def _superimpose_structures(structure, superimpose_reference):
""" Superimpose two structures.
@param structure: Structure to be superimposed.
@type structure: Structure
@param superimpose_reference: Structure to be superimposed.
@type superimpose_reference: Structure
@rtype: Structure
@return: The superimposed structure.
"""
ppb = PPBuilder()
sup = Superimposer()
pp_reference = ppb.build_peptides(superimpose_reference)[0]
pp_structure = ppb.build_peptides(structure)[0]
# CA only
fixed = pp_reference.get_ca_list()
moving = pp_structure.get_ca_list()
moving_all = Selection.unfold_entities(structure, "A")
sup.set_atoms(fixed, moving)
sup.apply(moving_all)
return structure
def get_contact_map(self, chain_id):
'''
Input:
self: Use Biopython.PDB structure which has been stored in an object variable
chain_id : String (usually in ['A','B', 'C' ...]. The number of chains
depends on the specific protein and the resulting structure)
Return:
Return a complete contact map (see description in exercise sheet)
for a given chain in a Biopython.PDB structure as numpy array.
The values in the matrix describe the c-alpha distance between all residues
in a chain of a Biopython.PDB structure.
Only integer values of the distance have to be given (see below).
'''
length = len(self.get_sequence(chain_id))
ppb = PPBuilder()
contact_map = np.zeros((length, length), dtype=np.float32)
for pp in ppb.build_peptides(self.structure[0][chain_id],
aa_only=True):
for i, residue_1 in enumerate(pp):
for j, residue_2 in enumerate(pp):
contact_map[i, j] = residue_1['CA'] - residue_2['CA']
return contact_map.astype(np.int) # return rounded (integer) values
def __init__(self,
prefix,
computedFeatsRootDir,
areForTrainAndTest=True,
boundAvailable=True,
res2res_dist=6.0,
statusManager=None):
'''
:param prefix: str. An id for the complex
:param computedFeatsRootDir: str. path where features will be stored
:param areForTrainAndTest: boolean. True if ligand and receptor are posed in interacting coordinates and thus,
we know the label. False if they are for prediction and thus, we cannot assign labels.
:param: boundAvailable. True if there is a bound and unbound pdb for each complex. False otherwise
:param res2res_dist: float. max distance between any heavy atoms of 2 amino acids to be considered as interacting
(Angstrom)
:param statusManager: class that implements .setStatus(msg) to communicate
'''
ToolManager.__init__(self,
computedFeatsRootDir,
statusManager=statusManager)
self.prefix = prefix
self.areForTrainAndTest = areForTrainAndTest
self.res2res_dist = res2res_dist
self.boundAvailable = boundAvailable
assert not (
boundAvailable == True and areForTrainAndTest == False
), "Error parameters in CMap: boundAvailable==True and areForTrainAndTest==False"
self.ppb = PPBuilder(
radius=200) # radius set to 200 to not worry about broken chains
self.outPath = myMakeDir(computedFeatsRootDir, "common")
self.outPathCM = myMakeDir(self.outPath, "contactMaps")
self.outPathResDict = myMakeDir(self.outPath, "includedResidues")
self.outPathNeigs = myMakeDir(self.outPath, "voroNeigs")
def _map(self, model):
"""Map (PRIVATE).
:param model: the model that will be mapped
:type model: L{Model}
"""
ppb = PPBuilder()
ppl = ppb.build_peptides(model)
fd = {}
for pp in ppl:
try:
# make fragments
flist = _make_fragment_list(pp, self.flength)
# classify fragments
mflist = _map_fragment_list(flist, self.reflist)
for i in range(0, len(pp)):
res = pp[i]
if i < self.edge:
# start residues
continue
elif i >= (len(pp) - self.edge):
# end residues
continue
else:
# fragment
index = i - self.edge
assert (index >= 0)
fd[res] = mflist[index]
except PDBException as why:
if why == 'CHAINBREAK':
# Funny polypeptide - skip
pass
else:
raise PDBException(why)
return fd
def match_pdb_residue_num_to_seq(model, ref=None):
"""Match PDB residue numbering (as given in PDB file) to
a reference sequence (can be pdb sequence) numbered by index.
Reference sequence is 1-indexed (and is indexed as such in output).
Args:
model: A biostructmap Model object.
ref (dict): A dictionary containing reference protein sequences for each
chain in the protein structure. Defaults to the protein sequences
given in PDB file.
Returns:
dict: A dictionary mapping reference sequence index (key) to
residue numbering as given in the PDB file (value). For example,
we might have a key of ('A', 17) for the 17th residue in the
reference sequence for chain 'A', with a value of
('A', (' ', 273, ' ')) that represents the Bio.PDB identifier for
the corresponding residue.
"""
ppb = PPBuilder()
polypeptides = ppb.build_peptides(model.parent().structure)
if ref is None:
ref = model.parent().sequences
output = {}
for peptide in polypeptides:
peptide_sequence = peptide.get_sequence()
# Presume that peptide belongs to a single chain
chain_id = peptide[0].get_full_id()[2]
_, ref_to_pdb = align_protein_sequences(peptide_sequence,
ref[chain_id])
for ref_pos, pdb_pos in ref_to_pdb.items():
output[(chain_id,
ref_pos)] = peptide[pdb_pos - 1].get_full_id()[2:4]
return output
def deleteChain():# Delete a complete chain from a pdb and save the new structure in pdbname_free.pdb
parser = PDBParser()
nameStruct=pdb_name.partition('.')[0]
structure = parser.get_structure(nameStruct, pdb_name)
header = parser.get_header()
trailer = parser.get_trailer()
seq=''
nb_chain=input('How many chain do you want to delete : ')
for i in range(nb_chain):
rm_chain=raw_input('What chain you want to delete : ')
for model in structure:
for chain in model:
if(chain.id==rm_chain):
model.detach_child(chain.id)
pept = raw_input('Do you want to get a pdb with the sequence in its name : ')
if(pept == 'y'):
ppb=PPBuilder()
for pp in ppb.build_peptides(structure):
seq = seq + pp.get_sequence()
seq=seq.lower()
seq=str(seq)
w = PDBIO()
w.set_structure(structure)
w.save(seq+'_bound.pdb')
else:
w = PDBIO()
w.set_structure(structure)
w.save(nameStruct+'_without'+rm_chain+'.pdb')
def _get_proteins_by_structure(self, pdb_structure, model, file_path):
"""
_get_proteins_by_structure: Given a pdb_structure, parse the essential protein data
"""
ppb = PPBuilder()
protein_data = []
# Parse for the chain_id and chain sequence
for c_ele in pdb_structure.get_chains():
if (c_ele):
c_ppd_list = []
for c_ppd in ppb.build_peptides(c_ele):
c_pp_seq = str(c_ppd.get_sequence())
c_ppd_list.append(c_pp_seq)
c_seq = ''.join(c_ppd_list)
protein_data.append({
'id':
os.path.basename(file_path),
'model_id':
model,
'chain_id':
c_ele.get_id(),
'sequence':
c_seq,
'md5':
hashlib.md5(c_seq.encode()).hexdigest()
})
return protein_data
def read_structure_seqs(self, strucm):
""" Extracts sequences from structure"""
# PDB extrated sequences
for mod in strucm.st:
ppb = PPBuilder()
for chn in mod.get_chains():
seqs = []
#self.sequences[ch_id]['pdb'][mod.id] = [1]
ch_id = chn.id
wrong_order = False
for frag in ppb.build_peptides(chn):
start = frag[0].get_id()[1]
end = frag[-1].get_id()[1]
frid = '{}:{}-{}'.format(ch_id, start, end)
sqr = SeqRecord(frag.get_sequence(), 'pdbsq_' + frid,
'pdbsq_' + frid,
'PDB sequence chain ' + frid)
if start < end:
sqr.features.append(
SeqFeature(FeatureLocation(start, end)))
else:
print("Warning: unusual residue numbering at chain ",
ch_id)
print(
"Warning: chain reconstruction may not be available"
)
sqr.features.append(
SeqFeature(FeatureLocation(end, start)))
wrong_order = True
seqs.append(sqr)
if ch_id not in self.data:
self.add_empty_chain(ch_id)
self.data[ch_id]['pdb'][mod.id] = seqs
self.data[ch_id]['pdb']['wrong_order'] = wrong_order
def _map(self, model):
"""
@param model: the model that will be mapped
@type model: L{Model}
"""
ppb=PPBuilder()
ppl=ppb.build_peptides(model)
fd={}
for pp in ppl:
try:
# make fragments
flist=_make_fragment_list(pp, self.flength)
# classify fragments
mflist=_map_fragment_list(flist, self.reflist)
for i in range(0, len(pp)):
res=pp[i]
if i<self.edge:
# start residues
continue
elif i>=(len(pp)-self.edge):
# end residues
continue
else:
# fragment
index=i-self.edge
assert(index>=0)
fd[res]=mflist[index]
except PDBException, why:
if why == 'CHAINBREAK':
# Funny polypeptide - skip
pass
else:
raise PDBException(why)
def main():
parser = optparse.OptionParser()
parser.add_option("-p", "--pdb", dest="pdb", help="path to PDB file", metavar="STRING")
parser.add_option("-f", "--pdb_fasta", dest="pdb_fasta", help="path to PDB fasta file (out)", metavar="STRING")
(options, args) = parser.parse_args()
pdb_fasta = options.pdb_fasta
pdb_file = options.pdb
pdb_name = os.path.basename(pdb_file).split(".")[0]
parser=BP.PDBParser()
ppb = PPBuilder(radius=1000) # retrieve all amino acids
pdbseq = ""
structure = parser.get_structure(pdb_name,pdb_file)
model = structure[0]
for chain in model:
for pp in ppb.build_peptides(model[chain.id], aa_only=False):
pdbseq += (pp.get_sequence())
print ">",pdb_name,len(pdbseq)
print pdbseq
with open(pdb_fasta,"w") as o:
o.write(">%s %i\n%s\n"%(pdb_name,len(pdbseq),pdbseq))
def fetch_protein(pdb_id: str) -> Tuple[List[str], np.ndarray]:
# retrieve pdb file from Protein Data Bank
pdb_file = f"{pdb_id}.pdb"
pdb_file_path = os.path.join(os.getcwd(), pdb_file)
protein_url = f"https://files.rcsb.org/download/{pdb_file}"
req = requests.get(protein_url)
with open(pdb_file_path, "w") as f:
f.write(req.text)
# parse pdb file
structure = PDBParser().get_structure(pdb_id, pdb_file)
peptides = PPBuilder().build_peptides(structure)[0]
# extract amino acid sequence and phi/psi angles
aa_sequence = list(peptides.get_sequence())
phi_psi_angles = np.array(
list(
map(
lambda x: (180 if not x[0] else np.rad2deg(x[0]), 180
if not x[1] else np.rad2deg(x[1])),
peptides.get_phi_psi_list()))).T
# remove pdb file
subprocess.check_output(["rm", pdb_file])
return aa_sequence, phi_psi_angles
def get_chain_position(input_file, global_index):
chain = None
position_in_chain = -1
file_name, _ = os.path.splitext(input_file)
file_name = file_name.replace('./', '')
parser = PDBParser()
structure = parser.get_structure(file_name, input_file)
builder = PPBuilder()
peptides = builder.build_peptides(structure, aa_only=False)
pps = [EPolyPeptide(pp) for pp in peptides]
total_length = sum([len(pp) for pp in pps])
if global_index >= total_length:
return None, -1
distance = 0
offset = 0
global_index = int(global_index) + 1
while distance < global_index:
pp = pps[offset]
distance += len(pp)
offset += 1
if global_index <= distance:
position_in_chain = global_index - (distance - len(pp))
chain = pp.chain_id
break
return chain, position_in_chain
def getBoundResList(fname_bound, fname_unbound, listOfDictsChainToResId):
parser = PDBParser(QUIET=True)
structureUnbound = parser.get_structure(fname_unbound, fname_unbound)
structureBound = parser.get_structure(fname_bound, fname_bound)
ppb = PPBuilder()
pp_list_unbound = ppb.build_peptides(structureUnbound, aa_only=False)
pp_list_bound = ppb.build_peptides(structureBound, aa_only=False)
mapper = BoundUnboundMapper(pp_list_unbound, pp_list_bound)
mapper.build_correspondence()
newDictsList = []
for dictOfChainsToRes in listOfDictsChainToResId:
tempDict = {}
for chainId_u in dictOfChainsToRes:
for resId_u in sorted(dictOfChainsToRes[chainId_u]):
chainId_b_resId_b = mapper.mapUnboundToBoundUsingId(
" " if chainId_u == "*" else chainId_u, resId_u)
# print(chainId_u, resId_u, chainId_b_resId_b)
if chainId_b_resId_b is None: continue
chainId_b, resId_b = chainId_b_resId_b
if not chainId_b in tempDict:
tempDict[chainId_b] = []
tempDict[chainId_b].append(resId_b)
newDictsList.append(tempDict)
return newDictsList
def deleteChain():# Delete a complete chain from a pdb and save the new structure in pdbname_free.pdb
parser = PDBParser()
nameStruct=pdb_name.partition('.')[0]
structure = parser.get_structure(nameStruct, pdb_name)
header = parser.get_header()
trailer = parser.get_trailer()
seq=''
nb_chain=input('How many chain do you want to delete : ')
for i in range(nb_chain):
rm_chain=raw_input('What chain you want to delete : ')
for model in structure:
for chain in model:
if(chain.id==rm_chain):
model.detach_child(chain.id)
pept = raw_input('Do you want to get a pdb with the sequence in its name : ')
if(pept == 'y'):
ppb=PPBuilder()
for pp in ppb.build_peptides(structure):
seq = seq + pp.get_sequence()
seq=seq.lower()
seq=str(seq)
w = PDBIO()
w.set_structure(structure)
w.save(seq+'_bound.pdb')
else:
w = PDBIO()
w.set_structure(structure)
w.save(nameStruct+'_without'+rm_chain+'.pdb')
def doChainAlignments(pdbID, structure, consensusFile, chainSequencesDir,
verbose):
print('Pairwise alignment of chain sequences with consensus...')
chains = [chain for chain in structure.get_chains()]
ppb = PPBuilder()
for chain in chains:
sequence = ""
for pp in ppb.build_peptides(chain):
sequence += pp.get_sequence()
sequenceID = pdbID + '_' + chain.get_id()
sequenceOutput = os.path.join(chainSequencesDir, sequenceID + '.fasta')
if (len(sequence) == 0):
print("ERROR: Unable to get chain sequence from PDB file.")
exit("Selected PDB-file does not contain protein structure.")
with open(sequenceOutput, 'w') as f:
f.write('>' + sequenceID + '\n' + str(sequence))
if verbose:
print('Chain ' + chain.get_id())
print(sequence)
subprocess.check_call([
'needle', '-asequence', sequenceOutput, '-bsequence',
consensusFile, '-noendweight', '-endopen', '10.0', '-endextend',
'0.5', '-brief', '-aformat', 'srspair', '-auto', '-aname_outfile',
pdbID + '_' + chain.get_id(), '-adirectory_outfile',
chainSequencesDir
])
print('OK')
def main():
parser = optparse.OptionParser()
parser.add_option("-p",
"--pdb",
dest="pdb",
help="path to PDB file",
metavar="STRING")
parser.add_option("-f",
"--pdb_fasta",
dest="pdb_fasta",
help="path to PDB fasta file (out)",
metavar="STRING")
(options, args) = parser.parse_args()
pdb_fasta = options.pdb_fasta
pdb_file = options.pdb
pdb_name = os.path.basename(pdb_file).split(".")[0]
parser = BP.PDBParser()
ppb = PPBuilder(radius=1000) # retrieve all amino acids
pdbseq = ""
structure = parser.get_structure(pdb_name, pdb_file)
model = structure[0]
for chain in model:
for pp in ppb.build_peptides(model[chain.id], aa_only=False):
pdbseq += (pp.get_sequence())
print ">", pdb_name, len(pdbseq)
print pdbseq
with open(pdb_fasta, "w") as o:
o.write(">%s %i\n%s\n" % (pdb_name, len(pdbseq), pdbseq))
def download(filelist: list, q: Queue, lock: Lock, cursor: sqlite3.Cursor, conn: sqlite3.Connection, dir_name: str):
"""
:param filelist:
:param q:
:param lock:
:param cursor:
:param conn:
:param dir_name:
"""
with open('status_tmp.txt', 'w') as f:
f.write('')
for file in filelist:
if file in open('status_tmp.txt').readlines():
continue
pdbl = PDBList()
pdbl.retrieve_pdb_file(file, pdir=os.path.join(dir_name, file), file_format='pdb')
if not os.path.exists(os.path.join(dir_name, file, 'pdb{:s}.ent'.format(file))):
print("File with ID PDB: {:s} not found!".format(file))
continue
parser = PDBParser()
structure = parser.get_structure('{:s}', os.path.join(dir_name, file, 'pdb{:s}.ent'.format(file)))
name = parser.header.get('name', '')
head = parser.header.get('head', '')
method = parser.header.get('structure_method', '')
res = parser.header.get('resolution', '')
ncomp = 0
nchain = 0
eclist = []
for values in parser.header['compound'].values():
ncomp += 1
nchain += len(values['chain'].split(','))
eclist.append(values.get('ec', '') or values.get('ec_number', ''))
ec = ", ".join(eclist)
nres = 0
mmass = 0
ppb = PPBuilder()
for pp in ppb.build_peptides(structure):
seq = pp.get_sequence()
nres += len(seq)
seqan = ProteinAnalysis(str(seq))
mmass += int(seqan.molecular_weight())
lock.acquire()
try:
cursor.execute("""INSERT INTO Structures (IDPDB, NAME, HEAD, METHOD, RESOLUTION, NCOMP, NCHAIN,
NRES, MMASS, EC) VALUES ("{:s}", "{:s}", "{:s}", "{:s}", {:.2f}, {:d}, {:d},{:d}, {:d}, "{:s}")""".format(
file, name, head, method, res, ncomp, nchain, nres, mmass, ec))
except sqlite3.DatabaseError as err:
print("Error: ", err)
continue
else:
print("Download Done for ID PDB: {:s}".format(file))
conn.commit()
q.put(file)
finally:
lock.release()
with open('status_tmp.txt', 'at') as f:
f.write((file + '\n'))
os.remove('status_tmp.txt')
q.put(None)
def generate_seq_file(score_file, save_file):
score_file = './dataFile/' + score_file
sf = pd.read_csv(score_file, sep='\t')
mut_chains = sf.iloc[:,0]
mut_dict = dict()
mut_track = set()
pdb_track = set()
for chain in mut_chains:
info = chain.split('_')
pdb_id = info[0]
chain_id = info[1]
wt_aa = info[2][0:3]
mu_aa = info[2][-3:]
mu_pos = int(''.join(filter(lambda x: x.isdigit(), info[2])))
if not chain in mut_track:
mut_track.add(chain)
if pdb_id in pdb_track:
mut_dict[pdb_id].append({'chain_id':chain_id,
'wt_aa': wt_aa,
'mu_aa': mu_aa,
'mu_pos': mu_pos,
'name': chain})
else:
mut_dict[pdb_id] = [{'chain_id': chain_id,
'wt_aa': wt_aa,
'mu_aa': mu_aa,
'mu_pos': mu_pos,
'name': chain}]
pdb_track.add(pdb_id)
del mut_track
del pdb_track
parser = PDBParser()
seq_builder = PPBuilder()
pdb_dl_handle = PDBList()
PDB_DIR = './dataFile/PDB_dl'
# check if pdb file exists
mut_collect = dict()
for pdb_id in mut_dict.keys():
if not os.path.exists(PDB_DIR+'/pdb'+pdb_id.lower()+'.ent'):
pdb_dl_handle.retrieve_pdb_file(pdb_code=pdb_id, file_format='pdb', overwrite=False, pdir=PDB_DIR)
pdb_file = PDB_DIR+'/pdb'+pdb_id.lower()+'.ent'
model = parser.get_structure(pdb_id, pdb_file)[0]
for mutation in mut_dict[pdb_id]:
protein_chain = model[mutation['chain_id']]
sequence = "".join([str(pp.get_sequence())
for pp in seq_builder.build_peptides(protein_chain)])
sequence = sequence.replace('\n', '').replace(' ', '')
assert sequence[mutation['mu_pos']-1] == three_to_one(mutation['wt_aa']), 'Wt amino acid failed to match'
mut_Seq_list = list(sequence)
mut_Seq_list[mutation['mu_pos']-1] = three_to_one(mutation['mu_aa'])
mut_Seq = ''.join(mut_Seq_list)
mut_collect[mutation['name']] = mut_Seq
with open(save_file, 'w') as output_hl:
for k, v in mut_collect.items():
output_hl.write(k+'\t'+v+'\n')
def real_seq():
structure = PDBParser().get_structure(protein.protein_id,
protein.protein_id + '.pdb')
ppb = PPBuilder()
seq = ''
for pp in ppb.build_peptides(structure):
seq += pp.get_sequence()
return seq
def polypeptide(pdbfile):
parser = PDBParser()
structure = parser.get_structure('test', pdbfile)
builder = PPBuilder()
pp, = builder.build_peptides(structure)
return pp
def get_phi_psi_data(pdb_id, chain=None):
'''Gets phi and phi angle data.'''
builder = PPBuilder()
return [polypep.get_phi_psi_list()
for model in get_structure(pdb_id)
for chn in model
if chain is None or chain == chn.get_id()
for polypep in builder.build_peptides(chn)]
def parse_structure(path):
"""
Parses a PDB formatter structure using Biopython's PDB Parser
Verifies the integrity of the structure (gaps) and its
suitability for the calculation (is it a complex?).
"""
print('[+] Reading structure file: {0}'.format(path))
fname = os.path.basename(path)
sname = '.'.join(fname.split('.')[:-1])
try:
s = P.get_structure(sname, path)
except Exception as e:
print('[!] Structure \'{0}\' could not be parsed'.format(sname),
file=sys.stderr)
raise Exception(e)
# Double occupancy check
for atom in list(s.get_atoms()):
if atom.is_disordered():
residue = atom.parent
sel_at = atom.selected_child
sel_at.altloc = ' '
sel_at.disordered_flag = 0
residue.detach_child(atom.id)
residue.add(sel_at)
# Remove HETATMs and solvent
res_list = list(s.get_residues())
n_res = len(res_list)
_ignore = lambda r: r.id[0][0] == 'W' or r.id[0][0] == 'H'
for res in res_list:
if _ignore(res):
chain = res.parent
chain.detach_child(res.id)
elif not is_aa(res, standard=True):
raise ValueError(
'Unsupported non-standard amino acid found: {0}'.format(
res.resname))
# Detect gaps and compare with no. of chains
pep_builder = PPBuilder()
peptides = pep_builder.build_peptides(s)
n_peptides = len(peptides)
n_chains = len(set([c.id for c in s.get_chains()]))
if n_peptides != n_chains:
print('[!] Structure contains gaps:', file=sys.stderr)
for i_pp, pp in enumerate(peptides):
print(
'\t{1.parent.id} {1.resname}{1.id[1]} < Fragment {0} > {2.parent.id} {2.resname}{2.id[1]}'
.format(i_pp, pp[0], pp[-1]),
file=sys.stderr)
#raise Exception('Calculation cannot proceed')
return (s, n_chains, n_res)
def get_pdb_amino_acid_sequences(pdb_path):
structure = Bio.PDB.PDBParser(QUIET=True).get_structure(
pdb_path[:-4], pdb_path)
ppb = PPBuilder()
pdb_aas = []
for pp in ppb.build_peptides(structure):
pdb_aa = str(pp.get_sequence())
pdb_aas.append(pdb_aa)
return pdb_aas
def find_pdb_limits(pdb_path):
""""""
pdb = PDBParser().get_structure('', pdb_path)
# takes the first (and only) polypeptide
pp = PPBuilder().build_peptides(pdb)[0]
start = pp[0].get_id()[1]
end = pp[-1].get_id()[1]
seq = pp.get_sequence()
return (start, end, seq)
def _model_file_to_data(self, file_path, params):
"""
_model_file_to_data:
Do the PDB conversion--parse the model pdb file for creating a pdb data object
"""
logging.info(
f'Parsing pdb file {file_path} to a pdb structure with params: {params}'
)
parser = PDB.PDBParser(PERMISSIVE=1)
pdb1 = file_path
pp_no = 0
data = {}
try:
structure = parser.get_structure("test", pdb1)
except (RuntimeError, TypeError, KeyError, ValueError) as e:
logging.info(f'PDBParser errored with message: {e.message}')
raise
else:
ppb = PPBuilder()
for pp in ppb.build_peptides(structure):
pp_no += 1
# logging.info(f'Getting pdb structure data for {structure}!')
(compound, source) = self._get_compound_source(structure)
(num_models,
model_ids) = self._get_models_from_structure(structure)
(num_chains,
chain_ids) = self._get_chains_from_structure(structure)
(num_residues,
residue_ids) = self._get_residues_from_structure(structure)
(num_atoms, atom_ids) = self._get_atoms_from_structure(structure)
model = structure[0]
protein_data = self._get_proteins_by_structure(
structure, model.get_id(), file_path)
(protein_data, params) = self._match_features(params, protein_data)
pdb_info = params.get('pdb_info', None)
if pdb_info and pdb_info.get('sequence_identities', None):
data = {
'name': structure.header.get('name', ''),
'num_chains': num_chains,
'num_residues': num_residues,
'num_atoms': num_atoms,
'compound': compound,
'source': source,
'proteins': protein_data
}
else:
logging.info(
f'Parsing pdb file {file_path} failed to match KBase genome/features!'
)
data = {}
finally:
return data, pp_no, params
def get_pdb_torsion_angles(pdb_path, chain_index):
structure = Bio.PDB.PDBParser(QUIET=True).get_structure(
pdb_path[:-4], pdb_path)
A = []
ppb = PPBuilder()
pdb_aas = []
model = ppb.build_peptides(structure)
chain = model[chain_index]
phi_psi_list = chain.get_phi_psi_list()
return [x[0] for x in phi_psi_list], [x[1] for x in phi_psi_list]
def get_primary_sequence(input_file):
file_name, _ = os.path.splitext(input_file)
file_name = file_name.replace('./', '')
parser = PDBParser()
structure = parser.get_structure(file_name, input_file)
builder = PPBuilder()
seq = ""
for chain in builder.build_peptides(structure, aa_only=False):
seq += chain.get_sequence()
return seq
def get_aa_encoded(protein_file):
structure = Bio.PDB.PDBParser(QUIET=True).get_structure(
pdb_path[:-4], pdb_path)
ppb = PPBuilder()
pdb_aas = []
for pp in ppb.build_peptides(structure):
pdb_aa = str(pp.get_sequence())
pdb_aas.append(pdb_aa)
encoded = int_encoding(pdb_aas, AA_CODES)
return encoded
def obtian_seq_wo_seq_file(score_file):
score_file = './dataFile/' + score_file
sf = pd.read_csv(score_file, sep='\t')
chains_involved = sf.iloc[:, 0]
pdb = dict()
pdb_track = set()
for chain in chains_involved:
chain_name = chain[0:6]
pdb_name = chain[0:4]
# if we encounter a old pdb
if pdb_name in pdb_track:
pdb[pdb_name].add(chain_name)
# else, we have a new pdb
else:
# update the track file
pdb_track.add(pdb_name)
pdb[pdb_name] = {chain_name}
# create the link to the PDB database and retrive all the file
# related to the files, store them locally under ./dataFile/PDB_dl/
PDB_DIR = './dataFile/PDB_dl'
if not os.path.exists(PDB_DIR):
os.mkdir(PDB_DIR)
# create the download handle
pdb_dl_handle = PDBList()
# download all of the pdb files
for item in pdb.keys():
if not os.path.exists(PDB_DIR + '/pdb' + item.lower() + '.ent'):
pdb_dl_handle.retrieve_pdb_file(pdb_code=item,
file_format='pdb',
overwrite=False,
pdir=PDB_DIR)
# for each pdb, we will construct the sequence
seq_dict = dict()
parser = PDBParser()
seq_builder = PPBuilder()
# key is the pdb_id, value is the chain in a
for pdb_id, chain_names in pdb.items():
pdb_file = PDB_DIR + '/pdb' + pdb_id.lower() + '.ent'
model = parser.get_structure(pdb_id, pdb_file)[0]
for chain in chain_names:
# extract the last letter, which is the chain name
chain_id = chain[-1]
protein_chain = model[chain_id]
sequence = "".join([
str(pp.get_sequence())
for pp in seq_builder.build_peptides(protein_chain)
])
sequence = sequence.replace('\n',
'').replace(' ',
'') # clean the bad chars
seq_dict[chain] = sequence
return seq_dict
def get_secondary_structure_details(self, name, pdb_file, aa_only=False):
parser = PDBParser()
structure = parser.get_structure(name, pdb_file)
dssp = DSSP(structure[0], pdb_file, acc_array="Wilke")
ss = "".join([aa[2] for aa in dssp])
sasa = [residues[aa[1]] * aa[3] for aa in dssp]
builder = PPBuilder()
seq = ""
for chain in builder.build_peptides(structure, aa_only=aa_only):
seq += chain.get_sequence()
return name, seq, ss, sasa, structure
def get_sequence( self, chain_id ):
'''
Input:
self: Use Biopython.PDB structure which has been stored in an object variable
chain_id : String (usually in ['A','B', 'C' ...]. The number of chains
depends on the specific protein and the resulting structure)
Return:
Return the amino acid sequence (single-letter alphabet!) of a given chain (chain_id)
in a Biopython.PDB structure as a string.
'''
ppb = PPBuilder()
return ppb.build_peptides(self.structure[chain_id])[0].get_sequence()
def test_add_residue():
structure = PeptideBuilder.initialize_res("A")
for aa in "CDEFGHIKLMNPQRSTVWY":
structure = PeptideBuilder.add_residue(structure, aa)
# extract peptide from structure and compare to expected
ppb = PPBuilder()
pp = next(iter(ppb.build_peptides(structure)))
assert pp.get_sequence() == "ACDEFGHIKLMNPQRSTVWY"
# now compare to saved reference structure
assert compare_to_reference(structure, "extended.pdb")
def __init__(self, path):
'''
Initialize every PDB_Parser with a path to a structure-file in CIF format.
An example file is included in the repository (7ahl.cif).
Tip: Store the parsed structure in an object variable instead of parsing it
again & again ...
'''
# parser object for reading in structure in CIF format
CIF_PARSER: MMCIFParser = MMCIFParser()
self.ppb = PPBuilder()
self.structure = CIF_PARSER.get_structure('structure', path)
self.chains: Dict[Entity] = {}
for chain in self.structure.get_chains():
self.chains[chain.id] = chain
def test_add_residue():
"""
Build a peptide containing all 20 amino acids
"""
structure = PeptideBuilder.initialize_res("A")
for aa in "CDEFGHIKLMNPQRSTVWY":
PeptideBuilder.add_residue(structure, aa)
# extract peptide from structure and compare to expected
ppb = PPBuilder()
pp = next(iter(ppb.build_peptides(structure)))
assert pp.get_sequence() == "ACDEFGHIKLMNPQRSTVWY"
assert compare_to_reference(structure, "extended.pdb")
def write_seqs(filename):
"""Process a given structure file to extract sequences and save them into files.
"""
struct_name = os.path.splitext(os.path.basename(filename))[0]
is_CIF = False
try:
parser = PDBParser()
structure = parser.get_structure(struct_name, filename)
except:
try:
parser = MMCIFParser()
structure = parser.get_structure(struct_name, filename)
is_CIF = True
except:
sys.stderr.write("ERROR: File {} is not a proper/supported protein structure file.\n".format(filename))
return
if is_CIF:
name, organism, resolution = get_info_from_cif_dict(filename)
else:
name, organism, resolution = get_info_from_header(structure)
description = "| {} | {} | Resolution {:.2f} A".format(name, organism, resolution)
ppb = PPBuilder()
chain_seqrecord_list = []
peptide_seqrecord_list = []
for model in structure:
for chain in model:
base_id = "{}.{:d}_{}".format(struct_name, model.id, chain.id)
chain_seq = Seq("")
for (pp_id, pp) in enumerate(ppb.build_peptides(chain)):
chain_seq += pp.get_sequence()
peptide_seqrecord_list.append(SeqRecord(pp.get_sequence(),
id = "{}.{:d}".format(base_id, pp_id),
description = description))
chain_seqrecord_list.append(SeqRecord(chain_seq,
id = base_id,
description = description))
base_output_name = os.path.splitext(filename)[0]
SeqIO.write(chain_seqrecord_list, "{}_chains.fasta".format(base_output_name), "fasta")
SeqIO.write(peptide_seqrecord_list, "{}_peptides.fasta".format(base_output_name), "fasta")
def pdb_extract_chain_seqs(struct):
"""
Takes a Bio.PDB.Structure object, returns a dictionary
of chains and sequences (eg {'A':'MTSSLGRF', 'B':'MSLQRGFIN'}
(for structures with multiple models, like NMR structures,
only the first model is considered).
"""
chains = {}
ppb=PPBuilder()
for chain in struct[0]: # takes model 1
for pp in ppb.build_peptides(chain, aa_only=False):
seq = str(pp.get_sequence())
chains[chain.id] = "".join(seq)
return chains
def getSequence(): # Get the sequence of a specific chain
parser = PDBParser()
nameStruct=pdb_name.partition('.')[0]
structure = parser.get_structure(nameStruct, pdb_name)
header = parser.get_header()
trailer = parser.get_trailer()
seq=''
what_chain=raw_input('For what chain do you want the sequence : ')
for model in structure:
for chain in model:
if chain.id != what_chain:
model.detach_child(chain.id)
ppb=PPBuilder()
for pp in ppb.build_peptides(structure):
seq = seq + pp.get_sequence()
seq=seq.upper()
print seq
def getPDBInfo(pdb, pdbpath):
# extract information from the PDB file using Biopython
# Biopython parsers
parser = BP.PDBParser()
ppb = PPBuilder()
pdbseq = ""
# PDB descriptors
# name = pdb.split("/")[-1].split(".")[0].split("_")[0]
if len(pdb.split("/")[-1].split(".")[0].split("_")) > 1:
chain = pdb.split("/")[-1].split(".")[0].split("_")[1]
else:
# not "_" delimiters in pdb name
chain = pdb.split("/")[-1].split(".")[0][4]
if os.path.exists(os.path.join(pdbpath, pdb + "_ren.pdb")):
structure = parser.get_structure(pdb, os.path.join(pdbpath, pdb + "_ren.pdb"))
residue_list = BP.Selection.unfold_entities(structure[0][chain], 'R')
# the build_peptides method has an option for treating non-standard amino acids
for pp in ppb.build_peptides(structure[0][chain], aa_only=False):
pdbseq += (pp.get_sequence())
return structure, residue_list, pdbseq
def create_sequence_from_file(chain_pdb, missing_residues, quiet_parser=False):
""" Read a PDB file and creates a sequence and mismask to represent
its content.
@param chain_pdb: The PDB file to be read.
@type chain_pd: str
@param missing_residues: A dictionary with the missing residues.
@type missing_residues: dict
@param quiet_parser: Disable PDBParser warnings.
@type quiet_parser: bool
"""
sequences = []
mismasks = []
output_data = []
output_mismask = []
parser = PDBParser(QUIET=quiet_parser)
structure = parser.get_structure("X", chain_pdb)
dssp = DSSP(model=structure[0], pdb_file=chain_pdb)
# Loop over residues in peptides
ppb = PPBuilder()
pp_list = ppb.build_peptides(structure[0])
chain_list = structure[0].get_list()
if len(pp_list) == 0:
raise TorusDBNBuildPolypeptideException(
"Could not create a list of Polypeptide objects from the file %s."
% (chain_pdb)
)
else:
pp_chains, chain_missing_residues = _get_pp_with_chain_break(
chain_pdb, pp_list, chain_list, missing_residues)
for pp_index, pp in enumerate(pp_chains):
phi_psi_list = pp.get_phi_psi_list()
missing_residues = chain_missing_residues[pp_index]
for i in xrange(1, len(phi_psi_list)-1):
seq = [0] * 6
mism = [eMISMASK.MOCAPY_HIDDEN] + 4 * [eMISMASK.MOCAPY_OBSERVED]
# Amino acid
res = pp[i]
res_name = res.get_resname()
res_index = res.get_id()[1]
aa_index = three_to_index(res_name)
if res_index in missing_residues:
seq[3] = aa_index
mism[1] = eMISMASK.MOCAPY_MISSING # angles unknown
mism[3] = eMISMASK.MOCAPY_MISSING # ss unknown
mism[4] = eMISMASK.MOCAPY_MISSING # cis unknown
else:
seq[3] = aa_index
# Secondary Structure
try:
ss = res.xtra["SS_DSSP"]
ss_index = dssp_to_index(ss)
seq[4] = ss_index
except:
mism[3] = eMISMASK.MOCAPY_MISSING # ss unknown
# Angles
if None in phi_psi_list[i]:
# Previous or next residue missing, therefore angles are
# Unknown
mism[1] = eMISMASK.MOCAPY_MISSING
else:
seq[1:3] = phi_psi_list[i]
# Cis/Trans information
if (res_index - 1) in missing_residues:
mism[4] = eMISMASK.MOCAPY_MISSING # cis unknown
else:
try:
seq[5] = _get_peptide_bond_conformation(res, pp[i-1])
except TorusDBNException:
mism[4] = eMISMASK.MOCAPY_MISSING # cis unknown
output_data.append(seq)
output_mismask.append(mism)
if output_data and output_mismask:
sequences.append(numpy.array(output_data))
mismasks.append(numpy.array(output_mismask, dtype = numpy.uint))
else:
raise TorusDBNException(
"Could not create training data from the file %s."
% (chain_pdb)
)
return sequences, mismasks
def create_residue_lists(pdb, chain):
print pdb, chain
res_lists = []
aa_list = ""
try:
ppb = PPBuilder()
p=PDB.PDBParser(QUIET = True)
s=p.get_structure('X', "../foldx_setup/repaired_pdbs/RepairPDB_" + pdb + "_" + chain + ".pdb")
pp = ppb.build_peptides(s)[0]
seq = str(pp.get_sequence())
#Get the structures
ref_struct = s[0]
ref_chain = ref_struct[chain]
ref_residues = []
ref_res_nums = []
for res in ref_chain:
ref_residues.append( res.resname )
ref_res_nums.append(res.id[1])
except KeyError:
print "Something is wrong with the mapped residues"
#continue
seq_array = ddG_var_helper.convert_to_one_letter_code(ref_residues)
count = 0
i = 0
while(i < len(seq_array)):
if (i < 101): #These statements split up the sequence into 100 aa chunks for performing a Position Scan
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 101):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
elif(i < 201 and i>101):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 201):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
elif(i < 301 and i>201):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 301):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
elif(i < 401 and i>301):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 401):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
elif(i < 501 and i>401):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 501):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
if (i < 601 and i>501):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 601):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
if(i < 701 and i>601):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 701):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
if (i < 801 and i>701):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 801):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
if (i < 901 and i>801):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 901):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
elif(i < 1001 and i>901):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 1001):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
elif(i < 1101 and i>1001):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 1101):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
elif(i < 1201 and i>1101):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 1201):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
aa_list = ""
elif(i < 1301 and i>1201):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
if(i == len(seq_array) - 1):
aa_list = aa_list + ";"
res_lists.append(aa_list)
elif(i == 1301):
aa_list = aa_list + ","
res_num = ref_res_nums[i]
aa_list = aa_list + seq_array[i] + chain + str(res_num) + "a"
aa_list = aa_list + ";"
res_lists.append(aa_list)
i = i + 1
return res_lists
pdb_file = gzip.open(os.path.join(input_path, filename))
pdb_parser = Bio.PDB.PDBParser(pdb_file)
## to get structural data
pdb_id = pdb_filename[7:11]
structure = pdb_parser.get_structure(pdb_id, pdb_file)
print structure
# Extract sequence from coordinate information
# Amino acid residues present in SEQRES but that doesn't have coordinate information
# are listed in REMARK 465
ppb = PPBuilder() # PPBuilder uses C--N distance to find polypeptides.
for pp in ppb.build_peptides(structure):
sequence = pp.get_sequence()
print "This is the polypeptide sequence of %s" %pdb_id
print sequence
print "length of sequence: ", len(sequence)
# OR extract sequence from SEQRES - ?
# when I aligned the sequence output of 1A27 here and the fasta sequence, I see 4 residues missing
# these 4 residues are reported as REMARK 465 MISSING RESIDUES (THE FOLLOWING RESIDUES WERE NOT LOCATED
# IN THE EXPERIMENT)
# does this mean unresolved or missing in protein construct?
def get_sequence(self):
ppb = PPBuilder()
polypeptide = ppb.build_peptides(self.structure[0][self.chain])
return polypeptide[0].get_sequence()
'''
Extract the protein sequence from a PDB chain.
-----------------------------------------------------------
(c) 2013 Allegra Via and Kristian Rother
Licensed under the conditions of the Python License
This code appears in section 21.4.2 of the book
"Managing Biological Data with Python".
-----------------------------------------------------------
'''
from Bio import PDB
from Bio.PDB.Polypeptide import PPBuilder
parser = PDB.PDBParser()
structure = parser.get_structure("2DN1", "dn/pdb2dn1.ent")
ppb = PPBuilder()
peptides = ppb.build_peptides(structure)
for pep in peptides:
print pep.get_sequence()
#####
#Extract chains with Chimera
nucl_xen=openModels.open('1kx5.pdb',type='PDB')
# nucl_yeast=openModels.open('1id3.pdb',type='PDB')
# h2a_xen=Seq(str(nucl[0].sequence('C')))
# h2a_yeast=Seq(str(nuclZ[0].sequence('C')))
rc('select :.A :.B :.C :.D :.E :.F :.G :.H')
rc('write selected format pdb #0 xen_nucl.pdb')
# rc('write selected format pdb #1 h2a_yeast_xray.pdb')
#generate alignments
#Biopython extracts seqs from pdb
p = PDBParser(PERMISSIVE=1)
s = p.get_structure('1kx5', '1kx5.pdb')
ppb=PPBuilder()
seqs_xen=dict()
for i in ['A','B','C','D','E','F','G','H']:
seqs_xen[i]=ppb.build_peptides(s[0][i])[0].get_sequence()
#Here we manually input the trunctaed versions of yeast sequences
seqs_yeast=dict()
#CSE4 - H3
#SSKQQWVSSAIQSDSSGRSLSNVNRLAGDQQSINDRALSLLQRTRATKNLFPRREERRRYESSKSDLDIETDYEDQAGNLEIETENEEEAEMETEVPAPVRTHSYALDRYVRQKRREKQRKQSLKR
#VEKKYTPSELALYEIRKYQRSTDLLISKIPFARLVKEVTDEFTTKDQDLRWQSMAIMALQEASEAYLVGLLEHTNLLALHAKRITIMKKDMQLARRIRGQFI
#VEKKYTPSELALYEIRKYQRSTDLLISKIPFARLVKEVTDEFTTKDQDLRWQSMAIMALQEASEAYLVGLLEHTNLLALHAKRITIMKKDMQLARRIRGQFI
seqs_yeast['A']=Seq('VEKKYTPSELALYEIRKYQRSTDLLISKIPFARLVKEVTDEFTTKDQDLRWQSMAIMALQEASEAYLVGLLEHTNLLALHAKRITIMKKDMQLARRIRGQFI')
seqs_yeast['E']=Seq('VEKKYTPSELALYEIRKYQRSTDLLISKIPFARLVKEVTDEFTTKDQDLRWQSMAIMALQEASEAYLVGLLEHTNLLALHAKRITIMKKDMQLARRIRGQFI')
#H4
seqs_yeast['B']=Seq('KRHRKILRDNIQGITKPAIRRLARRGGVKRISGLIYEEVRAVLKSFLESVIRDSVTYTEHAKRKTVTSLDVVYALKRQGRTLYGFGG')
seqs_yeast['F']=Seq('KRHRKILRDNIQGITKPAIRRLARRGGVKRISGLIYEEVRAVLKSFLESVIRDSVTYTEHAKRKTVTSLDVVYALKRQGRTLYGFGG')
def __init__(self):
PPBuilder.__init__(self)
def parse_structure(path):
"""
Parses a structure using Biopython's PDB/mmCIF Parser
Verifies the integrity of the structure (gaps) and its
suitability for the calculation (is it a complex?).
"""
print('[+] Reading structure file: {0}'.format(path))
fname = os.path.basename(path)
sname = '.'.join(fname.split('.')[:-1])
s_ext = fname.split('.')[-1]
_ext = set(('pdb', 'ent', 'cif'))
if s_ext not in _ext:
raise IOError('[!] Structure format \'{0}\' is not supported. Use \'.pdb\' or \'.cif\'.'.format(s_ext))
if s_ext in set(('pdb', 'ent')):
sparser = PDBParser(QUIET=1)
elif s_ext == 'cif':
sparser = MMCIFParser()
try:
s = sparser.get_structure(sname, path)
except Exception as e:
print('[!] Structure \'{0}\' could not be parsed'.format(sname), file=sys.stderr)
raise Exception(e)
# Keep first model only
if len(s) > 1:
print('[!] Structure contains more than one model. Only the first one will be kept')
model_one = s[0].id
for m in s.child_list[:]:
if m.id != model_one:
s.detach_child(m.id)
# Double occupancy check
for atom in list(s.get_atoms()):
if atom.is_disordered():
residue = atom.parent
sel_at = atom.selected_child
sel_at.altloc = ' '
sel_at.disordered_flag = 0
residue.detach_child(atom.id)
residue.add(sel_at)
# Remove HETATMs and solvent
res_list = list(s.get_residues())
def _is_het(residue):
return residue.id[0][0] == 'W' or residue.id[0][0] == 'H'
for res in res_list:
if _is_het(res):
chain = res.parent
chain.detach_child(res.id)
elif not is_aa(res, standard=True):
raise ValueError('Unsupported non-standard amino acid found: {0}'.format(res.resname))
n_res = len(list(s.get_residues()))
# Remove Hydrogens
atom_list = list(s.get_atoms())
def _is_hydrogen(atom):
return atom.element == 'H'
for atom in atom_list:
if _is_hydrogen(atom):
residue = atom.parent
residue.detach_child(atom.name)
# Detect gaps and compare with no. of chains
pep_builder = PPBuilder()
peptides = pep_builder.build_peptides(s)
n_peptides = len(peptides)
n_chains = len(set([c.id for c in s.get_chains()]))
if n_peptides != n_chains:
print('[!] Structure contains gaps:', file=sys.stderr)
for i_pp, pp in enumerate(peptides):
print('\t{1.parent.id} {1.resname}{1.id[1]} < Fragment {0} > {2.parent.id} {2.resname}{2.id[1]}'.format(i_pp, pp[0], pp[-1]), file=sys.stderr)
#raise Exception('Calculation cannot proceed')
return (s, n_chains, n_res)
def validate_structure(s, selection=None, clean=True):
# setup logging
logger = logging.getLogger('Prodigy')
# Keep first model only
if len(s) > 1:
logger.warning('[!] Structure contains more than one model. Only the first one will be kept')
model_one = s[0].id
for m in s.child_list[:]:
if m.id != model_one:
s.detach_child(m.id)
# process selected chains
chains = list(s.get_chains())
chain_ids = set([c.id for c in chains])
if selection:
sel_chains = []
# Match selected chain with structure
for sel in selection:
for c in sel.split(','):
sel_chains.append(c)
if c not in chain_ids:
raise ValueError('Selected chain not present in provided structure: {0}'.format(c))
# Remove unselected chains
_ignore = lambda x: x.id not in sel_chains
for c in chains:
if _ignore(c):
c.parent.detach_child(c.id)
# Double occupancy check
for atom in list(s.get_atoms()):
if atom.is_disordered():
residue = atom.parent
sel_at = atom.selected_child
sel_at.altloc = ' '
sel_at.disordered_flag = 0
residue.detach_child(atom.id)
residue.add(sel_at)
if clean:
# Remove HETATMs and solvent
res_list = list(s.get_residues())
_ignore = lambda r: r.id[0][0] == 'W' or r.id[0][0] == 'H'
for res in res_list:
if _ignore(res):
chain = res.parent
chain.detach_child(res.id)
elif not is_aa(res, standard=True):
raise ValueError('Unsupported non-standard amino acid found: {0}'.format(res.resname))
# Remove Hydrogens
atom_list = list(s.get_atoms())
_ignore = lambda x: x.element == 'H'
for atom in atom_list:
if _ignore(atom):
residue = atom.parent
residue.detach_child(atom.name)
# Detect gaps and compare with no. of chains
pep_builder = PPBuilder()
peptides = pep_builder.build_peptides(s)
n_peptides = len(peptides)
if n_peptides != len(chain_ids):
message = '[!] Structure contains gaps:\n'
for i_pp, pp in enumerate(peptides):
message += '\t{1.parent.id} {1.resname}{1.id[1]} < Fragment {0} > ' \
'{2.parent.id} {2.resname}{2.id[1]}\n'.format(i_pp, pp[0], pp[-1])
logger.warning(message)
# raise Exception(message)
return s
parser = PDB.PDBParser()
structure = parser.get_structure(myPDBfile, myPDBfile[1:3].lower() + "/pdb" + myPDBfile.lower() + ".ent")
if myAnswer == "No":
io = PDBIO()
io.set_structure(structure)
io.save(myPDBfile + ".pdb")
except:
print ("you structure is not available in the PDB")
parser = PDB.PDBParser()
structure = PDB.PDBParser().get_structure(myPDBfile, myPDBfile + ".pdb")
chains = [chain for chain in structure.get_chains()]
print (chains)
ppb = PPBuilder()
for chain in chains:
print (chain)
print (chain.get_id())
for chainseq in ppb.build_peptides(chain):
print (chainseq.get_sequence())
mySeq = chainseq.get_sequence()
myFastaA = ">" + myPDBfile + "_" + chain.get_id() + "\n" + chainseq.get_sequence()
print (myFastaA)
myFastaAfile = open(myPDBfile + "_" + chain.get_id() + ".fasta", "w")
myFastaAfile.write(">" + myPDBfile + "_" + chain.get_id() + "\n" + str(mySeq))
myFastaAfile.close()
myFastafiles = os.listdir(".")
myFastaIter = iter(myFastafiles)
