def write_PDB(entity, file, pdbid=None, chainid=None):
"""Write PDB file with HEADER and TITLE."""
with as_handle(file, 'w') as fp:
try:
if 'S' == entity.level:
if not pdbid:
pdbid = entity.header.get('idcode', None)
hdr = entity.header.get('head', None)
dd = entity.header.get('deposition_date', None)
if hdr:
fp.write(('HEADER {:40}{:8} {:4}\n'
).format(hdr.upper(), (dd or ''), (pdbid or '')))
nam = entity.header.get('name', None)
if nam:
fp.write('TITLE ' + nam.upper() + '\n')
io = PDBIO()
io.set_structure(entity)
io.save(fp)
else:
raise PDBException("level not 'S': "
+ str(entity.level))
except KeyError:
raise Exception(
"write_PIC: argument is not a Biopython PDB Entity "
+ str(entity))
def scwrl(self, altseq):
""" Repacks sidechains using SCWRL4 and returns a copy """
io = PDBIO()
seqfname = "temp/%d.txt" % multidigit_rand(10)
with open(seqfname, 'wb') as seqfile:
structfile = "temp/%d.pdb" % multidigit_rand(10)
seqfile.write(altseq)
scwrlfile = structfile + ".scwrl"
io.set_structure(self.structure)
io.save(structfile)
cmd = [
"scwrl", "-0", "-i", structfile, '-s', seqfname, '-o', scwrlfile
]
print "\n%s" % ' '.join(cmd)
sp.Popen(cmd, stdout=sp.PIPE, stderr=sp.PIPE).communicate()
p = PDBParser()
with open(scwrlfile, 'rb') as fin:
filterwarnings('ignore', category=PDBConstructionWarning)
s = p.get_structure(self.id, scwrlfile)
resetwarnings()
s = PDBMapStructure(s, pdb2pose={}, refseq=self.refseq)
os.remove(structfile)
os.remove(scwrlfile)
os.remove(seqfname)
return s
def test_pdbio_write_pqr_structure(self):
"""Write a full structure using PDBIO."""
# Create a PDBIO object in pqr mode with example_structure as an argument
io = PDBIO(is_pqr=True)
io.set_structure(self.example_structure)
# Write to a temporary file
filenumber, filename = tempfile.mkstemp()
os.close(filenumber)
try:
# Export example_structure to a temp file
io.save(filename)
# Parse exported structure
output_struct = self.pqr_parser.get_structure("1a8o", filename)
# Comparisons
self.assertEqual(len(output_struct),
len(self.example_structure)) # Structure Length
original_residues = len(list(
self.example_structure.get_residues()))
parsed_residues = len(list(output_struct.get_residues()))
self.assertEqual(parsed_residues,
original_residues) # Number of Residues
# Atom-wise comparison
original_atoms = self.example_structure.get_atoms()
for atom in output_struct.get_atoms():
self.assertEqual(atom, next(original_atoms))
finally:
os.remove(filename)
def cut_7_helix(self, source_pdb, target_folder, offset=0):
io = PDBIO()
parser = PDBParser(QUIET=True)
code = source_pdb[-8:-4]
struct = parser.get_structure(code, source_pdb)
plane = list(struct[0][' '].get_residues())
try:
up_plane = plane[1]['O'].get_coord()[2] + offset
except KeyError:
up_plane = plane[0]['O'].get_coord()[2] + offset
try:
down_plane = plane[0]['N'].get_coord()[2] - offset
except KeyError:
down_plane = plane[1]['N'].get_coord()[2] - offset
chain_id = self.get_TM_chain(list(struct[0]), up_plane, down_plane)
chain = struct[0][chain_id]
io.set_structure(struct)
io.save(target_folder + code + '_tm.pdb',
self.TMSelect(up_plane, down_plane, chain))
def main(pdbfile, scheme, outfile):
pdb_io = PDBIO()
parser = PDBParser()
structure = parser.get_structure('self', pdbfile)
model = structure[0]
chain = ' '
anarci_dict = {}
fastafile = Path(pdbfile).stem + '.fasta'
with open(fastafile, 'w+') as ff:
subprocess.run(['pdb_tofasta', '-multi', pdbfile], stdout=ff)
out = subprocess.run(['anarci', '-i', fastafile, '--scheme', scheme],
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT)
output = out.stdout.decode("utf-8").splitlines()
for line in output:
l = line.strip()
li = line.split()
if line.startswith('#'):
if re.search("PDB", l):
ch = l.split('|')
chain = ch[1]
anarci_dict[chain] = []
elif line.startswith(chain):
if len(li) == 3:
if li[2] == '-':
continue
else:
ch = li[0]
resseq = int(li[1])
inscode = ' '
residue = li[2]
het = ' '
tuple = (het, resseq, inscode)
anarci_dict[chain].append(tuple)
elif len(li) == 4:
ch = li[0]
resseq = int(li[1])
inscode = str(li[2])
residue = li[3]
het = ' '
tuple = (het, resseq, inscode)
anarci_dict[chain].append(tuple)
else:
continue
for residue in structure.get_residues():
residue.id = (' ', residue.id[1] + 900, residue.id[2])
for d in anarci_dict:
count = 0
for i, residue in enumerate(model[d]):
if i < len(anarci_dict[d]):
residue.id = anarci_dict[d][i]
count = residue.id[1]
else:
count = count + 1
residue.id = (' ', count, ' ')
pdb_io.set_structure(structure)
pdb_io.save(outfile)
def splitOnePDB(fname, outPath):
try:
s= parser.get_structure(fname, fname)
except Exception:
print ("Error loading pdb")
return 0
banLenChains=[]
try:
for chain in s[0]:
badResInChain=0
for res in chain.get_list():
if not is_aa(res,standard=True):
badResInChain+=1
chainLen= sum(1 for res in chain if "CA" in res) - badResInChain
if chainLen < MIN_SEQ_LEN or chainLen > MAX_SEQ_LEN:
print(chainLen)
banLenChains.append(chain.get_id())
except KeyError:
print ("Not good model")
return 0
for badChainId in banLenChains:
s[0].detach_child(badChainId)
receptorChainList= []
ligandChainList= []
if len( s[0].get_list())<2:
print(s)
print( s[0].get_list())
print("Not enough good chains")
return 0
for chain1 in s[0]:
tmpReceptorList=[]
for chain2 in s[0]:
if chain1!= chain2:
tmpReceptorList.append(chain2)
if len(tmpReceptorList)>1 or not tmpReceptorList[0] in ligandChainList:
ligandChainList.append(chain1)
receptorChainList.append(tmpReceptorList)
prefix= os.path.basename(fname).split(".")[0]
for i, (ligandChain, receptorChains) in enumerate(zip(ligandChainList, receptorChainList)):
io=PDBIO()
ligandStruct= Structure(prefix+"ligand")
ligandStruct.add(Model(0))
ligandChain.set_parent(ligandStruct[0])
ligandStruct[0].add(ligandChain)
io.set_structure(ligandStruct)
io.save(os.path.join(outPath,prefix+"-"+str(i)+"_l_u.pdb"))
io=PDBIO()
receptorStruct= Structure(prefix+"receptor")
receptorStruct.add(Model(0))
for receptorChain in receptorChains:
receptorChain.set_parent(receptorStruct[0])
receptorStruct[0].add(receptorChain)
io.set_structure(receptorStruct)
io.save(os.path.join(outPath,prefix+"-"+str(i)+"_r_u.pdb"))
print( "ligand:", ligandChain, "receptor:",receptorChains )
def write_PDB(entity: Structure,
file: str,
pdbid: str = None,
chainid: str = None) -> None:
"""Write PDB file with HEADER and TITLE."""
enumerate_atoms(entity)
with as_handle(file, "w") as fp:
try:
if "S" == entity.level:
if hasattr(entity, "header"):
if not pdbid:
pdbid = entity.header.get("idcode", None)
hdr = entity.header.get("head", None)
dd = pdb_date(entity.header.get("deposition_date", None))
if hdr:
fp.write(("HEADER {:40}{:8} {:4}\n").format(
hdr.upper(), (dd or ""), (pdbid or "")))
nam = entity.header.get("name", None)
if nam:
fp.write("TITLE " + nam.upper() + "\n")
io = PDBIO()
io.set_structure(entity)
io.save(fp, preserve_atom_numbering=True)
else:
raise PDBException("level not 'S': " + str(entity.level))
except KeyError:
raise Exception(
"write_PIC: argument is not a Biopython PDB Entity " +
str(entity))
def collect_1(self, checkboard = []):
def getChains(s):
ret = s.split('___')[:2]
assert(len(ret) == 2)
return ret
parser = PDBParser()
io = PDBIO()
for f in self.files:
if not checkboard:
break
if f not in checkboard:
continue
try:
os.mkdir(os.path.join( self.outpath, f))
except OSError as e:
if e.errno != errno.EEXIST:
raise
structure = parser.get_structure(f, os.path.join(self.inpath, f))
chain_A, chain_B = getChains(f)
io.set_structure(structure[0]['A'])
io.save(os.path.join(self.outpath,f,chain_A + '.pdb'))
io.set_structure(structure[0]['B'])
io.save(os.path.join(self.outpath,f,chain_B + '.pdb'))
#make this module can be reuse to other application
self.then_do(f)
#remove the finished file from checkboard
checkboard.remove(f)
def CreatePDB(self, coordArray, fPath, ofile):
sloppyparser = PDBParser(PERMISSIVE=True, QUIET=True)
structure = sloppyparser.get_structure("MD_system", fPath)
print("\nGenerating PDB file...")
sb = StructureBuilder()
sb.set_header(structure.header)
# Iterate through models
for i in range(len(list(structure.get_models()))):
# Iterate through chains
models = list(structure.get_models())
counter = 0
for j in range(len(list(models[i].get_chains()))):
chains = list(models[i].get_chains())
#Iterate thgouth residues
for k in range(len(list(chains[j].get_residues()))):
#Iterate through
residues = list(chains[j].get_residues())
for l in range(len(list(residues[k].get_atoms()))):
#Set coord for each
for atom in structure[i][chains[j].id][
residues[k].id].get_atoms():
structure[i][chains[j].id][residues[k].id][
atom.id].set_coord(
np.array((float(coordArray[counter][0]),
float(coordArray[counter][1]),
float(coordArray[counter][2]))))
#print(structure[i][chains[j].id][residues[k].id][atom.id].get_vector())
counter += 1
io = PDBIO()
io.set_structure(structure)
io.save(ofile)
print("Transform file written to: " + ofile)
def run_naccess(model,
pdb_file,
probe_size=None,
z_slice=None,
naccess='naccess',
temp_path='/tmp/'):
# make temp directory;
tmp_path = tempfile.mkdtemp(dir=temp_path)
# file name must end with '.pdb' to work with NACCESS
# -> create temp file of existing pdb
# or write model to temp file
handle, tmp_pdb_file = tempfile.mkstemp('.pdb', dir=tmp_path)
os.close(handle)
if pdb_file:
pdb_file = os.path.abspath(pdb_file)
shutil.copy(pdb_file, tmp_pdb_file)
else:
writer = PDBIO()
writer.set_structure(model.get_parent())
writer.save(tmp_pdb_file)
# chdir to temp directory, as NACCESS writes to current working directory
old_dir = os.getcwd()
os.chdir(tmp_path)
# create the command line and run
# catch standard out & err
command = [naccess, tmp_pdb_file]
if probe_size:
command.extend(['-p', probe_size])
if z_slice:
command.extend(['-z', z_slice])
p = subprocess.Popen(command,
universal_newlines=True,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
out, err = p.communicate()
os.chdir(old_dir)
rsa_file = tmp_pdb_file[:-4] + '.rsa'
asa_file = tmp_pdb_file[:-4] + '.asa'
# Alert user for errors
if err.strip():
warnings.warn(err)
if (not os.path.exists(rsa_file)) or (not os.path.exists(asa_file)):
raise Exception('NACCESS did not execute or finish properly.')
# get the output, then delete the temp directory
with open(rsa_file) as rf:
rsa_data = rf.readlines()
with open(asa_file) as af:
asa_data = af.readlines()
# shutil.rmtree(tmp_path, ignore_errors=True)
return rsa_data, asa_data
def extract(structure, chain_id, start, end, filename):
"""
Write out selected portion to filename.
"""
sel = ChainSelector(chain_id, start, end)
io = PDBIO()
io.set_structure(structure)
io.save(filename, sel)
def save_chain_to(chain, filename: str):
from Bio.PDB.PDBIO import PDBIO
io = PDBIO()
# io.set_structure(chain.get_bio_chain())
structure = Structure(filename)
structure.add(chain)
io.set_structure(structure)
io.save(filename)
def extract(structure, chain_id, start, end, filename):
"""
Write out selected portion to filename.
"""
sel = ChainSelector(chain_id, start, end)
io = PDBIO()
io.set_structure(structure)
io.save(filename, sel)
def writeFileBioPDB(struct,fn): io = PDBIO() io.set_structure(struct) try: io.save(fn) except Exception, e: print " "+str(e) sys.exit(1)
def splitOnePDB(fname, chainIdL, chainIdR, outPath):
print(os.path.basename(fname))
try:
s = parser.get_structure(os.path.basename(fname), fname)
except Exception:
print("Error loading pdb")
return 0
banLenChains = []
try:
for chain in s[0]:
badResInChain = 0
for res in chain.get_list():
if not is_aa(res, standard=True) and res.resname != "HOH":
badResInChain += 1
# for res in chain: print(res)
chainLen = sum(1 for res in chain if "CA" in res) - badResInChain
if chainLen < MIN_SEQ_LEN or chainLen > MAX_SEQ_LEN:
print(chain, chainLen)
banLenChains.append(chain.get_id())
except KeyError:
print("Not good model")
return 0
# print(banLenChains)
if len(s[0].get_list()) - len(banLenChains) < 2:
print(s)
print(s[0].get_list())
print("Not enough good chains")
return 0
ligandChains, receptorChains = findNeigChains(s, chainIdL, chainIdR)
print("ligand:", ligandChains, "receptor:", receptorChains)
prefix = os.path.basename(fname).split(".")[0]
io = PDBIO()
ligandStruct = Structure(prefix + "ligand")
ligandStruct.add(Model(0))
for ligandChain in ligandChains:
ligandChain.set_parent(ligandStruct[0])
ligandStruct[0].add(ligandChain)
io.set_structure(ligandStruct)
io.save(
os.path.join(outPath, prefix + "-" + chainIdL + chainIdR + "_l_u.pdb"))
io = PDBIO()
receptorStruct = Structure(prefix + "receptor")
receptorStruct.add(Model(0))
for receptorChain in receptorChains:
receptorChain.set_parent(receptorStruct[0])
receptorStruct[0].add(receptorChain)
io.set_structure(receptorStruct)
io.save(
os.path.join(outPath, prefix + "-" + chainIdL + chainIdR + "_r_u.pdb"))
def filter_pdb(input_path, output_path, chain):
"""
Filter a PDB file to the chain of interest
"""
pdb_name = Path(input_path).stem
pdb_parser = PDBParser()
structure = pdb_parser.get_structure(pdb_name, input_path)
pdbio = PDBIO()
pdbio.set_structure(structure)
pdbio.save(output_path, select=ChainSelect(chain))
def export_structure(structure, name, format):
"""
Writes the strucuture into a file. The file can be either a pdb or a mmcif.
"""
if format == "pdb":
io = PDBIO()
elif format == "cif":
io = pdb.MMCIFIO()
io.set_structure(structure)
io.save(name)
def pose(self):
""" Loads the PDBMapStructure as a Rosetta::Pose object """
import_rosetta()
io = PDBIO()
io.set_structure(self.structure)
with tempfile.NamedTemporaryFile('wrb',suffix='.pdb',delete=False) as tf:
io.save(tf.name)
pose = rosetta.Pose()
rosetta.pose_from_pdb(pose,tf.name)
os.remove(tf.name)
return pose
def get_pdb_string(pdb_path, select=None):
"""
Get string representation of a PDB file, filtered using select as in Bio.PDB.PDBIO
"""
pdb_parser = PDBParser()
structure = pdb_parser.get_structure('_', pdb_path)
pdbio = PDBIO()
pdbio.set_structure(structure)
with StringIO('PDB') as virtual_pdb_file:
pdbio.save(virtual_pdb_file, select=select)
return virtual_pdb_file.getvalue()
def dssp_dict_from_structure(structure, dssp="dsspcmbi", id=None):
"""
In keeping with the spirit of functional programming...
Creates a DSSP dictionary from more than just a filename.
Pipes the structure into a dssp process if you send it one.
@type structure: filename (string), Bio.PDB.Entity, hpf.hddb.db.Structure
@return (Bio.PDB.Entity, dssp, keys)
"""
from subprocess import Popen, PIPE
from cStringIO import StringIO
dssp = Popen("which %s" % dssp, shell=True, stdout=PIPE).communicate()[0].strip()
assert os.path.exists(dssp)
# If we have a structure object we will pipe it into DSSP
# otherwise it will be loaded and parsed.
if isinstance(structure, basestring):
pipe = None
dssp = "%s %s" % (dssp, structure)
from Bio.PDB import PDBParser
structure = PDBParser().get_structure(id if id else structure, structure)
else:
# We write to a buffer which will be piped into the DSSP stdin
# using pipe.getvalue(), the dssp stdin option must be added
dssp = "%s --" % dssp
import tempfile
pipe = tempfile.NamedTemporaryFile("w")
from Bio.PDB.Structure import Entity, Structure as BioStructure
if isinstance(structure, Entity):
s = structure
while s.get_parent() != None:
s = s.get_parent()
from Bio.PDB.PDBIO import PDBIO
io = PDBIO()
io.set_structure(s)
io.save(pipe.name)
else:
# Otherwise this is of type hpf.hddb.db.Structure
# avoid importing the class and mapped meta table stuff
with pipe as handle:
pipe.write(structure.text)
structure = structure.structure
# execute the process, piping data if necessary
# print pipe.getvalue()
out, err = Popen(dssp, shell=True, stdin=pipe if pipe else None, stdout=PIPE, stderr=PIPE).communicate()
io = StringIO()
io.write(out)
io.seek(0)
return (structure,) + make_dssp_dict(io)
def run_naccess(model, pdb_file, probe_size=None, z_slice=None,
naccess='naccess', temp_path='/tmp/'):
# make temp directory;
tmp_path = tempfile.mkdtemp(dir=temp_path)
# file name must end with '.pdb' to work with NACCESS
# -> create temp file of existing pdb
# or write model to temp file
handle, tmp_pdb_file = tempfile.mkstemp('.pdb', dir=tmp_path)
os.close(handle)
if pdb_file:
pdb_file = os.path.abspath(pdb_file)
shutil.copy(pdb_file, tmp_pdb_file)
else:
writer = PDBIO()
writer.set_structure(model.get_parent())
writer.save(tmp_pdb_file)
# chdir to temp directory, as NACCESS writes to current working directory
old_dir = os.getcwd()
os.chdir(tmp_path)
# create the command line and run
# catch standard out & err
command = [naccess, tmp_pdb_file]
if probe_size:
command.extend(['-p', probe_size])
if z_slice:
command.extend(['-z', z_slice])
p = subprocess.Popen(command, universal_newlines=True,
stdout=subprocess.PIPE, stderr=subprocess.PIPE)
out, err = p.communicate()
os.chdir(old_dir)
rsa_file = tmp_pdb_file[:-4] + '.rsa'
asa_file = tmp_pdb_file[:-4] + '.asa'
# Alert user for errors
if err.strip():
warnings.warn(err)
if (not os.path.exists(rsa_file)) or (not os.path.exists(asa_file)):
raise Exception('NACCESS did not execute or finish properly.')
# get the output, then delete the temp directory
with open(rsa_file) as rf:
rsa_data = rf.readlines()
with open(asa_file) as af:
asa_data = af.readlines()
# shutil.rmtree(tmp_path, ignore_errors=True)
return rsa_data, asa_data
def write_pdb(structure,
file_name,
selector=None,
preserve_atom_numbering=False):
""" Write a PDB file from a given structure with a given file_name. Optionally, write specific atoms with selector and preserve atom numbering. """
writer = PDBIO()
writer.set_structure(structure)
if selector is None:
writer.save(file_name, preserve_atom_numbering=preserve_atom_numbering)
else:
writer.save(file_name,
selector,
preserve_atom_numbering=preserve_atom_numbering)
def run_naccess(model,
pdb_file,
probe_size=None,
z_slice=None,
naccess='naccess',
temp_path='/tmp/'):
# make temp directory; chdir to temp directory,
# as NACCESS writes to current working directory
tmp_path = tempfile.mktemp(dir=temp_path)
os.mkdir(tmp_path)
old_dir = os.getcwd()
os.chdir(tmp_path)
# file name must end with '.pdb' to work with NACCESS
# -> create temp file of existing pdb
# or write model to temp file
tmp_pdb_file = tempfile.mktemp('.pdb', dir=tmp_path)
if pdb_file:
os.system('cp %s %s' % (pdb_file, tmp_pdb_file))
else:
writer = PDBIO()
writer.set_structure(model.get_parent())
writer.save(tmp_pdb_file)
# create the command line and run
# catch standard out & err
command = '%s %s ' % (naccess, tmp_pdb_file)
if probe_size:
command += '-p %s ' % probe_size
if z_slice:
command += '-z %s ' % z_slice
in_, out, err = os.popen3(command)
in_.close()
stdout = out.readlines()
out.close()
stderr = err.readlines()
err.close()
# get the output, then delete the temp directory
rsa_file = tmp_pdb_file[:-4] + '.rsa'
rf = open(rsa_file)
rsa_data = rf.readlines()
rf.close()
asa_file = tmp_pdb_file[:-4] + '.asa'
af = open(asa_file)
asa_data = af.readlines()
af.close()
os.chdir(old_dir)
os.system('rm -rf %s >& /dev/null' % tmp_path)
return rsa_data, asa_data
def save_structure(self, filename, superimpose_structure=None):
""" Save the generated sample to a pdb file.
@param filename: The file to which the structure will be written.
@type filename: str
@param superimpose_structure: Structure to which the sampled structure
is to be superimposed.
@type superimpose_structure: Structure
"""
io = PDBIO()
io.set_structure(self.get_structure())
io.save(filename)
def main():
if len(sys.argv) < 2:
print("Please input fasta filename as an argument for the script")
sys.exit()
filename = sys.argv[1]
if filename.endswith('.fasta'):
blast_result = blast_sequence(filename)
else:
print("Unknown file format (need to be fasta file)")
sys.exit()
pdb_filepath = download_pdb_support_sequence(blast_result)
filter_pdb(pdb_filepath)
p = PDBParser(PERMISSIVE=1)
structure = p.get_structure('file', 'filtered.pdb')
seqObj = generate_fasta_from_pdb(structure)
target_seq = SeqIO.read(filename, format="fasta").seq
alignments = pairwise_alignement(target_seq, seqObj.seq)
#Consider CA atoms only for computing distances
ca_atoms = [
atom for model in structure for chain in model for residue in chain
for atom in residue if atom.get_id() == "CA"
]
gaps = insert_gaps_in_atomlist(ca_atoms, alignments[0][0])
insertions = insert_gaps_in_atomlist(ca_atoms, alignments[0][1])
print(gaps)
print(insertions)
print("Searching for best part for gaps")
gap_parts = get_gaps_parts(gaps)
print("Searching for best part for insertions")
ins_parts = get_gaps_parts(
insertions, get_insertion_type(alignments[0][0], alignments[0][1]))
print("Completing gaps/insertions by found parts")
complete_atoms = [
atom for model in structure for chain in model for residue in chain
for atom in residue
]
complete_atoms = insert_gaps_insertions_in_atomlist(
complete_atoms, ins_parts, gap_parts)
print("Writing final pdb file in : final.pdb")
io = PDBIO()
io.set_structure(build_structure(complete_atoms))
io.save('final.pdb')
def generate_output_file(final_model, out_name):
""" This function takes as input both the final model created with the building algorithm and the output filename given by the user (if not defined, is macrocomplex by default). Eventually, it returns the file saved in either ".pdb" or ".mmcif" format. """
out_name = str(out_name.strip())
# If the output file is too big, we save it in ".mmcif" format
if len(list(final_model[0].get_atoms())) > 99999 or len(
list(final_model[0].get_chains())) > 62:
mmcif_IO = MMCIFIO()
mmcif_IO.set_structure(final_model[0])
mmcif_IO.save(out_name + ".cif")
# Otherwise, save it ".pdb" format
else:
pdb_IO = PDBIO()
pdb_IO.set_structure(final_model[0])
pdb_IO.save(out_name + ".pdb")
def clean(self):
p = PDBParser()
io = PDBIO()
with tempfile.NamedTemporaryFile('wrb',suffix='.pdb',delete=False) as tf:
io.set_structure(self.structure)
io.save(tf.name)
cmd = ['lib/clean_pdb.py',tf.name,'ignorechain','nopdbout']
logger.info("Shell to: %s"%' '.join(cmd))
proc = sp.Popen(cmd,stdout=sp.PIPE)
s = p.get_structure(self.get_id(),proc.stdout)
p = lib.PDBMapIO.PDBMapParser()
s = p.process_structure(s,force=True)
s = PDBMapStructure(s,pdb2pose=self._pdb2pose,refseq=self.refseq)
os.remove(tf.name)
return s
def main(args):
"""Main script"""
pdb_name = Path(args.pdb).stem
# deal with FoldX repaired PDBs
if pdb_name.endswith('_Repair'):
pdb_name = pdb_name.replace('_Repair', '')
pdb_parser = PDBParser()
structure = pdb_parser.get_structure(pdb_name, args.pdb)
sections = import_sections(args.yaml, pdb_name)
pdbio = PDBIO()
pdbio.set_structure(structure)
pdbio.save(sys.stdout, select=SectionSelecter(sections))
def run_naccess(model, pdb_file, probe_size=None, z_slice=None,
naccess='naccess', temp_path='/tmp/'):
# make temp directory;
tmp_path = tempfile.mkdtemp(dir=temp_path)
# file name must end with '.pdb' to work with NACCESS
# -> create temp file of existing pdb
# or write model to temp file
handle, tmp_pdb_file = tempfile.mkstemp('.pdb', dir=tmp_path)
os.close(handle)
if pdb_file:
pdb_file = os.path.abspath(pdb_file)
shutil.copy(pdb_file, tmp_pdb_file)
else:
writer = PDBIO()
writer.set_structure(model.get_parent())
writer.save(tmp_pdb_file)
# chdir to temp directory, as NACCESS writes to current working directory
old_dir = os.getcwd()
os.chdir(tmp_path)
# create the command line and run
# catch standard out & err
command = [naccess, tmp_pdb_file]
if probe_size:
command.extend(['-p', probe_size])
if z_slice:
command.extend(['-z', z_slice])
# p = subprocess.Popen(command, universal_newlines=True,
# stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell = True)
p = subprocess.call(" ".join(command), shell=True)
#out, err = p.communicate()
os.chdir(old_dir)
# get the output, then delete the temp directory
rsa_file = tmp_pdb_file[:-13] + 'SIFTS.rsa'
with open(rsa_file) as rf:
rsa_data = rf.readlines()
asa_file = tmp_pdb_file[:-13] + 'SIFTS.asa'
with open(asa_file) as af:
asa_data = af.readlines()
shutil.rmtree(tmp_path, ignore_errors=True)
return rsa_data, asa_data
def _temp(self,structure):
if isinstance(structure,basestring):
assert(os.path.exists(structure))
return structure
elif isinstance(structure,Structure):
temp = tempfile.NamedTemporaryFile("w")
# Save the structure in a tempfile
from Bio.PDB.PDBIO import PDBIO
io = PDBIO()
io.set_structure(structure)
io.save(temp)
self._temp_files.append(temp)
return temp.name
else:
print type(structure)
raise TypeError(structure)
def run_naccess(model, pdb_file, probe_size = None, z_slice = None, \
naccess = 'naccess', temp_path = '/tmp/'):
# make temp directory; chdir to temp directory,
# as NACCESS writes to current working directory
tmp_path = tempfile.mktemp(dir = temp_path)
os.mkdir(tmp_path)
old_dir = os.getcwd()
os.chdir(tmp_path)
# file name must end with '.pdb' to work with NACCESS
# -> create temp file of existing pdb
# or write model to temp file
tmp_pdb_file = tempfile.mktemp('.pdb', dir = tmp_path)
if pdb_file:
os.system('cp %s %s' % (pdb_file, tmp_pdb_file))
else:
writer = PDBIO()
writer.set_structure(model.get_parent())
writer.save(tmp_pdb_file)
# create the command line and run
# catch standard out & err
command = '%s %s ' % (naccess, tmp_pdb_file)
if probe_size:
command += '-p %s ' % probe_size
if z_slice:
command += '-z %s ' % z_slice
in_, out, err = os.popen3(command)
in_.close()
stdout = out.readlines()
out.close()
stderr = err.readlines()
err.close()
# get the output, then delete the temp directory
rsa_file = tmp_pdb_file[:-4] + '.rsa'
rf = open(rsa_file)
rsa_data = rf.readlines()
rf.close()
asa_file = tmp_pdb_file[:-4] + '.asa'
af = open(asa_file)
asa_data = af.readlines()
af.close()
os.chdir(old_dir)
os.system('rm -rf %s >& /dev/null' % tmp_path)
return rsa_data, asa_data
def remove_residues(self, request, claims):
"""
Remove residues from a PDB structure
For a detailed input description see the file:
mdstudio_structures/schemas/endpoints/removed_residues_request_v1.json
And for a detailed description of the output see:
mdstudio_structures/schemas/endpoints/removed_residues_response_v1.json
"""
request['workdir'] = os.path.abspath(request['workdir'])
# Parse the structure
parser = PDBParser(PERMISSIVE=True)
struc_obj = StringIO(request.get('mol'))
structure = parser.get_structure('mol_object', struc_obj)
struc_obj.close()
to_remove = [r.upper() for r in request.get('residues', [])]
removed = []
for model in structure:
for chain in model:
for residue in chain:
if residue.get_resname() in to_remove:
chain.detach_child(residue.id)
removed.append(residue.get_resname())
if len(chain) == 0:
model.detach_child(chain.id)
self.log.info('Removed residues: {0}'.format(','.join(removed)))
# Save to file or string
pdbio = PDBIO()
pdbio.set_structure(structure)
status = 'completed'
if request.get('workdir'):
result = os.path.join(request.get('workdir'), 'structure.pdb')
pdbio.save(result)
else:
outfile = StringIO()
pdbio.save(outfile)
outfile.seek(0)
result = outfile.read()
return {'status': status, 'mol': result}
def func1():
import sys
import re
import gzip
from Bio.PDB.MMCIFParser import MMCIFParser
parser = MMCIFParser(QUIET=True)
from Bio.PDB.PDBParser import PDBParser
parser1 = PDBParser(PERMISSIVE=0, QUIET=True)
from Bio.PDB.PDBIO import PDBIO
#pathmmcif = "/Users/tarun/Documents/mmCIF"
#pathmmcif = "/data/pdb/divided/mmCIF"
pathmmcif = "/Volumes/BIOINFO/mmCIF"
#pathmmcif = "/Volumes/RCSB_DATA/pdb"
#count = 0
#if count == 0:
try:
pdb1 = "{}".format(sys.argv[2])
fol = pdb1[1:3]
c1 = "{}".format(sys.argv[3])
pdbfile = "{}/{}/{}.cif.gz".format(pathmmcif, fol, pdb1)
#pdbfile = "{}/{}/pdb{}.ent.gz".format(pathmmcif,fol,pdb1)
tar = gzip.open("{}".format(pdbfile), "rb")
out = open("pdbprocess.cif", "wb")
#out = open("pdbprocess.pdb","wb")
out.write(tar.read())
tar.close()
out.close()
structure_id = "{}".format(pdb1)
filename = "pdbprocess.cif"
#filename = "pdbprocess.pdb"
structure = parser.get_structure(structure_id, filename)
model = structure[0]
chain = model["{}".format(c1)]
io = PDBIO()
io.set_structure(chain)
io.save("chain1.pdb")
except:
print("FILE NOT FOUND")
def collect_0(self):
def getChains(s):
ret = s.split('___')[:2]
assert(len(ret) == 2)
return ret
parser = PDBParser()
io = PDBIO()
for f in self.files:
try:
os.mkdir(os.path.join( self.outpath, f))
except OSError as e:
if e.errno != errno.EEXIST:
raise
structure = parser.get_structure(f, os.path.join(self.inpath, f))
chain_A, chain_B = getChains(f)
io.set_structure(structure[0]['A'])
io.save(os.path.join(self.outpath,f,chain_A + '.pdb'))
io.set_structure(structure[0]['B'])
io.save(os.path.join(self.outpath,f,chain_B + '.pdb'))
self.then_do(f)
def downloadUsingMmtf(pdbId, fnameOut, maxNumberOfChains=MAX_NUMBER_OF_CHAINS):
print("downloadUsingMmtf")
try:
parser = MMTFParser()
struct = parser.get_structure_from_url(pdbId)
if not 0 in struct:
return False
if len(struct[0]) > maxNumberOfChains:
raise NoValidPDBFile(
"The maximun number of allowed chains is %d (%d) for %s" %
(maxNumberOfChains, len(struct[0]), pdbId))
writter = PDBIO()
writter.set_structure(struct)
writter.save(fnameOut)
return True
except (Exception, ValueError, HTTPError) as e:
print(e)
if isinstance(e, NoValidPDBFile):
raise e
return False
def rmsd(pdbid,chain,decoy_file,astral=False):
"""Calculate the RMS between the two structures based on sequence alignment."""
if astral:
pdb = hpf.pdb.get_astral(pdbid)
else:
pdb = hpf.pdb.get_pdb(pdbid)
temp = tempfile.NamedTemporaryFile("w")
try:
# Save the pdbchain
io = PDBIO()
io.set_structure(pdb)
io.save(temp, select=hpf.pdb.PDBChainSelector(chain))
# Perform Mammoth alignment
decoy_id = os.path.basename(decoy_file)
cl = Mammoth.MammothCL(temp.name, decoy_file)
mm = Mammoth.do_alignment(cl)
return mm
finally:
temp.close()
def moveAndWriteAsPDBIfMmcif(fnameIn, fnameOut, removeInput=False):
from Config import Configuration
conf = Configuration()
minNumResidues, maxNumResidues = conf.minNumResiduesPartner, conf.maxNumResiduesPartner
try:
struct, __ = loadPdbIfIsPath(fnameIn)
totalNumRes = 0
for chain in struct[0]:
nResInChain = len(chain.get_list())
totalNumRes += nResInChain
if not (minNumResidues < totalNumRes < maxNumResidues):
raise BadNumberOfResidues(totalNumRes)
else:
writter = PDBIO()
writter.set_structure(struct)
writter.save(fnameOut)
if removeInput: os.remove(fnameIn)
return True
except Exception as e:
print("Error in moveAndWriteAsPDBIfMmcif !!!", e)
return False
def save_structure(self, output_pdb_path: str, mod_id: str = None):
"""
Saves structure on disk in PDB format
Args:
output_pdb_path: OS path to the output file
mod_id (optional): model to write
Errors:
OSError: Error saving the file
"""
if not output_pdb_path:
raise OutputPathNotProvidedError
pdbio = PDBIO()
if mod_id is None:
pdbio.set_structure(self.st)
pdbio.save(output_pdb_path)
else:
pdbio.set_structure(self.st[mod_id])
pdbio.save(output_pdb_path)
def extract(structure, chain_id, start, end, filename):
"""
Write out selected residues from a particular given pdb structure to filename.
Args:
structure: The four letter pdb code for the protein (this pdb must currently exist!)
chain_id: The chain in the pdb you are trying to extract
start: The beginning residue that you want to start your extraction from
end:
filename: The filename (ex. my_protein.pdb) of the pdb that you will extract the selected residues to
Returns:
A pdb file that contains only the selected residues from the original pdb structure given as an argument
Example of usage
p=PDBParser()
s=p.get_structure('X', '1RUZ.pdb')
extract(s, 'H', 40, 60, 'extracted.pdb')
"""
sel=ChainSelector(chain_id, start, end)
io=PDBIO()
io.set_structure(structure)
io.save(filename, sel)
def setup_structures_for_linking(filepath1, filepath2, charmmdir, pdb_path_dir):
cmc = md.CenterOfMassCalculator()
rig = MRM.Molecular_Rigid_Manipulation()
structure1 = pdb_parser.get_structure('Centered', filepath1)
rig.translate_molecule(structure1,rig.center_molecule(cmc.calculate_center_of_mass(structure1)))
structure2 = pdb_parser.get_structure('Rotated', filepath2)
rig.translate_molecule(structure2,rig.center_molecule(cmc.calculate_center_of_mass(structure2)))
# we have two structures with possible identical chain identifiers
# we need to make sure there are no duplicates when structure 1 and 2
# are merged. We will relable structure2.
# TODO: There can only be as many labels as letters in the alphabet.
# It is unlikely that we will need more lables than that in the near future,
# but constructs one day may have more chains than letters in the alphabet.
ids = {}
for i in string.ascii_uppercase:
ids[i] = False
# First We used model 0 of structure 1 and turned used_ids for that chain
# identifier to True.
for i in structure1[0]:
ids[i.id] = True
# Now we go through structure 2 and if there are any chains with the same id
# as those found in structure 1, we will change the chain ids to something else
for i in structure2[0]:
if ids[i.id]:
for j in string.ascii_uppercase:
if not ids[j]:
i.id = j
ids[j] = True
break
#print _calculate_center_of_charge(rtp, structure)
# We want to join the two structures into one structure, with one model
# and the chains of structure 1 and 2. First, deepcopy copies an object
# recursively
structure3 = copy.deepcopy(structure1)
structure3.id = 'Ensamble'
for i in structure2.get_chains():
structure3[0].add(i)
# TODO: This works only for angles between 0 and 90 not including 0, and 90
# and will generate angles in all 8 quadrants of the cartesian coordinate system
Angle_Separation = 45
locations = []
for h in range(0,3):
for i in range(0,360,Angle_Separation):
for j in range(0,90/Angle_Separation-1):
if h == 0:
z = 0
elif h == 1:
z = np.cos(45*np.pi/180)
elif h == 2:
z = -1*np.cos(45*np.pi/180)
locations.append([np.cos(i*np.pi/180),np.sin(i*np.pi/180),z])
locations.append([0,0,1])
locations.append([0,0,-1])
for i in range(0,len(locations)):
locations[i] = list(locations[i]/np.linalg.norm(locations[i]))
structure_id = 0
for i in locations:
ccc = md.ChargeCalculator(charmmdir)
center_of_charge2 = ccc.calculate_center_of_charge(structure2)
center_of_charge2 = center_of_charge2/np.linalg.norm(center_of_charge2)
RM = rig.alignVectors(i,center_of_charge2)
for j in structure2.get_atoms():
v2 = [j.get_coord()[0],j.get_coord()[1],j.get_coord()[2]]
jj = np.dot(v2,RM)
j.set_coord(jj)
ii = [k*45 for k in i]
rig.translate_molecule(structure2,ii)
io = PDBIO()
io.set_structure(structure3)
io.save(pdb_path_dir+'struct_'+str(structure_id)+'.pdb')
structure_id = structure_id + 1
rig.translate_molecule(structure2,rig.center_molecule(cmc.calculate_center_of_mass(structure2)))
def main(verbose=False, msafile=None, pdbfile=None, renumligs=False):
onelettercode = {'ASP':'D', 'GLU':'E', 'ASN':'N', 'GLN':'Q', 'ARG':'R', 'LYS':'K', 'PRO':'P', 'GLY':'G', 'CYS':'C', 'THR':'T', 'SER':'S', 'MET':'M', 'TRP':'W', 'PHE':'F', 'TYR':'Y', 'HIS':'H', 'ALA':'A', 'VAL':'V', 'LEU':'L', 'ILE':'I'}
wd = os.getcwd()
msa = AlignIO.read(read(msafile), 'fasta')
querypdbid = fileprefix(pdbfile)
querypdb = PDBParser(PERMISSIVE=1, QUIET=(not verbose)).get_structure(querypdbid, pdbfile)
#for each chain, get it's sequence
qseqdicts = dict()
chains = dict( (chain.get_id(), chain) for chain in querypdb.get_list()[0].get_list() )
for chainid in chains:
qseqdicts[chainid] = dict()
residuelist = chains[chainid].get_list()
for i, residue in enumerate(residuelist):
if residue.get_resname() not in onelettercode:
oletter = 'X'
else:
oletter = onelettercode[residue.get_resname()]
qseqdicts[chainid][int(residue.get_id()[1])] = oletter
#get seqs as strings
for chainid in qseqdicts:
print "\nCurrent chain is '%s'." % chainid
qseqdict = qseqdicts[chainid]
qseq = "".join( [qseqdict[resnr] for resnr in sorted(qseqdict.keys())] )
qseqkeys = [resnr for resnr in sorted(qseqdict.keys())]
qseq = SeqRecord(Seq(qseq,IUPAC.protein),id=querypdbid)
# determine the sequence closest to the one in the PDB file
i=0
maxid = 0 # maximum sequence identity
maxal = maxmsaseq = None
# align qseq to each seq in the msa and find the one with highest identity
for alignment in msa:
msaseq = SeqRecord(alignment.seq, id=alignment.id)
ids = (qseq.id, msaseq.id)
ali = Needle(pair=ids,records=(qseq, msaseq), name=ids, confopts={'gapopen':10, 'gapextend':0, 'brief':0}) # wd='/tmp/needle'
ali.align(force_protein=True)
seqid = NeedleSingle(outfile=ali.outfile).getResults()['Longest_Identity']
if seqid > maxid:
maxid = seqid
maxal = AlignIO.read(ali.outfile, 'emboss')
maxmsaseq = msaseq
try:
qseq = str(maxal[0].seq)
tseq = str(maxal[1].seq)
msaseq = str(maxmsaseq.seq)
print "Highest seq id is %.2f for:\n%s\n================" % (maxid, str(maxal))
except TypeError:
print "No alignment could be generated."
continue
# number letters in the msa sequence
# get the positions without gaps, this gives the actual positions in tseq
msaseqindices = [ i for i in range(1,len(msaseq)+1) if msaseq[i-1] != '-' ]
# get positions with gaps
# qseqgappos = [ i for i in range(len(qseq)) if tseq[i] == '-' ]
# qseqgappos.reverse()
# qseqkeys = range(len(qseq))
# for i in qseqgappos:
# del qseqkeys[i]
# trim qseq if some pos there are mapped to gaps in tseq
# expand the list of qseqkeys to align with MSA
tmp = list(qseqkeys)
qseqkeys = []
tmp.reverse()
for i in range(len(qseq)):
if qseq[i] != '-':
key = tmp.pop()
else:
key = None
if tseq[i] != '-':
qseqkeys.append(key)
qseq = [ qseq[i] for i in range(len(qseq)) if tseq[i] != '-' ]
# and trim gaps from tseq
tseq = [ tseq[i] for i in range(len(tseq)) if tseq[i] != '-' ]
# now, tseq is guaranteed gap-free
#replace each position in qseqindices by None if there is a gap in qseq
newqseqindices = list(msaseqindices)
for i in range(len(qseq)):
if qseq[i] == '-':
newqseqindices[i] = None
#print newqseqindices
# now newqseqindices is the list of indices for the renumbering in the order of the query sequence
#sanity check
assert(len(qseqkeys) == len(qseq) == len(tseq) == len(newqseqindices))
for i in range(len(qseqkeys)):
if qseqkeys[i] is None:
assert(newqseqindices[i] is None)
#remove empty positions and create a dict of the remapping
newqseqindices = [index for index in newqseqindices if index is not None]
qseqkeys = [index for index in qseqkeys if index is not None]
newqseqindices = dict(zip(qseqkeys,newqseqindices))
#renumber residues
chain = chains[chainid]
for residue in chain.get_list():
resid = list(residue.get_id())
index = resid[1]
is_het = len(resid[0].strip()) != 0
if index in newqseqindices and not is_het:
resid[1] = newqseqindices[index]
elif renumligs:
resid[1] = 0
residue.id = tuple(resid)
# write renumbered PDB file
io = PDBIO()
io.set_structure(querypdb)
io.save(os.path.join(wd, '%s_renum.pdb' % querypdbid))
num_count = 0
for i in range(0,shape(points)[0]):
num_count = num_count +1
res_id = (' ',num_count,' ')
residue = Residue(res_id,'ALA',' ')
cur_coord = tuple(points[i])
bfactor = bfactors[i]
atom = Atom('CA',cur_coord,bfactor,0,' ','CA',num_count,'C')
residue.add(atom)
chain.add(residue)
model.add(chain)
structure.add(model)
# --------------------------------------------------------------------
io=PDBIO()
io.set_structure(structure)
if ( args['dst'] is None):
fn = sys.stdout
io.save(fn)
if ( args['link'] ):
for i in range(1,shape(points)[0]):
fn.write( "CONECT%5d%5d\n" % (i, i+1))
else:
fn = args['dst']
io.save(fn)
fout = open(fn,"a")
if (args['link'] ):
for i in range(1,shape(points)[0]):
fout.write( "CONECT%5d%5d\n" % (i, i+1))
fout.close()
# print "output file: " + args['dst']
def main():
# validate file path
if not args:
print "Error: No file path provided."
sys.exit(1)
filepath1 = "/home/noel/Projects/Protein_design/Insulin/OIPD/2hiu_1H.pdb"
filepath2 = "/home/noel/Projects/Protein_design/Insulin/OIPD/2zta_1H.pdb"
# I added a file path for the lucine zipper molecule.
# The program will have two structures. The first one
# is to be centered, and the secondone is the one that
# will be placed around the first one in many different
# orientations. For now I will call them filepath1 and
# filepath2.
filepath1 = args[0]
if not os.path.exists(filepath1):
print "Error: File path for molecule to be centered does not exist."
sys.exit(1)
filepath2 = args[1]
if not os.path.exists(filepath2):
print "Error: File path for molecule to be rotated does not exist."
sys.exit(1)
# TODO We should eventually perform more rigorous validation,
# e.g. verifying file permissions.
# assign structure id. if one is not provided, default to file name.
structure_id = options.id
if not structure_id:
structure_id = os.path.splitext(os.path.basename(filepath1))[0]
# We read both structures and place insuline at the center and
# leucine zipper at [5,0,0]
structure1 = pdb_parser.get_structure("Centered One", filepath1)
center_of_mass1 = _calculate_center_of_mass(structure1)
# print center_of_mass1
location_vextor1 = center_of_mass1
translate_molecule(structure1, center_molecule(center_of_mass1))
center_of_mass1 = _calculate_center_of_mass(structure1)
print center_of_mass1
structure2 = pdb_parser.get_structure("Rotated One", filepath2)
center_of_mass2 = _calculate_center_of_mass(structure2)
# print center_of_mass2
translate_molecule(structure2, center_molecule(center_of_mass2))
location_vector2 = [45, 0, 0]
translate_molecule(structure2, location_vector2)
center_of_mass2 = _calculate_center_of_mass(structure2)
# print center_of_mass2
# we have two structures with possible identical chain identifiers
# we need to make sure there are no duplicates when structure 1 and 2
# are merged. We will relable structure2.
# TODO: There can only be as many labels as letters in the alphabet.
# It is unlikely that we will need more lables in the near future,
# but constructs one day may have more chains than letters in the alphabet.
ids = {}
for i in string.ascii_uppercase:
ids[i] = False
# First We used model 0 of structure 1 and turned used_ids for that chain
# identifier to True.
for i in structure1[0]:
ids[i.id] = True
# Now we go through structure 2 and if there are any chains with the same id
# as those found in structure 1, we will change the chain ids to something else
for i in structure2[0]:
if ids[i.id]:
for j in string.ascii_uppercase:
if not ids[j]:
i.id = j
ids[j] = True
break
# We want to join the two structures into one structure, with one model
# and the chains of structure 1 and 2. First, deepcopy copies an object
# recursively
structure3 = copy.deepcopy(structure1)
structure3.id = "Ensamble"
for i in structure2.get_chains():
structure3[0].add(i)
structure_id = 0
path_dir = "/home/noel/Projects/Protein_design/Insulin/OIPD/pdbs/"
# DELETED: (45,45,180),(45,45,360),(45,90,180),(45,90,360),(45,135,180),(45,135,360),(45,180,180),(45,180,360)
locations = [
(45, 0, 0),
(90, 0, 0),
(135, 0, 0),
(180, 0, 0),
(225, 0, 0),
(270, 0, 0),
(315, 0, 0),
(360, 0, 0),
(45, 45, 45),
(45, 45, 90),
(45, 45, 135),
(45, 45, 225),
(45, 45, 270),
(45, 45, 315),
(45, 90, 45),
(45, 90, 90),
(45, 90, 135),
(45, 90, 225),
(45, 90, 270),
(45, 90, 315),
(45, 135, 45),
(45, 135, 90),
(45, 135, 135),
(45, 135, 225),
(45, 135, 270),
(45, 135, 315),
(45, 180, 45),
(45, 180, 90),
(45, 180, 135),
(45, 180, 225),
(45, 180, 270),
(45, 180, 315),
]
for i in locations:
RotMat = genMatrix(i[0] * np.pi / 180, i[1] * np.pi / 180, i[2] * np.pi / 180)
center_of_mass2 = _calculate_center_of_mass(structure2)
translate_molecule(structure2[0], center_molecule(center_of_mass2))
translate_molecule(structure2[0], list(np.dot(np.asarray(location_vector2), RotMat)))
io = PDBIO()
io.set_structure(structure3)
io.save(path_dir + "struct_" + str(structure_id) + ".pdb")
# print(structure_id, center_of_mass2)
structure_id = structure_id + 1