def download_pdb(config, pdb_code: str) -> Path:
"""
Download PDB structure from PDB.
:param pdb_code: 4 character PDB accession code.
:type pdb_code: str
:return: returns filepath to downloaded structure.
:rtype: str
"""
if not config.pdb_dir:
config.pdb_dir = Path("/tmp/")
# Initialise class and download pdb file
pdbl = PDBList()
pdbl.retrieve_pdb_file(pdb_code,
pdir=config.pdb_dir,
overwrite=True,
file_format="pdb")
# Rename file to .pdb from .ent
os.rename(
config.pdb_dir / f"pdb{pdb_code}.ent",
config.pdb_dir / f"{pdb_code}.pdb",
)
# Assert file has been downloaded
assert any(pdb_code in s for s in os.listdir(config.pdb_dir))
log.info(f"Downloaded PDB file for: {pdb_code}")
return config.pdb_dir / f"{pdb_code}.pdb"
def get_pdb(pdb_list):
import os
from Bio.PDB import PDBList
out_dir = "PDB_benchmark_structures\\"
pdb = pdb_list
number_ids = len(pdb)
filename = []
not_found = []
print("Downloading in %s:\n" % out_dir)
for i, pdbid in enumerate(pdb):
print('%s' % pdbid[:4])
pdbl = PDBList()
try:
if not os.path.exists("{}{}.pdb".format(out_dir, pdbid)):
x = pdbl.retrieve_pdb_file(pdbid[:4],
file_format='pdb',
pdir=out_dir)
filename.append(x)
except FileNotFoundError:
not_found.append(pdbid)
print("(NOTE) {} not found.".format(pdbid))
return filename
def retrieve_cif_list():
server = PDBList(server='ftp://ftp.wwpdb.org', pdb='input_files', obsolete_pdb=None ,verbose=True)
pdb_list = open('input_files/protlist.txt','r')
content = pdb_list.read().split()
pdb_list.close()
server.download_pdb_files(content,pdir="input_files/cif",file_format='mmCif', overwrite=True,obsolete= False)
def get_unique(input_df):
from Bio.PDB import PDBList
unique_pdbs = input_df.CPX.unique()
pdbl = PDBList()
for single_pdb in unique_pdbs:
pdbl.retrieve_pdb_file(single_pdb, pdir='PDB', file_format="pdb")
def download_pdbs(base_dir, protein_codes):
"""
Downloads the PDB database (or a part of it) as PDB files. Every protein is stored in it's own
directory (with name the PDB code) under base_dir.
:param base_dir: where to download all the proteins.
:param protein_codes: the PDB codes of the proteins that should be downloaded.
"""
prot_codes = []
if isinstance(protein_codes, dict):
for key in protein_codes.keys():
prot_codes += protein_codes[key]
else:
prot_codes = protein_codes
prot_codes = list(set(prot_codes))
from Bio.PDB import PDBList
failed = 0
attempted = len(prot_codes)
for code in prot_codes:
try:
pl = PDBList(pdb=os.path.join(base_dir, code.upper()))
pl.flat_tree = 1
pl.retrieve_pdb_file(pdb_code=code)
except IOError:
log.warning("Failed to download protein {}".format(code))
failed += 1
continue
log.info("Downloaded {0}/{1} molecules".format(attempted - failed,
attempted))
def get_structure(pdb_data_folder, structure_PDB_ID):
"""
Function to retrieve information about structure of specified molecule
:param pdb_data_folder: path to folder contaiting all 3D structures
:param structure_PDB_ID: structures PDB ID
:return: the structure object
"""
if (not is_non_zero_file(pdb_data_folder / (structure_PDB_ID + ".pdb"))
) and (not is_non_zero_file(pdb_data_folder /
(structure_PDB_ID + ".cif"))):
PDBList().retrieve_pdb_file(structure_PDB_ID, pdir=pdb_data_folder)
if is_non_zero_file(pdb_data_folder / (structure_PDB_ID + ".pdb")):
parser_pdb = PDBParser()
structure = parser_pdb.get_structure(
structure_PDB_ID, pdb_data_folder / (structure_PDB_ID + ".pdb"))
if is_non_zero_file(pdb_data_folder / (structure_PDB_ID + ".cif")):
try:
parser_cif = MMCIFParser(QUIET=True)
structure = parser_cif.get_structure(
structure_PDB_ID,
pdb_data_folder / (structure_PDB_ID + ".cif"))
except:
PDBList().retrieve_pdb_file(structure_PDB_ID,
pdir=pdb_data_folder,
file_format='pdb')
parser_pdb = PDBParser()
structure = parser_pdb.get_structure(
structure_PDB_ID,
pdb_data_folder / (structure_PDB_ID + ".pdb"))
return structure
def from_id(cls, pdb_id):
"""
Initialize structure by PDB ID (fetches
structure from RCSB servers)
Parameters
----------
pdb_id : str
PDB identifier (e.g. 1hzx)
Returns
-------
PDB
initialized PDB structure
"""
from urllib.error import URLError
from Bio.PDB import PDBList
pdblist = PDBList()
try:
# download PDB file to temporary directory
pdb_file = pdblist.retrieve_pdb_file(pdb_id, pdir=tempdir())
return cls.from_file(pdb_file, file_format="pdb")
except URLError as e:
raise ResourceError(
"Could not fetch PDB data for {}".format(pdb_id)
) from e
def build_xtalstable(dbpathstr, sourcedbpathstrs, pdbformat='cif'):
dbpath = Path(dbpathstr)
today = datetime.date.today()
todaystr = f'{today.year}-{today.month:02d}-{today.day:02d}'
conn = seqdbutils.gracefuldbopen(dbpath)
xtaldirpath = Path(dbpath).parent / 'Xtals'
if not xtaldirpath.exists():
os.mkdir(xtaldirpath)
c = conn.cursor()
c.execute(
'''CREATE TABLE IF NOT EXISTS XTALS (pdbid text, acc text, srcdb text,dldate text,
relpath text, pdbformat text, dlsuccess int, obsolete int)''')
pdbl = PDBList()
cxRE = re.compile('([A-Za-z0-9]{4})\[')
#by default folder containing xtals is named 'xtals' and in same directory as xtalsdb
for srcdbpathstr in sourcedbpathstrs:
srcdbpath = Path(srcdbpathstr)
srcdbstr = srcdbpath.name
src_conn = seqdbutils.gracefuldbopen(srcdbpath)
seqdbutils.check_tables_exist(src_conn, ['CAZYSEQDATA'])
src_c = src_conn.cursor()
src_c.execute(
'SELECT acc,pdbids FROM CAZYSEQDATA WHERE pdbids NOT NULL')
pdbrows = src_c.fetchall()
dbpdbs = []
dbaccs = []
for pdbrow in pdbrows:
pdbentry = pdbrow['pdbids']
accentry = pdbrow['acc']
pdbs = cxRE.findall(pdbentry)
dbaccs.extend([accentry for _ in range(len(pdbs))])
dbpdbs.extend(pdbs)
#dbpdbs=['4IM4']
pdbl.download_pdb_files(dbpdbs, pdir=xtaldirpath) #,obsolete=True)
for acc, pdb in zip(dbaccs, dbpdbs):
rel_pdbpath = xtaldirpath / f'{pdb}.cif'
download_success = os.path.exists(rel_pdbpath)
str_relpath = str(rel_pdbpath)
c.execute(
'''SELECT COUNT(*) FROM XTALS WHERE pdbid=(?) AND dlsuccess=(?)''',
(pdb, 1))
already_downloaded = c.fetchone()[0]
if already_downloaded:
continue
c.execute(
'''SELECT COUNT(*) FROM XTALS WHERE pdbid=(?) AND dlsuccess=(?)''',
(pdb, 0))
previously_failed = c.fetchone()[0]
if previously_failed:
if download_success:
print(f'new download of previously failed {pdb}')
c.execute(
'''UPDATE XTALS SET dldate = (?), dlsuccess = (?) WHERE pdbid=(?)''',
(todaystr, 1, pdb))
continue
c.execute('''INSERT INTO XTALS VALUES (?,?,?,?,?,?,?,?)''',\
(pdb,acc,srcdbstr,todaystr,str_relpath,pdbformat,download_success,None))
conn.commit()
src_conn.close()
conn.close()
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 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 fetchPDB(name, path):
"""Fetch a pdb and save to path"""
from Bio.PDB import PDBList
pdbname = os.path.join(path,name+'.pdb')
pdbl = PDBList()
filename = pdbl.retrieve_pdb_file(name,pdir=path)
os.rename(filename, pdbname)
return
def struct_retrieve(self):
"""
Retrieve PDB structure given argparse ID
"""
self.pdb_id = str(self.args.id_input)
pdbl = PDBList()
pdbl.retrieve_pdb_file(self.pdb_id, file_format='pdb', pdir=".")
def downloadPdb(pdb_list):
os.system("mkdir -p original_pdbs")
for pdb_id in pdb_list:
pdb = f"{pdb_id.lower()[:4]}"
pdbFile = pdb + ".pdb"
if not os.path.isfile("original_pdbs/" + pdbFile):
pdbl = PDBList()
name = pdbl.retrieve_pdb_file(pdb, pdir='.', file_format='pdb')
os.system(f"mv {name} original_pdbs/{pdbFile}")
def struct_retrieve(self):
"""
Retrieve PDB structure given argparse ID
"""
pdbl = PDBList()
pdbl.retrieve_pdb_file(self.pdb_id,
file_format='pdb',
pdir=f"{self.out_dir}/")
def download_structure_file(pdb_id: str) -> None:
"""Download PDB/mmCIF file with a user provided identifer from PDB using BioPython library
:param pdb_id: the protein id in protein data bank
:type pdb_id: str
"""
pdb_list = PDBList()
pdb_list.retrieve_pdb_file(pdb_id)
return
def generate_random_PDB(a, b, c):
for i in range(b):
c.append(a[randint(0, len(a))])
print(c)
pdb1=PDBList()
for i in c:
pdb1.retrieve_pdb_file(i, pdir = 'PDB')
return c
def load_data(experiment: str, in_file: str, out_dir: str) -> None:
#in_file = os.path.join('../data/', experiment, 'full_list.txt')
print(in_file)
#out_dir = os.path.join('../data/raw/', experiment)
pdbl = PDBList(server='http://ftp.wwpdb.org', verbose=False)
with open(in_file, 'r') as molecule_id_list:
molecule_id_list = molecule_id_list.readlines()
for molecule_id in tqdm(molecule_id_list):
pdbl.retrieve_pdb_file(molecule_id.strip('\n').split('_')[0], pdir=out_dir, file_format='pdb')
def getPDB(self, ID=None):
'''
Retrives a PDB file from RCSB when ID is supplied
or OBJECT.id is defined
'''
from Bio.PDB import PDBList
if ID is not None :
return PDBList().retrieve_pdb_file(ID, pdir = '.', file_format = 'pdb')
elif self.id is not None:
return PDBList().retrieve_pdb_file(self.id, pdir = '.', file_format = 'pdb')
def retrieve_cif(prot_id):
server = PDBList(server='ftp://ftp.wwpdb.org',
pdb='input_files',
obsolete_pdb=None,
verbose=True)
server.retrieve_pdb_file(prot_id,
pdir="input_files/cif",
file_format='mmCif',
overwrite=True,
obsolete=False)
def descargarPDB(pdb):
pdbl = PDBList()
pdbl.retrieve_pdb_file(pdb, pdir='./Script/PDB', file_format='pdb')
parser = PDBParser()
ent_file = './Script/PDB/pdb' + pdb.lower() + '.ent'
structure = parser.get_structure(pdb, ent_file)
io = PDBIO()
io.set_structure(structure)
pdb_structure_file = './Script/PDBStructure/' + pdb + '.pdb'
io.save(pdb_structure_file)
def download_PDB(pdb_ids, pdb_dir='.'):
# Define pdb file fetching class
pdbl = PDBList()
# Fetch every protein
for pdb_id in pdb_ids:
# Debug
logging.debug('PDB file which will be downloaded')
logging.debug(pdb_id)
# Execute fetching of the protein (pdb file)
pdbl.retrieve_pdb_file(pdb_id, pdir=pdb_dir, file_format='pdb')
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 download_structure_file(self,
outdir,
file_type=None,
load_header_metadata=True,
force_rerun=False):
"""Download a structure file from the PDB, specifying an output directory and a file type. Optionally download
the mmCIF header file and parse data from it to store within this object.
Args:
outdir (str): Path to output directory
file_type (str): ``pdb``, ``mmCif``, ``xml``, ``mmtf`` - file type for files downloaded from the PDB
load_header_metadata (bool): If header metadata should be loaded into this object, fastest with mmtf files
force_rerun (bool): If structure file should be downloaded even if it already exists
"""
ssbio.utils.double_check_attribute(
object=self,
setter=file_type,
backup_attribute='file_type',
custom_error_text=
'Please set file type to be downloaded from the PDB: '
'pdb, mmCif, xml, or mmtf')
# XTODO: check if outfile exists using ssbio.utils.force_rerun, pdblist seems to take long if it exists
# I know why - it's because we're renaming the ent to pdb. need to have mapping from file type to final extension
# Then check if file exists, if not then download again
p = PDBList()
with ssbio.utils.suppress_stdout():
structure_file = p.retrieve_pdb_file(pdb_code=self.id,
pdir=outdir,
file_format=file_type,
overwrite=force_rerun)
if not op.exists(structure_file):
log.debug('{}: {} file not available'.format(self.id, file_type))
raise URLError('{}.{}: file not available to download'.format(
self.id, file_type))
else:
log.debug('{}: {} file saved'.format(self.id, file_type))
# Rename .ent files to .pdb
if file_type == 'pdb':
new_name = structure_file.replace('pdb',
'').replace('ent', 'pdb')
os.rename(structure_file, new_name)
structure_file = new_name
self.load_structure_path(structure_file, file_type)
if load_header_metadata and file_type == 'mmtf':
self.update(parse_mmtf_header(structure_file))
if load_header_metadata and file_type != 'mmtf':
self.update(
parse_mmcif_header(
download_mmcif_header(pdb_id=self.id,
outdir=outdir,
force_rerun=force_rerun)))
def download_pdb_structure(pdb_code, pdb_file_name, file_path='.'):
"""Downloads a PDB structure from the Protein Data Bank"""
pdbl = PDBList()
file_name = pdbl.retrieve_pdb_file(pdb_code,
file_format='pdb',
pdir=file_path,
overwrite=True)
if os.path.exists(file_name):
os.rename(file_name, pdb_file_name)
else:
raise Exception("Can not download structure: {0}".format(pdb_code))
def download_pdb(pdb_id, pdbs_path):
"""Downloads a pdb file
Parameters
----------
pdb_id : str
pdb id
pdbs_path: str, optional
path of folder containing the pdbs (default is "pdbs")
"""
pdbl = PDBList(obsolete_pdb=True)
pdbl.download_pdb_files(pdb_id, file_format="pdb", pdir=pdbs_path)
def get_pdb(pdb_list):
from Bio.PDB import PDBList
out_dir = "PDB_benchmark_structures\\"
pdb = pdb_list
number_ids = len(pdb)
print("Downloading in %s:\n" % out_dir)
for ids in pdb:
print('%s' % ids[:4])
pdbl = PDBList()
pdbl.retrieve_pdb_file(ids[:4], file_format='pdb', pdir=out_dir)
def readFromPDBDatabase(self, pdbID, dir=None, type='mmCif'):
"""
Retrieve structure from PDB
:param pdbID:
:param dir: save structure in this directory
:param type: mmCif or pdb
:return: filename with pdb file
"""
if dir is None:
dir = os.getcwd()
pdbl = PDBList(pdb=dir)
fileName = pdbl.retrieve_pdb_file(pdbID, pdir=dir, file_format=type)
return os.path.abspath(fileName)
def struct_retrieve(self):
"""Retrieve the PDB structure from the terminal argument.
Args:
args [argparse object]: Contains the id_input argument
Returns:
prompt [str]: File successfully written
"""
pdbl = PDBList()
pdbl.retrieve_pdb_file(self.pdb_id, file_format='pdb', pdir=self.out_dir)
def get_pdb(ids, dir):
# Get structures ids
ids_list = []
with open(ids, 'r') as file:
for line in file.readlines():
ids_list.append(line.split('\n')[0])
# Selecting structures from PDB
pdbl = PDBList()
for i in ids_list:
print(i)
pdbl.retrieve_pdb_file(i, pdir=dir, file_format='pdb')
def download_pdb():
# download the selected pdb file
result_handle = open(project_dir + spacer + "my_blast.xml")
blast_record = NCBIXML.read(result_handle)
global choose_pdbChoices
i = 0
list_blast_results = []
for alignment in blast_record.alignments:
for hsp in alignment.hsps:
title = alignment.title
e_value = hsp.expect
print e_value
length = alignment.length
identities = hsp.identities
positives = hsp.positives
gaps = hsp.gaps
choice = ("title: " + str(title[0:100]) + " ..." +
"\n" + "score: " + str(e_value) + " " +
"length: " + str(length) + "\n" +
"identities: " + str(identities) + " " +
"positives: " + str(positives) + " " +
"gaps: " + str(gaps) + "\n" )
if i <5:
choose_pdbChoices.append(choice)
list_blast_results.append(title)
choice = ""
i += 1
print choose_pdbChoices
app = wx.App(0)
MainApp =MyFrame2(None)
MainApp.Show()
MainApp.Maximize()
app.MainLoop()
print "bla"
print row
title = list_blast_results[int(row)]
info_file= open(project_dir + spacer +"info.txt", "a")
info_file.write("\n you chose this blastresult: \n" + str(list_blast_results[int(row)]))
info_file.close()
print title[17:21]
global pdbfile
pdb_dir = project_dir + spacer + project_name +"_blast_pdb"
pdbfile = project_dir + spacer + "tmppdb.pdb"
pdbl = PDBList()
pdbl.retrieve_pdb_file(title[17:21], obsolete = False, pdir = pdb_dir)
title_lower = title[17:21].lower()
shutil.copyfile(pdb_dir + spacer + "pdb" + title_lower + ".ent", project_dir + spacer + "tmppdb.pdb")
def online_input(structure_name, file_format=None):
"""
Uses BioPython's PDBList to download tertiary structure from PDB
:param structure_name: PDB correct name of RNA structure
:param file_format: File format to pull from database, currently only 'pdb' is supported
:return:
"""
if not file_format:
file_format = 'pdb'
pdbl = PDBList()
return pdbl.retrieve_pdb_file(pdb_code=structure_name, file_format=file_format,
pdir=ROOT_DIR + '/downloadedStructures/')
def DownloadTemplate(template):
"""
Downloads the desired template from the pdb database.
Arguments:
template: pdb code of the template to download.
"""
pdbl = PDBList()
pdbl.retrieve_pdb_file(template,
obsolete=False,
pdir="./",
file_format="pdb")
def pdb_download(code, path=None):
"""Downloads the structure of the pdb on a file.
cod is the pdb code of the structure
path is the localization where it will be downloaded
Returns the file name where it is stored"""
logging.info("Downloading pdb %s.", code)
logging.captureWarnings(True)
pdbl = PDBList(obsolete_pdb=os.getcwd())
if path is None:
file = pdbl.retrieve_pdb_file(code)
else:
file = pdbl.retrieve_pdb_file(code, pdir=path)
logging.captureWarnings(False)
return file
def download_and_get_chains():
from Bio.PDB import PDBParser, PDBIO
failed = []
pdbs_dict = read_rostdb_entries()
io = PDBIO()
pdbl = PDBList()
for pdb_e, chains in pdbs_dict.items():
for chain_e in chains:
try:
pdbl.retrieve_pdb_file(pdb_e, pdir='./')
pdb = PDBParser().get_structure(pdb_e, 'pdb'+pdb_e.lower()+'.ent')
for chain in pdb.get_chains():
if chain.get_id() == chain_e:
io.set_structure(chain)
io.save(pdb.get_id() + '_' + chain.get_id() + '.pdb')
except:
failed.append((pdb_e, chain_e))
print("failures:", failed)
def uniblast(sequence, db, evalue, tgts):
os.environ['BLASTDB'] = db
seq ='>%s\n%s' % sequence
blast_line = ['psiblast', '-db', db, '-evalue', str(evalue),
'-num_iterations', '0', '-max_target_seqs', str(tgts),
'-outfmt', '6 qaccver saccver pident evalue qcovs length '
'staxid']
taxon_line = ['taxonkit', 'lineage', '-i', '7']
taxon_line2 = ['taxonkit', 'reformat', '-i', '8', '-f', '{s}']
blast = Popen(blast_line, stdin=PIPE, stdout=PIPE, stderr=PIPE,
env=os.environ.copy(), encoding='utf8', cwd=os.getcwdu())
o, e = blast.communicate(seq)
txnkit1 = Popen(taxon_line, stdin=PIPE, stdout=PIPE, stderr=PIPE,
env=os.environ.copy(), encoding='utf8', cwd=os.getcwdu())
o1, e1 = txnkit1.communicate(o[:o.find('\n\n')] )
txnkit2 = Popen(taxon_line2, stdin=PIPE, stdout=PIPE, stderr=PIPE,
env=os.environ.copy(), encoding='utf8', cwd=os.getcwdu())
o2, e2 = txnkit2.communicate(o1)
df = pd.read_table(StringIO(o2), sep='\t', header=None,
names='qaccver saccver pident evalue qcovs length '
'staxid lineage species'.split(),
quoting=csv.QUOTE_NONE, encoding='utf-8')
df = df.sort_values(by=['pident', 'evalue', 'qcovs', 'length'],
ascending=[False, True, False, False])
df = df[(df.pident > 30) & (df.qcovs > 70)][~df.saccver.duplicated()]
pdbl = PDBList()
pdb_codes = df.saccver.unique()
for i in pdb_codes:
pdb = i[:4]
ch = i[-1]
# Download pdb
file_path = pdbl.retrieve_pdb_file(pdb, pdir='PDBs', file_format='pdb')
parser = PDBParser()
st = parser.get_structure(pdb, file_path)
ou = PDBIO()
ou.set_structure(st)
os.remove(os.path.join('PDBs', pdb))
return df
def fetch_pdb(self, pdb_code, pdb_dir): pdb_list = PDBList() pdb_list.retrieve_pdb_file(pdb_code, pdir=pdb_dir)
f.write("\nPosicao: %s\n" %ref.positions)
f.write("\nComentarios: %s\n" %ref.comments)
f.write("\nReferencias: %s\n" %ref.references)
f.write("\nAutores: %s\n" %ref.authors)
f.write("\nTitulo: %s\n" %ref.title)
f.write("\nLocalizacao: %s\n\n" %ref.location)
break
except Exception:
break
f.close()
#análise da estrutura das proteínas relevantes com base nos ficheiros PDB encontrados (código baseado no desenvolvido pelo grupo 10)
parser = PDBParser()
ficheiro= open("analise_pdb.txt", "w")
structure = parser.get_structure('4F67', '4F67.pdb')
pdbl = PDBList()
pdbl.retrieve_pdb_file('4F67')
ficheiro.write("****Analise do ficheiro 4F67.pdb****\n")
ficheiro.write("\nPalavras Chave: %s\n" %structure.header['keywords'])
ficheiro.write("\nNome do Organismo: %s\n" %structure.header['name'])
ficheiro.write("\nCabecalho: %s" %structure.header['head'])
ficheiro.write("\nData da deposicao: %s\n" %structure.header['deposition_date'])
ficheiro.write("\nData da publicacaos: %s\n" %structure.header['release_date'])
ficheiro.write("\nMetodo usado: %s\n" %structure.header['structure_method'])
ficheiro.write("\nResolucao: %s\n" %structure.header['resolution'])
ficheiro.write("\nReferencia da estrutura: %s\n" %structure.header['structure_reference'])
ficheiro.write("\nReferencia de artigo: %s\n" %structure.header['journal_reference'])
ficheiro.write("\nAutor: %s\n" %structure.header['author'])
ficheiro.write("\nComposto: %s" %structure.header['compound'])
ficheiro.close()
def get_pdb_files(self):
"""Retrieves all pdb files corresponding the domains of interest."""
pdb_list = PDBList()
for pdb in self.pdb_ids:
# put files in the directory pointed by the self.directory variable
pdb_list.retrieve_pdb_file(pdb, pdir=self.directory)
#!/usr/bin/env python
from Bio.PDB import PDBList, PDBParser, Selection
import networkx as nx
import matplotlib.pyplot as plt
from pprint import pprint as pp
import numpy as np
distanceThreshold = 1 # sys.argv[2]
pdbList = PDBList()
pdbParser = PDBParser()
proteinName = "1MBN"
structure = pdbParser.get_structure(proteinName, pdbList.retrieve_pdb_file(proteinName))
resList = Selection.unfold_entities(structure, "R")
distanceMatrix = np.zeros([len(resList), len(resList)])
def genDistanceMatrix(dMatrix, rList):
caMap = {res.id[1]: res["CA"] for res in rList if "CA" in res}
pp(caMap)
pp(len(caMap))
genDistanceMatrix(distanceMatrix, resList)
#!/usr/bin/env python
from Bio.PDB import PDBList
p = PDBList()
atp227 = [
'1A0I',
'1A49',
'1A82',
'1ATP',
'1AYL',
'1B0U',
'1B76',
'1B8A',
'1BCP',
'1BCP',
'1CSN',
'1D9Z',
'1DY3',
'1E2Q',
'1E4G',
'1E8X',
'1EE1',
'1ESQ',
'1F2U',
'1F2U',
'1F9A',
'1FMW',
'1G21',
'1G3I',
'1G5T',
def fetch_pdb(self, pdb_code): pdb_list = PDBList() pdb_list.retrieve_pdb_file(pdb_code, pdir=self.pdb_dir) self._rename_pdb_file(pdb_code)
serialize(entries, pdbredo_seq_folder, entries_json_file)
except IOError:
raise('Missing some file')
else:
entries = retrieve(pdbredo_seq_folder, entries_json_file)
if new_subset:
#grab some subset of the pdb, download files and parse for uniprot xreferences
os.mkdir(pdb_folder)
os.mkdir(uniprot_folder)
#select a pseudo_random subset of entries by slicing the entries dict
#(which is in pseudo-random) order
PDB_subset = list(entries.keys())[:n_entries]
PDB_subset_nochain = [x.split('_')[0] for x in PDB_subset]
#fetch and save all the pdb files
pdbl = PDBList()
for entry in PDB_subset_nochain:
pdbl.retrieve_pdb_file(entry, pdir=pdb_folder)
#serialize the PDB list for future use
serialize(PDB_subset, pdb_folder, pdb_list)
# parse the pdb headers for DBREF to uniprot
pdb_to_uniprot = find_uniprot_in_pdb(PDB_subset_nochain, pdb_folder)
if recompute_clean:
PDB_subset = retrieve(pdb_folder, pdb_list)
PDB_subset_nochain = [x.split('_')[0] for x in PDB_subset]
# parse the pdb headers for DBREF to uniprot
pdb_to_uniprot = find_uniprot_in_pdb(PDB_subset_nochain, pdb_folder)
#determine the uniprot references to fetch
to_fetch = []
for entry in pdb_to_uniprot.keys():
"""
Module Description:
This file imports PDB files from Network, and store them at appropiate place
"""
from Bio.PDB import PDBList
PDBListTemp = PDBList()
FILE = open("pfam_list.txt","r")
IN = FILE.readline()
while IN:
print IN
PDBListTemp.retrieve_pdb_file(IN)
def download_pdb(args):
from Bio.PDB import PDBParser, PDBIO, PDBList
io = PDBIO()
pdbl = PDBList()
pdbl.retrieve_pdb_file(args['name'], pdir=args['path'])
def get_pdb_file(self, directory):
"""Retrieves a pdb file."""
pdb_list = PDBList()
pdb_list.retrieve_pdb_file(self.pdb_id, pdir=directory)