mean_designed_protein_length = 0
designed_protein_lengths = []
for method in methods:
for protein in PDBS:
designed_length = [0]
pdb_id = protein[0:4].upper()
chain_id = protein[4]
file = pdb_id + "_" + chain_id + "_Aligned_Sequences.fasta"
fileparts = re.split("_",file)
print "Processsing file: " + file
print "PDB: " + pdb_id
print "CHAIN: " + chain_id
searchPDB = pdb_id + "_" + chain_id + ".pdb" #This is the pdb file that is parsered by dssp
pdbLocation = duncan_structure_path + searchPDB #This is the location of the pdb file
natural_sequences = af.get_natural_sequences_duncan(file) #Gets a list with the natural sequences
ancestor = natural_sequences[0] #Gets the "ancestral sequence"
ancestor_length = len(ancestor) #Grab the length of the ancestral sequence
#print "Ancestor Length: " + str(ancestor_length)
counter = 0
gaps = 0
gap_locations = []
#Counts the gaps within the ancestral sequence in the alignment. We must take the gaps out before counting the amino acids
while (counter < ancestor_length):
acid = ancestor[counter]
if acid == '-':
gaps = gaps + 1
gap_locations.append(counter) #This is an array that tracks which residues have gaps
counter = counter + 1
duncan_designed_sequence_path = "/Users/qian/Desktop/max_score_evol_sim/sequences/designed_sequences/"
duncan_natural_sequence_path = "/Users/qian/Desktop/max_score_evol_sim/sequences/aligned_sequences/"
duncan_structure_path = "/Users/qian/Desktop/max_score_evol_sim/structures/"
for protein in PDBS:
pdb_id = protein[0:4].upper()
chain_id = protein[4]
file = pdb_id + "_" + chain_id + "_Aligned_Sequences.fasta"
fileparts = re.split("_", file)
print "Processsing file: " + file
print "PDB: " + pdb_id
print "CHAIN: " + chain_id
searchPDB = pdb_id + "_" + chain_id + ".pdb" #This is the pdb file that is parsered by dssp
pdbLocation = duncan_structure_path + searchPDB #This is the location of the pdb file that dssp will be parsing.
natural_sequences = af.get_natural_sequences_duncan(
file) #Gets the natural sequences
ancestor = natural_sequences[0]
ancestor_length = len(ancestor) #Grab the length of the ancestral sequence
#print "Ancestor Length: " + str(ancestor_length)
counter = 0
gaps = 0
gap_locations = []
#Counts the gaps within the ancestral sequence in the alignment. We must take the gaps out before counting the amino acids
while (counter < ancestor_length):
acid = ancestor[counter]
if acid == '-':
gaps = gaps + 1
gap_locations.append(
counter
) #This is an array that tracks which residues have gaps
duncan_designed_sequence_path = "/Users/Eleisha/Documents/Wilke_Lab/Project_1/project/sequences/duncan_sequences/designed_sequences/"
duncan_natural_sequence_path = "/Users/Eleisha/Documents/Wilke_Lab/Project_1/project/sequences/duncan_sequences/aligned_sequences/"
duncan_structure_path = "/Users/Eleisha/Documents/Wilke_Lab/Project_1/project/structures/duncan_structures/"
for protein in PDBS:
pdb_id = protein[0:4].upper()
chain_id = protein[4]
file = pdb_id + "_" + chain_id + "_Aligned_Sequences.fasta"
fileparts = re.split("_",file)
print "Processsing file: " + file
print "PDB: " + pdb_id
print "CHAIN: " + chain_id
searchPDB = pdb_id + "_" + chain_id + ".pdb" #This is the pdb file that is parsered by dssp
pdbLocation = duncan_structure_path + searchPDB #This is the location of the pdb file that dssp will be parsing.
natural_sequences = af.get_natural_sequences_duncan(file) #Gets the natural sequences
ancestor = natural_sequences[0]
ancestor_length = len(ancestor) #Grab the length of the ancestral sequence
#print "Ancestor Length: " + str(ancestor_length)
counter = 0
gaps = 0
gap_locations = []
#Counts the gaps within the ancestral sequence in the alignment. We must take the gaps out before counting the amino acids
while (counter < ancestor_length):
acid = ancestor[counter]
if acid == '-':
gaps = gaps + 1
gap_locations.append(counter) #This is an array that tracks which residues have gaps
counter = counter + 1
duncan_natural_sequence_path = "/Users/Eleisha/Documents/Wilke_Lab/Project_1/project/sequences/duncan_sequences/aligned_sequences/"
duncan_structure_path = "/Users/Eleisha/Documents/Wilke_Lab/Project_1/project/structures/duncan_structures/"
for protein in PDBS:
pdb_id = protein[0:4].upper()
chain_id = protein[4]
file = pdb_id + "_" + chain_id + "_Aligned_Sequences.fasta"
fileparts = re.split("_",file)
print "Processsing file: " + file
print "PDB: " + pdb_id
print "CHAIN: " + chain_id
searchPDB = pdb_id + "_" + chain_id + ".pdb" #This is the pdb file that is parsered by dssp
pdbLocation = duncan_structure_path + searchPDB #This is the location of the pdb file that dssp will be parsing.
natural_sequences = af.get_natural_sequences_duncan(file) #Splits alignments into designed and natural alignment files
ancestor = natural_sequences[0]
ancestor_length = len(ancestor) #Grab the length of the ancestral sequence
print "Ancestor Length: " + str(ancestor_length)
print "Length of Alignment: " + str(len(natural_sequences))
counter = 0
gaps = 0
gap_locations = []
#Counts the gaps within the ancestral sequence in the alignment. We must take the gaps out before counting the amino acids
while (counter < ancestor_length):
acid = ancestor[counter]
if acid == '-':
gaps = gaps + 1
gap_locations.append(counter) #This is an array that tracks which residues have gaps
counter = counter + 1
mean_designed_protein_length = 0
designed_protein_lengths = []
for temp in temps:
for protein in PDBS:
designed_length = [0]
pdb_id = protein[0:4].upper()
chain_id = protein[4]
file = pdb_id + "_" + chain_id + "_Aligned_Sequences.fasta"
fileparts = re.split("_",file)
print "Processsing file: " + file
print "PDB: " + pdb_id
print "CHAIN: " + chain_id
searchPDB = pdb_id + "_" + chain_id + ".pdb" #This is the pdb file that is parsered by dssp
pdbLocation = duncan_structure_path + searchPDB #This is the location of the pdb file
natural_sequences = af.get_natural_sequences_duncan(file) #Gets a list with the natural sequences
ancestor = natural_sequences[0] #Gets the "ancestral sequence"
ancestor_length = len(ancestor) #Grab the length of the ancestral sequence
#print "Ancestor Length: " + str(ancestor_length)
counter = 0
gaps = 0
gap_locations = []
#Counts the gaps within the ancestral sequence in the alignment. We must take the gaps out before counting the amino acids
while (counter < ancestor_length):
acid = ancestor[counter]
if acid == '-':
gaps = gaps + 1
gap_locations.append(counter) #This is an array that tracks which residues have gaps
counter = counter + 1
