def exercise_lbfgs_simple (mon_lib_srv, ener_lib, verbose=False) :
# three peptides:
# 1 = poly-ALA, favored
# 2 = poly-ALA, outlier
# 3 = poly-TRP, outlier
#
# Note that the ramalyze score for the first actually gets slightly worse,
# but it's still good and we're starting from an excellent score anyway.
#
# residuals = [0.00024512, 307.616444, 294.913714]
residuals = [0.00168766995882, 186.24718562, 177.259069807]
for i, peptide in enumerate([pdb1, pdb2, pdb3]) :
pdb_in = iotbx.pdb.input(source_info="peptide",
lines=flex.split_lines(peptide))
params = pdb_interpretation.master_params.extract()
processed_pdb_file = pdb_interpretation.process(
mon_lib_srv=mon_lib_srv,
ener_lib=ener_lib,
params=params,
pdb_inp=pdb_in,
log=StringIO())
log = StringIO()
pdb_hierarchy = processed_pdb_file.all_chain_proxies.pdb_hierarchy
atoms = pdb_hierarchy.atoms()
sites_cart_1 = atoms.extract_xyz().deep_copy()
gradients_fd = flex.vec3_double(sites_cart_1.size(), (0,0,0))
gradients_an = flex.vec3_double(sites_cart_1.size(), (0,0,0))
params = ramachandran.master_phil.fetch().extract()
rama_manager = ramachandran.ramachandran_manager(
pdb_hierarchy, None, params, log)
assert rama_manager.get_n_proxies() == 1
residual_an = rama_manager.target_and_gradients(
unit_cell=None,
sites_cart=sites_cart_1,
gradient_array=gradients_an)
# print "comparing", residual_an
assert approx_equal(residual_an, residuals[i], eps=0.00001)
if verbose :
print ""
for i, peptide in enumerate([pdb1, pdb2, pdb3]) :
pdb_in = iotbx.pdb.input(source_info="peptide",
lines=flex.split_lines(peptide))
o = benchmark_structure(pdb_in, mon_lib_srv, ener_lib, verbose)
phi0, psi0 = o.r0.results[0].phi, o.r0.results[0].psi
phi1, psi1 = o.r1.results[0].phi, o.r1.results[0].psi
phi2, psi2 = o.r2.results[0].phi, o.r2.results[0].psi
r0 = o.r0.results[0].score
r1 = o.r1.results[0].score
r2 = o.r2.results[0].score
if verbose :
print "peptide %d" % (i+1)
print " before: rmsd_bonds=%-6.4f rmsd_angles=%-6.3f" % (o.b0,o.a0)
print " phi=%-6.1f psi=%-6.1f score=%-.2f" % (phi0, psi0, r0)
print " simple: rmsd_bonds=%-6.4f rmsd_angles=%-6.3f" % (o.b1,o.a1)
print " phi=%-6.1f psi=%-6.1f score=%-.2f" % (phi1, psi1, r1)
print " + Rama: rmsd_bonds=%-6.4f rmsd_angles=%-6.3f" % (o.b2,o.a2)
print " phi=%-6.1f psi=%-6.1f score=%-.2f" % (phi2, psi2, r2)
print ""
def exercise_lbfgs_simple(mon_lib_srv, ener_lib, verbose=False):
# three peptides:
# 1 = poly-ALA, favored
# 2 = poly-ALA, outlier
# 3 = poly-TRP, outlier
#
# Note that the ramalyze score for the first actually gets slightly worse,
# but it's still good and we're starting from an excellent score anyway.
#
residuals = [0.00168766995882, 170.84797160, 161.5214609]
for i, peptide in enumerate([pdb1, pdb2, pdb3]):
pdb_in = iotbx.pdb.input(source_info="peptide",
lines=flex.split_lines(peptide))
log = StringIO()
pdb_hierarchy = pdb_in.construct_hierarchy()
atoms = pdb_hierarchy.atoms()
sites_cart_1 = atoms.extract_xyz().deep_copy()
gradients_fd = flex.vec3_double(sites_cart_1.size(), (0, 0, 0))
gradients_an = flex.vec3_double(sites_cart_1.size(), (0, 0, 0))
params = ramachandran.master_phil.fetch().extract(
).ramachandran_plot_restraints
rama_manager = ramachandran.ramachandran_manager(
pdb_hierarchy, params, log)
assert rama_manager.get_n_proxies() == 1
residual_an = rama_manager.target_and_gradients(
unit_cell=None,
sites_cart=sites_cart_1,
gradient_array=gradients_an)
# print "comparing", residual_an
assert approx_equal(residual_an, residuals[i], eps=0.001)
# approx_equal(residual_an, residuals[i], eps=0.001)
if verbose:
print("")
for i, peptide in enumerate([pdb1, pdb2, pdb3]):
pdb_in = iotbx.pdb.input(source_info="peptide",
lines=flex.split_lines(peptide))
o = benchmark_structure(pdb_in, mon_lib_srv, ener_lib, verbose)
phi0, psi0 = o.r0.results[0].phi, o.r0.results[0].psi
phi1, psi1 = o.r1.results[0].phi, o.r1.results[0].psi
phi2, psi2 = o.r2.results[0].phi, o.r2.results[0].psi
r0 = o.r0.results[0].score
r1 = o.r1.results[0].score
r2 = o.r2.results[0].score
if verbose:
print("peptide %d" % (i + 1))
print(" before: rmsd_bonds=%-6.4f rmsd_angles=%-6.3f" %
(o.b0, o.a0))
print(" phi=%-6.1f psi=%-6.1f score=%-.2f" %
(phi0, psi0, r0))
print(" simple: rmsd_bonds=%-6.4f rmsd_angles=%-6.3f" %
(o.b1, o.a1))
print(" phi=%-6.1f psi=%-6.1f score=%-.2f" %
(phi1, psi1, r1))
print(" + Rama: rmsd_bonds=%-6.4f rmsd_angles=%-6.3f" %
(o.b2, o.a2))
print(" phi=%-6.1f psi=%-6.1f score=%-.2f" %
(phi2, psi2, r2))
print("")
def gen_null_peak(self):
record = self.pput.write_atom(0, "O", "", "NUL", "P", 0, "", 999.99,
999.99, 999.99, 0.0, 30.0, "O", "")
tmp_hier = iotbx.pdb.input(source_info=None,
lines=flex.split_lines(record))
pdb_str = tmp_hier.as_pdb_string(crystal_symmetry=self.orig_symmetry)
null_input = iotbx.pdb.input(source_info=None,
lines=flex.split_lines(pdb_str))
null_hier = null_input.construct_hierarchy()
return null_hier
def exercise_phi_psi_extraction():
for n_prox, raw_records in [
([0, 0], rec_1_residue),
([0, 0], rec_2_residues),
([4, 2], rec_3_residues),
([6, 4], rec_4_residues),
([0, 0], rec_2_chains),
([0, 0], rec_2_segids),
([8, 4], rec_2_acs_edge),
([8, 4], rec_2_acs_middle),
([6, 4], rec_4_residues_isertions),
([12, 10], pdb_1yjp),
([8, 4], pdb_1yjp_minus_4),
([4, 2], rec_3_res_ac_h),
([8, 4], rec_2_acs_middle_one_atom_1),
([8, 4], rec_2_acs_middle_one_atom_2),
([8, 4], rec_2_acs_middle_one_atom_3),
]:
tmp_hierarchy = iotbx.pdb.input(
source_info=None,
lines=flex.split_lines(raw_records)).construct_hierarchy()
for opp in range(2):
proxies = []
for three in generate_protein_threes(hierarchy=tmp_hierarchy,
geometry=None):
ppp = three.get_dummy_dihedral_proxies(only_psi_phi_pairs=opp)
print(three, 'ppp', len(ppp))
proxies.extend(ppp)
print(len(proxies), n_prox)
assert len(proxies) == n_prox[opp], \
"Expected %d, got %d" % (
n_prox[opp],
len(proxies),
)
def extract_unique_part_of_hierarchy(ph,target_ph=None,
allow_mismatch_in_number_of_copies=True,
allow_extensions=False,
min_similarity=1.0,out=sys.stdout):
# Container for unique chains:
new_hierarchy=iotbx.pdb.input(
source_info="Model",lines=flex.split_lines("")).construct_hierarchy()
mm=iotbx.pdb.hierarchy.model()
new_hierarchy.append_model(mm)
# Target location:
if target_ph:
target_centroid_list=flex.vec3_double()
for model in target_ph.models()[:1]:
target_centroid_list.append(model.atoms().extract_xyz().mean())
else:
target_centroid_list=None
# Get unique set of sequences
# Also save all the chains associated with each one
sequences=[]
chains=[]
for model in ph.models()[:1]:
for chain in model.chains():
try:
seq=chain.as_padded_sequence() # has XXX for missing residues
seq=seq.replace("X","")
sequences.append(seq)
chains.append(chain)
except Exception, e:
pass
def extract_unique_part_of_hierarchy(ph,target_ph=None,out=sys.stdout):
new_hierarchy=iotbx.pdb.input(
source_info="Model",lines=flex.split_lines("")).construct_hierarchy()
mm=iotbx.pdb.hierarchy.model()
new_hierarchy.append_model(mm)
if target_ph:
target_centroid_list=flex.vec3_double()
for model in target_ph.models()[:1]:
target_centroid_list.append(model.atoms().extract_xyz().mean())
else:
target_centroid_list=None
unique_sequences=[]
best_chain_dict={}
best_chain_dist_dict={}
for model in ph.models()[:1]:
for chain in model.chains():
try:
seq=chain.as_padded_sequence() # has XXX for missing residues
except Exception, e:
seq="XXX"
if not seq in unique_sequences:
unique_sequences.append(seq)
if target_centroid_list:
xx=flex.vec3_double()
xx.append(chain.atoms().extract_xyz().mean())
dist=xx.min_distance_between_any_pair(target_centroid_list)
else:
dist=0.
best_dist=best_chain_dist_dict.get(seq)
if best_dist is None or dist<best_dist:
best_chain_dist_dict[seq]=dist
best_chain_dict[seq]=chain
def exercise_phi_psi_extraction():
for n_prox, raw_records in [
([0, 0], rec_1_residue),
([0, 0], rec_2_residues),
([4, 2], rec_3_residues),
([6, 4], rec_4_residues),
([0, 0], rec_2_chains),
([0, 0], rec_2_segids),
([8, 4], rec_2_acs_edge),
([8, 4], rec_2_acs_middle),
([6, 4], rec_4_residues_isertions),
([12, 10], pdb_1yjp),
([8, 4], pdb_1yjp_minus_4),
([4, 2], rec_3_res_ac_h),
([8, 4], rec_2_acs_middle_one_atom_1),
([8, 4], rec_2_acs_middle_one_atom_2),
([8, 4], rec_2_acs_middle_one_atom_3),
]:
tmp_hierarchy = iotbx.pdb.input(
source_info=None,
lines=flex.split_lines(raw_records)).construct_hierarchy()
for opp in range(2):
proxies = []
for three in generate_protein_threes(
hierarchy=tmp_hierarchy,
geometry=None):
ppp = three.get_dummy_dihedral_proxies(only_psi_phi_pairs=opp)
print three,'ppp',len(ppp)
proxies.extend(ppp)
print len(proxies), n_prox
assert len(proxies) == n_prox[opp], \
"Expected %d, got %d" % (
n_prox[opp],
len(proxies),
)
def remove_ter(text): # remove blank lines and TER records
new_lines=[]
for line in flex.split_lines(text):
if not line.replace(" ",""): continue
if line.startswith("TER"): continue
new_lines.append(line)
return "\n".join(new_lines)
def remove_ter(text): # remove blank lines and TER records
new_lines=[]
for line in flex.split_lines(text):
if not line.replace(" ",""): continue
if line.startswith("TER"): continue
new_lines.append(line)
return "\n".join(new_lines)
def get_pdb_inp(text=None,file_name=None,source_info="string"):
import iotbx.pdb
if file_name:
text=open(file_name).read()
source_info="file %s" %(file_name)
elif not text:
text=""
from cctbx.array_family import flex
return iotbx.pdb.input(source_info=source_info,
lines=flex.split_lines(text))
def get_grm(self):
# first make whole grm using self.whole_pdb_h
params_line = grand_master_phil_str
params = iotbx.phil.parse(
input_string=params_line, process_includes=True).extract()
params.pdb_interpretation.clash_guard.nonbonded_distance_threshold=None
params.pdb_interpretation.peptide_link.ramachandran_restraints = True
params.pdb_interpretation.peptide_link.oldfield.weight_scale=3
params.pdb_interpretation.peptide_link.oldfield.plot_cutoff=0.03
params.pdb_interpretation.nonbonded_weight = 500
params.pdb_interpretation.c_beta_restraints=True
params.pdb_interpretation.max_reasonable_bond_distance = None
params.pdb_interpretation.peptide_link.apply_peptide_plane = True
params.pdb_interpretation.ncs_search.enabled = True
params.pdb_interpretation.restraints_library.rdl = True
processed_pdb_files_srv = mmtbx.utils.\
process_pdb_file_srv(
crystal_symmetry= self.whole_xrs.crystal_symmetry(),
pdb_interpretation_params = params.pdb_interpretation,
stop_for_unknowns = False,
log=self.log,
cif_objects=None)
processed_pdb_file, junk = processed_pdb_files_srv.\
process_pdb_files(raw_records=flex.split_lines(self.whole_pdb_h.as_pdb_string()))
self.mon_lib_srv = processed_pdb_files_srv.mon_lib_srv
self.ener_lib = processed_pdb_files_srv.ener_lib
self.rotamer_manager = RotamerEval(mon_lib_srv=self.mon_lib_srv)
self.whole_grm = get_geometry_restraints_manager(
processed_pdb_file, self.whole_xrs, params=params)
# set SS restratins
if self.params.use_ss_restraints:
ss_manager = manager(
pdb_hierarchy=self.whole_pdb_h,
geometry_restraints_manager=self.whole_grm.geometry,
sec_str_from_pdb_file=self.filtered_whole_ann,
params=None,
mon_lib_srv=self.mon_lib_srv,
verbose=-1,
log=self.log)
# self.whole_pdb_h.write_pdb_file(file_name="for_ss.pdb")
self.whole_pdb_h.reset_atom_i_seqs()
self.whole_grm.geometry.set_secondary_structure_restraints(
ss_manager=ss_manager,
hierarchy=self.whole_pdb_h,
log=self.log)
# now select part of it for working with master hierarchy
if self.using_ncs:
self.master_grm = self.whole_grm.select(self.master_sel)
self.working_grm = self.master_grm
else:
self.working_grm = self.whole_grm
def rotations(self, peak_object, ref_object, write_pdb=False):
cc_f_sum, cc_f_sq_sum, cc_2_sum, cc_2_sq_sum = 0.0, 0.0, 0.0, 0.0
for axis in (1, 2, 3, 4):
rotated_fofc = self.rotate_so4(self.features['so4_fofc_ref_hier'],
axis, 60)
rotated_2fofc = self.rotate_so4(
self.features['so4_2fofc_ref_hier'], axis, 60)
if write_pdb:
rotated_fofc.write_pdb_file(self.features['db_id'] +
"_rot60_f" + str(axis) + ".pdb")
rotated_2fofc.write_pdb_file(self.features['db_id'] +
"_rot60_2" + str(axis) + ".pdb")
#hack to get this back into cctbx?
rotf_pdb = iotbx.pdb.input(source_info=None,
lines=flex.split_lines(
rotated_fofc.as_pdb_string()))
rot2f_pdb = iotbx.pdb.input(source_info=None,
lines=flex.split_lines(
rotated_2fofc.as_pdb_string()))
rotf_xrs = rotf_pdb.xray_structure_simple(
crystal_symmetry=peak_object.symmetry)
rot2f_xrs = rot2f_pdb.xray_structure_simple(
crystal_symmetry=peak_object.symmetry)
cc60_f = self.rscc(rotated_fofc, rotf_xrs, "resname SO4",
ref_object.fofc_map_data)
cc60_2 = self.rscc(rotated_2fofc, rot2f_xrs, "resname SO4",
ref_object.twofofc_map_data)
cc_f_sum = cc_f_sum + cc60_f
cc_f_sq_sum = cc_f_sq_sum + cc60_f**2
cc_2_sum = cc_2_sum + cc60_2
cc_2_sq_sum = cc_2_sq_sum + cc60_2**2
meanf = cc_f_sum / 4.0
mean2 = cc_2_sum / 4.0
self.features[
'so4_fofc_mean_cc60'] = meanf #average cc for all 4 rotations
self.features['so4_2fofc_mean_cc60'] = mean2
self.features['so4_fofc_stdev_cc60'] = np.sqrt(cc_f_sq_sum / 4.0 -
meanf**2) #std
self.features['so4_2fofc_stdev_cc60'] = np.sqrt(cc_2_sq_sum / 4.0 -
mean2**2)
def place_so4(self, b_fac=35.0, occ=1.00):
#places a sulfate at the origin of a 10A cubic P1 cell
pdb_string="CRYST1%9.3f%9.3f%9.3f 90.00 90.00 90.00 P 1 1\n" % \
(2.0*self.bound,2.0*self.bound,2.0*self.bound)
x1, y1, z1 = 5.0, 5.0, 5.0
x2, y2, z2 = x1 + 0.873, y1 + 0.873, z1 + 0.873
x3, y3, z3 = x1 - 0.873, y1 - 0.873, z1 + 0.873
x4, y4, z4 = x1 - 0.873, y1 + 0.873, z1 - 0.873
x5, y5, z5 = x1 + 0.873, y1 - 0.873, z1 - 0.873
so4_dict = {
"sx": x1,
"sy": y1,
"sz": z1,
"o1x": x2,
"o1y": y2,
"o1z": z2,
"o2x": x3,
"o2y": y3,
"o2z": z3,
"o3x": x4,
"o3y": y4,
"o3z": z4,
"o4x": x5,
"o4y": y5,
"o4z": z5
}
pdb_entry = ""
pdb_entry = pdb_entry + self.write_atom(
1, "S", "", "SO4", "X", 1, "", so4_dict['sx'], so4_dict['sy'],
so4_dict['sz'], occ, b_fac, "S", "")
pdb_entry = pdb_entry + self.write_atom(
2, "O1", "", "SO4", "X", 1, "", so4_dict['o1x'], so4_dict['o1y'],
so4_dict['o1z'], occ, b_fac, "O", "")
pdb_entry = pdb_entry + self.write_atom(
3, "O2", "", "SO4", "X", 1, "", so4_dict['o2x'], so4_dict['o2y'],
so4_dict['o2z'], occ, b_fac, "O", "")
pdb_entry = pdb_entry + self.write_atom(
4, "O3", "", "SO4", "X", 1, "", so4_dict['o3x'], so4_dict['o3y'],
so4_dict['o3z'], occ, b_fac, "O", "")
pdb_entry = pdb_entry + self.write_atom(
5, "O4", "", "SO4", "X", 1, "", so4_dict['o4x'], so4_dict['o4y'],
so4_dict['o4z'], occ, b_fac, "O", "")
sulfate_pdb = pdb_string + pdb_entry
std_so4_pdb = iotbx.pdb.input(source_info=None,
lines=flex.split_lines(sulfate_pdb))
local_sym = std_so4_pdb.crystal_symmetry()
std_so4_hier = std_so4_pdb.construct_hierarchy(set_atom_i_seq=True)
std_so4_xrs = std_so4_hier.extract_xray_structure(
crystal_symmetry=local_sym)
return std_so4_pdb, std_so4_hier, std_so4_xrs
def minimize_hierarchy(hierarchy, xrs, original_pdb_h, excl_string_selection, log=None):
from mmtbx.monomer_library.pdb_interpretation import grand_master_phil_str
from mmtbx.refinement.geometry_minimization import run2
from mmtbx.geometry_restraints import reference
if log is None:
log = null_out()
params_line = grand_master_phil_str
params = iotbx.phil.parse(input_string=params_line, process_includes=True).extract()
params.pdb_interpretation.clash_guard.nonbonded_distance_threshold = None
params.pdb_interpretation.peptide_link.ramachandran_restraints = True
params.pdb_interpretation.peptide_link.oldfield.weight_scale = 3
params.pdb_interpretation.peptide_link.oldfield.plot_cutoff = 0.03
params.pdb_interpretation.c_beta_restraints = True
processed_pdb_files_srv = mmtbx.utils.process_pdb_file_srv(
crystal_symmetry=xrs.crystal_symmetry(),
pdb_interpretation_params=params.pdb_interpretation,
stop_for_unknowns=False,
log=log,
cif_objects=None,
)
processed_pdb_file, junk = processed_pdb_files_srv.process_pdb_files(
raw_records=flex.split_lines(hierarchy.as_pdb_string())
)
grm = get_geometry_restraints_manager(processed_pdb_file, xrs)
asc = original_pdb_h.atom_selection_cache()
sel = asc.selection(excl_string_selection)
grm.geometry.append_reference_coordinate_restraints_in_place(
reference.add_coordinate_restraints(
sites_cart=original_pdb_h.atoms().extract_xyz().select(sel), selection=sel, sigma=0.5
)
)
obj = run2(
restraints_manager=grm,
pdb_hierarchy=hierarchy,
correct_special_position_tolerance=1.0,
max_number_of_iterations=300,
number_of_macro_cycles=5,
bond=True,
nonbonded=True,
angle=True,
dihedral=True,
chirality=True,
planarity=True,
fix_rotamer_outliers=True,
log=log,
)
def place_wat(self, b_fac=35.0, occ=1.00):
#create a dummy pdb, put water
pdb_string="CRYST1%9.3f%9.3f%9.3f 90.00 90.00 90.00 P 1 1\n" % \
(2.0*self.bound,2.0*self.bound,2.0*self.bound)
x1, y1, z1 = 5.0, 5.0, 5.0
pdb_entry = ""
pdb_entry = pdb_entry + self.write_atom(
1, "O", "", "HOH", "X", 1, "", x1, y1, z1, occ, b_fac, "O", "")
wat_pdb = pdb_string + pdb_entry
std_wat_pdb = iotbx.pdb.input(source_info=None,
lines=flex.split_lines(wat_pdb))
local_sym = std_wat_pdb.crystal_symmetry()
std_wat_hier = std_wat_pdb.construct_hierarchy()
std_wat_xrs = std_wat_hier.extract_xray_structure(
crystal_symmetry=local_sym)
return std_wat_pdb, std_wat_hier, std_wat_xrs
def extract_copies_identical_to_target_from_hierarchy(ph,
allow_extensions=False,
min_similarity=None,target_ph=None,out=sys.stdout):
new_hierarchy=iotbx.pdb.input(
source_info="Model",lines=flex.split_lines("")).construct_hierarchy()
mm=iotbx.pdb.hierarchy.model()
new_hierarchy.append_model(mm)
assert target_ph is not None
target_seq=None
for model in target_ph.models()[:1]:
for chain in model.chains():
try:
target_seq=chain.as_padded_sequence() # has XXX for missing residues
target_seq.replace("X","")
break
except Exception, e:
pass
def merge_hier(self, hier_list, symmetry):
pdb2str = lambda hier: hier.as_pdb_string(write_scale_records=False,
append_end=False,
interleaved_conf=0,
atom_hetatm=True,
sigatm=False,
anisou=False,
siguij=False,
output_break_records=False)
allpdb = ""
for index, hier in enumerate(hier_list):
allpdb = allpdb + "MODEL %s\n" % str(index + 1)
allpdb = allpdb + pdb2str(hier)
allpdb = allpdb + "ENDMDL\n"
dummy_pdb = iotbx.pdb.input(source_info=None,
lines=flex.split_lines(allpdb))
dummy_hier = dummy_pdb.construct_hierarchy()
dummy_hier.remove_hd()
dummy_hier.atoms_reset_serial()
#dummy_hier.write_pdb_file('merge.pdb')
return dummy_hier
def run_resolve(self):
from solve_resolve.resolve_python import resolve_in_memory
from iotbx import pdb
from scitbx.array_family import flex
make_sub_header("RESOLVE build", out=self.out)
mean_density_start = self.mean_density_at_sites()
cc_start = self.cc_model_map()
sites_start = self.get_selected_sites(hydrogens=False)
t1 = time.time()
pdb_inp = self.box_selected_hierarchy.as_pdb_input()
inp_hierarchy = pdb_inp.construct_hierarchy()
chain = inp_hierarchy.only_model().only_chain()
first_resseq = chain.residue_groups()[0].resseq_as_int()
seq = "".join(
chain.only_conformer().as_sequence(substitute_unknown='A'))
resolve_args = [
"start_chain 1 %d" % first_resseq,
"extend_only",
"skip_hetatm",
"no_merge_ncs_copies",
"no_optimize_ncs",
"i_ran_seed %d" % int(time.time() % os.getpid()),
]
if (self.params.build_new_loop): # XXX not really working...
n_res = len(chain.residue_groups())
assert (n_res >= 3)
k = 0
for residue_group in chain.residue_groups()[1:-1]:
print >> self.out, " removing residue group %s %s" % \
(chain.id, residue_group.resid())
chain.remove_residue_group(residue_group)
resolve_args.extend([
"loop_only",
"build_outside_model",
"no_sub_segments",
"n_random_loop %d" % self.params.n_random_loop,
"loop_length %d" % (n_res - 2),
"rms_random_loop 0.3",
"rho_min_main_low 0.5",
"rho_min_main_base 0.5",
"n_internal_start 0",
])
else:
resolve_args.extend([
"rebuild_in_place",
"replace_existing",
"richardson_rotamers",
"min_z_value_rho -3.0",
"delta_phi 20.00",
"dist_cut_base 3.0",
"n_random_frag 0",
"group_ca_length 4",
"group_length 2",
])
out = null_out()
if (self.debug):
out = self.out
cmn = resolve_in_memory.run(map_coeffs=self.box_map_coeffs,
pdb_inp=inp_hierarchy.as_pdb_input(),
build=True,
input_text="\n".join(resolve_args),
chain_type="PROTEIN",
seq_file_as_string=seq,
out=out)
new_pdb_input = pdb.input(source_info='string',
lines=flex.split_lines(
cmn.atom_db.pdb_out_as_string))
new_hierarchy = new_pdb_input.construct_hierarchy()
print >> self.out, " %d atoms rebuilt" % len(new_hierarchy.atoms())
new_hierarchy.write_pdb_file("resolve.pdb")
selection_moved = flex.size_t()
sites_new = flex.vec3_double()
for atom in new_hierarchy.atoms():
id_str = atom.id_str()
if (not id_str in self.atom_id_mapping):
raise KeyError("Atom ID %s not recognized in RESOLVE model." %
id_str)
i_seq = self.atom_id_mapping[id_str]
selection_moved.append(i_seq)
sites_new.append(atom.xyz)
sites_cart_selected = self.box_selected_hierarchy.atoms().extract_xyz()
sites_cart_selected.set_selected(selection_moved, sites_new)
self.box_selected_hierarchy.atoms().set_xyz(sites_cart_selected)
sites_cart_box = self.box.xray_structure_box.sites_cart()
sites_cart_box.set_selected(self.selection_in_box, sites_cart_selected)
self.box.xray_structure_box.set_sites_cart(sites_cart_box)
self.box.pdb_hierarchy_box.atoms().set_xyz(sites_cart_box)
t2 = time.time()
print >> self.out, " RESOLVE time: %.1fs" % (t2 - t1)
selection_rebuilt = self.selection_in_box.select(selection_moved)
minimize_sel = flex.bool(self.n_sites_box, False).set_selected(
self.selection_in_box, True).set_selected(selection_rebuilt, False)
# atoms present in the selection but not in the RESOLVE model (usually
# hydrogen atoms) need to be minimized to follow the rebuilt sites
if (minimize_sel.count(True) > 0):
print >> self.out, " Performing geometry minimzation on unbuilt sites"
self.geometry_minimization(selection=minimize_sel, nonbonded=False)
self.box.write_pdb_file("box_resolve.pdb")
# two alternatives here: restrain other atoms tightly, and minimize the
# entire box, or restrain selected atoms loosely, and refine only those
self.restrain_atoms(selection=self.others_in_box, reference_sigma=0.02)
if (self.params.anneal):
self.anneal(start_temperature=2500)
else:
self.real_space_refine(selection=self.selection_all_box)
self.box.write_pdb_file("box_refined.pdb")
self.box.write_ccp4_map()
mean_density_end = self.mean_density_at_sites()
cc_end = self.cc_model_map()
print >> self.out, " mean density level: start=%.2fsigma end=%.2fsigma" \
% (mean_density_start, mean_density_end)
print >> self.out, " model-map CC: start=%.3f end=%.3f" % (cc_start,
cc_end)
sites_final = self.get_selected_sites(hydrogens=False)
print >> self.out, " rmsd to starting model: %.3f Angstrom" % \
sites_final.rms_difference(sites_start)
t3 = time.time()
print >> self.out, " Total build and refine time: %.1fs" % (t3 - t1)
def __init__ (self, fmodel, pdb_hierarchy, crystal_symmetry=None, cc_min=0.8,
molprobity_map_params=None) :
from iotbx.pdb.amino_acid_codes import one_letter_given_three_letter
from mmtbx import real_space_correlation
validation.__init__(self)
# arrays for different components
self.everything = list()
self.protein = list()
self.other = list()
self.water = list()
aa_codes = one_letter_given_three_letter.keys()
# redo real_space_corelation.simple to use map objects instead of filenames
self.overall_rsc = None
rsc = None
try :
rsc_params = real_space_correlation.master_params().extract()
rsc_params.detail="residue"
rsc_params.map_1.fill_missing_reflections = False
rsc_params.map_2.fill_missing_reflections = False
use_maps = False
if (molprobity_map_params is not None):
rsc_params.map_coefficients_file_name = \
molprobity_map_params.map_coefficients_file_name
rsc_params.map_coefficients_label = \
molprobity_map_params.map_coefficients_label
if (molprobity_map_params.map_file_name is not None):
use_maps = True
# use mmtbx/command_line/map_model_cc.py for maps
self.fsc = None
if (use_maps):
from scitbx.array_family import flex
import iotbx.pdb
from mmtbx.maps import map_model_cc
from mmtbx.command_line.map_model_cc import get_fsc
from iotbx.file_reader import any_file
from cctbx import crystal, sgtbx
params = map_model_cc.master_params().extract()
params.map_model_cc.resolution = molprobity_map_params.d_min
map_object = any_file(molprobity_map_params.map_file_name).file_object
# ---------------------------------------------------------------------
# check that model crystal symmetry matches map crystal symmetry
# if inconsistent, map parameters take precedence
# TODO: centralize data consistency checks prior to running validation
map_crystal_symmetry = crystal.symmetry(
unit_cell=map_object.unit_cell(),
space_group=sgtbx.space_group_info(
map_object.space_group_number).group())
if (not map_crystal_symmetry.is_similar_symmetry(crystal_symmetry)):
crystal_symmetry = map_crystal_symmetry
# ---------------------------------------------------------------------
map_data = map_object.map_data()
rsc_object = map_model_cc.map_model_cc(
map_data, pdb_hierarchy, crystal_symmetry, params.map_model_cc)
rsc_object.validate()
rsc_object.run()
rsc = rsc_object.get_results()
self.overall_rsc = (rsc.cc_mask, rsc.cc_volume, rsc.cc_peaks)
# pdb_hierarchy.as_pdb_input is being phased out since that function
# just re-processes the file from text and can be lossy
# this is a placeholder until tools get updated to use the model class
pdb_input = iotbx.pdb.input(
source_info='pdb_hierarchy',
lines=flex.split_lines(pdb_hierarchy.as_pdb_string()))
model = mmtbx.model.manager(model_input = pdb_input)
self.fsc = get_fsc(map_data, model, params.map_model_cc)
#
self.fsc.atom_radius = rsc.atom_radius
rsc = rsc.cc_per_residue
# mmtbx/real_space_correlation.py for X-ray/neutron data and map
# coefficients
else:
self.overall_rsc, rsc = real_space_correlation.simple(
fmodel=fmodel,
pdb_hierarchy=pdb_hierarchy,
params=rsc_params,
log=null_out())
except Exception, e :
raise
def contacts_to_coord(self, coord, pdb_hier, symmetry, cutoff=6.0):
"""
Used to use extract map_model, but that caused problems
This function takes cartesian coordinate, pdb_hier, and symmetry and returns
sorted list of dictionaries, each a particular contact
very hacked together, jams pdb strings together
create a dummy pdb, put water at the peak site in the original coordinate system
then use fast pair generater to get all contacts to our peak atom
"""
dummy_atom = self.pput.write_atom(1, "O", "", "HOH", "ZZ", 9999, "",
coord[0], coord[1], coord[2], 1.0,
35.0, "O", "")
#hack to add an atom to a pdb
orig_str = pdb_hier.as_pdb_string(write_scale_records=False,
append_end=False,
interleaved_conf=0,
atoms_reset_serial_first_value=1,
atom_hetatm=True,
sigatm=False,
anisou=False,
siguij=False,
output_break_records=False)
nmodels = len(pdb_hier.models())
if nmodels == 1:
comb = orig_str + dummy_atom
else:
newmodel = nmodels + 1
comb = orig_str + "MODEL %s\n" % newmodel
comb = comb + dummy_atom
comb = comb + "ENDMDL\n"
dummy_pdb = iotbx.pdb.input(source_info=None,
lines=flex.split_lines(comb))
dummy_hier = dummy_pdb.construct_hierarchy()
atsel = "chain ZZ and resid 9999"
dummy_select = dummy_hier.atom_selection_cache().selection(
string=atsel)
atsel_index = np.argwhere(dummy_select.as_numpy_array())
dummy_xrs = dummy_pdb.xray_structure_simple(crystal_symmetry=symmetry)
#find neighbors with symmetry -- use pair_finding with asu_mappings
#doing this for each peak may be a bad idea, use all_contacts version instead if possible
asu_mappings = dummy_xrs.asu_mappings(buffer_thickness=cutoff)
pair_generator = crystal.neighbors_fast_pair_generator(
asu_mappings, distance_cutoff=cutoff)
peak_vector_list = []
#neighbor_mask = pair_generator.neighbors_of(atsel_arr)
#neighbors = pair_generator.select(neighbor_mask)
for pair in pair_generator:
if pair.i_seq == atsel_index:
#our peak is first atom, but we want pairs in both directions
#to provide exhaustive list of contacts
#store index number and difference vector and sym to make unique
#we don't care which symop, just how far away
rdist = int(
np.sqrt(pair.dist_sq) * 1000) / 1000.0 #avoid float error
peak_vector_list.append((pair.j_seq, rdist, pair.j_sym))
if pair.j_seq == atsel_index:
rdist = int(np.sqrt(pair.dist_sq) * 1000) / 1000.0
peak_vector_list.append((pair.i_seq, rdist, pair.j_sym))
unique = set(peak_vector_list)
dummy_atoms = dummy_hier.atoms()
#selection is boolean flex array, sizeof no atoms, can be indexed directly
#get awl for our dummy atom
s_awl = dummy_atoms.select(dummy_select)[0].fetch_labels()
#list((awl_db[c_at[0]],c_at[1],c_at[2]) for c_at in uni_c )
#next, get list of contacts (awl,dist)
selection = dummy_hier.atom_selection_cache().selection("not all")
if len(unique) == 0:
return []
cont_list = []
for conti in unique:
selection[conti[0]] = True
sel_awl = dummy_atoms.select(selection)[0].fetch_labels()
cont_list.append(
(sel_awl, conti[1],
conti[2])) #pass source awl, index for target, distance
selection[conti[0]] = False #unselect
contacts, s_unal = self.get_contacts(s_awl, cont_list, cutoff=cutoff)
return contacts
def exercise_geo_output(mon_lib_srv, ener_lib):
pdb_str = """\
CRYST1 18.879 16.714 25.616 90.00 90.00 90.00 P 1
ATOM 1 N ALA 1 13.515 7.809 20.095 1.00 0.00 N
ATOM 2 CA ALA 1 13.087 6.532 19.536 1.00 0.00 C
ATOM 3 C ALA 1 11.716 6.653 18.880 1.00 0.00 C
ATOM 4 O ALA 1 11.425 5.972 17.896 1.00 0.00 O
ATOM 5 CB ALA 1 13.065 5.461 20.616 1.00 0.00 C
ATOM 6 N ALA 2 10.876 7.524 19.431 1.00 0.00 N
ATOM 7 CA ALA 2 9.535 7.735 18.900 1.00 0.00 C
ATOM 8 C ALA 2 9.565 8.647 17.678 1.00 0.00 C
ATOM 9 O ALA 2 8.787 8.471 16.741 1.00 0.00 O
ATOM 10 CB ALA 2 8.626 8.316 19.973 1.00 0.00 C
ATOM 11 N ALA 3 10.469 9.622 17.697 1.00 0.00 N
ATOM 12 CA ALA 3 10.606 10.565 16.593 1.00 0.00 C
ATOM 13 C ALA 3 11.132 9.871 15.340 1.00 0.00 C
ATOM 14 O ALA 3 10.687 10.157 14.228 1.00 0.00 O
ATOM 15 CB ALA 3 11.520 11.714 16.987 1.00 0.00 C
ATOM 16 N ALA 4 12.081 8.960 15.530 1.00 0.00 N
ATOM 17 CA ALA 4 12.656 8.209 14.421 1.00 0.00 C
ATOM 18 C ALA 4 11.624 7.266 13.812 1.00 0.00 C
ATOM 19 O ALA 4 11.570 7.090 12.595 1.00 0.00 O
ATOM 20 CB ALA 4 13.879 7.432 14.883 1.00 0.00 C
ATOM 21 N ALA 5 10.805 6.663 14.669 1.00 0.00 N
ATOM 22 CA ALA 5 9.753 5.761 14.218 1.00 0.00 C
ATOM 23 C ALA 5 8.662 6.528 13.481 1.00 0.00 C
ATOM 24 O ALA 5 8.107 6.045 12.494 1.00 0.00 O
ATOM 25 CB ALA 5 9.165 5.000 15.396 1.00 0.00 C
ATOM 26 N ALA 6 8.360 7.728 13.967 1.00 0.00 N
ATOM 27 CA ALA 6 7.358 8.580 13.338 1.00 0.00 C
ATOM 28 C ALA 6 7.860 9.106 11.998 1.00 0.00 C
ATOM 29 O ALA 6 7.078 9.322 11.072 1.00 0.00 O
ATOM 30 CB ALA 6 6.986 9.732 14.257 1.00 0.00 C
ATOM 31 N ALA 7 9.169 9.311 11.903 1.00 0.00 N
ATOM 32 CA ALA 7 9.781 9.787 10.668 1.00 0.00 C
ATOM 33 C ALA 7 9.912 8.655 9.655 1.00 0.00 C
ATOM 34 O ALA 7 9.905 8.886 8.446 1.00 0.00 O
ATOM 35 CB ALA 7 11.141 10.405 10.952 1.00 0.00 C
ATOM 36 N ALA 8 10.030 7.429 10.157 1.00 0.00 N
ATOM 37 CA ALA 8 10.152 6.258 9.297 1.00 0.00 C
ATOM 38 C ALA 8 8.788 5.809 8.786 1.00 0.00 C
ATOM 39 O ALA 8 8.667 5.312 7.666 1.00 0.00 O
ATOM 40 CB ALA 8 10.839 5.124 10.041 1.00 0.00 C
ATOM 41 N ALA 9 7.762 5.988 9.613 1.00 0.00 N
ATOM 42 CA ALA 9 6.405 5.603 9.243 1.00 0.00 C
ATOM 43 C ALA 9 5.816 6.576 8.228 1.00 0.00 C
ATOM 44 O ALA 9 5.000 6.195 7.389 1.00 0.00 O
ATOM 45 CB ALA 9 5.521 5.526 10.478 1.00 0.00 C
ATOM 46 N ALA 10 6.235 7.835 8.309 1.00 0.00 N
ATOM 47 CA ALA 10 5.751 8.864 7.397 1.00 0.00 C
ATOM 48 C ALA 10 6.434 8.760 6.038 1.00 0.00 C
ATOM 49 O ALA 10 5.773 8.734 5.000 1.00 0.00 O
ATOM 50 CB ALA 10 5.966 10.246 7.995 1.00 0.00 C
TER
END
"""
pdb_inp = iotbx.pdb.input(source_info="peptide",lines=flex.split_lines(pdb_str))
hierarchy = pdb_inp.construct_hierarchy()
atoms = hierarchy.atoms()
sites_cart = atoms.extract_xyz()
params = ramachandran.master_phil.fetch().extract()
params.rama_potential = "emsley"
rama_manager = ramachandran.ramachandran_manager(
hierarchy, params, StringIO())
out = StringIO()
rama_manager.show_sorted(
by_value="residual",
sites_cart=sites_cart,
site_labels=[a.id_str() for a in atoms],
f=out)
gv = out.getvalue()
# print out.getvalue()
# STOP()
assert not show_diff(gv, """\
Ramachandran plot restraints (Oldfield): 0
Sorted by residual:
Ramachandran plot restraints (Emsley): 8
Sorted by residual:
phi-psi angles formed by residual
pdb=" C ALA 7 " 1.53e+01
pdb=" N ALA 8 "
pdb=" CA ALA 8 "
pdb=" C ALA 8 "
pdb=" N ALA 9 "
phi-psi angles formed by residual
pdb=" C ALA 1 " 1.52e+01
pdb=" N ALA 2 "
pdb=" CA ALA 2 "
pdb=" C ALA 2 "
pdb=" N ALA 3 "
phi-psi angles formed by residual
pdb=" C ALA 6 " 1.20e+01
pdb=" N ALA 7 "
pdb=" CA ALA 7 "
pdb=" C ALA 7 "
pdb=" N ALA 8 "
phi-psi angles formed by residual
pdb=" C ALA 2 " 1.14e+01
pdb=" N ALA 3 "
pdb=" CA ALA 3 "
pdb=" C ALA 3 "
pdb=" N ALA 4 "
phi-psi angles formed by residual
pdb=" C ALA 8 " 1.06e+01
pdb=" N ALA 9 "
pdb=" CA ALA 9 "
pdb=" C ALA 9 "
pdb=" N ALA 10 "
phi-psi angles formed by residual
pdb=" C ALA 4 " 1.06e+01
pdb=" N ALA 5 "
pdb=" CA ALA 5 "
pdb=" C ALA 5 "
pdb=" N ALA 6 "
phi-psi angles formed by residual
pdb=" C ALA 3 " 1.03e+01
pdb=" N ALA 4 "
pdb=" CA ALA 4 "
pdb=" C ALA 4 "
pdb=" N ALA 5 "
phi-psi angles formed by residual
pdb=" C ALA 5 " 7.58e+00
pdb=" N ALA 6 "
pdb=" CA ALA 6 "
pdb=" C ALA 6 "
pdb=" N ALA 7 "
""")
params.rama_potential = "oldfield"
rama_manager = ramachandran.ramachandran_manager(
hierarchy, params, StringIO())
out = StringIO()
rama_manager.show_sorted(
by_value="residual",
sites_cart=sites_cart,
site_labels=[a.id_str() for a in atoms],
f=out)
gv = out.getvalue()
assert not show_diff(gv, """\
Ramachandran plot restraints (Oldfield): 8
Sorted by residual:
phi-psi angles formed by residual
pdb=" C ALA 5 " 3.46e-02
pdb=" N ALA 6 "
pdb=" CA ALA 6 "
pdb=" C ALA 6 "
pdb=" N ALA 7 "
phi-psi angles formed by residual
pdb=" C ALA 6 " 2.86e-02
pdb=" N ALA 7 "
pdb=" CA ALA 7 "
pdb=" C ALA 7 "
pdb=" N ALA 8 "
phi-psi angles formed by residual
pdb=" C ALA 2 " 2.54e-02
pdb=" N ALA 3 "
pdb=" CA ALA 3 "
pdb=" C ALA 3 "
pdb=" N ALA 4 "
phi-psi angles formed by residual
pdb=" C ALA 8 " 2.00e-02
pdb=" N ALA 9 "
pdb=" CA ALA 9 "
pdb=" C ALA 9 "
pdb=" N ALA 10 "
phi-psi angles formed by residual
pdb=" C ALA 1 " 1.21e-02
pdb=" N ALA 2 "
pdb=" CA ALA 2 "
pdb=" C ALA 2 "
pdb=" N ALA 3 "
phi-psi angles formed by residual
pdb=" C ALA 4 " 1.00e-02
pdb=" N ALA 5 "
pdb=" CA ALA 5 "
pdb=" C ALA 5 "
pdb=" N ALA 6 "
phi-psi angles formed by residual
pdb=" C ALA 3 " 9.28e-03
pdb=" N ALA 4 "
pdb=" CA ALA 4 "
pdb=" C ALA 4 "
pdb=" N ALA 5 "
phi-psi angles formed by residual
pdb=" C ALA 7 " 3.90e-03
pdb=" N ALA 8 "
pdb=" CA ALA 8 "
pdb=" C ALA 8 "
pdb=" N ALA 9 "
Ramachandran plot restraints (Emsley): 0
Sorted by residual:
""")
def minimize_wrapper_for_ramachandran(
hierarchy,
xrs,
original_pdb_h,
excl_string_selection,
log=None,
ss_annotation = None,
reference_rotamers = True,
run_first_minimization_without_reference=False,
oldfield_weight_scale=3,
oldfield_plot_cutoff=0.03,
nonbonded_weight=500,
reference_sigma=0.7):
""" Wrapper around geometry minimization specifically tuned for eliminating
Ramachandran outliers.
"""
import pickle
from time import time
from mmtbx.monomer_library.pdb_interpretation import grand_master_phil_str
from mmtbx.geometry_restraints import reference
from mmtbx.command_line.geometry_minimization import \
get_geometry_restraints_manager
from mmtbx.geometry_restraints.torsion_restraints.reference_model import \
reference_model, reference_model_params
from libtbx.utils import null_out
from scitbx.array_family import flex
if log is None:
log = null_out()
params_line = grand_master_phil_str
params = iotbx.phil.parse(
input_string=params_line, process_includes=True).extract()
params.pdb_interpretation.clash_guard.nonbonded_distance_threshold=None
params.pdb_interpretation.peptide_link.ramachandran_restraints = True
params.pdb_interpretation.peptide_link.oldfield.weight_scale=oldfield_weight_scale
params.pdb_interpretation.peptide_link.oldfield.plot_cutoff=oldfield_plot_cutoff
params.pdb_interpretation.nonbonded_weight = nonbonded_weight
params.pdb_interpretation.c_beta_restraints=True
params.pdb_interpretation.max_reasonable_bond_distance = None
params.pdb_interpretation.peptide_link.apply_peptide_plane = True
params.pdb_interpretation.ncs_search.enabled = True
params.pdb_interpretation.restraints_library.rdl = True
processed_pdb_files_srv = mmtbx.utils.\
process_pdb_file_srv(
crystal_symmetry= xrs.crystal_symmetry(),
pdb_interpretation_params = params.pdb_interpretation,
stop_for_unknowns = False,
log=log,
cif_objects=None)
processed_pdb_file, junk = processed_pdb_files_srv.\
process_pdb_files(raw_records=flex.split_lines(hierarchy.as_pdb_string()))
mon_lib_srv = processed_pdb_files_srv.mon_lib_srv
ener_lib = processed_pdb_files_srv.ener_lib
ncs_restraints_group_list = []
if processed_pdb_file.ncs_obj is not None:
ncs_restraints_group_list = processed_pdb_file.ncs_obj.get_ncs_restraints_group_list()
grm = get_geometry_restraints_manager(
processed_pdb_file, xrs, params=params)
if reference_rotamers and original_pdb_h is not None:
# make selection excluding rotamer outliers
from mmtbx.rotamer.rotamer_eval import RotamerEval
rotamer_manager = RotamerEval(mon_lib_srv=mon_lib_srv)
non_rot_outliers_selection = flex.bool([False]*hierarchy.atoms().size())
for model in original_pdb_h.models():
for chain in model.chains():
for conf in chain.conformers():
for res in conf.residues():
ev = rotamer_manager.evaluate_residue_2(res)
if ev != "OUTLIER" or ev is None:
for a in res.atoms():
non_rot_outliers_selection[a.i_seq] = True
rm_params = reference_model_params.extract()
rm_params.reference_model.enabled=True
rm_params.reference_model.strict_rotamer_matching=False
rm_params.reference_model.main_chain=False
rm = reference_model(
processed_pdb_file=processed_pdb_file,
reference_file_list=None,
reference_hierarchy_list=[original_pdb_h],
mon_lib_srv=mon_lib_srv,
ener_lib=ener_lib,
has_hd=None,
params=rm_params.reference_model,
selection=non_rot_outliers_selection,
log=log)
rm.show_reference_summary(log=log)
grm.geometry.adopt_reference_dihedral_manager(rm)
# dealing with SS
if ss_annotation is not None:
from mmtbx.secondary_structure import manager
ss_manager = manager(
pdb_hierarchy=hierarchy,
geometry_restraints_manager=grm.geometry,
sec_str_from_pdb_file=ss_annotation,
params=None,
mon_lib_srv=mon_lib_srv,
verbose=-1,
log=log)
grm.geometry.set_secondary_structure_restraints(
ss_manager=ss_manager,
hierarchy=hierarchy,
log=log)
# grm pickle-unpickle
# t0 = time()
# prefix="grm"
# pklfile = open("%s.pkl" % prefix, 'wb')
# pickle.dump(grm.geometry, pklfile)
# pklfile.close()
# t1 = time()
# pklfile = open("%s.pkl" % prefix, 'rb')
# grm_from_file = pickle.load(pklfile)
# pklfile.close()
# t2 = time()
# print "Time pickling/unpickling: %.4f, %.4f" % (t1-t0, t2-t1)
# grm.geometry=grm_from_file
if run_first_minimization_without_reference:
obj = run2(
restraints_manager=grm,
pdb_hierarchy=hierarchy,
correct_special_position_tolerance=1.0,
ncs_restraints_group_list=ncs_restraints_group_list,
max_number_of_iterations=300,
number_of_macro_cycles=5,
bond=True,
nonbonded=True,
angle=True,
dihedral=True,
chirality=True,
planarity=True,
fix_rotamer_outliers=True,
log=log)
if original_pdb_h is not None:
if len(excl_string_selection) == 0:
excl_string_selection = "all"
asc = original_pdb_h.atom_selection_cache()
sel = asc.selection("(%s) and (name CA or name C or name N or name O)" % excl_string_selection)
grm.geometry.append_reference_coordinate_restraints_in_place(
reference.add_coordinate_restraints(
sites_cart = original_pdb_h.atoms().extract_xyz().select(sel),
selection = sel,
sigma = reference_sigma,
top_out_potential=True))
obj = run2(
restraints_manager = grm,
pdb_hierarchy = hierarchy,
correct_special_position_tolerance = 1.0,
ncs_restraints_group_list=ncs_restraints_group_list,
max_number_of_iterations = 300,
number_of_macro_cycles = 5,
bond = True,
nonbonded = True,
angle = True,
dihedral = True,
chirality = True,
planarity = True,
fix_rotamer_outliers = True,
log = log)
def exercise () :
from mmtbx.monomer_library import pdb_interpretation
import cStringIO
open("tmp.pdb", "w").write("""\
CRYST1 50.800 50.800 155.300 90.00 90.00 90.00 P 43 21 2 8
ATOM 4 N SER A 1 8.753 29.755 61.685 1.00 49.13
ATOM 5 CA SER A 1 9.242 30.200 62.974 1.00 46.62
ANISOU 5 CA SER A 1 343 490 2719 -45 -169 617
ATOM 6 C SER A 1 10.453 29.500 63.579 1.00 41.99
ATOM 7 O SER A 1 10.593 29.607 64.814 1.00 43.24
ANISOU 7 O SER A 1 343 490 2719 -45 -169 617
ATOM 8 CB SER A 1 8.052 30.189 63.974 1.00 53.00
ATOM 9 OG SER A 1 7.294 31.409 63.930 1.00 57.79
ATOM 10 N ARG A 2 11.360 28.819 62.827 1.00 36.48
ATOM 11 CA ARG A 2 12.548 28.316 63.532 1.00 30.20
ATOM 12 C ARG A 2 13.502 29.501 63.500 1.00 25.54
ATOM 13 O ARG A 2 13.730 30.037 62.407 1.00 23.86
ATOM 14 CB ARG A 2 13.241 27.119 62.861 1.00 27.44
ATOM 15 CG ARG A 2 12.412 25.849 62.964 1.00 23.66
ATOM 16 CD ARG A 2 13.267 24.651 63.266 1.00 23.98
ATOM 17 NE ARG A 2 13.948 24.115 62.135 1.00 22.71
ATOM 18 CZ ARG A 2 15.114 23.487 62.201 1.00 21.38
ATOM 19 NH1 ARG A 2 15.845 23.331 63.301 1.00 19.34
ATOM 20 NH2 ARG A 2 15.575 23.030 61.051 1.00 26.66
ATOM 21 N PRO A 3J 13.947 29.997 64.680 1.00 22.94
ATOM 22 CA PRO A 3J 14.902 31.100 64.827 1.00 20.19
ATOM 23 C PRO A 3J 16.195 30.718 64.086 1.00 18.44
ATOM 24 O PRO A 3J 16.545 29.521 64.086 1.00 19.76
ATOM 25 CB PRO A 3J 15.133 31.218 66.313 1.00 19.17
ATOM 26 CG PRO A 3J 14.065 30.364 66.951 1.00 15.12
ATOM 27 CD PRO A 3J 13.816 29.289 65.966 1.00 19.56
ATOM 28 N AILE A 4 16.953 31.648 63.512 1.00 15.29
ATOM 29 CA AILE A 4 18.243 31.372 62.859 1.00 14.32
ATOM 30 C AILE A 4 19.233 32.112 63.743 1.00 13.54
ATOM 31 O AILE A 4 19.105 33.315 64.009 1.00 11.84
ATOM 32 CB AILE A 4 18.298 31.951 61.406 1.00 13.62
ATOM 33 CG1AILE A 4 17.157 31.300 60.620 1.00 18.39
ATOM 34 CG2AILE A 4 19.661 31.747 60.743 1.00 13.64
ATOM 35 CD1AILE A 4 16.879 32.102 59.355 1.00 16.69
ATOM 28 N BILE A 4 16.953 31.648 63.512 1.00 15.29
ATOM 29 CA BILE A 4 18.243 31.372 62.859 1.00 14.32
ATOM 30 C BILE A 4 19.233 32.112 63.743 1.00 13.54
ATOM 31 O BILE A 4 19.105 33.315 64.009 1.00 11.84
ATOM 32 CB BILE A 4 18.298 31.951 61.406 1.00 13.62
ATOM 33 CG1BILE A 4 17.157 31.300 60.620 1.00 18.39
ATOM 34 CG2BILE A 4 19.661 31.747 60.743 1.00 13.64
ATOM1200035 CD1BILE A 4 16.879 32.102 59.355 1.00 16.69
HETATM 1475 S SO4 S 188 31.424 42.923 60.396 1.00 55.69 S4+
HETATM 1476 O1 SO4 S 188 31.631 41.513 60.336 1.00 59.84 O1-
HETATM 1477 O2 SO4 S 188 32.533 43.699 59.932 1.00 49.98 O1-
HETATM 1478 O3 SO4 S 188 31.128 43.217 61.738 1.00 59.44 O1-
HETATM 1479 O4 SO4 S 188 30.353 43.201 59.539 1.00 60.54 O1-
HETATM 1480 O HOH W 200 29.478 23.354 61.364 1.00 8.67 WATE
END""")
out = cStringIO.StringIO()
processed_pdb_file = pdb_interpretation.run(args=["tmp.pdb"], log=out)
m = mouse_selection_manager()
pdb_hierarchy = processed_pdb_file.all_chain_proxies.pdb_hierarchy
pdb_hierarchy.atoms().reset_i_seq()
m.update_selection_handlers(
pdb_hierarchy=pdb_hierarchy,
mmtbx_selection_function=processed_pdb_file.all_chain_proxies.selection)
assert m.selection_size() == 0
m.apply_selection("chain A")
assert m.selection_size() == 40
m.clear_selection()
m.toggle_chain_selection(5)
assert m.selection_size() == 40
m.toggle_residue_selection(10)
assert m.selection_size() == 29
m.toggle_atom_selection(10) # XXX: doesn't work!
assert m.selection_size() == 29
m.toggle_atom_selection(20)
assert m.selection_size() == 28
from iotbx import pdb
from scitbx.array_family import flex
pdb_hierarchy = pdb.input(source_info=None, lines=flex.split_lines("""\
HETATM 4049 O HOH W 1 2.954 13.042 11.632 1.00 37.53 O
HETATM 4050 O HOH W 2 5.539 14.595 10.951 1.00 31.25 O
HETATM 4051 O HOH W 3 -2.971 14.661 14.669 1.00 38.68 O
HETATM 4052 O HOH W 4 6.281 34.000 7.684 1.00 39.58 O
HETATM 4053 O HOH W 5 16.004 9.039 10.335 1.00 37.31 O
HETATM 4054 O HOH W 6 2.144 5.718 20.447 1.00 49.77 O
HETATM 4055 O HOH W 7 -1.180 10.517 14.630 1.00 32.95 O
HETATM 4056 O AHOH W 8 9.227 8.636 12.535 1.00 32.52 O
HETATM 4056 O BHOH W 8 9.227 8.636 12.535 1.00 32.52 O
HETATM 4057 O AHOH W 9 11.070 -0.570 15.047 1.00 30.24 O
HETATM 4057 O BHOH W 9 11.070 -0.570 15.047 1.00 30.24 O
HETATM 4058 O AHOH W 10 15.630 -6.169 12.853 1.00 31.08 O
HETATM 4058 O BHOH W 10 15.630 -6.169 12.853 1.00 31.08 O
HETATM 4059 O HOH W 11 14.854 -8.299 16.887 1.00 32.65 O
HETATM 4060 O HOH W 12 27.586 0.391 24.184 1.00 31.29 O
HETATM 4061 O HOH W 13 3.240 7.801 38.401 1.00 32.09 O
END""")).construct_hierarchy()
m = mouse_selection_manager()
pdb_hierarchy.atoms().reset_i_seq()
m.update_selection_handlers(pdb_hierarchy=pdb_hierarchy,
mmtbx_selection_function=None)
assert m.selection_size() == 0
m.apply_selection("chain W")
assert m.selection_size() == 16
m.start_range_selection(5)
m.end_range_selection(15, deselect=False, ignore_altloc=True)
assert m.selection_size() == 11
m.start_range_selection(6)
m.end_range_selection(10, deselect=False, ignore_altloc=True)
assert m.selection_size() == 11 # no change because of deselect=False
m.start_range_selection(6)
m.end_range_selection(9, deselect=True, ignore_altloc=True)
assert m.selection_size() == 6
m.start_range_selection(10)
m.end_range_selection(12, deselect=True, ignore_altloc=False)
assert m.selection_size() == 5
print "OK"
for chain in model.chains():
try:
target_seq=chain.as_padded_sequence() # has XXX for missing residues
target_seq.replace("X","")
chain_length=len(target_seq)
except Exception, e:
chain_length=0
if chain_length and (longest_chain is None or chain_length>longest_chain):
longest_chain=chain_length
biggest_chain=chain
if biggest_chain is None:
print >>out,"Unable to extract unique part of hierarchy"
return None
biggest_chain_hierarchy=iotbx.pdb.input(
source_info="Model",lines=flex.split_lines("")).construct_hierarchy()
mm=iotbx.pdb.hierarchy.model()
biggest_chain_hierarchy.append_model(mm)
mm.append_chain(biggest_chain.detached_copy())
# ready with biggest chain
copies_of_biggest_chain_ph=extract_copies_identical_to_target_from_hierarchy(
ph,target_ph=biggest_chain_hierarchy,
allow_extensions=False,out=sys.stdout)
return copies_of_biggest_chain_ph
def extract_copies_identical_to_target_from_hierarchy(ph,
allow_extensions=False,
min_similarity=None,target_ph=None,out=sys.stdout):
new_hierarchy=iotbx.pdb.input(
def exercise_geo_output(mon_lib_srv, ener_lib):
pdb_inp = iotbx.pdb.input(source_info="peptide",
lines=flex.split_lines(pdb_str))
hierarchy = pdb_inp.construct_hierarchy()
atoms = hierarchy.atoms()
sites_cart = atoms.extract_xyz()
params = ramachandran.master_phil.fetch().extract()
params = params.ramachandran_plot_restraints
params.favored = 'emsley'
params.allowed = 'emsley'
params.outlier = 'emsley'
params.inject_emsley8k_into_oldfield_favored = False
rama_manager = ramachandran.ramachandran_manager(hierarchy, params,
StringIO())
out = StringIO()
rama_manager.show_sorted(by_value="residual",
sites_cart=sites_cart,
site_labels=[a.id_str() for a in atoms],
f=out)
gv = out.getvalue()
assert not show_diff(
gv, """\
Ramachandran plot restraints (Oldfield): 0
Sorted by residual:
Ramachandran plot restraints (Emsley): 8
Sorted by residual:
phi-psi angles formed by residual
pdb=" C ALA 7 " 1.53e+01
pdb=" N ALA 8 "
pdb=" CA ALA 8 "
pdb=" C ALA 8 "
pdb=" N ALA 9 "
phi-psi angles formed by residual
pdb=" C ALA 1 " 1.52e+01
pdb=" N ALA 2 "
pdb=" CA ALA 2 "
pdb=" C ALA 2 "
pdb=" N ALA 3 "
phi-psi angles formed by residual
pdb=" C ALA 6 " 1.20e+01
pdb=" N ALA 7 "
pdb=" CA ALA 7 "
pdb=" C ALA 7 "
pdb=" N ALA 8 "
phi-psi angles formed by residual
pdb=" C ALA 2 " 1.14e+01
pdb=" N ALA 3 "
pdb=" CA ALA 3 "
pdb=" C ALA 3 "
pdb=" N ALA 4 "
phi-psi angles formed by residual
pdb=" C ALA 8 " 1.06e+01
pdb=" N ALA 9 "
pdb=" CA ALA 9 "
pdb=" C ALA 9 "
pdb=" N ALA 10 "
phi-psi angles formed by residual
pdb=" C ALA 4 " 1.06e+01
pdb=" N ALA 5 "
pdb=" CA ALA 5 "
pdb=" C ALA 5 "
pdb=" N ALA 6 "
phi-psi angles formed by residual
pdb=" C ALA 3 " 1.03e+01
pdb=" N ALA 4 "
pdb=" CA ALA 4 "
pdb=" C ALA 4 "
pdb=" N ALA 5 "
phi-psi angles formed by residual
pdb=" C ALA 5 " 7.58e+00
pdb=" N ALA 6 "
pdb=" CA ALA 6 "
pdb=" C ALA 6 "
pdb=" N ALA 7 "
Ramachandran plot restraints (emsley8k): 0
Sorted by residual:
Ramachandran plot restraints (phi/psi/2): 0
Sorted by residual:
""")
params.favored = 'oldfield'
params.allowed = 'oldfield'
params.outlier = 'oldfield'
params.inject_emsley8k_into_oldfield_favored = False
rama_manager = ramachandran.ramachandran_manager(hierarchy, params,
StringIO())
out = StringIO()
rama_manager.show_sorted(by_value="residual",
sites_cart=sites_cart,
site_labels=[a.id_str() for a in atoms],
f=out)
gv = out.getvalue()
#print(gv)
#STOP()
assert not show_diff(
gv, """\
Ramachandran plot restraints (Oldfield): 8
Sorted by residual:
phi-psi angles formed by residual
pdb=" C ALA 5 " 3.46e-02
pdb=" N ALA 6 "
pdb=" CA ALA 6 "
pdb=" C ALA 6 "
pdb=" N ALA 7 "
phi-psi angles formed by residual
pdb=" C ALA 6 " 2.86e-02
pdb=" N ALA 7 "
pdb=" CA ALA 7 "
pdb=" C ALA 7 "
pdb=" N ALA 8 "
phi-psi angles formed by residual
pdb=" C ALA 2 " 2.54e-02
pdb=" N ALA 3 "
pdb=" CA ALA 3 "
pdb=" C ALA 3 "
pdb=" N ALA 4 "
phi-psi angles formed by residual
pdb=" C ALA 8 " 2.00e-02
pdb=" N ALA 9 "
pdb=" CA ALA 9 "
pdb=" C ALA 9 "
pdb=" N ALA 10 "
phi-psi angles formed by residual
pdb=" C ALA 1 " 1.21e-02
pdb=" N ALA 2 "
pdb=" CA ALA 2 "
pdb=" C ALA 2 "
pdb=" N ALA 3 "
phi-psi angles formed by residual
pdb=" C ALA 4 " 1.00e-02
pdb=" N ALA 5 "
pdb=" CA ALA 5 "
pdb=" C ALA 5 "
pdb=" N ALA 6 "
phi-psi angles formed by residual
pdb=" C ALA 3 " 9.28e-03
pdb=" N ALA 4 "
pdb=" CA ALA 4 "
pdb=" C ALA 4 "
pdb=" N ALA 5 "
phi-psi angles formed by residual
pdb=" C ALA 7 " 3.90e-03
pdb=" N ALA 8 "
pdb=" CA ALA 8 "
pdb=" C ALA 8 "
pdb=" N ALA 9 "
Ramachandran plot restraints (Emsley): 0
Sorted by residual:
Ramachandran plot restraints (emsley8k): 0
Sorted by residual:
Ramachandran plot restraints (phi/psi/2): 0
Sorted by residual:
""")
def exercise_manager_selection(mon_lib_srv, ener_lib):
pdb_inp = iotbx.pdb.input(source_info="peptide",
lines=flex.split_lines(pdb_str))
hierarchy = pdb_inp.construct_hierarchy()
atoms = hierarchy.atoms()
sites_cart = atoms.extract_xyz()
params = ramachandran.master_phil.fetch().extract()
params = params.ramachandran_plot_restraints
params.favored = 'emsley'
params.allowed = 'emsley'
params.outlier = 'emsley'
params.inject_emsley8k_into_oldfield_favored = False
rama_manager = ramachandran.ramachandran_manager(hierarchy, params,
StringIO())
out = StringIO()
s_out = StringIO()
rama_manager.show_sorted(by_value="residual",
sites_cart=sites_cart,
site_labels=[a.id_str() for a in atoms],
f=out)
selected_m = rama_manager.proxy_select(n_seq=hierarchy.atoms_size(),
iselection=flex.size_t(range(40)))
selected_m.show_sorted(by_value="residual",
sites_cart=sites_cart,
site_labels=[a.id_str() for a in atoms],
f=s_out)
assert not show_diff(
s_out.getvalue(), """\
Ramachandran plot restraints (Oldfield): 0
Sorted by residual:
Ramachandran plot restraints (Emsley): 6
Sorted by residual:
phi-psi angles formed by residual
pdb=" C ALA 1 " 1.52e+01
pdb=" N ALA 2 "
pdb=" CA ALA 2 "
pdb=" C ALA 2 "
pdb=" N ALA 3 "
phi-psi angles formed by residual
pdb=" C ALA 6 " 1.20e+01
pdb=" N ALA 7 "
pdb=" CA ALA 7 "
pdb=" C ALA 7 "
pdb=" N ALA 8 "
phi-psi angles formed by residual
pdb=" C ALA 2 " 1.14e+01
pdb=" N ALA 3 "
pdb=" CA ALA 3 "
pdb=" C ALA 3 "
pdb=" N ALA 4 "
phi-psi angles formed by residual
pdb=" C ALA 4 " 1.06e+01
pdb=" N ALA 5 "
pdb=" CA ALA 5 "
pdb=" C ALA 5 "
pdb=" N ALA 6 "
phi-psi angles formed by residual
pdb=" C ALA 3 " 1.03e+01
pdb=" N ALA 4 "
pdb=" CA ALA 4 "
pdb=" C ALA 4 "
pdb=" N ALA 5 "
phi-psi angles formed by residual
pdb=" C ALA 5 " 7.58e+00
pdb=" N ALA 6 "
pdb=" CA ALA 6 "
pdb=" C ALA 6 "
pdb=" N ALA 7 "
Ramachandran plot restraints (emsley8k): 0
Sorted by residual:
Ramachandran plot restraints (phi/psi/2): 0
Sorted by residual:
""")
def run_resolve (self) :
from solve_resolve.resolve_python import resolve_in_memory
from iotbx import pdb
from scitbx.array_family import flex
make_sub_header("RESOLVE build", out=self.out)
mean_density_start = self.mean_density_at_sites()
cc_start = self.cc_model_map()
sites_start = self.get_selected_sites(hydrogens=False)
t1 = time.time()
pdb_inp = self.box_selected_hierarchy.as_pdb_input()
inp_hierarchy = pdb_inp.construct_hierarchy()
chain = inp_hierarchy.only_model().only_chain()
first_resseq = chain.residue_groups()[0].resseq_as_int()
seq = "".join(chain.only_conformer().as_sequence(substitute_unknown='A'))
resolve_args = [
"start_chain 1 %d" % first_resseq,
"extend_only",
"skip_hetatm",
"no_merge_ncs_copies",
"no_optimize_ncs",
"i_ran_seed %d" % int(time.time() % os.getpid()),
]
if (self.params.build_new_loop) : # XXX not really working...
n_res = len(chain.residue_groups())
assert (n_res >= 3)
k = 0
for residue_group in chain.residue_groups()[1:-1] :
print >> self.out, " removing residue group %s %s" % \
(chain.id, residue_group.resid())
chain.remove_residue_group(residue_group)
resolve_args.extend([
"loop_only",
"build_outside_model",
"no_sub_segments",
"n_random_loop %d" % self.params.n_random_loop,
"loop_length %d" % (n_res - 2),
"rms_random_loop 0.3",
"rho_min_main_low 0.5",
"rho_min_main_base 0.5",
"n_internal_start 0",
])
else :
resolve_args.extend([
"rebuild_in_place",
"replace_existing",
"richardson_rotamers",
"min_z_value_rho -3.0",
"delta_phi 20.00",
"dist_cut_base 3.0",
"n_random_frag 0",
"group_ca_length 4",
"group_length 2",
])
out = null_out()
if (self.debug) :
out = self.out
cmn = resolve_in_memory.run(
map_coeffs=self.box_map_coeffs,
pdb_inp=inp_hierarchy.as_pdb_input(),
build=True,
input_text="\n".join(resolve_args),
chain_type="PROTEIN",
seq_file_as_string=seq,
out=out)
new_pdb_input = pdb.input(
source_info='string',
lines=flex.split_lines(cmn.atom_db.pdb_out_as_string))
new_hierarchy = new_pdb_input.construct_hierarchy()
print >> self.out, " %d atoms rebuilt" % len(new_hierarchy.atoms())
new_hierarchy.write_pdb_file("resolve.pdb")
selection_moved = flex.size_t()
sites_new = flex.vec3_double()
for atom in new_hierarchy.atoms() :
id_str = atom.id_str()
if (not id_str in self.atom_id_mapping) :
raise KeyError("Atom ID %s not recognized in RESOLVE model." % id_str)
i_seq = self.atom_id_mapping[id_str]
selection_moved.append(i_seq)
sites_new.append(atom.xyz)
sites_cart_selected = self.box_selected_hierarchy.atoms().extract_xyz()
sites_cart_selected.set_selected(selection_moved, sites_new)
self.box_selected_hierarchy.atoms().set_xyz(sites_cart_selected)
sites_cart_box = self.box.xray_structure_box.sites_cart()
sites_cart_box.set_selected(self.selection_in_box, sites_cart_selected)
self.box.xray_structure_box.set_sites_cart(sites_cart_box)
self.box.pdb_hierarchy_box.atoms().set_xyz(sites_cart_box)
t2 = time.time()
print >> self.out, " RESOLVE time: %.1fs" % (t2-t1)
selection_rebuilt = self.selection_in_box.select(selection_moved)
minimize_sel = flex.bool(self.n_sites_box, False).set_selected(
self.selection_in_box, True).set_selected(selection_rebuilt, False)
# atoms present in the selection but not in the RESOLVE model (usually
# hydrogen atoms) need to be minimized to follow the rebuilt sites
if (minimize_sel.count(True) > 0) :
print >> self.out, " Performing geometry minimzation on unbuilt sites"
self.geometry_minimization(
selection=minimize_sel,
nonbonded=False)
self.box.write_pdb_file("box_resolve.pdb")
# two alternatives here: restrain other atoms tightly, and minimize the
# entire box, or restrain selected atoms loosely, and refine only those
self.restrain_atoms(
selection=self.others_in_box,
reference_sigma=0.02)
if (self.params.anneal) :
self.anneal(start_temperature=2500)
else :
self.real_space_refine(selection=self.selection_all_box)
self.box.write_pdb_file("box_refined.pdb")
self.box.write_ccp4_map()
mean_density_end = self.mean_density_at_sites()
cc_end = self.cc_model_map()
print >> self.out, " mean density level: start=%.2fsigma end=%.2fsigma" \
% (mean_density_start, mean_density_end)
print >> self.out, " model-map CC: start=%.3f end=%.3f" % (cc_start,
cc_end)
sites_final = self.get_selected_sites(hydrogens=False)
print >> self.out, " rmsd to starting model: %.3f Angstrom" % \
sites_final.rms_difference(sites_start)
t3 = time.time()
print >> self.out, " Total build and refine time: %.1fs" % (t3-t1)
def exercise_geo_output(mon_lib_srv, ener_lib):
pdb_str = """\
CRYST1 18.879 16.714 25.616 90.00 90.00 90.00 P 1
ATOM 1 N ALA 1 13.515 7.809 20.095 1.00 0.00 N
ATOM 2 CA ALA 1 13.087 6.532 19.536 1.00 0.00 C
ATOM 3 C ALA 1 11.716 6.653 18.880 1.00 0.00 C
ATOM 4 O ALA 1 11.425 5.972 17.896 1.00 0.00 O
ATOM 5 CB ALA 1 13.065 5.461 20.616 1.00 0.00 C
ATOM 6 N ALA 2 10.876 7.524 19.431 1.00 0.00 N
ATOM 7 CA ALA 2 9.535 7.735 18.900 1.00 0.00 C
ATOM 8 C ALA 2 9.565 8.647 17.678 1.00 0.00 C
ATOM 9 O ALA 2 8.787 8.471 16.741 1.00 0.00 O
ATOM 10 CB ALA 2 8.626 8.316 19.973 1.00 0.00 C
ATOM 11 N ALA 3 10.469 9.622 17.697 1.00 0.00 N
ATOM 12 CA ALA 3 10.606 10.565 16.593 1.00 0.00 C
ATOM 13 C ALA 3 11.132 9.871 15.340 1.00 0.00 C
ATOM 14 O ALA 3 10.687 10.157 14.228 1.00 0.00 O
ATOM 15 CB ALA 3 11.520 11.714 16.987 1.00 0.00 C
ATOM 16 N ALA 4 12.081 8.960 15.530 1.00 0.00 N
ATOM 17 CA ALA 4 12.656 8.209 14.421 1.00 0.00 C
ATOM 18 C ALA 4 11.624 7.266 13.812 1.00 0.00 C
ATOM 19 O ALA 4 11.570 7.090 12.595 1.00 0.00 O
ATOM 20 CB ALA 4 13.879 7.432 14.883 1.00 0.00 C
ATOM 21 N ALA 5 10.805 6.663 14.669 1.00 0.00 N
ATOM 22 CA ALA 5 9.753 5.761 14.218 1.00 0.00 C
ATOM 23 C ALA 5 8.662 6.528 13.481 1.00 0.00 C
ATOM 24 O ALA 5 8.107 6.045 12.494 1.00 0.00 O
ATOM 25 CB ALA 5 9.165 5.000 15.396 1.00 0.00 C
ATOM 26 N ALA 6 8.360 7.728 13.967 1.00 0.00 N
ATOM 27 CA ALA 6 7.358 8.580 13.338 1.00 0.00 C
ATOM 28 C ALA 6 7.860 9.106 11.998 1.00 0.00 C
ATOM 29 O ALA 6 7.078 9.322 11.072 1.00 0.00 O
ATOM 30 CB ALA 6 6.986 9.732 14.257 1.00 0.00 C
ATOM 31 N ALA 7 9.169 9.311 11.903 1.00 0.00 N
ATOM 32 CA ALA 7 9.781 9.787 10.668 1.00 0.00 C
ATOM 33 C ALA 7 9.912 8.655 9.655 1.00 0.00 C
ATOM 34 O ALA 7 9.905 8.886 8.446 1.00 0.00 O
ATOM 35 CB ALA 7 11.141 10.405 10.952 1.00 0.00 C
ATOM 36 N ALA 8 10.030 7.429 10.157 1.00 0.00 N
ATOM 37 CA ALA 8 10.152 6.258 9.297 1.00 0.00 C
ATOM 38 C ALA 8 8.788 5.809 8.786 1.00 0.00 C
ATOM 39 O ALA 8 8.667 5.312 7.666 1.00 0.00 O
ATOM 40 CB ALA 8 10.839 5.124 10.041 1.00 0.00 C
ATOM 41 N ALA 9 7.762 5.988 9.613 1.00 0.00 N
ATOM 42 CA ALA 9 6.405 5.603 9.243 1.00 0.00 C
ATOM 43 C ALA 9 5.816 6.576 8.228 1.00 0.00 C
ATOM 44 O ALA 9 5.000 6.195 7.389 1.00 0.00 O
ATOM 45 CB ALA 9 5.521 5.526 10.478 1.00 0.00 C
ATOM 46 N ALA 10 6.235 7.835 8.309 1.00 0.00 N
ATOM 47 CA ALA 10 5.751 8.864 7.397 1.00 0.00 C
ATOM 48 C ALA 10 6.434 8.760 6.038 1.00 0.00 C
ATOM 49 O ALA 10 5.773 8.734 5.000 1.00 0.00 O
ATOM 50 CB ALA 10 5.966 10.246 7.995 1.00 0.00 C
TER
END
"""
pdb_inp = iotbx.pdb.input(source_info="peptide",lines=flex.split_lines(pdb_str))
hierarchy = pdb_inp.construct_hierarchy()
atoms = hierarchy.atoms()
sites_cart = atoms.extract_xyz()
params = ramachandran.master_phil.fetch().extract()
params.rama_potential = "emsley"
rama_manager = ramachandran.ramachandran_manager(
hierarchy, None, params, StringIO())
out = StringIO()
rama_manager.show_sorted(
by_value="residual",
sites_cart=sites_cart,
site_labels=[a.id_str() for a in atoms],
f=out)
gv = out.getvalue()
# print out.getvalue()
# STOP()
assert gv == """\
Ramachandran plot restraints: 8
Sorted by residual:
phi-psi angles formed by residual
pdb=" C ALA 7 " 1.53e+01
pdb=" N ALA 8 "
pdb=" CA ALA 8 "
pdb=" C ALA 8 "
pdb=" N ALA 9 "
phi-psi angles formed by residual
pdb=" C ALA 1 " 1.52e+01
pdb=" N ALA 2 "
pdb=" CA ALA 2 "
pdb=" C ALA 2 "
pdb=" N ALA 3 "
phi-psi angles formed by residual
pdb=" C ALA 6 " 1.20e+01
pdb=" N ALA 7 "
pdb=" CA ALA 7 "
pdb=" C ALA 7 "
pdb=" N ALA 8 "
phi-psi angles formed by residual
pdb=" C ALA 2 " 1.14e+01
pdb=" N ALA 3 "
pdb=" CA ALA 3 "
pdb=" C ALA 3 "
pdb=" N ALA 4 "
phi-psi angles formed by residual
pdb=" C ALA 8 " 1.06e+01
pdb=" N ALA 9 "
pdb=" CA ALA 9 "
pdb=" C ALA 9 "
pdb=" N ALA 10 "
phi-psi angles formed by residual
pdb=" C ALA 4 " 1.06e+01
pdb=" N ALA 5 "
pdb=" CA ALA 5 "
pdb=" C ALA 5 "
pdb=" N ALA 6 "
phi-psi angles formed by residual
pdb=" C ALA 3 " 1.03e+01
pdb=" N ALA 4 "
pdb=" CA ALA 4 "
pdb=" C ALA 4 "
pdb=" N ALA 5 "
phi-psi angles formed by residual
pdb=" C ALA 5 " 7.58e+00
pdb=" N ALA 6 "
pdb=" CA ALA 6 "
pdb=" C ALA 6 "
pdb=" N ALA 7 "
"""
params.rama_potential = "oldfield"
rama_manager = ramachandran.ramachandran_manager(
hierarchy, None, params, StringIO())
out = StringIO()
rama_manager.show_sorted(
by_value="residual",
sites_cart=sites_cart,
site_labels=[a.id_str() for a in atoms],
f=out)
gv = out.getvalue()
# print out.getvalue()
# STOP()
assert not show_diff(gv, """\
Ramachandran plot restraints: 8
Sorted by residual:
phi-psi angles formed by residual
pdb=" C ALA 7 " 1.52e-01
pdb=" N ALA 8 "
pdb=" CA ALA 8 "
pdb=" C ALA 8 "
pdb=" N ALA 9 "
phi-psi angles formed by residual
pdb=" C ALA 4 " 1.28e-01
pdb=" N ALA 5 "
pdb=" CA ALA 5 "
pdb=" C ALA 5 "
pdb=" N ALA 6 "
phi-psi angles formed by residual
pdb=" C ALA 6 " 5.19e-02
pdb=" N ALA 7 "
pdb=" CA ALA 7 "
pdb=" C ALA 7 "
pdb=" N ALA 8 "
phi-psi angles formed by residual
pdb=" C ALA 5 " 3.46e-02
pdb=" N ALA 6 "
pdb=" CA ALA 6 "
pdb=" C ALA 6 "
pdb=" N ALA 7 "
phi-psi angles formed by residual
pdb=" C ALA 2 " 2.54e-02
pdb=" N ALA 3 "
pdb=" CA ALA 3 "
pdb=" C ALA 3 "
pdb=" N ALA 4 "
phi-psi angles formed by residual
pdb=" C ALA 8 " 2.00e-02
pdb=" N ALA 9 "
pdb=" CA ALA 9 "
pdb=" C ALA 9 "
pdb=" N ALA 10 "
phi-psi angles formed by residual
pdb=" C ALA 1 " 1.21e-02
pdb=" N ALA 2 "
pdb=" CA ALA 2 "
pdb=" C ALA 2 "
pdb=" N ALA 3 "
phi-psi angles formed by residual
pdb=" C ALA 3 " 9.28e-03
pdb=" N ALA 4 "
pdb=" CA ALA 4 "
pdb=" C ALA 4 "
pdb=" N ALA 5 "
""")
def minimize_wrapper_for_ramachandran(
hierarchy,
xrs,
original_pdb_h,
excl_string_selection,
grm=None,
log=None,
ncs_restraints_group_list=[],
ss_annotation=None,
mon_lib_srv=None,
ener_lib=None,
rotamer_manager=None,
reference_rotamers=True,
number_of_cycles=1,
run_first_minimization_without_reference=False,
oldfield_weight_scale=3,
oldfield_plot_cutoff=0.03,
nonbonded_weight=500,
reference_sigma=0.7):
""" Wrapper around geometry minimization specifically tuned for eliminating
Ramachandran outliers.
"""
try:
import cPickle as pickle
except ImportError:
import pickle
from time import time
from mmtbx.monomer_library.pdb_interpretation import grand_master_phil_str
from mmtbx.geometry_restraints import reference
from mmtbx.command_line.geometry_minimization import \
get_geometry_restraints_manager
from mmtbx.geometry_restraints.torsion_restraints.reference_model import \
reference_model, reference_model_params
from libtbx.utils import null_out
from scitbx.array_family import flex
if log is None:
log = null_out()
# assert hierarchy.atoms_size()==xrs.scatterers().size(), "%d %d" % (
# hierarchy.atoms_size(), xrs.scatterers().size())
params_line = grand_master_phil_str
params = iotbx.phil.parse(input_string=params_line,
process_includes=True).extract()
params.pdb_interpretation.clash_guard.nonbonded_distance_threshold = None
params.pdb_interpretation.peptide_link.ramachandran_restraints = True
params.pdb_interpretation.peptide_link.oldfield.weight_scale = oldfield_weight_scale
params.pdb_interpretation.peptide_link.oldfield.plot_cutoff = oldfield_plot_cutoff
params.pdb_interpretation.nonbonded_weight = nonbonded_weight
params.pdb_interpretation.c_beta_restraints = True
params.pdb_interpretation.max_reasonable_bond_distance = None
params.pdb_interpretation.peptide_link.apply_peptide_plane = True
params.pdb_interpretation.ncs_search.enabled = True
params.pdb_interpretation.restraints_library.rdl = True
processed_pdb_files_srv = mmtbx.utils.\
process_pdb_file_srv(
crystal_symmetry= xrs.crystal_symmetry(),
pdb_interpretation_params = params.pdb_interpretation,
stop_for_unknowns = False,
log=log,
cif_objects=None)
processed_pdb_file, junk = processed_pdb_files_srv.\
process_pdb_files(raw_records=flex.split_lines(hierarchy.as_pdb_string()))
mon_lib_srv = processed_pdb_files_srv.mon_lib_srv
ener_lib = processed_pdb_files_srv.ener_lib
ncs_restraints_group_list = []
if processed_pdb_file.ncs_obj is not None:
ncs_restraints_group_list = processed_pdb_file.ncs_obj.get_ncs_restraints_group_list(
)
if grm is None:
grm = get_geometry_restraints_manager(processed_pdb_file,
xrs,
params=params)
else:
grm.geometry.pair_proxies(sites_cart=hierarchy.atoms().extract_xyz())
if grm.geometry.ramachandran_manager is not None:
grm.geometry.ramachandran_manager.update_phi_psi_targets(
sites_cart=hierarchy.atoms().extract_xyz())
if reference_rotamers and original_pdb_h is not None:
# make selection excluding rotamer outliers
from mmtbx.rotamer.rotamer_eval import RotamerEval
# print "Excluding rotamer outliers"
if rotamer_manager is None:
rotamer_manager = RotamerEval(mon_lib_srv=mon_lib_srv)
non_rot_outliers_selection = flex.bool(hierarchy.atoms_size(), False)
for model in original_pdb_h.models():
for chain in model.chains():
for conf in chain.conformers():
for res in conf.residues():
ev = rotamer_manager.evaluate_residue_2(res)
if ev != "OUTLIER" or ev is None:
for a in res.atoms():
non_rot_outliers_selection[a.i_seq] = True
# else:
# print " ", res.id_str()
rm_params = reference_model_params.extract()
rm_params.reference_model.enabled = True
rm_params.reference_model.strict_rotamer_matching = False
rm_params.reference_model.main_chain = False
rm = reference_model(processed_pdb_file=processed_pdb_file,
reference_file_list=None,
reference_hierarchy_list=[original_pdb_h],
mon_lib_srv=mon_lib_srv,
ener_lib=ener_lib,
has_hd=None,
params=rm_params.reference_model,
selection=non_rot_outliers_selection,
log=log)
rm.show_reference_summary(log=log)
grm.geometry.adopt_reference_dihedral_manager(rm)
# dealing with SS
if ss_annotation is not None:
from mmtbx.secondary_structure import manager
ss_manager = manager(pdb_hierarchy=hierarchy,
geometry_restraints_manager=grm.geometry,
sec_str_from_pdb_file=ss_annotation,
params=None,
mon_lib_srv=mon_lib_srv,
verbose=-1,
log=log)
grm.geometry.set_secondary_structure_restraints(ss_manager=ss_manager,
hierarchy=hierarchy,
log=log)
# grm pickle-unpickle
# t0 = time()
# prefix="grm"
# pklfile = open("%s.pkl" % prefix, 'wb')
# pickle.dump(grm.geometry, pklfile)
# pklfile.close()
# t1 = time()
# pklfile = open("%s.pkl" % prefix, 'rb')
# grm_from_file = pickle.load(pklfile)
# pklfile.close()
# t2 = time()
# print "Time pickling/unpickling: %.4f, %.4f" % (t1-t0, t2-t1)
# grm.geometry=grm_from_file
if run_first_minimization_without_reference:
obj = run2(restraints_manager=grm,
pdb_hierarchy=hierarchy,
correct_special_position_tolerance=1.0,
ncs_restraints_group_list=ncs_restraints_group_list,
max_number_of_iterations=300,
number_of_macro_cycles=number_of_cycles,
bond=True,
nonbonded=True,
angle=True,
dihedral=True,
chirality=True,
planarity=True,
fix_rotamer_outliers=True,
log=log)
if original_pdb_h is not None:
if len(excl_string_selection) == 0:
excl_string_selection = "all"
asc = original_pdb_h.atom_selection_cache()
sel = asc.selection(
"(%s) and (name CA or name C or name N or name O)" %
excl_string_selection)
grm.geometry.append_reference_coordinate_restraints_in_place(
reference.add_coordinate_restraints(
sites_cart=original_pdb_h.atoms().extract_xyz().select(sel),
selection=sel,
sigma=reference_sigma,
top_out_potential=True))
# grm.geometry.write_geo_file(
# sites_cart=hierarchy.atoms().extract_xyz(),
# site_labels=[atom.id_str() for atom in hierarchy.atoms()],
# file_name="last_gm.geo")
obj = run2(restraints_manager=grm,
pdb_hierarchy=hierarchy,
correct_special_position_tolerance=1.0,
ncs_restraints_group_list=ncs_restraints_group_list,
max_number_of_iterations=300,
number_of_macro_cycles=number_of_cycles,
bond=True,
nonbonded=True,
angle=True,
dihedral=True,
chirality=True,
planarity=True,
fix_rotamer_outliers=True,
log=log)
grm.geometry.reference_dihedral_manager = None
