def pperp_outliers(hierarchy, chain):
kin_out = "@vectorlist {ext} color= magenta master= {base-P perp}\n"
rv = rna_validate.rna_puckers(pdb_hierarchy=hierarchy)
outliers = rv.results
params = rna_sugar_pucker_analysis.master_phil.extract()
outlier_key_list = []
for outlier in outliers:
outlier_key_list.append(outlier.id_str())
for conformer in chain.conformers():
for residue in conformer.residues():
if common_residue_names_get_class(
residue.resname) != "common_rna_dna":
continue
ra1 = residue_analysis(
residue_atoms=residue.atoms(),
distance_tolerance=params.bond_detection_distance_tolerance)
if (ra1.problems is not None): continue
if (not ra1.is_rna): continue
try:
key = residue.find_atom_by(name=" C1'").pdb_label_columns()[4:]
except Exception:
continue
if key in outlier_key_list:
if rv.pucker_perp_xyz[key][0] is not None:
perp_xyz = rv.pucker_perp_xyz[key][0] #p_perp_xyz
else:
perp_xyz = rv.pucker_perp_xyz[key][1] #o3p_perp_xyz
if rv.pucker_dist[key][0] is not None:
perp_dist = rv.pucker_dist[key][0]
if perp_dist < 2.9:
pucker_text = " 2'?"
else:
pucker_text = " 3'?"
else:
perp_dist = rv.pucker_dist[key][1]
if perp_dist < 2.4:
pucker_text = " 2'?"
else:
pucker_text = " 3'?"
key = key[0:4].lower() + key[4:]
key += pucker_text
kin_out += kin_vec(key, perp_xyz[0], key, perp_xyz[1])
a = matrix.col(perp_xyz[1])
b = matrix.col(residue.find_atom_by(name=" C1'").xyz)
c = (a - b).normalize()
new = a - (c * .8)
kin_out += kin_vec(key, perp_xyz[1], key, tuple(new), 4)
new = a + (c * .4)
kin_out += kin_vec(key, perp_xyz[1], key, tuple(new), 4)
r_vec = matrix.col(perp_xyz[1]) - matrix.col(perp_xyz[0])
r = r_vec.axis_and_angle_as_r3_rotation_matrix(angle=90,
deg=True)
new = r * (new - a) + a
kin_out += kin_vec(key, perp_xyz[1], key, tuple(new), 4)
r = r_vec.axis_and_angle_as_r3_rotation_matrix(angle=180,
deg=True)
new = r * (new - a) + a
kin_out += kin_vec(key, perp_xyz[1], key, tuple(new), 4)
return kin_out
def __init__ (self, pdb_hierarchy, params=None, outliers_only=True) :
if (params is None) :
params = rna_sugar_pucker_analysis.master_phil.extract()
self.pucker_states = []
self.pucker_perp_xyz = {}
self.pucker_dist = {}
rna_geometry.__init__(self)
from iotbx.pdb.rna_dna_detection import residue_analysis
for model in pdb_hierarchy.models():
for chain in model.chains():
for conformer in chain.conformers():
altloc = conformer.altloc
if altloc == "":
altloc = " "
residues = conformer.residues()
for i_residue,residue in enumerate(residues):
def _get_next_residue():
j = i_residue + 1
if (j == len(residues)): return None
return residues[j]
ra1 = residue_analysis(
residue_atoms=residue.atoms(),
distance_tolerance=params.bond_detection_distance_tolerance)
if (ra1.problems is not None): continue
if (not ra1.is_rna): continue
residue_2_p_atom = None
next_pdb_residue = _get_next_residue()
if (next_pdb_residue is not None):
residue_2_p_atom = next_pdb_residue.find_atom_by(name=" P ")
if (get_res_class(residue.resname) != "common_rna_dna") :
continue
ana = rna_sugar_pucker_analysis.evaluate(
params=params,
residue_1_deoxy_ribo_atom_dict=ra1.deoxy_ribo_atom_dict,
residue_1_c1p_outbound_atom=ra1.c1p_outbound_atom,
residue_2_p_atom=residue_2_p_atom)
self.pucker_states.append(ana)
self.n_total += 1
is_outlier = ana.is_delta_outlier or ana.is_epsilon_outlier
if (is_outlier) :
self.n_outliers += 1
if (is_outlier or not outliers_only) :
pucker = rna_pucker(
chain_id=chain.id,
resseq=residue.resseq,
icode=residue.icode,
altloc=conformer.altloc,
resname=residue.resname,
delta_angle=ana.delta,
is_delta_outlier=ana.is_delta_outlier,
epsilon_angle=ana.epsilon,
is_epsilon_outlier=ana.is_epsilon_outlier,
outlier=is_outlier)
self.results.append(pucker)
key = pucker.id_str() #[8:-1]
self.pucker_perp_xyz[key] = [ana.p_perp_xyz, ana.o3p_perp_xyz]
self.pucker_dist[key] = [ana.p_distance_c1p_outbound_line,
ana.o3p_distance_c1p_outbound_line]
def __init__ (self, pdb_hierarchy, params=None, outliers_only=True) :
if (params is None) :
params = rna_sugar_pucker_analysis.master_phil.extract()
self.pucker_states = []
self.pucker_perp_xyz = {}
self.pucker_dist = {}
rna_geometry.__init__(self)
from iotbx.pdb.rna_dna_detection import residue_analysis
for model in pdb_hierarchy.models():
for chain in model.chains():
for conformer in chain.conformers():
altloc = conformer.altloc
if altloc == "":
altloc = " "
residues = conformer.residues()
for i_residue,residue in enumerate(residues):
def _get_next_residue():
j = i_residue + 1
if (j == len(residues)): return None
return residues[j]
ra1 = residue_analysis(
residue_atoms=residue.atoms(),
distance_tolerance=params.bond_detection_distance_tolerance)
if (ra1.problems is not None): continue
if (not ra1.is_rna): continue
residue_2_p_atom = None
next_pdb_residue = _get_next_residue()
if (next_pdb_residue is not None):
residue_2_p_atom = next_pdb_residue.find_atom_by(name=" P ")
if (get_res_class(residue.resname) != "common_rna_dna") :
continue
ana = rna_sugar_pucker_analysis.evaluate(
params=params,
residue_1_deoxy_ribo_atom_dict=ra1.deoxy_ribo_atom_dict,
residue_1_c1p_outbound_atom=ra1.c1p_outbound_atom,
residue_2_p_atom=residue_2_p_atom)
self.pucker_states.append(ana)
self.n_total += 1
is_outlier = ana.is_delta_outlier or ana.is_epsilon_outlier
if (is_outlier) :
self.n_outliers += 1
if (is_outlier or not outliers_only) :
pucker = rna_pucker(
chain_id=chain.id,
resseq=residue.resseq,
icode=residue.icode,
altloc=conformer.altloc,
resname=residue.resname,
delta_angle=ana.delta,
is_delta_outlier=ana.is_delta_outlier,
epsilon_angle=ana.epsilon,
is_epsilon_outlier=ana.is_epsilon_outlier,
outlier=is_outlier)
self.results.append(pucker)
key = pucker.id_str() #[8:-1]
self.pucker_perp_xyz[key] = [ana.p_perp_xyz, ana.o3p_perp_xyz]
self.pucker_dist[key] = [ana.p_distance_c1p_outbound_line,
ana.o3p_distance_c1p_outbound_line]
def pperp_outliers(hierarchy, chain):
kin_out = "@vectorlist {ext} color= magenta master= {base-P perp}\n"
rv = rna_validate.rna_puckers(pdb_hierarchy=hierarchy)
outliers = rv.results
params = rna_sugar_pucker_analysis.master_phil.extract()
outlier_key_list = []
for outlier in outliers:
outlier_key_list.append(outlier.id_str())
for conformer in chain.conformers():
for residue in conformer.residues():
if common_residue_names_get_class(residue.resname) != "common_rna_dna":
continue
ra1 = residue_analysis(
residue_atoms=residue.atoms(),
distance_tolerance=params.bond_detection_distance_tolerance)
if (ra1.problems is not None): continue
if (not ra1.is_rna): continue
try:
key = residue.find_atom_by(name=" C1'").pdb_label_columns()[4:]
except Exception:
continue
if key in outlier_key_list:
if rv.pucker_perp_xyz[key][0] is not None:
perp_xyz = rv.pucker_perp_xyz[key][0] #p_perp_xyz
else:
perp_xyz = rv.pucker_perp_xyz[key][1] #o3p_perp_xyz
if rv.pucker_dist[key][0] is not None:
perp_dist = rv.pucker_dist[key][0]
if perp_dist < 2.9:
pucker_text = " 2'?"
else:
pucker_text = " 3'?"
else:
perp_dist = rv.pucker_dist[key][1]
if perp_dist < 2.4:
pucker_text = " 2'?"
else:
pucker_text = " 3'?"
key = key[0:4].lower()+key[4:]
key += pucker_text
kin_out += kin_vec(key, perp_xyz[0], key, perp_xyz[1])
a = matrix.col(perp_xyz[1])
b = matrix.col(residue.find_atom_by(name=" C1'").xyz)
c = (a-b).normalize()
new = a-(c*.8)
kin_out += kin_vec(key, perp_xyz[1], key, tuple(new), 4)
new = a+(c*.4)
kin_out += kin_vec(key, perp_xyz[1], key, tuple(new), 4)
r_vec = matrix.col(perp_xyz[1]) - matrix.col(perp_xyz[0])
r = r_vec.axis_and_angle_as_r3_rotation_matrix(angle=90, deg=True)
new = r*(new-a)+a
kin_out += kin_vec(key, perp_xyz[1], key, tuple(new), 4)
r = r_vec.axis_and_angle_as_r3_rotation_matrix(angle=180, deg=True)
new = r*(new-a)+a
kin_out += kin_vec(key, perp_xyz[1], key, tuple(new), 4)
return kin_out
