def align_chain(self, i):
import mmtbx.alignment
chain = self.chains[i]
best_alignment = None
best_sequence = None
best_seq_id = None
best_identity = self.minimum_identity
best_width = sys.maxsize
best_length = sys.maxsize
for i_seq, seq_object in enumerate(self.sequences):
alignment = mmtbx.alignment.align(
seq_a=chain.sequence,
seq_b=seq_object.sequence).extract_alignment()
identity = alignment.calculate_sequence_identity(skip_chars=['X'])
# if the identities of two alignments are equal, then we prefer the
# alignment that has the narrowest range for the match and the
# shortest sequence
width = alignment.match_codes.rfind('m') - alignment.match_codes.find('m')
length = len(seq_object.sequence)
if ((identity > best_identity) or
(approx_equal_core(identity, best_identity, 1.e-6, 1.e10, None, "")
and width <= best_width and length < best_length)):
best_identity = identity
best_alignment = alignment
best_sequence = seq_object.name
best_seq_id = i_seq
best_width = width
best_length = length
return best_alignment, best_sequence, best_seq_id
def find_similar_chains (pdb_hierarchy,
sequence,
source_info=None,
first_chain_only=False,
remove_alt_confs=True,
reset_chain_id=None,
min_identity=0.95,
min_identity_epsilon=0.02,
log=null_out()) :
"""
Find all chains with at least the specified fractional sequence identity to
the target, and extract as related_chain objects with new pdb hierarchies.
"""
import mmtbx.alignment
import iotbx.pdb.hierarchy
results = []
for chain in pdb_hierarchy.only_model().chains() :
if (chain.is_protein()) :
chain_seq = chain.as_padded_sequence(pad=True,
substitute_unknown='X',
pad_at_start=False)
alignment = mmtbx.alignment.align(
seq_a=chain_seq,
seq_b=sequence).extract_alignment()
identity = alignment.calculate_sequence_identity(skip_chars=['X'])
if (identity >= min_identity - min_identity_epsilon) :
root = iotbx.pdb.hierarchy.root()
model = iotbx.pdb.hierarchy.model()
root.append_model(model)
chain_id = chain.id
if (reset_chain_id is not None) :
chain_id = reset_chain_id
new_chain = iotbx.pdb.hierarchy.chain(id=chain_id)
model.append_chain(new_chain)
for residue_group in chain.residue_groups() :
atom_groups = residue_group.atom_groups()
new_rg = iotbx.pdb.hierarchy.residue_group(
resseq=residue_group.resseq,
icode=residue_group.icode)
for k, atom_group in enumerate(atom_groups) :
if ((remove_alt_confs) and
((k > 0) or (not atom_group.altloc.strip() in ['','A']))) :
continue
new_rg.append_atom_group(atom_group.detached_copy())
new_chain.append_residue_group(new_rg)
xrs = root.extract_xray_structure()
xrs.convert_to_isotropic()
root.atoms().set_adps_from_scatterers(xrs.scatterers(),
xrs.unit_cell())
results.append(
related_chain(
source_info=source_info,
chain_id=chain.id,
pdb_hierarchy=root,
identity=identity))
if (first_chain_only) : break
return results
def find_similar_chains(pdb_hierarchy,
sequence,
source_info=None,
first_chain_only=False,
remove_alt_confs=True,
reset_chain_id=None,
min_identity=0.95,
min_identity_epsilon=0.02,
log=null_out()):
"""
Find all chains with at least the specified fractional sequence identity to
the target, and extract as related_chain objects with new pdb hierarchies.
"""
import mmtbx.alignment
import iotbx.pdb.hierarchy
results = []
for chain in pdb_hierarchy.only_model().chains():
if (chain.is_protein()):
chain_seq = chain.as_padded_sequence(pad=True,
substitute_unknown='X',
pad_at_start=False)
alignment = mmtbx.alignment.align(
seq_a=chain_seq,
seq_b=sequence).extract_alignment()
identity = alignment.calculate_sequence_identity(skip_chars=['X'])
if (identity >= min_identity - min_identity_epsilon):
root = iotbx.pdb.hierarchy.root()
model = iotbx.pdb.hierarchy.model()
root.append_model(model)
chain_id = chain.id
if (reset_chain_id is not None):
chain_id = reset_chain_id
new_chain = iotbx.pdb.hierarchy.chain(id=chain_id)
model.append_chain(new_chain)
for residue_group in chain.residue_groups():
atom_groups = residue_group.atom_groups()
new_rg = iotbx.pdb.hierarchy.residue_group(
resseq=residue_group.resseq,
icode=residue_group.icode)
for k, atom_group in enumerate(atom_groups):
if ((remove_alt_confs) and
((k > 0) or (not atom_group.altloc.strip() in ['','A']))):
continue
new_rg.append_atom_group(atom_group.detached_copy())
new_chain.append_residue_group(new_rg)
xrs = root.extract_xray_structure()
xrs.convert_to_isotropic()
root.atoms().set_adps_from_scatterers(xrs.scatterers(),
xrs.unit_cell())
results.append(
related_chain(
source_info=source_info,
chain_id=chain.id,
pdb_hierarchy=root,
identity=identity))
if (first_chain_only) : break
return results
def align_chain (self, i) :
import mmtbx.alignment
chain = self.chains[i]
best_alignment = None
best_sequence = None
best_seq_id = None
best_identity = self.minimum_identity
best_width = sys.maxint
for i_seq, seq_object in enumerate(self.sequences) :
alignment = mmtbx.alignment.align(
seq_a=chain.sequence,
seq_b=seq_object.sequence).extract_alignment()
identity = alignment.calculate_sequence_identity(skip_chars=['X'])
# if the identities of two alignments are equal, then we prefer the
# alignment that has the narrowest range for the match
width = alignment.match_codes.rfind('m') - alignment.match_codes.find('m')
if ((identity > best_identity) or
(identity == best_identity and width < best_width)):
best_identity = identity
best_alignment = alignment
best_sequence = seq_object.name
best_seq_id = i_seq
best_width = width
return best_alignment, best_sequence, best_seq_id
