def exercise_1():
pdb_file = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/1yjp_h.pdb",
test=os.path.isfile)
mtz_file = libtbx.env.find_in_repositories(
relative_path="phenix_regression/reflection_files/1yjp.mtz",
test=os.path.isfile)
if (None in [pdb_file, mtz_file]) :
print "phenix_regression not found, skipping test"
return False
pdb_in = file_reader.any_file(pdb_file)
hierarchy = pdb_in.file_object.hierarchy
hierarchy.atoms().reset_i_seq()
xrs = pdb_in.file_object.xray_structure_simple()
mtz_in = file_reader.any_file(mtz_file)
f_obs = mtz_in.file_server.miller_arrays[0]
r_free = mtz_in.file_server.miller_arrays[1]
r_free = r_free.customized_copy(data=(r_free.data()==1))
fmodel = mmtbx.utils.fmodel_simple(
f_obs=f_obs,
r_free_flags=r_free,
xray_structures=[xrs],
scattering_table="n_gaussian")
map_stats = real_space_correlation.map_statistics_for_fragment(
fragment=hierarchy,
fmodel=fmodel)
assert approx_equal(map_stats.cc, 0.960, eps=0.01)
edm = fmodel.electron_density_map()
map1_coeffs = edm.map_coefficients("2mFo-DFc")
map1 = map1_coeffs.fft_map(
resolution_factor=0.25).apply_sigma_scaling().real_map()
map2_coeffs = edm.map_coefficients("Fmodel")
map2 = map2_coeffs.fft_map(
resolution_factor=0.25).apply_sigma_scaling().real_map()
xray_structure = fmodel.xray_structure
map_stats2 = real_space_correlation.map_statistics_for_atom_selection(
atom_selection=flex.bool(xrs.sites_cart().size(), True),
map1=map1,
map2=map2,
xray_structure=xrs)
assert approx_equal(map_stats2.cc, map_stats.cc, 0.01)
# XXX other code outside cctbx depends on the current API - do not simply
# change the test if this breaks!
results = real_space_correlation.simple(
fmodel=fmodel,
pdb_hierarchy=hierarchy,
log=null_out())
assert isinstance(results, list)
assert isinstance(results[0], group_args)
assert (results[0].n_atoms == 1)
assert (results[0].id_str == " A GLY 1 N ")
return True
def exercise_1():
pdb_file = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/1yjp_h.pdb", test=os.path.isfile)
mtz_file = libtbx.env.find_in_repositories(
relative_path="phenix_regression/reflection_files/1yjp.mtz",
test=os.path.isfile)
if (None in [pdb_file, mtz_file]):
print "phenix_regression not found, skipping test"
return False
pdb_in = file_reader.any_file(pdb_file)
hierarchy = pdb_in.file_object.hierarchy
hierarchy.atoms().reset_i_seq()
xrs = pdb_in.file_object.xray_structure_simple()
mtz_in = file_reader.any_file(mtz_file)
f_obs = mtz_in.file_server.miller_arrays[0]
r_free = mtz_in.file_server.miller_arrays[1]
r_free = r_free.customized_copy(data=(r_free.data() == 1))
fmodel = mmtbx.utils.fmodel_simple(f_obs=f_obs,
r_free_flags=r_free,
xray_structures=[xrs],
scattering_table="n_gaussian")
map_stats = real_space_correlation.map_statistics_for_fragment(
fragment=hierarchy, fmodel=fmodel)
assert approx_equal(map_stats.cc, 0.960, eps=0.01)
edm = fmodel.electron_density_map()
map1_coeffs = edm.map_coefficients("2mFo-DFc")
map1 = map1_coeffs.fft_map(
resolution_factor=0.25).apply_sigma_scaling().real_map()
map2_coeffs = edm.map_coefficients("Fmodel")
map2 = map2_coeffs.fft_map(
resolution_factor=0.25).apply_sigma_scaling().real_map()
xray_structure = fmodel.xray_structure
map_stats2 = real_space_correlation.map_statistics_for_atom_selection(
atom_selection=flex.bool(xrs.sites_cart().size(), True),
map1=map1,
map2=map2,
xray_structure=xrs)
assert approx_equal(map_stats2.cc, map_stats.cc, 0.01)
# XXX other code outside cctbx depends on the current API - do not simply
# change the test if this breaks!
overall_cc, results = real_space_correlation.simple(
fmodel=fmodel, pdb_hierarchy=hierarchy, log=null_out())
assert isinstance(overall_cc, float)
assert isinstance(results, list)
assert isinstance(results[0], group_args)
assert (results[0].n_atoms == 1)
assert (results[0].id_str == " A GLY 1 N ")
return True
def exercise_rejoin():
from mmtbx.building.alternate_conformations.tst_build_simple import pdb_raw
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=pdb_raw)
hierarchy = pdb_in.hierarchy
params = alternate_conformations.rejoin_phil.extract()
n_modified = alternate_conformations.rejoin_split_single_conformers(
pdb_hierarchy=hierarchy,
params=params,
model_error_ml=0.5,
log=null_out())
assert (n_modified == 3), n_modified # Gln5
# split residue 6 without changing coordinates, set occupancy very low
chain = hierarchy.only_model().chains()[0]
rg6 = chain.residue_groups()[5]
ag = rg6.only_atom_group().detached_copy()
for atom in ag.atoms():
atom.occ = 0.05
for atom in rg6.atoms():
atom.occ = 0.95
rg6.only_atom_group().altloc = 'A'
ag.altloc = 'B'
rg6.append_atom_group(ag)
n_modified = alternate_conformations.rejoin_split_single_conformers(
pdb_hierarchy=hierarchy.deep_copy(),
params=params,
model_error_ml=0.5,
log=null_out())
assert (n_modified == 1), n_modified
# now with higher B-factors for all atoms
for atom in hierarchy.atoms():
atom.b = atom.b * 10
n_modified = alternate_conformations.rejoin_split_single_conformers(
pdb_hierarchy=hierarchy, params=params, log=null_out())
assert (n_modified == 1), n_modified
def exercise_map_utils () :
#
# UNSTABLE
#
hierarchy, fmodel = get_1yjp_pdb_and_fmodel()
sel_cache = hierarchy.atom_selection_cache()
sele = sel_cache.selection("resseq 5 and (name CD or name OE1 or name NE2)")
sele_all = sel_cache.selection("resseq 5")
fmodel.xray_structure.scale_adp(factor=0.5, selection=sele)
fmodel.update_xray_structure(update_f_calc=True)
two_fofc_map, fofc_map = building.get_difference_maps(fmodel)
map_stats = building.local_density_quality(
fofc_map=fofc_map,
two_fofc_map=two_fofc_map,
atom_selection=sele_all,
xray_structure=fmodel.xray_structure)
out = StringIO()
map_stats.show_atoms_outside_density(out=out, two_fofc_cutoff=3.0)
pdb_strs = [ l.split(":")[0] for l in out.getvalue().splitlines() ]
assert len(pdb_strs) > 0
# XXX there seems to be a stochastic effect here
#assert (pdb_strs == ['pdb=" CA GLN A 5 "', 'pdb=" CB GLN A 5 "',
# 'pdb=" CD GLN A 5 "', 'pdb=" NE2 GLN A 5 "']), \
# pdb_strs
fc_map = fmodel.map_coefficients(map_type="Fc").fft_map(
resolution_factor=0.25).apply_sigma_scaling().real_map_unpadded()
assert (map_stats.number_of_atoms_below_fofc_map_level() == 3)
assert (map_stats.fraction_of_nearby_grid_points_above_cutoff() > 0.0)
stats = building.get_model_map_stats(
selection=sele_all,
target_map=two_fofc_map,
model_map=fc_map,
unit_cell=fmodel.xray_structure.unit_cell(),
sites_cart=fmodel.xray_structure.sites_cart(),
pdb_atoms=hierarchy.atoms())
def load_pdb_structure(id, format="pdb", allow_unknowns=False,
local_cache=None):
"""
Simple utility method to load the PDB hierarchy and xray structure objects
directly (without intermediate files).
"""
data = fetch(id=id, format=format, log=null_out(), local_cache=local_cache)
import iotbx.pdb.hierarchy
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=data.read())
hierarchy = pdb_in.hierarchy
hierarchy.atoms().reset_i_seq()
# XXX enable_scattering_type_unknown can be modified here because the PDB
# (unfortunately) contains many unknowns which would crash this
xray_structure = pdb_in.input.xray_structure_simple(
enable_scattering_type_unknown=allow_unknowns)
return hierarchy, xray_structure
def exercise_map_utils () :
#
# UNSTABLE 2x
#
hierarchy, fmodel = get_1yjp_pdb_and_fmodel()
sel_cache = hierarchy.atom_selection_cache()
sele = sel_cache.selection("resseq 5 and (name CD or name OE1 or name NE2)")
sele_all = sel_cache.selection("resseq 5")
fmodel.xray_structure.scale_adp(factor=0.5, selection=sele)
fmodel.update_xray_structure(update_f_calc=True)
two_fofc_map, fofc_map = building.get_difference_maps(fmodel)
map_stats = building.local_density_quality(
fofc_map=fofc_map,
two_fofc_map=two_fofc_map,
atom_selection=sele_all,
xray_structure=fmodel.xray_structure)
out = StringIO()
map_stats.show_atoms_outside_density(out=out, two_fofc_cutoff=3.0)
pdb_strs = [ l.split(":")[0] for l in out.getvalue().splitlines() ]
assert len(pdb_strs) > 0
# XXX there seems to be a stochastic effect here
#assert (pdb_strs == ['pdb=" CA GLN A 5 "', 'pdb=" CB GLN A 5 "',
# 'pdb=" CD GLN A 5 "', 'pdb=" NE2 GLN A 5 "']), \
# pdb_strs
fc_map = fmodel.map_coefficients(map_type="Fc").fft_map(
resolution_factor=0.25).apply_sigma_scaling().real_map_unpadded()
assert (map_stats.number_of_atoms_below_fofc_map_level() == 3)
assert (map_stats.fraction_of_nearby_grid_points_above_cutoff() > 0.0)
stats = building.get_model_map_stats(
selection=sele_all,
target_map=two_fofc_map,
model_map=fc_map,
unit_cell=fmodel.xray_structure.unit_cell(),
sites_cart=fmodel.xray_structure.sites_cart(),
pdb_atoms=hierarchy.atoms())
def load_pdb_structure (id, format="pdb", allow_unknowns=False,
local_cache=None) :
"""
Simple utility method to load the PDB hierarchy and xray structure objects
directly (without intermediate files).
"""
data = fetch(id=id, format=format, log=null_out(), local_cache=local_cache)
import iotbx.pdb.hierarchy
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=data.read())
hierarchy = pdb_in.hierarchy
hierarchy.atoms().reset_i_seq()
# XXX enable_scattering_type_unknown can be modified here because the PDB
# (unfortunately) contains many unknowns which would crash this
xray_structure = pdb_in.input.xray_structure_simple(
enable_scattering_type_unknown=allow_unknowns)
return hierarchy, xray_structure
def exercise () :
from mmtbx.building.alternate_conformations import conformer_generation
from mmtbx.monomer_library import server
import iotbx.pdb.hierarchy
generate_inputs()
params = master_phil().extract()
mon_lib_srv = server.server()
pdb_in = iotbx.pdb.hierarchy.input(file_name="shear_frag_single.pdb")
hierarchy = pdb_in.hierarchy
pdb_atoms = hierarchy.atoms()
pdb_atoms.reset_i_seq()
sites_cart = pdb_atoms.extract_xyz()
xrs = pdb_in.input.xray_structure_simple()
models = []
prev_res = next_res = next_next_res = None
for chain in hierarchy.only_model().chains() :
residue_groups = chain.residue_groups()
n_rg = len(residue_groups) # should be 4
for i_res, residue_group in enumerate(residue_groups) :
sites_orig = sites_cart.deep_copy()
next_res = next_next_res = None
if (i_res < (n_rg - 1)) :
next_res = residue_groups[i_res+1].atom_groups()[0]
if (i_res < (n_rg - 2)) :
next_next_res = residue_groups[i_res+2].atom_groups()[0]
atom_groups = residue_group.atom_groups()
primary_conf = atom_groups[0]
out = StringIO()
confs = []
for conf in conformer_generation.generate_single_residue_confs(
atom_group=primary_conf,
sites_cart=sites_cart.deep_copy(),
mon_lib_srv=mon_lib_srv,
params=params.torsion_search,
prev_residue=prev_res,
next_residue=next_res,
next_next_residue=next_next_res,
backrub=False,
shear=True) :
conf.show_summary(out=out)
confs.append(conf)
prev_res = primary_conf
if (confs is None) :
continue
if (i_res == 1) :
assert (""" A ILE 7 None 4.0 mt""")
for conf in confs :
sites_new = sites_cart.set_selected(conf.sites_selection,
conf.sites_selected())
pdb_atoms.set_xyz(sites_new)
models.append(hierarchy.only_model().detached_copy())
new_hierarchy = iotbx.pdb.hierarchy.root()
for i_model, conf in enumerate(models) :
conf.id = str(i_model + 1)
new_hierarchy.append_model(conf)
open("shear_frag_naive_ensemble.pdb", "w").write(
new_hierarchy.as_pdb_string())
def exercise_set_charge () :
from iotbx import file_reader
input_pdb = """
ATOM 1 CL CL X 1 0.000 0.000 0.000 1.00 20.00 CL
END
"""
open("tmp_cl.pdb", "w").write(input_pdb)
easy_run.call('phenix.pdbtools tmp_cl.pdb charge_selection="element Cl" charge=-1 --quiet')
pdb_in = file_reader.any_file("tmp_cl.pdb_modified.pdb").file_object
hierarchy = pdb_in.hierarchy
xrs = pdb_in.xray_structure_simple()
assert (xrs.scatterers()[0].scattering_type == 'Cl1-')
assert (hierarchy.atoms()[0].charge == '1-')
def exercise_set_charge():
from iotbx import file_reader
input_pdb = """
ATOM 1 CL CL X 1 0.000 0.000 0.000 1.00 20.00 CL
END
"""
open("tmp_cl.pdb", "w").write(input_pdb)
easy_run.call(
'phenix.pdbtools tmp_cl.pdb charge_selection="element Cl" charge=-1 --quiet'
)
pdb_in = file_reader.any_file("tmp_cl.pdb_modified.pdb").file_object
hierarchy = pdb_in.hierarchy
xrs = pdb_in.xray_structure_simple()
assert (xrs.scatterers()[0].scattering_type == 'Cl1-')
assert (hierarchy.atoms()[0].charge == '1-')
def realign (self, atom_selection_string) :
self.atom_selection_string = atom_selection_string
ref_atoms = self.reference_hierarchy.atoms()
ref_atoms.reset_i_seq()
if (self.atom_selection_string is not None) :
assert (not self.calpha_only) and (self.backbone_only != True)
elif (self.calpha_only) :
self.atom_selection_string = "name CA"
elif (self.backbone_only) :
self.atom_selection_string = \
"name CA or name CB or name C or name N or name O"
else :
self.atom_selection_string = "all"
from scitbx.array_family import flex
sel_cache = self.reference_hierarchy.atom_selection_cache()
self.atom_selection = sel_cache.selection(self.atom_selection_string)
assert (self.atom_selection.count(True) > 0)
self.atoms_ref = []
ref_sel = flex.size_t()
ref_chain = self.reference_hierarchy.only_model().only_chain()
for residue_group in ref_chain.residue_groups() :
rg_atoms = residue_group.only_atom_group().atoms()
for atom in rg_atoms :
if (not self.atom_selection[atom.i_seq]) :
continue
resid = residue_group.resid()
self.atoms_ref.append("%s %s" % (resid, atom.name.strip()))
ref_sel.append(atom.i_seq)
assert (len(ref_sel) > 0)
sites_ref = ref_atoms.extract_xyz()
self.reference_sites = sites_ref.select(ref_sel)
sites_moved = easy_mp.pool_map(
iterable=range(len(self.related_chains)),
fixed_func=self.align_model,
processes=self.nproc)
self.selection_moved = []
for k, lsq_fit in enumerate(sites_moved) :
hierarchy = self.related_chains[k].pdb_hierarchy
if (lsq_fit is None) :
print >> self.log, "No LSQ fit for model %s:%s" % \
(self.related_chains[k].source_info, self.related_chains[k].chain_id)
continue
self.selection_moved.append(k)
pdb_atoms = hierarchy.atoms()
sites_cart = lsq_fit.r.elems * pdb_atoms.extract_xyz() + lsq_fit.t.elems
pdb_atoms.set_xyz(sites_cart)
def realign(self, atom_selection_string):
self.atom_selection_string = atom_selection_string
ref_atoms = self.reference_hierarchy.atoms()
ref_atoms.reset_i_seq()
if (self.atom_selection_string is not None):
assert (not self.calpha_only) and (self.backbone_only != True)
elif (self.calpha_only):
self.atom_selection_string = "name CA"
elif (self.backbone_only):
self.atom_selection_string = \
"name CA or name CB or name C or name N or name O"
else :
self.atom_selection_string = "all"
from scitbx.array_family import flex
sel_cache = self.reference_hierarchy.atom_selection_cache()
self.atom_selection = sel_cache.selection(self.atom_selection_string)
assert (self.atom_selection.count(True) > 0)
self.atoms_ref = []
ref_sel = flex.size_t()
ref_chain = self.reference_hierarchy.only_model().only_chain()
for residue_group in ref_chain.residue_groups():
rg_atoms = residue_group.only_atom_group().atoms()
for atom in rg_atoms :
if (not self.atom_selection[atom.i_seq]):
continue
resid = residue_group.resid()
self.atoms_ref.append("%s %s" % (resid, atom.name.strip()))
ref_sel.append(atom.i_seq)
assert (len(ref_sel) > 0)
sites_ref = ref_atoms.extract_xyz()
self.reference_sites = sites_ref.select(ref_sel)
sites_moved = easy_mp.pool_map(
iterable=range(len(self.related_chains)),
fixed_func=self.align_model,
processes=self.nproc)
self.selection_moved = []
for k, lsq_fit in enumerate(sites_moved):
hierarchy = self.related_chains[k].pdb_hierarchy
if (lsq_fit is None):
print("No LSQ fit for model %s:%s" % \
(self.related_chains[k].source_info, self.related_chains[k].chain_id), file=self.log)
continue
self.selection_moved.append(k)
pdb_atoms = hierarchy.atoms()
sites_cart = lsq_fit.r.elems * pdb_atoms.extract_xyz() + lsq_fit.t.elems
pdb_atoms.set_xyz(sites_cart)
def exercise_rejoin () :
from mmtbx.building.alternate_conformations.tst_build_simple import pdb_raw
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=pdb_raw)
hierarchy = pdb_in.hierarchy
params = alternate_conformations.rejoin_phil.extract()
n_modified = alternate_conformations.rejoin_split_single_conformers(
pdb_hierarchy=hierarchy,
params=params,
model_error_ml=0.5,
log=null_out())
assert (n_modified == 3), n_modified # Gln5
# split residue 6 without changing coordinates, set occupancy very low
chain = hierarchy.only_model().chains()[0]
rg6 = chain.residue_groups()[5]
ag = rg6.only_atom_group().detached_copy()
for atom in ag.atoms() :
atom.occ = 0.05
for atom in rg6.atoms() :
atom.occ = 0.95
rg6.only_atom_group().altloc = 'A'
ag.altloc = 'B'
rg6.append_atom_group(ag)
n_modified = alternate_conformations.rejoin_split_single_conformers(
pdb_hierarchy=hierarchy.deep_copy(),
params=params,
model_error_ml=0.5,
log=null_out())
assert (n_modified == 1), n_modified
# now with higher B-factors for all atoms
for atom in hierarchy.atoms() :
atom.b = atom.b * 10
n_modified = alternate_conformations.rejoin_split_single_conformers(
pdb_hierarchy=hierarchy,
params=params,
log=null_out())
assert (n_modified == 1), n_modified
def __init__(
self,
hierarchy=None,
# XXX warning, ncs_phil_groups can be changed inside...
ncs_phil_groups=None,
params=None,
log=None,
):
"""
TODO:
1. Transfer get_ncs_info_as_spec() to ncs/ncs.py:ncs
Select method to build ncs_group_object
order of implementation:
1) ncs_phil_groups - user-supplied definitions are filtered
2) hierarchy only - Performing NCS search
Args:
-----
ncs_phil_groups: iotbx.phil.parse(ncs_group_phil_str).extract().ncs_group
chain_max_rmsd (float): limit of rms difference between chains to be considered
as copies
min_percent (float): Threshold for similarity between chains
similarity define as:
(number of matching res) / (number of res in longer chain)
chain_similarity_threshold (float): min similarity between matching chains
residue_match_radius (float): max allow distance difference between pairs of matching
atoms of two residues
"""
self.number_of_ncs_groups = 0 # consider removing/replacing with function
self.ncs_restraints_group_list = class_ncs_restraints_group_list()
# keep hierarchy for writing (To have a source of atoms labels)
self.hierarchy = hierarchy
# residues common to NCS copies. Used for .spec representation
self.common_res_dict = {}
# Collect messages, recommendation and errors
self.messages = '' # Not used outside...
self.old_i_seqs = None
self.original_hierarchy = None
self.truncated_hierarchy = None
self.truncated_h_asc = None
self.chains_info = None
extension = ''
# set search parameters
self.params = params
if self.params is None:
self.params = input.get_default_params().ncs_search
#
if log is None:
self.log = sys.stdout
else:
self.log = log
if hierarchy:
# for a in hierarchy.atoms():
# print "oo", a.i_seq, a.id_str()
# print "====="
hierarchy.atoms().reset_i_seq()
self.original_hierarchy = hierarchy.deep_copy()
self.original_hierarchy.reset_atom_i_seqs()
if self.params.exclude_selection is not None:
# pdb_hierarchy_inp.hierarchy.write_pdb_file("in_ncs_pre_before.pdb")
cache = hierarchy.atom_selection_cache()
sel = cache.selection("not (%s)" %
self.params.exclude_selection)
self.truncated_hierarchy = hierarchy.select(sel)
else:
# this could be to save iseqs but I'm not sure
self.truncated_hierarchy = hierarchy.select(
flex.size_t_range(hierarchy.atoms_size()))
self.old_i_seqs = self.truncated_hierarchy.atoms().extract_i_seq()
# print "self.old_i_seqs", list(self.old_i_seqs)
# self.truncated_hierarchy.atoms().reset_i_seq()
self.truncated_hierarchy.reset_atom_i_seqs()
self.truncated_h_asc = self.truncated_hierarchy.atom_selection_cache(
)
# self.truncated_hierarchy.write_pdb_file("in_ncs_pre_after.pdb")
self.chains_info = ncs_search.get_chains_info(
self.truncated_hierarchy)
if self.truncated_hierarchy.atoms_size() == 0:
return
#
# print "ncs_groups before validation", ncs_phil_groups
validated_ncs_phil_groups = None
validated_ncs_phil_groups = self.validate_ncs_phil_groups(
pdb_h=self.truncated_hierarchy,
ncs_phil_groups=ncs_phil_groups,
asc=self.truncated_h_asc)
if validated_ncs_phil_groups is None:
# print "Last chance, building from hierarchy"
self.build_ncs_obj_from_pdb_asu(pdb_h=self.truncated_hierarchy,
asc=self.truncated_h_asc)
# error handling
if self.ncs_restraints_group_list.get_n_groups() == 0:
print >> self.log, '========== WARNING! ============\n'
print >> self.log, ' No NCS relation were found !!!\n'
print >> self.log, '================================\n'
if self.messages != '':
print >> self.log, self.messages
def exercise():
from mmtbx.building.alternate_conformations import density_sampling
from mmtbx.utils import fmodel_simple
from mmtbx.monomer_library import server
from iotbx import file_reader
import iotbx.pdb.hierarchy
generate_inputs()
fmodel_params = """
high_resolution = 1.2
r_free_flags_fraction = 0.1
add_sigmas = True
pdb_file = ser_frag.pdb
output {
label = F
type = *real complex
file_name = ser_frag.mtz
}
fmodel.k_sol = 0.3
fmodel.b_sol = 20
"""
open("ser_frag_fmodel.eff", "w").write(fmodel_params)
assert (easy_run.fully_buffered("phenix.fmodel ser_frag_fmodel.eff").
raise_if_errors().return_code == 0)
assert os.path.isfile("ser_frag.mtz")
mtz_in = file_reader.any_file("ser_frag.mtz")
f_obs = mtz_in.file_server.miller_arrays[0]
flags = mtz_in.file_server.miller_arrays[1]
flags = flags.customized_copy(data=(flags.data() == 1))
mon_lib_srv = server.server()
pdb_in = iotbx.pdb.hierarchy.input(file_name="ser_frag_single.pdb")
hierarchy = pdb_in.hierarchy
pdb_atoms = hierarchy.atoms()
pdb_atoms.reset_i_seq()
sites_cart = pdb_atoms.extract_xyz()
xrs = pdb_in.input.xray_structure_simple()
fmodel = fmodel_simple(f_obs=f_obs,
xray_structures=[xrs],
scattering_table="n_gaussian",
r_free_flags=flags,
skip_twin_detection=True)
models = []
prev_res = next_res = next_next_res = None
for chain in hierarchy.only_model().chains():
residue_groups = chain.residue_groups()
n_rg = len(residue_groups)
for i_res, residue_group in enumerate(residue_groups):
sites_orig = sites_cart.deep_copy()
next_res = next_next_res = None
if (i_res < (n_rg - 1)):
next_res = residue_groups[i_res + 1].atom_groups()[0]
if (i_res < (n_rg - 2)):
next_next_res = residue_groups[i_res + 2].atom_groups()[0]
atom_groups = residue_group.atom_groups()
primary_conf = atom_groups[0]
out = StringIO()
confs = density_sampling.screen_residue(
residue=primary_conf,
prev_residue=prev_res,
next_residue=next_res,
next_next_residue=next_next_res,
sites_cart=sites_cart,
fmodel=fmodel,
mon_lib_srv=mon_lib_srv,
params=None,
backrub=True,
shear=False,
verbose=True,
out=out)
prev_res = primary_conf
if (confs is None):
continue
# TODO tweak density sampling to allow a backrubbed conformer with a
# chi1 t rotamer for Ser 99
if (i_res == 1):
assert (""" A SER 99 20.0 None t"""
in out.getvalue())
for conf in confs:
sites_new = sites_cart.set_selected(conf.sites_selection,
conf.sites_selected())
pdb_atoms.set_xyz(sites_new)
models.append(hierarchy.only_model().detached_copy())
confs = density_sampling.screen_residue(
residue=primary_conf,
prev_residue=prev_res,
next_residue=next_res,
next_next_residue=next_next_res,
sites_cart=sites_cart,
fmodel=fmodel,
mon_lib_srv=mon_lib_srv,
params=None,
backrub=False,
out=out)
if (i_res == 1):
print len(confs)
new_hierarchy = iotbx.pdb.hierarchy.root()
for i_model, conf in enumerate(models):
conf.id = str(i_model + 1)
new_hierarchy.append_model(conf)
open("ser_frag_guided_ensemble.pdb",
"w").write(new_hierarchy.as_pdb_string())
reference_sites=sites_cart_pentagon,
other_sites=sites_cart)
sites_cart_out = sup.other_sites_best_fit()
for site_label,site_cart in zip(atom_names, sites_cart_out):
atom = iotbx.pdb.hierarchy.atom()
atom.name = " %-3s" % site_label
atom.xyz = matrix.col(site_cart) + matrix.col((0,0,i_stack*1.5))
atom.occ = 1
atom.b = 20
atom.element = " " + site_label[0]
atom_group.append_atom(atom)
residue_group = iotbx.pdb.hierarchy.residue_group(
resseq="%4d" % (i_stack+1), icode=" ")
residue_group.append_atom_group(atom_group)
chain.append_residue_group(residue_group)
hierarchy.atoms().reset_serial()
pdb_str = hierarchy.as_pdb_string(append_end=True)
file_name = "puckers.pdb"
print "Writing file:", file_name
open(file_name, "w").write("""\
REMARK random_puckers.py
REMARK 1 = 3'
REMARK 2 = 2'
REMARK 3 = A
REMARK 4 = B
""" + pdb_str)
#
print "OK"
if (__name__ == "__main__"):
run(args=sys.argv[1:])
def exercise () :
from mmtbx.building.alternate_conformations import density_sampling
from mmtbx.utils import fmodel_simple
from mmtbx.monomer_library import server
from iotbx import file_reader
import iotbx.pdb.hierarchy
generate_inputs()
fmodel_params = """
high_resolution = 1.2
r_free_flags_fraction = 0.1
add_sigmas = True
pdb_file = shear_frag.pdb
output {
label = F
type = *real complex
file_name = shear_frag.mtz
}
fmodel.k_sol = 0.3
fmodel.b_sol = 20
"""
open("shear_frag_fmodel.eff", "w").write(fmodel_params)
assert (easy_run.fully_buffered("phenix.fmodel shear_frag_fmodel.eff"
).raise_if_errors().return_code == 0)
assert os.path.isfile("shear_frag.mtz")
mtz_in = file_reader.any_file("shear_frag.mtz")
f_obs = mtz_in.file_server.miller_arrays[0]
flags = mtz_in.file_server.miller_arrays[1]
flags = flags.customized_copy(data=(flags.data()==1))
mon_lib_srv = server.server()
pdb_in = iotbx.pdb.hierarchy.input(file_name="shear_frag_single.pdb")
hierarchy = pdb_in.hierarchy
pdb_atoms = hierarchy.atoms()
pdb_atoms.reset_i_seq()
sites_cart = pdb_atoms.extract_xyz()
xrs = pdb_in.input.xray_structure_simple()
fmodel = fmodel_simple(
f_obs=f_obs,
xray_structures=[xrs],
scattering_table="n_gaussian",
r_free_flags=flags,
skip_twin_detection=True)
models = []
prev_res = next_res = next_next_res = None
for chain in hierarchy.only_model().chains() :
residue_groups = chain.residue_groups()
n_rg = len(residue_groups) # should be 4
for i_res, residue_group in enumerate(residue_groups) :
sites_orig = sites_cart.deep_copy()
next_res = next_next_res = None
if (i_res < (n_rg - 1)) :
next_res = residue_groups[i_res+1].atom_groups()[0]
if (i_res < (n_rg - 2)) :
next_next_res = residue_groups[i_res+2].atom_groups()[0]
atom_groups = residue_group.atom_groups()
primary_conf = atom_groups[0]
out = StringIO()
confs = density_sampling.screen_residue(
residue=primary_conf,
prev_residue=prev_res,
next_residue=next_res,
next_next_residue=next_next_res,
sites_cart=sites_cart,
fmodel=fmodel,
mon_lib_srv=mon_lib_srv,
params=None,
backrub=True,
shear=True,
verbose=True,
out=out)
prev_res = primary_conf
if (confs is None) :
continue
if (i_res == 1) :
assert (""" A ILE 7 None 4.0 mt""")
for conf in confs :
sites_new = sites_cart.set_selected(conf.sites_selection,
conf.sites_selected())
pdb_atoms.set_xyz(sites_new)
models.append(hierarchy.only_model().detached_copy())
new_hierarchy = iotbx.pdb.hierarchy.root()
for i_model, conf in enumerate(models) :
conf.id = str(i_model + 1)
new_hierarchy.append_model(conf)
open("shear_frag_naive_ensemble.pdb", "w").write(
new_hierarchy.as_pdb_string())
def run(args):
assert args in [[], ["--verbose"]]
if (len(args) != 0):
cout = sys.stdout
else:
cout = null_out()
edge_list_bonds = [(0, 1), (0, 4), (1, 2), (2, 3), (3, 4)]
bond_list = [(("C1*", "C2*"), 1.529), (("C1*", "O4*"), 1.412),
(("C2*", "C3*"), 1.526), (("C3*", "C4*"), 1.520),
(("C4*", "O4*"), 1.449)]
angle_list = [
(("C1*", "C2*", "C3*"), 101.3), (("C2*", "C3*", "C4*"), 102.3),
(("C3*", "C4*", "O4*"), 104.2), (("C4*", "O4*", "C1*"), 110.0)
]
sites_cart, geo_manager = cctbx.geometry_restraints.manager \
.construct_non_crystallographic_conserving_bonds_and_angles(
sites_cart=sites_cart_3p,
edge_list_bonds=edge_list_bonds,
edge_list_angles=[])
for bond_atom_names, distance_ideal in bond_list:
i, j = [atom_names.index(atom_name) for atom_name in bond_atom_names]
bond_params = geo_manager.bond_params_table[i][j]
assert approx_equal(bond_params.distance_ideal,
distance_ideal,
eps=1.e-2)
bond_params.distance_ideal = distance_ideal
bond_params.weight = 1 / 0.02**2
assert geo_manager.angle_proxies is None
geo_manager.angle_proxies = cctbx.geometry_restraints.shared_angle_proxy()
for angle_atom_names, angle_ideal in angle_list:
i_seqs = [
atom_names.index(atom_name) for atom_name in angle_atom_names
]
geo_manager.angle_proxies.append(
cctbx.geometry_restraints.angle_proxy(i_seqs=i_seqs,
angle_ideal=angle_ideal,
weight=1 / 3**2))
geo_manager.show_sorted(site_labels=atom_names,
sites_cart=sites_cart,
f=cout)
def lbfgs(sites_cart):
for i_lbfgs_restart in range(3):
minimized = cctbx.geometry_restraints.lbfgs.lbfgs(
sites_cart=sites_cart, geometry_restraints_manager=geo_manager)
assert is_below_limit(value=minimized.final_target_value,
limit=1e-10)
return minimized
lbfgs(sites_cart=sites_cart_3p)
lbfgs(sites_cart=sites_cart_2p)
conformer_counts = [0] * 4
sites_cart = sites_cart.deep_copy()
mt = flex.mersenne_twister(seed=0)
for i_trial in range(20):
while True:
for i in range(sites_cart.size()):
sites_cart[i] = mt.random_double_point_on_sphere()
try:
lbfgs(sites_cart=sites_cart)
except RuntimeError as e:
if (not str(e).startswith(
"Bond distance > max_reasonable_bond_distance: ")):
raise
else:
break
rmsd_list = flex.double()
for reference_sites in [
sites_cart_3p, sites_cart_2p, sites_cart_a, sites_cart_b
]:
sup = scitbx.math.superpose.least_squares_fit(
reference_sites=reference_sites, other_sites=sites_cart)
rmsd = reference_sites.rms_difference(sup.other_sites_best_fit())
rmsd_list.append(rmsd)
oline = " ".join(["%.3f" % rmsd for rmsd in rmsd_list])
print(oline, file=cout)
assert is_below_limit(min(rmsd_list), 1e-3)
conformer_counts[flex.min_index(rmsd_list)] += 1
print("conformer_counts:", conformer_counts)
#
if (libtbx.env.has_module("iotbx")):
import iotbx.pdb.hierarchy
hierarchy = iotbx.pdb.hierarchy.root()
model = iotbx.pdb.hierarchy.model(id="")
chain = iotbx.pdb.hierarchy.chain(id="A")
model.append_chain(chain)
hierarchy.append_model(model)
#
sites_cart_pentagon = pentagon_sites_cart()
for i_stack, sites_cart in enumerate(
[sites_cart_3p, sites_cart_2p, sites_cart_a, sites_cart_b]):
atom_group = iotbx.pdb.hierarchy.atom_group(resname=" U",
altloc="")
sup = scitbx.math.superpose.least_squares_fit(
reference_sites=sites_cart_pentagon, other_sites=sites_cart)
sites_cart_out = sup.other_sites_best_fit()
for site_label, site_cart in zip(atom_names, sites_cart_out):
atom = iotbx.pdb.hierarchy.atom()
atom.name = " %-3s" % site_label
atom.xyz = matrix.col(site_cart) + matrix.col(
(0, 0, i_stack * 1.5))
atom.occ = 1
atom.b = 20
atom.element = " " + site_label[0]
atom_group.append_atom(atom)
residue_group = iotbx.pdb.hierarchy.residue_group(resseq="%4d" %
(i_stack + 1),
icode=" ")
residue_group.append_atom_group(atom_group)
chain.append_residue_group(residue_group)
hierarchy.atoms().reset_serial()
pdb_str = hierarchy.as_pdb_string(append_end=True)
file_name = "puckers.pdb"
print("Writing file:", file_name)
open(file_name, "w").write("""\
REMARK random_puckers.py
REMARK 1 = 3'
REMARK 2 = 2'
REMARK 3 = A
REMARK 4 = B
""" + pdb_str)
#
print("OK")
def combine_ensembles (self, pdb_hierarchy) :
"""
Iterate over all residues covered by the group, and pick the alternate
conformers out for each residue to combine into a continous fragment.
If additional conformers are needed, the previously existing atom group
will be duplicated as necessary.
"""
from mmtbx import building
from scitbx.array_family import flex
hierarchy = pdb_hierarchy.deep_copy()
pdb_atoms = hierarchy.atoms()
pdb_atoms.reset_i_seq()
n_atoms = len(pdb_atoms)
covered_selection = flex.bool(pdb_atoms.size(), False)
sites_cart = pdb_atoms.extract_xyz().deep_copy()
residue_groups = []
n_max = self.n_confs_max()
selection = self.get_entire_selection()
central_selection = self.get_central_residues_selection()
sub_hierarchy = hierarchy.deep_copy().select(selection)
sub_hierarchy.atoms().reset_i_seq()
sub_iselection = pdb_atoms.extract_i_seq().select(selection)
sub_central_selection = flex.bool(pdb_atoms.size(),
False).set_selected(central_selection, True).select(sub_iselection)
fragment_atom_groups = []
fragment_i_seqs = []
for residue_group in mmtbx.building.iter_residue_groups(sub_hierarchy) :
new_atom_groups = []
n_confs = 0
atom_group = residue_group.only_atom_group()
ag_new_isel = atom_group.atoms().extract_i_seq()
ag_old_isel = sub_iselection.select(ag_new_isel)
fragment_i_seqs.append(ag_old_isel)
original_sel = flex.bool(n_atoms, False).set_selected(ag_old_isel, True)
def new_atom_group (trial, selection) :
sites_new = sites_cart.deep_copy()
sites_new.set_selected(selection, trial.sites_cart)
new_ag = atom_group.detached_copy()
new_ag.atoms().set_xyz(sites_new.select(original_sel))
#for k, atom in enumerate(new_ag.atoms()) :
# atom.i_seq = ag_old_isel[k]
return new_ag
if (sub_central_selection.select(ag_new_isel).all_eq(True)) :
# residue is the center of the window for a single ensemble, so use
# the coordinates from that enemble
found_residue = False
for ens in self.ensembles :
if (original_sel.select(ens.residue_selection).all_eq(True)):
assert (not found_residue)
for trial in self.sites_trials :
new_atom_groups.append(new_atom_group(trial,
ens.selection))
n_confs += 1
found_residue = True
assert (found_residue)
else :
# adjacent residue only, so we take the best n_max out of all
# conformations (padding with the first conf if necessary)
all_trials = []
ens_selection = None
for ens in self.ensembles :
ens_selection_ = flex.bool(n_atoms, False).set_selected(
ens.selection, True)
if (ens_selection_.select(ag_old_isel).all_eq(True)) :
all_trials.extend(ens.sites_trials)
ens_selection = ens.selection
break
if (len(all_trials) == 0) :
raise RuntimeError("No matching atoms found for %s" %
atom_group.id_str())
# XXX sort by maximum deviation, or rmsd?
all_trials.sort(lambda a,b: cmp(b.max_dev, a.max_dev))
k = 0
while (n_confs < n_max) and (k < len(all_trials)) :
trial = all_trials[k]
new_atom_groups.append(new_atom_group(trial, ens_selection))
n_confs += 1
k += 1
# fill in the remaining conformations with copies of the first
while (n_confs < n_max) :
new_ag = atom_group.detached_copy()
new_atom_groups.append(new_ag)
n_confs += 1
fragment_atom_groups.append(new_atom_groups)
return fragment_atom_groups, fragment_i_seqs
cmdline = mmtbx.utils.cmdline_load_pdb_and_data(
args=args,
master_phil=master_phil,
process_pdb_file=False,
scattering_table="n_gaussian")
params = cmdline.params
working_phil = master_phil.format(python_object=params)
master_phil.fetch_diff(source=working_phil).show(out=out)
fmodel = cmdline.fmodel
hierarchy = cmdline.pdb_hierarchy
sele_cache = hierarchy.atom_selection_cache()
assert (params.selection is not None)
selection = sele_cache.selection(params.selection)
assert (selection.count(True) > 0)
have_results = False
pdb_atoms = hierarchy.atoms()
sites_cart = pdb_atoms.extract_xyz()
ensembles = []
t1 = time.time()
for chain in hierarchy.only_model().chains() :
prev_residue = next_residue = None
residue_groups = chain.residue_groups()
n_groups = len(residue_groups)
for i_res, residue_group in enumerate(residue_groups) :
if (i_res < n_groups - 1) :
next_residue = residue_groups[i_res+1].atom_groups()[0]
i_seqs = residue_group.atoms().extract_i_seq()
if (selection.select(i_seqs).all_eq(True)) :
atom_group = residue_group.only_atom_group()
if (get_class(atom_group.resname) != "common_amino_acid") :
continue
def combine_ensembles(self, pdb_hierarchy):
"""
Iterate over all residues covered by the group, and pick the alternate
conformers out for each residue to combine into a continous fragment.
If additional conformers are needed, the previously existing atom group
will be duplicated as necessary.
"""
from mmtbx import building
from scitbx.array_family import flex
hierarchy = pdb_hierarchy.deep_copy()
pdb_atoms = hierarchy.atoms()
pdb_atoms.reset_i_seq()
n_atoms = len(pdb_atoms)
covered_selection = flex.bool(pdb_atoms.size(), False)
sites_cart = pdb_atoms.extract_xyz().deep_copy()
residue_groups = []
n_max = self.n_confs_max()
selection = self.get_entire_selection()
central_selection = self.get_central_residues_selection()
sub_hierarchy = hierarchy.deep_copy().select(selection)
sub_hierarchy.atoms().reset_i_seq()
sub_iselection = pdb_atoms.extract_i_seq().select(selection)
sub_central_selection = flex.bool(pdb_atoms.size(),
False).set_selected(central_selection, True).select(sub_iselection)
fragment_atom_groups = []
fragment_i_seqs = []
for residue_group in mmtbx.building.iter_residue_groups(sub_hierarchy):
new_atom_groups = []
n_confs = 0
atom_group = residue_group.only_atom_group()
ag_new_isel = atom_group.atoms().extract_i_seq()
ag_old_isel = sub_iselection.select(ag_new_isel)
fragment_i_seqs.append(ag_old_isel)
original_sel = flex.bool(n_atoms, False).set_selected(ag_old_isel, True)
def new_atom_group(trial, selection):
sites_new = sites_cart.deep_copy()
sites_new.set_selected(selection, trial.sites_cart)
new_ag = atom_group.detached_copy()
new_ag.atoms().set_xyz(sites_new.select(original_sel))
#for k, atom in enumerate(new_ag.atoms()):
# atom.i_seq = ag_old_isel[k]
return new_ag
if (sub_central_selection.select(ag_new_isel).all_eq(True)):
# residue is the center of the window for a single ensemble, so use
# the coordinates from that enemble
found_residue = False
for ens in self.ensembles :
if (original_sel.select(ens.residue_selection).all_eq(True)):
assert (not found_residue)
for trial in self.sites_trials :
new_atom_groups.append(new_atom_group(trial,
ens.selection))
n_confs += 1
found_residue = True
assert (found_residue)
else :
# adjacent residue only, so we take the best n_max out of all
# conformations (padding with the first conf if necessary)
all_trials = []
ens_selection = None
for ens in self.ensembles :
ens_selection_ = flex.bool(n_atoms, False).set_selected(
ens.selection, True)
if (ens_selection_.select(ag_old_isel).all_eq(True)):
all_trials.extend(ens.sites_trials)
ens_selection = ens.selection
break
if (len(all_trials) == 0):
raise RuntimeError("No matching atoms found for %s" %
atom_group.id_str())
# XXX sort by maximum deviation, or rmsd?
all_trials.sort(key=operator.attrgetter("max_dev"), reverse=True)
k = 0
while (n_confs < n_max) and (k < len(all_trials)):
trial = all_trials[k]
new_atom_groups.append(new_atom_group(trial, ens_selection))
n_confs += 1
k += 1
# fill in the remaining conformations with copies of the first
while (n_confs < n_max):
new_ag = atom_group.detached_copy()
new_atom_groups.append(new_ag)
n_confs += 1
fragment_atom_groups.append(new_atom_groups)
return fragment_atom_groups, fragment_i_seqs
def run(args, out=None):
if (out is None): out = sys.stdout
from mmtbx.building.alternate_conformations import density_sampling
import mmtbx.maps.utils
import mmtbx.utils
from mmtbx.monomer_library import server
import iotbx.pdb.hierarchy
get_class = iotbx.pdb.common_residue_names_get_class
mon_lib_srv = server.server()
cmdline = mmtbx.utils.cmdline_load_pdb_and_data(
args=args,
master_phil=master_phil,
process_pdb_file=False,
scattering_table="n_gaussian")
params = cmdline.params
working_phil = master_phil.format(python_object=params)
master_phil.fetch_diff(source=working_phil).show(out=out)
fmodel = cmdline.fmodel
hierarchy = cmdline.pdb_hierarchy
sele_cache = hierarchy.atom_selection_cache()
assert (params.selection is not None)
selection = sele_cache.selection(params.selection)
assert (selection.count(True) > 0)
have_results = False
pdb_atoms = hierarchy.atoms()
sites_cart = pdb_atoms.extract_xyz()
ensembles = []
t1 = time.time()
for chain in hierarchy.only_model().chains():
prev_residue = next_residue = None
residue_groups = chain.residue_groups()
n_groups = len(residue_groups)
for i_res, residue_group in enumerate(residue_groups):
if (i_res < n_groups - 1):
next_residue = residue_groups[i_res + 1].atom_groups()[0]
i_seqs = residue_group.atoms().extract_i_seq()
if (selection.select(i_seqs).all_eq(True)):
atom_group = residue_group.only_atom_group()
if (get_class(atom_group.resname) != "common_amino_acid"):
continue
confs = density_sampling.screen_residue(
residue=atom_group,
prev_residue=prev_residue,
next_residue=next_residue,
sites_cart=sites_cart,
fmodel=fmodel,
mon_lib_srv=mon_lib_srv,
params=params,
map_file_name="map_coeffs.mtz",
out=out)
ensemble = []
for conf in confs:
conf_atoms = conf.set_atom_sites(pdb_atoms)
pdb_lines = []
for atom in conf_atoms:
pdb_lines.append(atom.format_atom_record())
ensemble.append("\n".join(pdb_lines))
ensembles.append(ensemble)
prev_residue = residue_group.atom_groups()[0]
if (len(ensembles) == 0):
raise Sorry("No alternate conformations found.")
t2 = time.time()
print("search time: %.1fs" % (t2 - t1), file=out)
for i_ens, ensemble in enumerate(ensembles):
ensemble_hierarchy = iotbx.pdb.hierarchy.root()
for k, model_str in enumerate(ensemble):
input = iotbx.pdb.hierarchy.input(pdb_string=model_str)
model = input.hierarchy.only_model().detached_copy()
model.id = str(k + 1)
ensemble_hierarchy.append_model(model)
f = open("ensemble_%d.pdb" % (i_ens + 1), "w")
f.write(ensemble_hierarchy.as_pdb_string())
f.close()
print("wrote ensemble_%d.pdb" % (i_ens + 1))
if (params.coot):
easy_run.call(
"coot --pdb %s --auto map_coeffs.mtz --pdb ensemble.pdb" %
params.input.pdb.file_name[0])
def run (args, out=None ):
if (out is None) : out = sys.stdout
from mmtbx.building.alternate_conformations import density_sampling
import mmtbx.maps.utils
import mmtbx.utils
from mmtbx.monomer_library import server
import iotbx.pdb.hierarchy
get_class = iotbx.pdb.common_residue_names_get_class
mon_lib_srv = server.server()
cmdline = mmtbx.utils.cmdline_load_pdb_and_data(
args=args,
master_phil=master_phil,
process_pdb_file=False,
scattering_table="n_gaussian")
params = cmdline.params
working_phil = master_phil.format(python_object=params)
master_phil.fetch_diff(source=working_phil).show(out=out)
fmodel = cmdline.fmodel
hierarchy = cmdline.pdb_hierarchy
sele_cache = hierarchy.atom_selection_cache()
assert (params.selection is not None)
selection = sele_cache.selection(params.selection)
assert (selection.count(True) > 0)
have_results = False
pdb_atoms = hierarchy.atoms()
sites_cart = pdb_atoms.extract_xyz()
ensembles = []
t1 = time.time()
for chain in hierarchy.only_model().chains() :
prev_residue = next_residue = None
residue_groups = chain.residue_groups()
n_groups = len(residue_groups)
for i_res, residue_group in enumerate(residue_groups) :
if (i_res < n_groups - 1) :
next_residue = residue_groups[i_res+1].atom_groups()[0]
i_seqs = residue_group.atoms().extract_i_seq()
if (selection.select(i_seqs).all_eq(True)) :
atom_group = residue_group.only_atom_group()
if (get_class(atom_group.resname) != "common_amino_acid") :
continue
confs = density_sampling.screen_residue(
residue=atom_group,
prev_residue=prev_residue,
next_residue=next_residue,
sites_cart=sites_cart,
fmodel=fmodel,
mon_lib_srv=mon_lib_srv,
params=params,
map_file_name="map_coeffs.mtz",
out=out)
ensemble = []
for conf in confs :
conf_atoms = conf.set_atom_sites(pdb_atoms)
pdb_lines = []
for atom in conf_atoms :
pdb_lines.append(atom.format_atom_record())
ensemble.append("\n".join(pdb_lines))
ensembles.append(ensemble)
prev_residue = residue_group.atom_groups()[0]
if (len(ensembles) == 0) :
raise Sorry("No alternate conformations found.")
t2 = time.time()
print >> out, "search time: %.1fs" % (t2-t1)
for i_ens, ensemble in enumerate(ensembles) :
ensemble_hierarchy = iotbx.pdb.hierarchy.root()
for k, model_str in enumerate(ensemble) :
input = iotbx.pdb.hierarchy.input(pdb_string=model_str)
model = input.hierarchy.only_model().detached_copy()
model.id = str(k+1)
ensemble_hierarchy.append_model(model)
f = open("ensemble_%d.pdb" % (i_ens+1), "w")
f.write(ensemble_hierarchy.as_pdb_string())
f.close()
print "wrote ensemble_%d.pdb" % (i_ens+1)
if (params.coot) :
easy_run.call("coot --pdb %s --auto map_coeffs.mtz --pdb ensemble.pdb" %
params.input.pdb.file_name[0])
