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# This code is part of the Biopython distribution and governed by its
# license. Please see the LICENSE file that should have been included
# as part of this package.
"""Several routines used to extract information from FSSP sections.
filter: filters a passed summary section and alignment section according to a numeric
attribute in the summary section. Returns new summary and alignment sections
For example, to filter in only those records which have a zscore greater than
4.0 and lesser than 7.5:
new_sum, new_align = filter(sum, align, 'zscore', 4, 7.5)
"""
from Bio import FSSP
import copy
from Bio.Align import MultipleSeqAlignment
from Bio import Alphabet
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
class FSSPAlign(MultipleSeqAlignment):
def _add_numbering_table(self, new_record):
new_record.annotations['abs2pdb'] = {}
new_record.annotations['pdb2abs'] = {}
class FSSPMultAlign(dict):
def __init__(self):
self.abs_res = []
self.pdb_res = []
self.data = {}
def mult_align(sum_dict, align_dict):
"""Returns a biopython multiple alignment instance (MultipleSeqAlignment)"""
mult_align_dict = {}
for j in align_dict.abs(1).pos_align_dict:
mult_align_dict[j] = ''
for i in range(1, len(align_dict) + 1):
# loop on positions
for j in align_dict.abs(i).pos_align_dict:
# loop within a position
mult_align_dict[j] += align_dict.abs(i).pos_align_dict[j].aa
alpha = Alphabet.Gapped(Alphabet.IUPAC.extended_protein)
fssp_align = MultipleSeqAlignment([], alphabet=alpha)
for i in sorted(mult_align_dict):
fssp_align.append(SeqRecord(Seq(mult_align_dict[i], alpha),
sum_dict[i].pdb2 + sum_dict[i].chain2))
return fssp_align
#
# Warning: this function really slows down when filtering large FSSP files.
# The reason is the use of copy.deepcopy() to copy align_dict into
# new_align_dict. I have to figure out something better.
# Took me ~160 seconds for the largest FSSP file (1reqA.fssp)
#
def filter(sum_dict, align_dict, filter_attribute, low_bound, high_bound):
"""Filters a passed summary section and alignment section according to a numeric
attribute in the summary section. Returns new summary and alignment sections"""
new_sum_dict = FSSP.FSSPSumDict()
new_align_dict = copy.deepcopy(align_dict)
# for i in align_dict:
# new_align_dict[i] = copy.copy(align_dict[i])
# new_align_dict = copy.copy(align_dict)
for prot_num in sum_dict:
attr_value = getattr(sum_dict[prot_num], filter_attribute)
if attr_value >= low_bound and attr_value <= high_bound:
new_sum_dict[prot_num] = sum_dict[prot_num]
prot_numbers = sorted(new_sum_dict)
for pos_num in new_align_dict.abs_res_dict:
new_align_dict.abs(pos_num).pos_align_dict = {}
for prot_num in prot_numbers:
new_align_dict.abs(pos_num).pos_align_dict[prot_num] = \
align_dict.abs(pos_num).pos_align_dict[prot_num]
return new_sum_dict, new_align_dict
def name_filter(sum_dict, align_dict, name_list):
"""Accepts a list of names. Returns a new Summary block and Alignment block which
contain the info only for those names passed."""
new_sum_dict = FSSP.FSSPSumDict()
new_align_dict = copy.deepcopy(align_dict)
for cur_pdb_name in name_list:
for prot_num in sum_dict:
if sum_dict[prot_num].pdb2 + sum_dict[prot_num].chain2 == cur_pdb_name:
new_sum_dict[prot_num] = sum_dict[prot_num]
prot_numbers = sorted(new_sum_dict)
for pos_num in new_align_dict.abs_res_dict:
new_align_dict.abs(pos_num).pos_align_dict = {}
for prot_num in prot_numbers:
new_align_dict.abs(pos_num).pos_align_dict[prot_num] = \
align_dict.abs(pos_num).pos_align_dict[prot_num]
return new_sum_dict, new_align_dict
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