def test1(self):
pdb = self.pdb.filter(ContainsLProteinChain()) \
.flatMap(StructureToPolymerChains()) \
.filter(ContainsLProteinChain())
seq = secondaryStructureExtractor.get_dataset(pdb)
self.assertTrue(seq.count() == 5)
def test1(self):
pdb_1 = self.pdb.filter(ContainsLProteinChain())
results_1 = pdb_1.keys().collect()
self.assertTrue('2ONX' in results_1)
self.assertFalse('1JLP' in results_1)
self.assertTrue('5X6H' in results_1)
self.assertFalse('5L2G' in results_1)
self.assertFalse('2MK1' in results_1)
def test2(self):
pdb_2 = self.pdb.filter(ContainsLProteinChain(exclusive=True))
results_2 = pdb_2.keys().collect()
self.assertTrue('2ONX' in results_2)
self.assertFalse('1JLP' in results_2)
self.assertFalse('5X6H' in results_2)
self.assertFalse('5L2G' in results_2)
self.assertFalse('2MK1' in results_2)
def test3(self):
pdb_3 = self.pdb.flatMap(StructureToPolymerChains())
pdb_3 = pdb_3.filter(ContainsLProteinChain())
results_3 = pdb_3.keys().collect()
self.assertTrue('2ONX.A' in results_3)
self.assertFalse('1JLP.A' in results_3)
self.assertTrue('5X6H.B' in results_3)
self.assertFalse('5L2G.A' in results_3)
self.assertFalse('5L2G.B' in results_3)
self.assertFalse('2MK1.A' in results_3)
# ## Read MMTF Hadoop sequence file and
#
# Create a non-redundant set(<=20% seq. identity) of L-protein chains
# In[3]:
path = "../../resources/mmtf_reduced_sample/"
sequenceIdentity = 20
resolution = 2.0
fraction = 0.1
seed = 123
pdb = mmtfReader.read_sequence_file(
path, sc).flatMap(StructureToPolymerChains()).filter(
Pisces(sequenceIdentity,
resolution)).filter(ContainsLProteinChain()).sample(
False, fraction, seed)
# ## Get content
# In[4]:
segmentLength = 11
data = secondaryStructureSegmentExtractor.get_dataset(pdb,
segmentLength).cache()
print(f"original data : {data.count()}")
# ## Drop Q3 and sequence duplicates
# In[5]:
# ## Read in MMTF Files
# In[3]:
path = "../../resources/mmtf_reduced_sample/"
pdb = mmtfReader.read_sequence_file(path, sc)
# ## Filter proteins that cotinas Dna chain and L protein chain
#
# 1) Retain pdb entires that exclusively contain L-peptide chains
# 2) Retain pdb entries that exclusively contain L-Dna
# In[4]:
structures = pdb.filter(ContainsLProteinChain()).filter(ContainsDnaChain())
# ## Count number of entires
# In[5]:
count = structures.count()
print(f"Number of entires that contain L-protein and L-DNA: {count}")
# ## Visualize Structures
# In[7]:
structure_names = structures.keys().collect()
view_structure(structure_names)
sc = SparkContext(conf=conf)
# ## Read MMTF Hadoop sequence file and
#
# Create a non-redundant set(<=20% seq. identity) of L-protein chains
# In[3]:
path = "../../resources/mmtf_reduced_sample/"
fraction = 0.05
seed = 123
pdb = mmtfReader.read_sequence_file(path, sc).flatMap(
StructureToPolymerChains(False,
True)).filter(ContainsLProteinChain()).sample(
False, fraction, seed)
# ## Extract Element "H" from Secondary Structure
# In[4]:
label = "H"
data = secondaryStructureElementExtractor.get_dataset(pdb, label).cache()
print(f"original data : {data.count()}")
data.show(10, False)
# ## Word2Vec encoded feature Vector
# In[6]:
# ## Read MMTF Hadoop sequence file and
#
# Create a non-redundant set(<=20% seq. identity) of L-protein chains
# In[3]:
path = "../../resources/mmtf_reduced_sample/"
sequenceIdentity = 20
resolution = 2.0
fraction = 0.1
seed = 123
pdb = mmtfReader .read_sequence_file(path, sc) .flatMap(StructureToPolymerChains()) .filter(Pisces(sequenceIdentity, resolution)) .filter(ContainsLProteinChain()) .sample(False, fraction, seed)
# ## Get content
# In[4]:
segmentLength = 11
data = secondaryStructureSegmentExtractor.get_dataset(pdb, segmentLength).cache()
print(f"original data : {data.count()}")
# ## Drop Q3 and sequence duplicates
# In[5]:
"secondaryStructureElementDemo") sc = SparkContext(conf=conf) # ## Download protein (1STP) # # ### Note: Need to use SparkContext as parameter to download Mmtf files # In[12]: pdb = mmtfReader.download_mmtf_files(['1STP'], sc).cache() # ## Map protein to polymer chains and apply LProteinChain filter # In[13]: pdb = pdb.flatMap(StructureToPolymerChains()).filter(ContainsLProteinChain()) # ## Extract secondary structure element 'E' # In[14]: ds = secondaryStructureElementExtractor.get_dataset(pdb, 'E', 6) ds.show(50, False) # ## Terminate Spark # In[15]: sc.stop()
# input parameters
resolution = 2.0
minInteractions = 2
maxInteractions = 4
distanceCutoff = 3.0
bFactorCutoff = 1.645
includeWaters = True
# ## Read PDB and filter by resolution and only include proteins
# In[3]:
pdb = mmtfReader.read_sequence_file(path, sc)
pdb = pdb.filter(Resolution(minResolution=0.0, maxResolution=2.0)).filter(
ContainsLProteinChain(exclusive=True))
# ## Setup criteria for metal interactions
# In[4]:
interactions_filter = InteractionFilter()
interactions_filter.set_distance_cutoff(3.0)
interactions_filter.set_normalized_b_factor_cutoff(1.645)
interactions_filter.set_min_interactions(2)
interactions_filter.set_max_interactions(4)
interactions_filter.set_query_groups(True, ["HOH"])
interactions_filter.set_query_elements(True, "O") # Only use water oxygen
interactions_filter.set_target_elements(True, ["O", "N", "S"])
# ## Exclude "uninteresting" ligands
