def testAtomMatch(self):
fdefBlock = \
"""
DefineFeature HAcceptor1 [#7,#8]
Family HBondAcceptor
Weights 1.0
EndFeature
DefineFeature Arom1 a1aaaaa1
Family Aromatic
Weights 1.0,1.0,1.0,1.0,1.0,1.0
EndFeature
"""
cfac = ChemicalFeatures.BuildFeatureFactoryFromString(fdefBlock)
self.failUnless(cfac.GetNumFeatureDefs() == 2)
mol = Chem.MolFromSmiles('n1ccccc1')
feats = cfac.GetFeaturesForMol(mol)
self.failUnless(len(feats)==2)
m = ChemicalFeatures.GetAtomMatch(feats)
self.failIf(m)
mol = Chem.MolFromSmiles('c1ccccc1N')
feats = cfac.GetFeaturesForMol(mol)
self.failUnless(len(feats)==2)
m = ChemicalFeatures.GetAtomMatch(feats)
self.failUnless(len(m)==2)
def testBasic(self):
ffeat = ChemicalFeatures.FreeChemicalFeature()
ffeat.SetId(123)
pos = ffeat.GetId()
self.assertTrue(pos == 123)
ffeat.SetFamily("HBondDonor")
self.assertTrue(ffeat.GetFamily() == "HBondDonor")
ffeat.SetPos(geom.Point3D(1.0, 2.0, 3.0))
pos = ffeat.GetPos()
self.assertTrue(ptFeq(pos, geom.Point3D(1.0, 2.0, 3.0)))
ffeat.SetType("HBondDonor1")
self.assertTrue(ffeat.GetType() == "HBondDonor1")
ffeat = ChemicalFeatures.FreeChemicalFeature("HBondDonor", "HBondDonor1", geom.Point3D(1.0, 2.0,
3.0))
self.assertTrue(ffeat.GetId() == -1)
self.assertTrue(ffeat.GetFamily() == "HBondDonor")
self.assertTrue(ffeat.GetType() == "HBondDonor1")
ffeat = ChemicalFeatures.FreeChemicalFeature("HBondDonor", "HBondDonor1",
geom.Point3D(1.0, 2.0, 3.0), id=123)
self.assertTrue(ffeat.GetId() == 123)
self.assertTrue(ffeat.GetFamily() == "HBondDonor")
self.assertTrue(ffeat.GetType() == "HBondDonor1")
pos = ffeat.GetPos()
self.assertTrue(ptFeq(pos, geom.Point3D(1.0, 2.0, 3.0)))
ffeat = ChemicalFeatures.FreeChemicalFeature(id=123, type="HBondDonor1", family="HBondDonor",
loc=geom.Point3D(1.0, 2.0, 3.0))
self.assertTrue(ffeat.GetId() == 123)
self.assertTrue(ffeat.GetFamily() == "HBondDonor")
self.assertTrue(ffeat.GetType() == "HBondDonor1")
pos = ffeat.GetPos()
self.assertTrue(ptFeq(pos, geom.Point3D(1.0, 2.0, 3.0)))
def setUp(self):
self.dataDir = os.path.join(RDConfig.RDCodeDir,
'Chem/Pharm3D/test_data')
self.fdefBlock = """
DefineFeature HAcceptor1 [N,O;H0]
Family HBondAcceptor
Weights 1.0
EndFeature
DefineFeature HDonor1 [N,O;!H0]
Family HBondDonor
Weights 1.0
EndFeature
DefineFeature Aromatic1 c1ccccc1
Family Aromatic
Weights 1.,1.,1.,1.,1.,1.
EndFeature\n"""
self.featFactory = ChemicalFeatures.BuildFeatureFactoryFromString(
self.fdefBlock)
self.feats = [
ChemicalFeatures.FreeChemicalFeature(
'HBondAcceptor', 'HAcceptor1', Geometry.Point3D(0.0, 0.0,
0.0)),
ChemicalFeatures.FreeChemicalFeature(
'HBondDonor', 'HDonor1', Geometry.Point3D(2.65, 0.0, 0.0)),
ChemicalFeatures.FreeChemicalFeature(
'Aromatic', 'Aromatic1', Geometry.Point3D(5.12, 0.908, 0.0)),
]
self.pcophore = Pharmacophore.Pharmacophore(self.feats)
self.pcophore.setLowerBound(0, 1, 2.0)
self.pcophore.setUpperBound(0, 1, 3.3)
self.pcophore.setLowerBound(0, 2, 5.0)
self.pcophore.setUpperBound(0, 2, 5.4)
self.pcophore.setLowerBound(1, 2, 2.6)
self.pcophore.setUpperBound(1, 2, 3.0)
def setUp(self):
self.fdefBlock = \
"""DefineFeature HAcceptor1 [N,O;H0]
Family HBondAcceptor
Weights 1.0
EndFeature
DefineFeature HDonor1 [N,O;!H0]
Family HBondDonor
Weights 1.0
EndFeature
DefineFeature Aromatic1 c1ccccc1
Family Aromatic
Weights 1.0,1.0,1.0,1.0,1.0,1.0
EndFeature\n"""
self.featFactory = ChemicalFeatures.BuildFeatureFactoryFromString(
self.fdefBlock)
self.feats = [
ChemicalFeatures.FreeChemicalFeature(
'HBondAcceptor', 'HAcceptor1', Geometry.Point3D(0.0, 0.0,
0.0)),
ChemicalFeatures.FreeChemicalFeature(
'HBondDonor', 'HDonor1', Geometry.Point3D(2.65, 0.0, 0.0)),
ChemicalFeatures.FreeChemicalFeature(
'Aromatic', 'Aromatic1', Geometry.Point3D(5.12, 0.908, 0.0)),
]
self.pcophore = Pharmacophore.Pharmacophore(self.feats)
def test4Search(self):
featFactory = ChemicalFeatures.BuildFeatureFactory(os.path.join(self.dataDir,
'BaseFeatures.fdef'))
activeFeats = [ChemicalFeatures.FreeChemicalFeature('Acceptor',
Geometry.Point3D(0.0, 0.0, 0.0)),
ChemicalFeatures.FreeChemicalFeature('Donor',
Geometry.Point3D(0.0, 0.0, 0.0)),
ChemicalFeatures.FreeChemicalFeature('Aromatic',
Geometry.Point3D(0.0, 0.0, 0.0))]
pcophore= Pharmacophore.Pharmacophore(activeFeats)
pcophore.setLowerBound(0,1,2.251)
pcophore.setUpperBound(0,1,2.451)
pcophore.setUpperBound2D(0,1,3)
pcophore.setLowerBound(0,2,4.970)
pcophore.setUpperBound(0,2,5.170)
pcophore.setUpperBound2D(0,2,6)
pcophore.setLowerBound(1,2,2.681)
pcophore.setUpperBound(1,2,2.881)
pcophore.setUpperBound2D(1,2,6)
inF = gzip.open(os.path.join(self.dataDir,'cdk2-syn-clip100.pkl.gz'),'rb')
nDone = 0
nMatches = 0
nHits = 0
while 1:
try:
name,molPkl,boundsMat = cPickle.load(inF, encoding='latin1')
if PY3:
molPkl = bytes(molPkl, encoding='latin1')
except:
break
nDone += 1
mol = Chem.Mol(molPkl)
boundsMat = rdDistGeom.GetMoleculeBoundsMatrix(mol)
DG.DoTriangleSmoothing(boundsMat)
canMatch,matches = EmbedLib.MatchPharmacophoreToMol(mol,featFactory,
pcophore)
if canMatch:
nMatches+=1
r = EmbedLib.MatchPharmacophore(matches,boundsMat,pcophore,
useDownsampling=True,use2DLimits=True,
mol=mol)
failed,bm,match,details = r
if not failed:
nHits+=1
self.assertEqual(nDone,100)
self.assertEqual(nMatches,93)
#print 'nhits:',nHits
self.assertEqual(nHits,67)
def setUp(self):
fdefFile = os.path.join(RDConfig.RDCodeDir, 'Chem', 'Pharm2D',
'test_data', 'BaseFeatures.fdef')
featFactory = ChemicalFeatures.BuildFeatureFactory(fdefFile)
self.factory = SigFactory.SigFactory(featFactory, minPointCount=2, maxPointCount=3)
self.factory.SetBins([(0, 2), (2, 5), (5, 8)])
self.factory.Init()
def _getFeatureFamily(mol):
FEATURE_DEF_FILE = os.path.join(RDConfig.RDDataDir, 'BaseFeatures.fdef')
feat_factory = ChemicalFeatures.BuildFeatureFactory(FEATURE_DEF_FILE)
hmol = rdkit.Chem.AddHs(mol)
AllChem.EmbedMolecule(hmol, useRandomCoords=True)
rc = rdkit.Chem.AllChem.EmbedMolecule(hmol)
logging.debug("Getting features for mol " + mol.GetProp("_Name"))
if rc < 0:
rc = rdkit.Chem.AllChem.EmbedMolecule(hmol, useRandomCoords=True)
if rc == 0:
try:
if rdkit.Chem.AllChem.UFFOptimizeMolecule(hmol) != 0:
rdkit.Chem.AllChem.UFFOptimizeMolecule(hmol, maxIters=1000)
except ValueError:
logging.error("Problem with 3D version of molecule " +
hmol.GetProp("_Name"))
pass
feats = feat_factory.GetFeaturesForMol(hmol)
atomFeatures = [["" for feature in range(len(feats))]
for atom in range(hmol.GetNumAtoms())]
for feature in feats:
for atomId in feature.GetAtomIds():
if feature.GetFamily() not in atomFeatures[atomId]:
atomFeatures[atomId].append(feature.GetFamily())
return atomFeatures
def testIncludeOnly(self):
cfac = ChemicalFeatures.BuildFeatureFactory(
os.path.join(RDConfig.RDBaseDir, 'Code', 'GraphMol', 'MolChemicalFeatures', 'test_data',
'featDef.txt'))
self.failUnless(cfac.GetNumFeatureDefs() == 2)
mol = Chem.MolFromSmiles("COCN")
rdDistGeom.EmbedMolecule(mol)
self.failUnless(cfac.GetNumMolFeatures(mol, includeOnly="HBondAcceptor") == 2)
self.failUnless(cfac.GetNumMolFeatures(mol, includeOnly="HBondDonor") == 1)
self.failUnless(cfac.GetNumMolFeatures(mol, includeOnly="Bogus") == 0)
self.failUnlessRaises(IndexError, lambda: cfac.GetMolFeature(mol, 1, includeOnly="HBondDonor"))
self.failUnlessRaises(IndexError,
lambda: cfac.GetMolFeature(mol, 2, includeOnly="HBondAcceptor"))
f = cfac.GetMolFeature(mol, 0, includeOnly="HBondDonor")
self.failUnless(f.GetFamily() == 'HBondDonor')
feats = cfac.GetFeaturesForMol(mol, includeOnly="HBondAcceptor")
self.failUnless(len(feats) == 2)
feats = cfac.GetFeaturesForMol(mol, includeOnly="HBondDonor")
self.failUnless(len(feats) == 1)
feats = cfac.GetFeaturesForMol(mol, includeOnly="Bogus")
self.failUnless(len(feats) == 0)
def ConstrainedEnum(matches,mol,pcophore,bounds,use2DLimits=False,
index=0,soFar=[]):
""" Enumerates the list of atom mappings a molecule
has to a particular pharmacophore.
We do check distance bounds here.
"""
nMatches = len(matches)
if index>=nMatches:
yield soFar,[]
elif index==nMatches-1:
for entry in matches[index]:
nextStep = soFar+[entry]
if index != 0:
atomMatch = _checkMatch(nextStep,mol,bounds,pcophore,use2DLimits)
else:
atomMatch = ChemicalFeatures.GetAtomMatch(nextStep)
if atomMatch:
yield soFar+[entry],atomMatch
else:
for entry in matches[index]:
nextStep = soFar+[entry]
if index != 0:
atomMatch = _checkMatch(nextStep,mol,bounds,pcophore,use2DLimits)
if not atomMatch:
continue
for val in ConstrainedEnum(matches,mol,pcophore,bounds,use2DLimits=use2DLimits,
index=index+1,soFar=nextStep):
if val:
yield val
def testPickle(self):
ffeat = ChemicalFeatures.FreeChemicalFeature(
"HBondDonor", "HBondDonor1", geom.Point3D(1.0, 2.0, 3.0), 123)
pkl = cPickle.dumps(ffeat)
ffeat2 = cPickle.loads(pkl, encoding='bytes')
self.assertTrue(ffeat2.GetId() == ffeat.GetId())
self.assertTrue(ffeat2.GetFamily() == ffeat.GetFamily())
self.assertTrue(ffeat2.GetType() == ffeat.GetType())
self.assertTrue(ptFeq(ffeat2.GetPos(), ffeat.GetPos()))
# Check that the old pickled versions have not been broken
inF = open(
os.path.join(RDConfig.RDBaseDir,
'Code/ChemicalFeatures/Wrap/testData/feat.pkl'), 'rb')
ffeat2 = cPickle.load(inF, encoding='bytes')
# this version (1.0) does not have an id in the byte stream
self.assertTrue(ffeat2.GetFamily() == ffeat.GetFamily())
self.assertTrue(ffeat2.GetType() == ffeat.GetType())
self.assertTrue(ptFeq(ffeat2.GetPos(), ffeat.GetPos()))
# Test the new version also has the id and works as expected
# uncomment the following to generate (overrwrite) new version of pickled
# data file
#cPickle.dump(ffeat,file(os.path.join(RDConfig.RDBaseDir, 'Code/ChemicalFeatures/Wrap/testData/featv2.pkl'),'wb+'))
inF = open(
os.path.join(RDConfig.RDBaseDir,
'Code/ChemicalFeatures/Wrap/testData/featv2.pkl'),
'rb')
ffeat2 = cPickle.load(inF, encoding='bytes')
self.assertTrue(ffeat2.GetId() == ffeat.GetId())
self.assertTrue(ffeat2.GetFamily() == ffeat.GetFamily())
self.assertTrue(ffeat2.GetType() == ffeat.GetType())
self.assertTrue(ptFeq(ffeat2.GetPos(), ffeat.GetPos()))
def initFromLines(self, lines):
import re
spaces = re.compile('[\ \t]+')
feats = []
rads = []
for lineNum, line in enumerate(lines):
txt = line.split('#')[0].strip()
if txt:
splitL = spaces.split(txt)
if len(splitL) < 5:
logger.error(
'Input line %d only contains %d fields, 5 are required. Read failed.'
% (lineNum, len(splitL)))
return
fName = splitL[0]
try:
xP = float(splitL[1])
yP = float(splitL[2])
zP = float(splitL[3])
rad = float(splitL[4])
except ValueError:
logger.error(
'Error parsing a number of line %d. Read failed.' %
(lineNum))
return
feats.append(
ChemicalFeatures.FreeChemicalFeature(
fName, fName, Geometry.Point3D(xP, yP, zP)))
rads.append(rad)
self._initializeFeats(feats, rads)
def processArgs(args, parser):
try:
factory = ChemicalFeatures.BuildFeatureFactory(args.fdefFilename)
except Exception:
parser.error(
"Could not parse Fdef file {0.fdefFilename}.".format(args))
with open(args.smilesFilename) as inF:
for lineNo, line in enumerate(inF, 1):
if lineNo == args.maxLines + 1:
break
smi = splitExpr.split(line.strip())[0].strip()
mol = Chem.MolFromSmiles(smi)
if mol is None:
logger.warning("Could not process smiles '%s' on line %d." %
(smi, lineNo))
continue
print('Mol-%d\t%s' % (lineNo, smi))
if args.reverseIt:
feats = factory.GetFeaturesForMol(mol)
for feat in feats:
print('\t%s-%s: ' % (feat.GetFamily(), feat.GetType()),
end='')
print(', '.join([str(x) for x in feat.GetAtomIds()]))
else:
featInfo = GetAtomFeatInfo(factory, mol)
for i, v in enumerate(featInfo):
print('\t% 2s(%d)' %
(mol.GetAtomWithIdx(i).GetSymbol(), i + 1),
end='')
if v:
print('\t', ', '.join(v))
else:
print()
def get_hydrogen_bonding(self):
"""Gets hydrogen bonding character for all atoms.
Returns:
A dict mapping RDKit Atom indices to a HydrogenBonding object. Atom
indices not in the dict are neither acceptors nor donors.
Raises:
TypeError: if more than one atom index is associated with the same
acceptor or donor.
"""
self.check_indices()
factory = ChemicalFeatures.BuildFeatureFactoryFromString(_HBOND_FEATURE_DEF)
features = factory.GetFeaturesForMol(self.mol)
hb = collections.defaultdict(lambda: HydrogenBonding(False, False))
for feat in features:
family = feat.GetFamily().lower()
if family in ['acceptor', 'donor']:
if len(feat.GetAtomIds()) != 1:
raise TypeError('More than one atom index for %s.' % family)
idx = feat.GetAtomIds()[0]
# pylint:disable=protected-access
if family == 'acceptor':
hb[idx] = hb[idx]._replace(acceptor=True)
elif family == 'donor':
hb[idx] = hb[idx]._replace(donor=True)
# pylint:enable=protected-access
return hb
def _align_molecules(self, molecules: List[Chem.Mol]) -> None:
""" Align a list of molecules to a given pharmacophore.
Parameters
----------
molecules : list of rdkit.Chem.Mol
List of molecules to align.
"""
self.n_molecules += len(molecules)
rdkit_pharmacophore, radii = self.pharmacophore.to_rdkit()
apply_radii_to_bounds(radii, rdkit_pharmacophore)
fdef = os.path.join(RDConfig.RDDataDir, 'BaseFeatures.fdef')
featFactory = ChemicalFeatures.BuildFeatureFactory(fdef)
MolScore = namedtuple("MolScore", ["score", "id", "mol"])
for mol in tqdm(molecules):
bounds_matrix = rdDistGeom.GetMoleculeBoundsMatrix(mol)
can_match, all_matches = EmbedLib.MatchPharmacophoreToMol(
mol, featFactory, rdkit_pharmacophore)
if can_match:
failed, _, matched_mols, _ = EmbedLib.MatchPharmacophore(
all_matches,
bounds_matrix,
rdkit_pharmacophore,
useDownsampling=True)
if failed:
matched_mol = MolScore(0.0, mol.GetProp("_Name"), mol)
self.molecules.append(matched_mol)
continue
else:
matched_mol = MolScore(0.0, mol.GetProp("_Name"), mol)
self.molecules.append(matched_mol)
continue
atom_match = [list(x.GetAtomIds()) for x in matched_mols]
try:
mol_H = Chem.AddHs(mol)
_, embeddings, _ = EmbedLib.EmbedPharmacophore(
mol_H, atom_match, rdkit_pharmacophore, count=10)
except:
continue
SSDs = transform_embeddings(rdkit_pharmacophore, embeddings,
atom_match)
if len(SSDs) == 0:
matched_mol = MolScore(0.0, mol.GetProp("_Name"), mol)
self.molecules.append(matched_mol)
continue
best_fit_index = min(enumerate(SSDs), key=itemgetter(1))[0]
score = 1 / SSDs[best_fit_index]
matched_mol = MolScore(score, mol.GetProp("_Name"),
embeddings[best_fit_index])
self.molecules.append(matched_mol)
def testGithub2603(self):
cfac = ChemicalFeatures.BuildFeatureFactory(
os.path.join(RDConfig.RDDataDir, "BaseFeatures.fdef"))
m = Chem.MolFromSmiles('OCc1ccccc1CN')
feats = cfac.GetFeaturesForMol(m)
self.assertEqual(feats[0].GetFamily(), 'Donor')
cfac = None
self.assertEqual(feats[0].GetFamily(), 'Donor')
def alchemy_nodes(mol):
"""Featurization for all atoms in a molecule. The atom indices
will be preserved.
Parameters
----------
mol : rdkit.Chem.rdchem.Mol
RDKit molecule object
Returns
-------
atom_feats_dict : dict
Dictionary for atom features
"""
atom_feats_dict = defaultdict(list)
is_donor = defaultdict(int)
is_acceptor = defaultdict(int)
fdef_name = osp.join(RDConfig.RDDataDir, 'BaseFeatures.fdef')
mol_featurizer = ChemicalFeatures.BuildFeatureFactory(fdef_name)
mol_feats = mol_featurizer.GetFeaturesForMol(mol)
mol_conformers = mol.GetConformers()
assert len(mol_conformers) == 1
for i in range(len(mol_feats)):
if mol_feats[i].GetFamily() == 'Donor':
node_list = mol_feats[i].GetAtomIds()
for u in node_list:
is_donor[u] = 1
elif mol_feats[i].GetFamily() == 'Acceptor':
node_list = mol_feats[i].GetAtomIds()
for u in node_list:
is_acceptor[u] = 1
num_atoms = mol.GetNumAtoms()
for u in range(num_atoms):
atom = mol.GetAtomWithIdx(u)
atom_type = atom.GetAtomicNum()
num_h = atom.GetTotalNumHs()
atom_feats_dict['node_type'].append(atom_type)
h_u = []
h_u += atom_type_one_hot(atom, ['H', 'C', 'N', 'O', 'F', 'S', 'Cl'])
h_u.append(atom_type)
h_u.append(is_acceptor[u])
h_u.append(is_donor[u])
h_u += atom_is_aromatic(atom)
h_u += atom_hybridization_one_hot(atom, [Chem.rdchem.HybridizationType.SP,
Chem.rdchem.HybridizationType.SP2,
Chem.rdchem.HybridizationType.SP3])
h_u.append(num_h)
atom_feats_dict['n_feat'].append(F.tensor(np.asarray(h_u, dtype=np.float32)))
atom_feats_dict['n_feat'] = F.stack(atom_feats_dict['n_feat'], dim=0)
atom_feats_dict['node_type'] = F.tensor(
np.asarray(atom_feats_dict['node_type'], dtype=np.int64))
return atom_feats_dict
def str2molgraph(
rawstr, length
): # rawstr :tuple() e.g. ('<RX_6>', 'N', 'c', '1', 'n', 'c', '2', '[', 'n', 'H', ']', 'c', '(', 'C', 'C', 'C', 'c', '3', 'c', 's', 'c', '(', 'C', '(', '=', 'O', ')', 'O', ')', 'c', '3', ')', 'c', 'c', '2', 'c', '(', '=', 'O', ')', '[', 'n', 'H', ']', '1')
smiles = ''.join(rawstr[:length])
m = Chem.MolFromSmiles(smiles)
g = nx.Graph()
fdef_name = os.path.join(RDConfig.RDDataDir, 'BaseFeatures.fdef')
factory = ChemicalFeatures.BuildFeatureFactory(fdef_name)
feats = factory.GetFeaturesForMol(m)
atom_true_index = {}
atom_index = 0
# Nodes
for i in range(len(rawstr)):
if not need_emb(rawstr[i], EMB_ATOMS):
g.add_node(i)
else:
atom_true_index[
atom_index] = i # meanwhile, set a map dict to find the true index of atoms
atom_i = m.GetAtomWithIdx(atom_index)
atom_index += 1
g.add_node(i,
a_type=atom_i.GetSymbol(),
a_num=atom_i.GetAtomicNum(),
acceptor=0,
donor=0,
aromatic=atom_i.GetIsAromatic(),
hybridization=atom_i.GetHybridization(),
num_h=atom_i.GetTotalNumHs())
# Donor and Acceptor properties
for i in range(0, len(feats)):
if feats[i].GetFamily() == 'Donor':
node_list = feats[i].GetAtomIds()
for i in node_list:
if i in atom_true_index:
g.nodes[atom_true_index[i]]['donor'] = 1
elif feats[i].GetFamily() == 'Acceptor':
node_list = feats[i].GetAtomIds()
for i in node_list:
if i in atom_true_index:
g.nodes[atom_true_index[i]]['acceptor'] = 1
#Edges
for i in range(0, m.GetNumAtoms()):
for j in range(0, m.GetNumAtoms()):
e_ij = m.GetBondBetweenAtoms(i, j)
if e_ij is not None and i in atom_true_index and j in atom_true_index:
g.add_edge(atom_true_index[i],
atom_true_index[j],
b_type=e_ij.GetBondType())
return g
def __config_feature_factory(self):
"""
Initialize the 'feature factory' rdkit module with the
current molecule.
"""
fdefName = os.path.join(RDConfig.RDDataDir, 'BaseFeatures.fdef')
self.__feat_factory = ChemicalFeatures.BuildFeatureFactory(fdefName)
return
def testParseErrorHandling(self):
fdefBlock = \
"""DefineFeature HDonor1 [N,O;!HQ]
Family HBondDonor
Weights 1.0
EndFeature
"""
self.failUnlessRaises(ValueError,
lambda: ChemicalFeatures.BuildFeatureFactoryFromString(fdefBlock))
fdefBlock = \
"""DefineFeature HDonor1 [N,O;!H0]
Family HBondDonor
Weights 1.0
"""
self.failUnlessRaises(ValueError,
lambda: ChemicalFeatures.BuildFeatureFactoryFromString(fdefBlock))
self.failUnlessRaises(IOError, lambda: ChemicalFeatures.BuildFeatureFactory('noSuchFile.txt'))
def get_factory(self):
"""
Generate the Ph4 feature factory
:return:
"""
if self.factory is None:
this_dir, this_filename = os.path.split(__file__)
data_path = os.path.join(this_dir, "data", "RDKitPh4.fdef")
self.factory = ChemicalFeatures.BuildFeatureFactory(data_path)
return self.factory
def test4Github252(self):
fdef = os.path.join(RDConfig.RDDataDir, 'BaseFeatures.fdef')
feat_factory = ChemicalFeatures.BuildFeatureFactory(fdef)
m1 = Chem.MolFromSmiles('Cc1ccccc1')
feats = feat_factory.GetFeaturesForMol(m1)
self.assertRaises(RuntimeError, lambda: Pharmacophore.Pharmacophore(feats))
AllChem.Compute2DCoords(m1)
Pharmacophore.Pharmacophore(feats)
def _initializeFeats(self, feats):
self._feats = []
for feat in feats:
if isinstance(feat, ChemicalFeatures.MolChemicalFeature):
pos = feat.GetPos()
newFeat = ChemicalFeatures.FreeChemicalFeature(feat.GetFamily(), feat.GetType(),
Geometry.Point3D(pos[0], pos[1], pos[2]))
self._feats.append(newFeat)
else:
self._feats.append(feat)
def GetAllPharmacophoreMatches(matches,
bounds,
pcophore,
useDownsampling=0,
progressCallback=None,
use2DLimits=False,
mol=None,
verbose=False):
res = []
nDone = 0
for match in CombiEnum(matches):
atomMatch = ChemicalFeatures.GetAtomMatch(match)
if atomMatch and use2DLimits and mol:
pass2D = Check2DBounds(atomMatch, mol, pcophore)
if verbose:
print('..', atomMatch)
print(' ..Pass2d:', pass2D)
else:
pass2D = True
if atomMatch and pass2D and \
CoarseScreenPharmacophore(atomMatch,bounds,pcophore,verbose=verbose):
if verbose:
print(' ..CoarseScreen: Pass')
bm = bounds.copy()
if verbose:
print('pre update:')
for row in bm:
print(' ', ' '.join(['% 4.2f' % x for x in row]))
bm = UpdatePharmacophoreBounds(bm, atomMatch, pcophore)
sz = bm.shape[0]
if verbose:
print('pre downsample:')
for row in bm:
print(' ', ' '.join(['% 4.2f' % x for x in row]))
if useDownsampling:
indices = []
for entry in atomMatch:
indices += list(entry)
bm = DownsampleBoundsMatrix(bm, indices)
if verbose:
print('post downsample:')
for row in bm:
print(' ', ' '.join(['% 4.2f' % x for x in row]))
if DG.DoTriangleSmoothing(bm):
res.append(match)
elif verbose:
print('cannot smooth')
nDone += 1
if progressCallback:
progressCallback(nDone)
return res
def get_instance(cls):
try:
from rdkit import RDConfig
from rdkit.Chem import ChemicalFeatures
except ModuleNotFoundError:
raise ValueError("This class requires RDKit to be installed.")
if not cls._instance:
fdefName = os.path.join(RDConfig.RDDataDir, 'BaseFeatures.fdef')
cls._instance = ChemicalFeatures.BuildFeatureFactory(fdefName)
return cls._instance
def __init__(self, atms: typing.List[str]):
self.atms_to_idx = dict(zip(atms, range(len(atms))))
self.number_atom_options = len(self.atms_to_idx)
self.hyb_mapping = {Chem.rdchem.HybridizationType.SP:0 ,
Chem.rdchem.HybridizationType.SP2: 1,
Chem.rdchem.HybridizationType.SP3: 2}
self.number_hyb_options = len(self.hyb_mapping)
self.fdef_name = os.path.join(RDDataDir, 'BaseFeatures.fdef')
self.feats_factory = ChemicalFeatures.BuildFeatureFactory(self.fdef_name)
def numpy_pp_fps(mols):
""" Calculate Gobbi and Poppinger pharmacophore fingerprints and return them as numpy.ndarrays
:param mols: {list} list of molecules (RDKit mols)
:return: numpy array containing row-wise fingerprints for every molecule
"""
feat_fact = ChemicalFeatures.BuildFeatureFactory()
sig_fact = SigFactory(feat_fact, useCounts=False, minPointCount=2, maxPointCount=3)
sig_fact.SetBins([(0, 2), (2, 4), (4, 6), (6, 8), (8, 100)])
sig_fact.Init()
return _rdk2numpy([Generate.Gen2DFingerprint(m, sig_fact) for m in mols if m])
def rdkit_featuredefinition() -> ChemicalFeatures.MolChemicalFeatureFactory:
""" Loads rdkit chemical feature factory.
Returns
-------
rdkit.Chem.rdMolChemicalFeatures.MolChemicalFeatureFactory
The feature factory.
"""
fdefName = os.path.join(RDConfig.RDDataDir, 'BaseFeatures.fdef')
return ChemicalFeatures.BuildFeatureFactory(fdefName)
def __call__(self, mol):
"""Featurizes the input molecule.
Parameters
----------
mol : rdkit.Chem.rdchem.Mol
RDKit molecule instance.
Returns
-------
dict
Mapping atom_data_field as specified in the input argument to the atom
features, which is a float32 tensor of shape (N, M), N is the number of
atoms and M is the feature size.
"""
atom_features = []
AllChem.ComputeGasteigerCharges(mol)
num_atoms = mol.GetNumAtoms()
# Get information for donor and acceptor
fdef_name = osp.join(RDConfig.RDDataDir, 'BaseFeatures.fdef')
mol_featurizer = ChemicalFeatures.BuildFeatureFactory(fdef_name)
mol_feats = mol_featurizer.GetFeaturesForMol(mol)
is_donor, is_acceptor = self.get_donor_acceptor_info(mol_feats)
# Get a symmetrized smallest set of smallest rings
# Following the practice from Chainer Chemistry (https://github.com/chainer/
# chainer-chemistry/blob/da2507b38f903a8ee333e487d422ba6dcec49b05/chainer_chemistry/
# dataset/preprocessors/weavenet_preprocessor.py)
sssr = Chem.GetSymmSSSR(mol)
for i in range(num_atoms):
atom = mol.GetAtomWithIdx(i)
# Features that can be computed directly from RDKit atom instances, which is a list
feats = self._featurizer(atom)
# Donor/acceptor indicator
feats.append(float(is_donor[i]))
feats.append(float(is_acceptor[i]))
# Count the number of rings the atom belongs to for ring size between 3 and 8
count = [0 for _ in range(3, 9)]
for ring in sssr:
ring_size = len(ring)
if i in ring and 3 <= ring_size <= 8:
count[ring_size - 3] += 1
feats.extend(count)
atom_features.append(feats)
atom_features = np.stack(atom_features)
return {
self._atom_data_field:
F.zerocopy_from_numpy(atom_features.astype(np.float32))
}
def extract_features(mol):
factory = ChemicalFeatures.BuildFeatureFactory('./LigityFeatures.fdef')
feats = factory.GetFeaturesForMol(mol)
features = []
for feat in feats:
feature = feat.GetFamily()
if feature in pharmacophores:
id = feat.GetId()
x, y, z = list(feat.GetPos())
string = str(id) + ',' + feature + ',' + str(x) + ',' + str(
y) + ',' + str(z)
features.append(string)
return features
def construct_hydrogen_bonding(mol, num_max_atoms=WEAVE_DEFAULT_NUM_MAX_ATOMS):
fdefName = os.path.join(RDConfig.RDDataDir, 'BaseFeatures.fdef')
factory = ChemicalFeatures.BuildFeatureFactory(fdefName)
feats = factory.GetFeaturesForMol(mol)
hydrogen_bonding_vec = numpy.zeros((num_max_atoms, 2), dtype=numpy.float32)
for f in feats:
if f.GetFamily() == 'Donor':
idx = f.GetAtomIds()[0]
hydrogen_bonding_vec[idx, 0] = 1.0
if f.GetFamily() == 'Acceptor':
idx = f.GetAtomIds()[0]
hydrogen_bonding_vec[idx, 1] = 1.0
return hydrogen_bonding_vec
