best. In general, the correlation of model density with the map is used as the criterion. In cases where unequal numbers of residues are considered, then this correlation is weighted by the square root of the number of residues in each case. During the optional merge_second_model step, the scoring is optionally based on correlation of density, or by default, based on density at the positions of the main-chain atoms in the model. If the two input models are not in the same asymmetric unit of the crystal, then combine_models will move the pieces from the second model to the corresponding locations in the first model. In this way the final model has all its parts in the same place. Combine_models has four main steps, each of which is optional:
Output files from combine_modelscombine_models.pdb: A PDB file with your combined model. ExamplesStandard run of combine_models:Running combine_models is easy. From the command-line you can type: phenix.combine_models pdb_in=first.pdb \ second_pdb_in=second.pdb \ seq.dat \ map_coeffs.mtzThis will combine first.pdb and second.pdb based on fit to the map from map_coeffs.mtz, recheck the sequence alignment to seq.dat, and write out the resulting model. Selecting pieces from the two models:To take first.pdb and then see if residues A21-A30 of second.pdb can improve it, you can type: phenix.combine_models pdb_in=first.pdb \ second_pdb_in=second.pdb \ seq.dat \ map_coeffs.mtz \ second_pdb_in_selection="(chain A and resid 21:30)" \ Replacing a specific segment:To take first.pdb and then see if residues A21-A30 and B21-B30 can be improved by replacing them with residues C10-C20 and D10-D20 of second.pdb, you can tell combine_models to ignore residues A22-A29 and B22-B29 and to consider only residues C10-C20 and D10-D20 of second.pdb: phenix.combine_models pdb_in=first.pdb \ second_pdb_in=second.pdb \ seq.dat \ map_coeffs.mtz \ pdb_in_selection="(not ( (chain A or chain B) and resid 22:29) )" \ second_pdb_in_selection="( (chain C or chain D) and resid 10:20)" \ Crossing two models that have entirely matched residues:If your first.pdb and second.pdb have exactly the same residues present, and just differ in coordinates, then you might want to preserve all the connectivity by skipping the merge_second_model step, and by skipping the non_matching crossover step, and by skipping the reassignment of sequence. You can type preserve_connectivity=True as a shortcut for this: phenix.combine_models pdb_in=first.pdb \ second_pdb_in=second.pdb \ seq.dat \ map_coeffs.mtz \ preserve_connectivity=True Possible ProblemsSpecific limitations and problems:LiteratureAdditional informationList of all combine_models keywords
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Legend: black bold - scope names
black - parameter names
red - parameter values
blue - parameter help
blue bold - scope help
Parameter values:
* means selected parameter (where multiple choices are available)
False is No
True is Yes
None means not provided, not predefined, or left up to the program
"%3d" is a Python style formatting descriptor
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combine_models
input_files
pdb_in= None Input starting PDB file. This model will be the default
output model. Parts of the model that are better in the second
model be replaced by the second model.
pdb_in_atom_selection= None Any selection specified with
pdb_in_atom_selection is applied to the pdb_in
input model before using it.
second_pdb_in= None Input second PDB file. Parts that are better in this
model will replace corresponding parts of the first
model.
second_pdb_in_atom_selection= None Any selection specified with
second_pdb_in_atom_selection is applied to
the second_pdb_in input model before using
it .
mtz_in= None Input MTZ file with map coefficients
map_coeff_labels= None If map coefficients cannot be identified
automatically from your MTZ file, you can specify the
label or labels for them. (Please separate labels with
blank space, MTZ columns grouped together separated by
commas with no blanks.) You can specify:
map_coeff_labels (e.g., FWT,PHIFWT) amplitudes and
phases (e.g., FP,SIGFP PHIB) or amplitudes, phases,
weights (e.g., FP,SIGFP PHIB FOM)
seq_file= None Sequence file for sequence alignment
output_files
pdb_out= combine_models.pdb Output PDB file
log= combine_models.log Output log file
params_out= combine_models_params.eff Parameters file to rerun
combine_models
directories
output_dir= "" Output directory where files are to be written
crossing
high_resolution= None Resolution used in map calculation
match_distance= 0.5 Residue pairs must have rmsd of match_distance (A)
or lower to be crossed. A value between 0.5 A and 1 A is
generally best.
merge_second_model= True Cut second model into pieces and merge them
into first model. (Useful for filling in gaps in
first model.)
merge_both_models= False Cut first and second models into pieces and
merge them (useful for combining all pieces of both
models). Alternative to merge_second_model.
trim_in_merge= False Trim all the fragments of first and second model
back to match density before merging of models. See also
remove_bad_fragments in merge which removes bad fragments
(after any trimming is done).
remove_bad_fragments_in_merge= True Remove bad fragments in merge. See
also trim_in_merge which trims back
fragments before trying to merge them.
extend_in_merge= False Extend fragments of first and second model during
merging of models
fragment_length= 10 Length of pieces that second model will be cut down
to in merge_second_model or merge_both_models
use_cc_in_combine_extend= False You can choose to use the correlation of
density rather than density at atomic
positions to score models in the
merge_second_model or merge_both_models step.
This may be useful at lower resolution (> 3
A)
matching= True Carry out crossover using segments that match (have the
same number of residues)
non_matching= True Carry out crossover using segments that do not match
(do not have the same number of residues)
check_sequence= None After running all other procedures, redo the
sequence assignment. This may be necessary if the models
did not have the same sequence assignments or if
unassigned pieces are now put together and can be
assigned. If None, then check_sequence will be set to
True if non_matching=True.
preserve_connectivity= None This is a shortcut for turning off
merge_second_model, merge_both_models,
non_matching, and check_sequence. It is useful if
your two models have the same residues, just with
different coordinates, and you want to maintain
the connectivity.
merge_only= None This is a shortcut for turning off everything except
merge_second_model and merge_both_models.
solvent_fraction= None You can specify the solvent fraction
control
verbose= False Verbose output
raise_sorry= False Raise sorry if problems
debug= False Debugging output
dry_run= False Just read in and check parameter names
resolve_command_list= None You can supply any resolve command here NOTE:
for command-line usage you need to enclose the
whole set of commands in double quotes (")
and each individual command in single quotes (')
like this: resolve_command_list="'no_build'
'b_overall 23' "
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