def test_get_data_from_3zt9_via_AddSequenceToMmcif_get_best_match(self):
self.test_files.one_sequence()
expected_result = self.test_files.sample_seq['pdb|3zt9|A']
entity_dict = self.test_files.observed_seq
mm = AddSequenceToMmcif(input_mmcif=self.test_files.cif,
output_mmcif='output.cif',
fasta_file=self.test_files.fasta)
mm.process_input_sequences()
best_seq, best_score = mm.get_best_match(
mmcif_sequence=entity_dict['1']['sequence'])
self.assertTrue(best_seq == expected_result)
self.assertTrue(best_score > 0)
def test_missing_fasta_file(self):
mm = AddSequenceToMmcif(input_mmcif='input.cif',
output_mmcif='output.cif',
fasta_file='missing_file.fasta')
data = mm.process_input_sequences()
self.assertEqual(data, dict())
self.assertTrue(len(data.keys()) == 0)
def test_invalid_fasta_file(self):
mm = AddSequenceToMmcif(
input_mmcif='input.cif',
output_mmcif='output.cif',
fasta_file=self.test_files.TEST_INVALID_FASTA_ONE_SEQUENCE)
data = mm.process_input_sequences()
self.assertEqual(data, dict())
self.assertTrue(len(data.keys()) == 0)
def test_process_fasta_five_chains(self):
self.test_files.five_sequences()
expected_result = self.test_files.sample_seq
mm = AddSequenceToMmcif(input_mmcif='input.cif',
output_mmcif='output.cif',
fasta_file=self.test_files.fasta)
data = mm.process_input_sequences()
self.assertTrue(len(data.keys()) == 5)
for key in data:
self.assertTrue(key in expected_result)
self.assertTrue(data[key] == expected_result[key])
def test_process_sequence_two_chains(self):
sequence = 'MEKLEVGIYTRAREGEIACGDACLVKRVEGVIFLAVGDGIGHGPEAARAAEIAIASMESSMNTGLVNIFQLCHRELRGTRGAVAALCRVDRRQGLWQAAIVGNIHVKILSAKGIITPLATPGILGYNYPHQLLIAKGSYQEGDLFLIHSDGIQEGAVPLALLANYRLTAEELVRLIGEKYGRRDDDVAVIVAR'
chains = 'A,B'
mm = AddSequenceToMmcif(input_mmcif='input.cif',
output_mmcif='output.cif',
input_chainids=chains,
input_sequence=sequence)
data = mm.process_input_sequences()
self.assertTrue(len(data.keys()) == 2)
for key in data:
self.assertTrue(key in chains.split(','))
self.assertTrue(data[key] == sequence)