def get_score(self, ref):
"""Assigns scores (lrmsd, irmsd, fnat, dockQ, bin_class, capri_class) to a protein graph
Args:
ref (path): path to the reference structure required to compute the different score
"""
ref_name = os.path.splitext(os.path.basename(ref))[0]
sim = StructureSimilarity(self.pdb, ref)
# Input pre-computed zone files
if os.path.exists(ref_name + '.lzone'):
self.score['lrmsd'] = sim.compute_lrmsd_fast(method='svd',
lzone=ref_name +
'.lzone')
self.score['irmsd'] = sim.compute_irmsd_fast(method='svd',
izone=ref_name +
'.izone')
# Compute zone files
else:
self.score['lrmsd'] = sim.compute_lrmsd_fast(method='svd')
self.score['irmsd'] = sim.compute_irmsd_fast(method='svd')
self.score['fnat'] = sim.compute_fnat_fast()
self.score['dockQ'] = sim.compute_DockQScore(self.score['fnat'],
self.score['lrmsd'],
self.score['irmsd'])
self.score['bin_class'] = self.score['irmsd'] < 4.0
self.score['capri_class'] = 5
for thr, val in zip([6.0, 4.0, 2.0, 1.0], [4, 3, 2, 1]):
if self.score['irmsd'] < thr:
self.score['capri_class'] = val
def __compute_target__(decoy, targrp):
"""Calculate DOCKQ.
Args:
decoy(bytes): pdb data of the decoy
targrp(hdf5 file handle): HDF5 'targets' group
"""
tarname = 'DOCKQ'
if tarname in targrp.keys():
del targrp[tarname]
warnings.warn(f"Removed old {tarname} from {targrp.parent.name}")
tarelems = ['FNAT', 'LRMSD', 'IRMSD']
vals = {}
for tarelem in tarelems:
# if target element exist, then use its value; otherwise calculate it
if tarelem not in targrp:
_ = rmsd_fnat.__compute_target__(decoy, targrp, tarelem)
# empty dataset
elif targrp[tarelem][()].shape is None:
_ = rmsd_fnat.__compute_target__(decoy, targrp, tarelem)
# get the value
vals[tarelem] = targrp[tarelem][()]
dockQ = StructureSimilarity.compute_DockQScore(
vals['FNAT'], vals['LRMSD'], vals['IRMSD'])
targrp.create_dataset(tarname, data=np.array(dockQ))
def get_score(self, ref):
ref_name = os.path.splitext(os.path.basename(ref))[0]
sim = StructureSimilarity(self.pdb, ref)
self.score['lrmsd'] = sim.compute_lrmsd_fast(
method='svd', lzone=ref_name+'.lzone')
self.score['irmsd'] = sim.compute_irmsd_fast(
method='svd', izone=ref_name+'.izone')
self.score['fnat'] = sim.compute_fnat_fast()
self.score['dockQ'] = sim.compute_DockQScore(
self.score['fnat'], self.score['lrmsd'], self.score['irmsd'])
self.score['binclass'] = self.score['irmsd'] < 4.0
def __compute_target__(decoy, targrp):
"""Calculate CAPRI class.
CAPRI class name and ID:
- 'high': 0
- 'medium': 1
- 'accepetable': 2
- 'incorrect': 3
Args:
decoy(bytes): pdb data of the decoy
targrp(hdf5 file handle): HDF5 'targets' group
"""
categories = {'high': 0, 'medium': 1, 'accepetable': 2, 'incorrect': 3}
tarname = 'CAPRI_CLASS'
if tarname in targrp.keys():
del targrp[tarname]
warnings.warn(f"Removed old {tarname} from {targrp.parent.name}")
tarelems = ['FNAT', 'LRMSD', 'IRMSD']
vals = {}
for tarelem in tarelems:
# if target element exist, then use its value; otherwise calculate it
if tarelem not in targrp:
_ = rmsd_fnat.__compute_target__(decoy, targrp, tarelem)
# empty dataset
elif targrp[tarelem][()].shape is None:
_ = rmsd_fnat.__compute_target__(decoy, targrp, tarelem)
# get the value
vals[tarelem] = targrp[tarelem][()]
label = StructureSimilarity.compute_CapriClass(vals['FNAT'], vals['LRMSD'],
vals['IRMSD'])
targrp.create_dataset(tarname, data=np.array(categories[label]))
def __compute_target__(decoy, targrp, tarname, save_file=False):
"""Calcuate CAPRI metric IRMSD, LRMSD or FNAT.
Args:
decoy(bytes): pdb data of the decoy
targrp(hdf5 file handle): HDF5 'targets' group
tarnames(str): it must be IRMSD, LRMSD or FNAT.
save_file(bool): save .izone, .lzone or .ref_pairs file or not,
defaults to False.
Returns:
float: value of IRMSD, LRMSD or FNAT.
Raises:
ValueError: Wrong target name
ValueError: native complex not exist
ValueError: native complex has empty dataset
Examples:
>>> f = h5py.File('1LFD.hdf5')
>>> decoy = f['1LFD_9w/complex'][()]
>>> targrp = f['1LFD_9w/targets']
"""
# check tarname
tarname = tarname.upper()
if tarname not in ("IRMSD", "LRMSD", "FNAT"):
raise ValueError(f'Target name is wrong: {tarname}. '
f'It must be "IRMSD", "LRMSD", "FNAT"')
# fet the mol group
molgrp = targrp.parent
molname = molgrp.name
if save_file:
path = os.path.dirname(os.path.realpath(__file__))
ZONE = path + '/zones/'
if not os.path.isdir(ZONE):
os.mkdir(ZONE)
if tarname in targrp.keys():
del targrp[tarname]
warnings.warn(f"Removed old {tarname} from {molname}")
# if we have a ref
if '_' not in molname:
if tarname in ("IRMSD", "LRMSD"):
target = 0.0
elif tarname == "FNAT":
target = 1.0
targrp.create_dataset(tarname, data=np.array(target))
warnings.warn(
f"{molname} is a native/reference complex "
f"without '_' in filename. Assign {target} for {tarname}")
# or it's a decoy
else:
if 'native' not in molgrp:
raise ValueError(
f"'native' not exist for {molname}. "
f"You must provide reference pdb for computing targets")
elif molgrp['native'][()].shape is None:
raise ValueError(
f"'native' dataset is empty for {molname}. "
f"You must provide reference pdb for computing targets")
molname = molname.split('_')[0]
# init the class
decoy = molgrp['complex'][()]
ref = molgrp['native'][()]
sim = StructureSimilarity(decoy, ref)
# comppute the izone/lzone/ref_pairs
if tarname == "IRMSD":
if save_file:
izone = ZONE + molname + '.izone'
else:
izone = None
target = sim.compute_irmsd_fast(method='svd', izone=izone)
elif tarname == "LRMSD":
if save_file:
lzone = ZONE + molname + '.lzone'
else:
lzone = None
target = sim.compute_lrmsd_fast(method='svd', lzone=lzone)
elif tarname == "FNAT":
target = sim.compute_fnat_fast()
targrp.create_dataset(tarname, data=np.array(target))
return target