def exercise(pdb_str):
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
model = mmtbx.model.manager(model_input=pdb_inp, log=null_out())
model.process(make_restraints=True)
pdb_hierarchy = model.get_hierarchy()
sites_cart = model.get_sites_cart()
atoms = pdb_hierarchy.atoms()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
h_parameterization = riding_h_manager.h_parameterization
diagnostics = riding_h_manager.diagnostics(sites_cart=sites_cart,
threshold=0.05)
diagnostics = riding_h_manager.diagnostics(sites_cart=sites_cart,
threshold=0.05)
h_distances = diagnostics.h_distances
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_parameterization) - h_parameterization.count(None)
# There are 90 H atoms in pdb_string, check if all of them are recognized
assert (number_h_para == number_h), 'Not all H atoms are parameterized'
for ih in h_distances:
labels = atoms[ih].fetch_labels()
assert (h_distances[ih] < 0.01), \
'distance too large: %s atom: %s (%s) residue: %s ' \
% (h_parameterization[ih].htype, atoms[ih].name, ih, labels.resseq.strip())
def exercise3(pdb_str, type_list_known):
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
model = mmtbx.model.manager(
model_input = pdb_inp,
build_grm = True)
pdb_hierarchy = model.get_hierarchy()
sites_cart = model.get_sites_cart()
atoms = pdb_hierarchy.atoms()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
h_para = riding_h_manager.h_parameterization
diagnostics = riding_h_manager.diagnostics(
sites_cart = sites_cart,
threshold = 0.05)
h_distances = diagnostics.h_distances
type_list = diagnostics.type_list
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_para) - h_para.count(None)
assert (number_h_para == number_h-2), 'Not all H atoms are parameterized'
for ih in h_distances:
labels = atoms[ih].fetch_labels()
assert (h_distances[ih] < 0.2), \
'distance too large: %s atom: %s (%s) residue: %s ' \
% (h_para[ih].htype, atoms[ih].name, ih, labels.resseq.strip())
for type1, type2 in zip(type_list, type_list_known):
assert (type1 == type2)
def exercise1(pdb_str, cif_str):
model = prepare_inputs(pdb_str, cif_str)
riding_h_manager = model.get_riding_h_manager()
atoms = model.get_hierarchy().atoms()
h_para = riding_h_manager.h_parameterization
diagnostics = riding_h_manager.diagnostics(
sites_cart=model.get_sites_cart(), threshold=0.05)
h_distances = diagnostics.h_distances
type_list = diagnostics.type_list
# number of H atoms
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_para) - h_para.count(None)
assert (number_h_para == number_h), 'Not all H atoms are parameterized'
for ih in h_distances:
# One atom is expected to be moved
if (ih == 16):
continue
labels = atoms[ih].fetch_labels()
assert (h_distances[ih] < 0.1), \
'distance too large: %s atom: %s (%s) residue: %s ' \
% (h_para[ih].htype, atoms[ih].name, ih, labels.resseq.strip())
for type1, type2 in zip(type_list, type_list_known1):
assert (type1 == type2)
def exercise(pdb_str):
params = mmtbx.model.manager.get_default_pdb_interpretation_params()
params.pdb_interpretation.use_neutron_distances = True
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
model = mmtbx.model.manager(model_input=pdb_inp, log=null_out())
model.process(pdb_interpretation_params=params, make_restraints=True)
pdb_hierarchy = model.get_hierarchy()
sites_cart = model.get_sites_cart()
atoms = pdb_hierarchy.atoms()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
h_parameterization = riding_h_manager.h_parameterization
diagnostics = riding_h_manager.diagnostics(sites_cart=sites_cart,
threshold=0.05)
h_distances = diagnostics.h_distances
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_parameterization) - h_parameterization.count(None)
if (pdb_str != pdb_str_02):
assert (number_h_para == number_h), 'Not all H atoms are parameterized'
# For each H atom, check if distance between computed H and that in input model is
# not too large
for ih in h_distances:
labels = atoms[ih].fetch_labels()
assert (h_distances[ih] < 0.1), \
'distance too large: %s atom: %s (%s) residue: %s ' \
% (h_parameterization[ih].htype, atoms[ih].name, ih, labels.resseq.strip())
def exercise3(pdb_str, type_list_known):
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
params = mmtbx.model.manager.get_default_pdb_interpretation_scope(
).extract()
params.pdb_interpretation.allow_polymer_cross_special_position = True
model = mmtbx.model.manager(model_input=pdb_inp, log=null_out())
model.process(pdb_interpretation_params=params, make_restraints=True)
pdb_hierarchy = model.get_hierarchy()
sites_cart = model.get_sites_cart()
atoms = pdb_hierarchy.atoms()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
h_para = riding_h_manager.h_parameterization
diagnostics = riding_h_manager.diagnostics(sites_cart=sites_cart,
threshold=0.05)
h_distances = diagnostics.h_distances
type_list = diagnostics.type_list
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_para) - h_para.count(None)
assert (number_h_para == number_h - 2), 'Not all H atoms are parameterized'
for ih in h_distances:
labels = atoms[ih].fetch_labels()
assert (h_distances[ih] < 0.2), \
'distance too large: %s atom: %s (%s) residue: %s ' \
% (h_para[ih].htype, atoms[ih].name, ih, labels.resseq.strip())
for type1, type2 in zip(type_list, type_list_known):
assert (type1 == type2)
def exercise2():
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
model = mmtbx.model.manager(
model_input = pdb_inp,
log = null_out())
model.process(make_restraints=True)
pdb_hierarchy = model.get_hierarchy()
#sites_cart = model.get_sites_cart()
#atoms = pdb_hierarchy.atoms()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
h_parameterization = riding_h_manager.h_parameterization
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_parameterization) - h_parameterization.count(None)
# Check that all H atoms are parameterized in original manager
assert (number_h_para == number_h - 1), 'Not all H atoms are parameterized'
# Test several selections and compare with known answers
#
print('selection1 = not (name CE1 or name CB)')
selection1 = pdb_hierarchy.atom_selection_cache().\
selection("not (name CE1 or name CB)")
answers1 = group_args(
entries_selected_h_para = 19,
entries_cpp_selected = 2,
h_in_selected_hierarchy = 9)
apply_selection(
riding_h_manager = riding_h_manager,
selection = selection1,
answers = answers1)
#
print('selection2 = not (name CD1 or name HD2 or name C)')
selection2 = pdb_hierarchy.atom_selection_cache().\
selection("not (name CD1 or name HD2 or name C)")
answers2 = group_args(
entries_selected_h_para = 18,
entries_cpp_selected = 4,
h_in_selected_hierarchy = 8)
apply_selection(
riding_h_manager = riding_h_manager,
selection = selection2,
answers = answers2)
#
print('selection3 = not (name N or name HB2 or name CE2)')
selection3 = pdb_hierarchy.atom_selection_cache().\
selection("not (name N or name HB2 or name CE2)")
answers3 = group_args(
entries_selected_h_para = 18,
entries_cpp_selected = 4,
h_in_selected_hierarchy = 8)
apply_selection(
riding_h_manager = riding_h_manager,
selection = selection3,
answers = answers3)
def exercise(pdb_str, eps):
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
model = mmtbx.model.manager(
model_input = pdb_inp,
build_grm = True,
log = null_out())
geometry_restraints = model.restraints_manager.geometry
xray_structure = model.get_xray_structure()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
riding_h_manager.idealize(xray_structure = xray_structure)
sites_cart = xray_structure.sites_cart()
g_analytical = geometry_restraints.energies_sites(
sites_cart = sites_cart,
compute_gradients = True).gradients
hd_selection = xray_structure.hd_selection()
g_analytical_reduced = riding_h_manager.gradients_reduced_cpp(
gradients = g_analytical,
sites_cart = sites_cart,
hd_selection = hd_selection)
#
ex = [eps,0,0]
ey = [0,eps,0]
ez = [0,0,eps]
g_fd = flex.vec3_double()
for i_site in xrange(sites_cart.size()):
g_fd_i = []
for e in [ex,ey,ez]:
ts = []
for sign in [-1,1]:
sites_cart_ = sites_cart.deep_copy()
xray_structure_ = xray_structure.deep_copy_scatterers()
sites_cart_[i_site] = [
sites_cart_[i_site][j]+e[j]*sign for j in xrange(3)]
xray_structure_.set_sites_cart(sites_cart_)
# after shift, recalculate H position
riding_h_manager.idealize(
xray_structure=xray_structure_)
sites_cart_ = xray_structure_.sites_cart()
ts.append(geometry_restraints.energies_sites(
sites_cart = sites_cart_,
compute_gradients = False).target)
g_fd_i.append((ts[1]-ts[0])/(2*eps))
g_fd.append(g_fd_i)
g_fd_reduced = g_fd.select(~hd_selection)
for g1, g2 in zip(g_analytical_reduced, g_fd_reduced):
assert approx_equal(g1,g2, 1.e-4)
def setup_riding(model):
model.setup_riding_h_manager(ignore_h_with_dof=True)
riding_h_manager = model.get_riding_h_manager()
h_para = riding_h_manager.h_parameterization
sel_h = model.get_hd_selection()
sel_h_in_para = flex.bool(
[bool(x) for x in riding_h_manager.h_parameterization])
sel_h_not_in_para = sel_h_in_para.exclusive_or(sel_h)
return (list(sel_h_not_in_para.iselection()))
def exercise1():
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
model = mmtbx.model.manager(
model_input = pdb_inp,
log = null_out())
model.process(make_restraints=True)
pdb_hierarchy = model.get_hierarchy()
sites_cart = model.get_sites_cart()
atoms = pdb_hierarchy.atoms()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
h_parameterization = riding_h_manager.h_parameterization
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_parameterization) - h_parameterization.count(None)
assert (number_h_para == number_h-1), 'Not all H atoms are parameterized'
rc = h_parameterization[20]
new_manager = riding_h_manager.deep_copy()
new_h_parameterization = new_manager.h_parameterization
rc_new = new_h_parameterization[20]
assert (rc_new.htype == rc.htype)
assert (rc_new.ih == rc.ih)
assert (rc_new.a0 == rc.a0)
assert (rc_new.a1 == rc.a1)
assert (rc_new.a2 == rc.a2)
assert (rc_new.a3 == rc.a3)
assert (rc_new.a == rc.a)
assert (rc_new.b == rc.b)
assert (rc_new.h == rc.h)
assert (rc_new.n == rc.n)
assert (rc_new.disth == rc.disth)
rc_new.htype = 'unk'
rc_new.ih = 0
rc_new.a0 = 1
rc_new.a1 = 2
rc_new.a2 = 3
rc_new.a3 = 4
assert (rc_new.htype != rc.htype)
assert (rc_new.ih != rc.ih)
assert (rc_new.a0 != rc.a0)
assert (rc_new.a1 != rc.a1)
assert (rc_new.a2 != rc.a2)
assert (rc_new.a3 != rc.a3)
def prepare_inputs(pdb_str, cif_str):
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
cif_object = iotbx.cif.reader(input_string=cif_str).model()
# bla.cif does not exist, but cif_objects needs a filename in first position
# of the tuple
cif_objects = [('bla.cif', cif_object)]
model = mmtbx.model.manager(model_input=pdb_inp,
build_grm=True,
restraint_objects=cif_objects)
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
return model
def exercise2(pdb_str, cif_str):
model = prepare_inputs(pdb_str, cif_str)
riding_h_manager = model.get_riding_h_manager()
atoms = model.get_hierarchy().atoms()
h_para = riding_h_manager.h_parameterization
diagnostics = riding_h_manager.diagnostics(
sites_cart=model.get_sites_cart(), threshold=0.05)
h_distances = diagnostics.h_distances
type_list = diagnostics.type_list
# number of H atoms
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_para) - h_para.count(None)
assert (number_h_para == 0), 'Not all H atoms are parameterized'
def exercise():
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
model = mmtbx.model.manager(
model_input = pdb_inp,
build_grm = True)
pdb_hierarchy = model.get_hierarchy()
sites_cart = model.get_sites_cart()
atoms = pdb_hierarchy.atoms()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
h_parameterization = riding_h_manager.h_parameterization
diagnostics = riding_h_manager.diagnostics(
sites_cart = sites_cart,
threshold = 0.05)
h_distances = diagnostics.h_distances
type_list = diagnostics.type_list
# number of H atoms in model
number_h = model.get_hd_selection().count(True)
# number of H in parameterization
number_h_para = len(h_parameterization) - h_parameterization.count(None)
# There are 152 H atoms in pdb_string, check if all of them are parameterized
assert (number_h_para == number_h), 'Not all H atoms are parameterized'
# For each H atom, check if distance compared to input model is not > 0.05
# 0.0014 = uncertainty for distance if uncertainty of coordinate = 0.001
for ih in h_distances:
labels = atoms[ih].fetch_labels()
assert (h_distances[ih] < 0.05), \
'distance too large: %s atom: %s (%s) residue: %s ' \
% (h_parameterization[ih].htype, atoms[ih].name, ih, labels.resseq.strip())
# KEEP: useful for debugging
#for ih in h_parameterization.keys():
# hp = h_parameterization[ih]
# print "'"+hp.htype+"'"+',',
for type1, type2 in zip(type_list, type_list_known):
assert (type1 == type2)
def exercise():
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
cif_object = iotbx.cif.reader(input_string=cif_str).model()
# bla.cif does not exist, but cif_objects needs a filename in first position
# of the tuple
cif_objects = [('bla.cif', cif_object)]
model = mmtbx.model.manager(model_input=pdb_inp,
build_grm=True,
restraint_objects=cif_objects)
pdb_hierarchy = model.get_hierarchy()
sites_cart = model.get_sites_cart()
atoms = pdb_hierarchy.atoms()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
h_para = riding_h_manager.h_parameterization
diagnostics = riding_h_manager.diagnostics(sites_cart=sites_cart,
threshold=0.05)
h_distances = diagnostics.h_distances
type_list = diagnostics.type_list
# number of H atoms
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_para) - h_para.count(None)
assert (number_h_para == number_h), 'Not all H atoms are parameterized'
for ih in h_distances:
# One atom is expected to be moved
if (ih == 16):
continue
labels = atoms[ih].fetch_labels()
assert (h_distances[ih] < 0.1), \
'distance too large: %s atom: %s (%s) residue: %s ' \
% (h_para[ih].htype, atoms[ih].name, ih, labels.resseq.strip())
for type1, type2 in zip(type_list, type_list_known):
assert (type1 == type2)
def exercise():
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
model = mmtbx.model.manager(
model_input = pdb_inp,
build_grm = True,
log = null_out())
pdb_hierarchy = model.get_hierarchy()
sites_cart = model.get_sites_cart()
atoms = pdb_hierarchy.atoms()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
h_parameterization = riding_h_manager.h_parameterization
diagnostics = riding_h_manager.diagnostics(
sites_cart = sites_cart,
threshold = 0.05)
h_distances = diagnostics.h_distances
type_list = diagnostics.type_list
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_parameterization) - h_parameterization.count(None)
# There are 90 H atoms in pdb_string, check if all of them are recognized
assert (number_h_para == number_h), 'Not all H atoms are parameterized'
# For every H , check if distance between computed H and H in input model is
# < 0.03 A
for ih in h_distances:
labels = atoms[ih].fetch_labels()
assert (h_distances[ih] < 0.03), 'distance too large: %s atom: %s (%s) residue: %s ' \
% (h_parameterization[ih].htype, atoms[ih].name, ih, labels.resseq.strip())
# Check if parameterization types are correct
for type1, type2 in zip(type_list, type_list_known):
assert (type1 == type2)
def exercise1():
pdb_str = """
CRYST1 21.850 24.325 24.603 90.00 90.00 90.00 P 1
SCALE1 0.045767 0.000000 0.000000 0.00000
SCALE2 0.000000 0.041110 0.000000 0.00000
SCALE3 0.000000 0.000000 0.040645 0.00000
ATOM 1 N CYS D 37 8.132 18.794 15.343 1.00143.27 D N
ANISOU 1 N CYS D 37 26762 17628 10046 -3652 3033 538 D N
ATOM 2 CA CYS D 37 9.229 18.179 14.592 1.00143.16 D C
ANISOU 2 CA CYS D 37 26739 17512 10144 -3661 2916 574 D C
ATOM 3 C CYS D 37 10.551 18.924 14.744 1.00143.18 D C
ANISOU 3 C CYS D 37 26760 17474 10166 -3627 2815 455 D C
ATOM 4 O CYS D 37 11.615 18.295 14.696 1.00141.47 D O
ANISOU 4 O CYS D 37 26571 17211 9972 -3636 2700 489 D O
ATOM 5 CB CYS D 37 8.857 18.048 13.112 1.00144.61 D C
ANISOU 5 CB CYS D 37 26841 17595 10509 -3672 2948 608 D C
ATOM 6 SG CYS D 37 7.159 17.517 12.843 1.00142.64 D S
ANISOU 6 SG CYS D 37 26553 17390 10253 -3704 3086 716 D S
ATOM 7 H CYS D 37 7.635 19.325 14.885 1.00172.08 D H
ATOM 8 HA CYS D 37 9.365 17.282 14.934 1.00171.95 D H
ATOM 9 HB2 CYS D 37 8.970 18.910 12.683 1.00173.69 D H
ATOM 10 HB3 CYS D 37 9.442 17.394 12.699 1.00173.69 D H
ATOM 11 N CYS D 40 13.775 17.698 16.644 1.00154.41 D N
ANISOU 11 N CYS D 40 28359 18912 11399 -3629 2475 474 D N
ATOM 12 CA CYS D 40 14.636 16.639 16.128 1.00149.28 D C
ANISOU 12 CA CYS D 40 27712 18183 10825 -3653 2369 564 D C
ATOM 13 C CYS D 40 15.084 16.830 14.685 1.00148.00 D C
ANISOU 13 C CYS D 40 27476 17888 10868 -3647 2342 540 D C
ATOM 14 O CYS D 40 16.158 16.339 14.335 1.00149.38 D O
ANISOU 14 O CYS D 40 27657 17989 11113 -3652 2233 563 D O
ATOM 15 CB CYS D 40 13.921 15.279 16.208 1.00140.80 D C
ANISOU 15 CB CYS D 40 26653 17143 9703 -3698 2398 729 D C
ATOM 16 SG CYS D 40 13.262 14.779 17.830 1.00136.64 D S
ANISOU 16 SG CYS D 40 26211 16771 8936 -3714 2439 794 D S
ATOM 17 H CYS D 40 13.032 17.777 16.218 1.00185.45 D H
ATOM 18 HA CYS D 40 15.432 16.588 16.680 1.00179.29 D H
ATOM 19 HB2 CYS D 40 13.174 15.295 15.590 1.00169.12 D H
ATOM 20 HB3 CYS D 40 14.548 14.592 15.932 1.00169.12 D H
HETATM 21 NB HEC D1001 9.421 13.220 11.858 1.00140.59 N
ANISOU 21 NB HEC D1001 26354 16953 10112 -3810 2765 1093 N
HETATM 22 ND HEC D1001 12.886 11.034 12.753 1.00144.24 N
ANISOU 22 ND HEC D1001 26954 17334 10517 -3839 2396 1214 N
HETATM 23 C1A HEC D1001 12.227 10.592 9.833 1.00139.00 C
ANISOU 23 C1A HEC D1001 26141 16470 10203 -3864 2452 1283 C
HETATM 24 C1B HEC D1001 8.860 13.248 10.595 1.00143.63 C
ANISOU 24 C1B HEC D1001 26666 17264 10645 -3817 2816 1110 C
HETATM 25 C1C HEC D1001 10.125 13.804 14.697 1.00139.27 C
ANISOU 25 C1C HEC D1001 26337 16981 9599 -3780 2714 1003 C
HETATM 26 C1D HEC D1001 13.435 10.960 14.028 1.00134.69 C
ANISOU 26 C1D HEC D1001 25819 16201 9156 -3833 2339 1204 C
HETATM 27 C2A HEC D1001 11.928 10.386 8.429 1.00142.28 C
ANISOU 27 C2A HEC D1001 26487 16789 10784 -3875 2476 1314 C
HETATM 28 C2B HEC D1001 7.789 14.214 10.617 1.00141.94 C
ANISOU 28 C2B HEC D1001 26417 17097 10418 -3798 2937 1044 C
HETATM 29 C2C HEC D1001 10.451 14.023 16.100 1.00140.94 C
ANISOU 29 C2C HEC D1001 26625 17289 9635 -3766 2687 965 C
HETATM 30 C2D HEC D1001 14.546 10.022 13.991 1.00142.48 C
ANISOU 30 C2D HEC D1001 26834 17133 10168 -3850 2214 1270 C
HETATM 31 C3A HEC D1001 10.804 11.059 8.149 1.00136.41 C
ANISOU 31 C3A HEC D1001 25701 16075 10056 -3866 2591 1279 C
HETATM 32 C3B HEC D1001 7.744 14.781 11.826 1.00143.82 C
ANISOU 32 C3B HEC D1001 26706 17431 10509 -3780 2957 983 C
HETATM 33 C3C HEC D1001 11.528 13.271 16.400 1.00137.87 C
ANISOU 33 C3C HEC D1001 26282 16879 9224 -3777 2567 1011 C
HETATM 34 C3D HEC D1001 14.632 9.534 12.538 1.00144.35 C
ANISOU 34 C3D HEC D1001 27005 17250 10590 -3867 2201 1319 C
HETATM 35 C4A HEC D1001 10.358 11.714 9.366 1.00144.69 C
ANISOU 35 C4A HEC D1001 26789 17236 10949 -3849 2645 1224 C
HETATM 36 C4B HEC D1001 8.768 14.145 12.649 1.00137.78 C
ANISOU 36 C4B HEC D1001 26012 16687 9651 -3787 2848 1015 C
HETATM 37 C4C HEC D1001 11.920 12.537 15.214 1.00134.63 C
ANISOU 37 C4C HEC D1001 25826 16356 8971 -3798 2515 1081 C
HETATM 38 C4D HEC D1001 13.570 10.218 11.849 1.00138.72 C
ANISOU 38 C4D HEC D1001 26232 16533 9944 -3858 2317 1280 C
HETATM 39 CAA HEC D1001 12.769 9.532 7.451 1.00132.04 C
ANISOU 39 CAA HEC D1001 25171 15378 9621 -3893 2385 1376 C
HETATM 40 CAB HEC D1001 6.719 15.866 12.240 1.00138.71 C
ANISOU 40 CAB HEC D1001 26042 16858 9803 -3757 3079 901 C
HETATM 41 CAC HEC D1001 12.297 13.190 17.738 1.00135.76 C
ANISOU 41 CAC HEC D1001 26101 16686 8794 -3768 2488 993 C
HETATM 42 CAD HEC D1001 15.637 8.535 11.925 1.00138.75 C
ANISOU 42 CAD HEC D1001 26295 16445 9980 -3888 2089 1394 C
HETATM 43 CBA HEC D1001 11.998 8.251 7.139 1.00132.66 C
ANISOU 43 CBA HEC D1001 25237 15456 9711 -3938 2416 1524 C
HETATM 44 CBB HEC D1001 5.650 15.212 13.142 1.00135.28 C
ANISOU 44 CBB HEC D1001 25642 16531 9227 -3784 3158 997 C
HETATM 45 CBC HEC D1001 11.427 12.956 18.987 1.00146.99 C
ANISOU 45 CBC HEC D1001 27580 18242 10026 -3778 2561 1040 C
HETATM 46 CBD HEC D1001 14.919 7.222 11.642 1.00139.54 C
ANISOU 46 CBD HEC D1001 26386 16545 10089 -3933 2120 1549 C
HETATM 47 CGA HEC D1001 12.527 7.624 5.875 1.00128.84 C
ANISOU 47 CGA HEC D1001 24714 14851 9389 -3953 2359 1570 C
HETATM 48 CGD HEC D1001 15.891 6.207 11.098 1.00141.03 C
ANISOU 48 CGD HEC D1001 26575 16642 10368 -3955 2011 1625 C
HETATM 49 CHA HEC D1001 13.299 10.063 10.513 1.00146.02 C
ANISOU 49 CHA HEC D1001 27088 17363 11029 -3868 2342 1305 C
HETATM 50 CHB HEC D1001 9.227 12.490 9.500 1.00144.37 C
ANISOU 50 CHB HEC D1001 26723 17255 10876 -3837 2764 1179 C
HETATM 51 CHC HEC D1001 9.083 14.384 13.975 1.00144.74 C
ANISOU 51 CHC HEC D1001 26964 17660 10370 -3774 2826 976 C
HETATM 52 CHD HEC D1001 12.978 11.644 15.133 1.00137.25 C
ANISOU 52 CHD HEC D1001 26183 16634 9330 -3815 2394 1143 C
HETATM 53 CMA HEC D1001 10.090 11.136 6.782 1.00134.85 C
ANISOU 53 CMA HEC D1001 25424 15802 10009 -3872 2656 1294 C
HETATM 54 CMB HEC D1001 6.909 14.580 9.402 1.00138.00 C
ANISOU 54 CMB HEC D1001 25835 16541 10059 -3798 3022 1038 C
HETATM 55 CMC HEC D1001 9.714 15.017 17.030 1.00140.17 C
ANISOU 55 CMC HEC D1001 26549 17298 9410 -3741 2781 878 C
HETATM 56 CMD HEC D1001 15.472 9.587 15.143 1.00143.64 C
ANISOU 56 CMD HEC D1001 27061 17330 10186 -3851 2112 1287 C
HETATM 57 NA HEC D1001 11.246 11.403 10.381 1.00142.02 N
ANISOU 57 NA HEC D1001 26521 16938 10501 -3848 2558 1228 N
HETATM 58 NC HEC D1001 11.031 12.874 14.214 1.00135.40 N
ANISOU 58 NC HEC D1001 25852 16413 9183 -3799 2607 1074 N
HETATM 59 O1A HEC D1001 13.768 7.499 5.723 1.00127.91 O
ANISOU 59 O1A HEC D1001 24612 14669 9319 -3944 2254 1548 O
HETATM 60 O1D HEC D1001 15.705 5.000 11.405 1.00143.73 O
ANISOU 60 O1D HEC D1001 26943 17007 10662 -3991 1995 1754 O
HETATM 61 O2A HEC D1001 11.708 7.243 5.000 1.00126.20 O
ANISOU 61 O2A HEC D1001 24330 14482 9138 -3973 2418 1629 O
HETATM 62 O2D HEC D1001 16.850 6.595 10.375 1.00138.38 O
ANISOU 62 O2D HEC D1001 26214 16212 10153 -3936 1943 1558 O
HETATM 63 FE HEC D1001 11.115 12.157 12.415 1.00158.39 Fe
ANISOU 63 FE HEC D1001 28683 19178 12321 -3824 2585 1151 Fe
HETATM 64 HAB HEC D1001 6.266 16.109 11.430 1.00166.61 H
HETATM 65 HAC HEC D1001 13.016 12.556 17.688 1.00163.06 H
HETATM 66 HHA HEC D1001 13.931 9.523 9.993 1.00175.38 H
HETATM 67 HHB HEC D1001 8.617 12.507 8.733 1.00173.40 H
HETATM 68 HHC HEC D1001 8.518 15.025 14.454 1.00173.84 H
HETATM 69 HHD HEC D1001 13.462 11.479 15.969 1.00164.85 H
HETATM 70 HAA1 HEC D1001 13.619 9.309 7.860 1.00158.61 H
HETATM 71 HAA2 HEC D1001 12.922 10.028 6.632 1.00158.61 H
HETATM 72 HAD1 HEC D1001 16.364 8.380 12.549 1.00166.66 H
HETATM 73 HAD2 HEC D1001 15.991 8.897 11.097 1.00166.66 H
HETATM 74 HBA1 HEC D1001 11.058 8.462 7.024 1.00159.35 H
HETATM 75 HBA2 HEC D1001 12.100 7.627 7.874 1.00159.35 H
HETATM 76 HBB1 HEC D1001 5.203 14.504 12.651 1.00162.49 H
HETATM 77 HBB2 HEC D1001 5.000 15.880 13.409 1.00162.49 H
HETATM 78 HBB3 HEC D1001 6.076 14.841 13.930 1.00162.49 H
HETATM 79 HBC1 HEC D1001 11.697 12.130 19.419 1.00176.54 H
HETATM 80 HBC2 HEC D1001 10.495 12.894 18.725 1.00176.54 H
HETATM 81 HBC3 HEC D1001 11.541 13.696 19.603 1.00176.54 H
HETATM 82 HBD1 HEC D1001 14.216 7.374 10.991 1.00167.61 H
HETATM 83 HBD2 HEC D1001 14.529 6.885 12.463 1.00167.61 H
HETATM 84 HMA1 HEC D1001 9.181 10.779 6.867 1.00161.97 H
HETATM 85 HMA2 HEC D1001 10.588 10.607 6.123 1.00161.97 H
HETATM 86 HMA3 HEC D1001 10.048 12.069 6.487 1.00161.97 H
HETATM 87 HMB1 HEC D1001 7.003 15.525 9.208 1.00165.76 H
HETATM 88 HMB2 HEC D1001 5.981 14.382 9.604 1.00165.76 H
HETATM 89 HMB3 HEC D1001 7.190 14.061 8.632 1.00165.76 H
HETATM 90 HMC1 HEC D1001 9.327 14.535 17.777 1.00168.36 H
HETATM 91 HMC2 HEC D1001 9.010 15.463 16.534 1.00168.36 H
HETATM 92 HMC3 HEC D1001 10.343 15.677 17.362 1.00168.36 H
HETATM 93 HMD1 HEC D1001 16.399 9.817 14.922 1.00172.53 H
HETATM 94 HMD2 HEC D1001 15.399 8.618 15.274 1.00172.53 H
HETATM 95 HMD3 HEC D1001 15.209 10.048 15.966 1.00172.53 H
TER
END
"""
edits = """
geometry_restraints.edits {
bond {
atom_selection_1 = chain D and resseq 40 and name SG
atom_selection_2 = chain D and resseq 1001 and name CAC
distance_ideal = 1.81
sigma = 0.05
}
bond {
atom_selection_1 = chain D and resseq 37 and name SG
atom_selection_2 = chain D and resseq 1001 and name CAB
distance_ideal = 1.81
sigma = 0.05
}
angle {
atom_selection_1 = chain D and resseq 40 and name SG
atom_selection_2 = chain D and resseq 1001 and name CAC
atom_selection_3 = chain D and resseq 1001 and name CBC
angle_ideal = 109
sigma = 2
}
angle {
atom_selection_1 = chain D and resseq 40 and name SG
atom_selection_2 = chain D and resseq 1001 and name CAC
atom_selection_3 = chain D and resseq 1001 and name C3C
angle_ideal = 109
sigma = 2
}
angle {
atom_selection_1 = chain D and resseq 37 and name SG
atom_selection_2 = chain D and resseq 1001 and name CAB
atom_selection_3 = chain D and resseq 1001 and name CBB
angle_ideal = 109
sigma = 2
}
angle {
atom_selection_1 = chain D and resseq 1001 and name HAB
atom_selection_2 = chain D and resseq 1001 and name CAB
atom_selection_3 = chain D and resseq 37 and name SG
angle_ideal = 109
sigma = 1.1
}
angle {
atom_selection_1 = chain D and resseq 1001 and name HAC
atom_selection_2 = chain D and resseq 1001 and name CAC
atom_selection_3 = chain D and resseq 40 and name SG
angle_ideal = 109
sigma = 1.1
}
}
"""
gm_phil = iotbx.phil.parse(input_string=grand_master_phil_str,
process_includes=True)
edits_phil = iotbx.phil.parse(edits)
working_phil = gm_phil.fetch(edits_phil)
params = working_phil.extract()
# Make sure the angle edit is present
assert (params.geometry_restraints.edits.angle[3].atom_selection_1 == \
"chain D and resseq 1001 and name HAB")
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
model = mmtbx.model.manager(model_input=pdb_inp,
build_grm=True,
pdb_interpretation_params=params)
pdb_hierarchy = model.get_hierarchy()
sites_cart = model.get_sites_cart()
atoms = pdb_hierarchy.atoms()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
h_para = riding_h_manager.h_parameterization
diagnostics = riding_h_manager.diagnostics(sites_cart=sites_cart,
threshold=0.05)
h_distances = diagnostics.h_distances
type_list = diagnostics.type_list
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_para) - h_para.count(None)
for rc in h_para:
if rc:
assert (rc.ih != 63), 'Wrong atom not recognized.'
# Test if number of paramterized H atoms is correct
assert (number_h == number_h_para + 1), 'Not all H atoms are parameterized'
type_list_known = [
'alg1b', '3neigbs', '2tetra', '2tetra', 'alg1b', '3neigbs', '2tetra',
'2tetra', '3neigbs', 'flat_2neigbs', 'flat_2neigbs', 'flat_2neigbs',
'flat_2neigbs', '2tetra', '2tetra', '2tetra', '2tetra', '2tetra',
'2tetra', 'prop', 'prop', 'prop', 'prop', 'prop', 'prop', '2tetra',
'2tetra', 'prop', 'prop', 'prop', 'prop', 'prop', 'prop', 'prop',
'prop', 'prop', 'prop', 'prop', 'prop'
]
for ih in h_distances:
# One H atom is expected to be far (HAC)
if (ih == 64):
continue
labels = atoms[ih].fetch_labels()
if (h_distances[ih] > 0.1):
assert (h_distances[ih] < 0.1), \
'distance too large: %s atom: %s (%s) residue: %s ' \
% (h_para[ih].htype, atoms[ih].name, ih, labels.resseq.strip())
#
for type1, type2 in zip(type_list, type_list_known):
assert (type1 == type2)
def exercise2():
pdb_str = """
CRYST1 16.660 12.742 18.240 90.00 90.00 90.00 P 1
SCALE1 0.060024 0.000000 0.000000 0.00000
SCALE2 0.000000 0.078481 0.000000 0.00000
SCALE3 0.000000 0.000000 0.054825 0.00000
ATOM 1 N TYR A 7 9.837 5.000 6.625 1.00 15.00 N
ATOM 2 CA TYR A 7 10.084 6.426 6.798 1.00 15.00 C
ATOM 3 C TYR A 7 11.431 6.813 6.197 1.00 15.00 C
ATOM 4 O TYR A 7 11.660 6.642 5.000 1.00 15.00 O
ATOM 5 CB TYR A 7 10.042 6.803 8.281 1.00 15.00 C
ATOM 6 CG TYR A 7 8.697 6.593 8.948 1.00 15.00 C
ATOM 7 CD1 TYR A 7 7.540 6.413 8.198 1.00 15.00 C
ATOM 8 CD2 TYR A 7 8.586 6.575 10.332 1.00 15.00 C
ATOM 9 CE1 TYR A 7 6.315 6.222 8.807 1.00 15.00 C
ATOM 10 CE2 TYR A 7 7.364 6.384 10.950 1.00 15.00 C
ATOM 11 CZ TYR A 7 6.233 6.208 10.183 1.00 15.00 C
ATOM 12 OH TYR A 7 5.015 6.018 10.794 1.00 15.00 O
ATOM 13 HA TYR A 7 9.398 6.930 6.331 1.00 15.00 H
ATOM 14 HB2 TYR A 7 10.693 6.264 8.757 1.00 15.00 H
ATOM 15 HB3 TYR A 7 10.270 7.742 8.369 1.00 15.00 H
ATOM 16 HD1 TYR A 7 7.589 6.422 7.269 1.00 15.00 H
ATOM 17 HD2 TYR A 7 9.347 6.694 10.853 1.00 15.00 H
ATOM 18 HE1 TYR A 7 5.550 6.103 8.292 1.00 15.00 H
ATOM 19 HE2 TYR A 7 7.306 6.375 11.878 1.00 15.00 H
ATOM 20 HH TYR A 7 5.000 6.415 11.534 1.00 15.00 H
TER
HETATM 21 O HOH B 1 5.307 7.545 13.240 1.00 30.00 O
TER
END
"""
edits = """
geometry_restraints.edits {
bond {
atom_selection_1 = chain A and resseq 7 and name HH
atom_selection_2 = chain B and resseq 1 and name O
distance_ideal = 1.81
sigma = 0.05
}
}
"""
type_list_known = [
'3neigbs', '2tetra', '2tetra', 'flat_2neigbs', 'flat_2neigbs',
'flat_2neigbs', 'flat_2neigbs', 'alg1b'
]
gm_phil = iotbx.phil.parse(input_string=grand_master_phil_str,
process_includes=True)
edits_phil = iotbx.phil.parse(edits)
working_phil = gm_phil.fetch(edits_phil)
params = working_phil.extract()
# Make sure the angle edit is present
assert (params.geometry_restraints.edits.bond[0].atom_selection_1 == \
"chain A and resseq 7 and name HH")
pdb_inp = iotbx.pdb.input(lines=pdb_str.split("\n"), source_info=None)
model = mmtbx.model.manager(model_input=pdb_inp,
build_grm=True,
pdb_interpretation_params=params)
pdb_hierarchy = model.get_hierarchy()
sites_cart = model.get_sites_cart()
atoms = pdb_hierarchy.atoms()
model.setup_riding_h_manager()
riding_h_manager = model.get_riding_h_manager()
h_para = riding_h_manager.h_parameterization
diagnostics = riding_h_manager.diagnostics(sites_cart=sites_cart,
threshold=0.05)
h_distances = diagnostics.h_distances
type_list = diagnostics.type_list
number_h = model.get_hd_selection().count(True)
number_h_para = len(h_para) - h_para.count(None)
connectivity_manager = connectivity.determine_connectivity(
pdb_hierarchy=pdb_hierarchy,
geometry_restraints=model.get_restraints_manager().geometry)
double_H = connectivity_manager.double_H
# Test if number of paramterized H atoms is correct
assert (number_h == number_h_para), 'Not all H atoms are parameterized'
assert (double_H[19] == [11,
20]), 'H bound to two atoms wrongly recognized'
assert (number_h_para == 8), 'Not all H atoms are parameterized'
for ih in h_distances:
labels = atoms[ih].fetch_labels()
if (h_distances[ih] > 0.1):
assert (h_distances[ih] < 0.1), \
'distance too large: %s atom: %s (%s) residue: %s ' \
% (h_para[ih].htype, atoms[ih].name, ih, labels.resseq.strip())
for type1, type2 in zip(type_list, type_list_known):
assert (type1 == type2)
