def to_graph(smiles, dataset):
mol = Chem.MolFromSmiles(smiles)
if mol is None:
return [], []
# Kekulize it
if need_kekulize(mol):
rdmolops.Kekulize(mol)
if mol is None:
return None, None
# remove stereo information, such as inward and outward edges
Chem.RemoveStereochemistry(mol)
edges = []
nodes = []
for bond in mol.GetBonds():
edges.append((bond.GetBeginAtomIdx(), bond_dict[str(bond.GetBondType())], bond.GetEndAtomIdx()))
assert bond_dict[str(bond.GetBondType())] != 3
for atom in mol.GetAtoms():
if dataset=='qm9' or dataset=="cep":
nodes.append(onehot(dataset_info(dataset)['atom_types'].index(atom.GetSymbol()), len(dataset_info(dataset)['atom_types'])))
elif dataset=='zinc': # transform using "<atom_symbol><valence>(<charge>)" notation
symbol = atom.GetSymbol()
valence = atom.GetTotalValence()
charge = atom.GetFormalCharge()
atom_str = "%s%i(%i)" % (symbol, valence, charge)
if atom_str not in dataset_info(dataset)['atom_types']:
print('unrecognized atom type %s' % atom_str)
return [], []
nodes.append(onehot(dataset_info(dataset)['atom_types'].index(atom_str), len(dataset_info(dataset)['atom_types'])))
return nodes, edges
def _build_drug_graph(self, smiles):
"""
Builds a molecular graph form a smiles string. Taken from [FIND SOURCE!]
"""
mol = Chem.MolFromSmiles(smiles)
if mol is None:
raise ValueError('Molecule construction failed on Inchi %s' %
smiles)
# Kekulize it
if self.need_kekulize(mol):
rdmolops.Kekulize(mol)
if mol is None:
return None, None
# remove stereo information, such as inward and outward edges
Chem.RemoveStereochemistry(mol)
edges = []
nodes = []
for bond in mol.GetBonds():
edges.append((bond.GetBeginAtomIdx(),
self.bond_dict[str(bond.GetBondType())],
bond.GetEndAtomIdx()))
assert self.bond_dict[str(bond.GetBondType())] != 3
for atom in mol.GetAtoms():
# This could probably be spead up....
nodes.append(
onehot(self.dataset_info['atom_types'].index(atom.GetSymbol()),
len(self.dataset_info['atom_types'])))
nodes = torch.tensor(nodes).float()
edges = torch.tensor(edges)
return nodes, edges, mol
def to_graph(smiles, dataset):
mol = Chem.MolFromSmiles(smiles)
mol = Chem.AddHs(mol)
if mol is None:
return [], []
if need_kekulize(mol):
rdmolops.Kekulize(mol)
if mol is None:
return [], []
Chem.RemoveStereochemistry(mol)
edges = []
nodes = []
for bond in mol.GetBonds():
edges.append(
(bond.GetBeginAtomIdx(), bond_dict[str(bond.GetBondType())],
bond.GetEndAtomIdx()))
for atom in mol.GetAtoms():
symbol = atom.GetSymbol()
valence = atom.GetTotalValence()
charge = atom.GetFormalCharge()
atom_str = "%s%i(%i)" % (symbol, valence, charge)
if atom_str not in dataset_info(dataset)['atom_types']:
return [], []
nodes.append(
onehot(
dataset_info(dataset)['atom_types'].index(atom_str),
len(dataset_info(dataset)['atom_types'])))
return nodes, edges
def prepare_mol(self, mol: rdchem.Mol) -> Tuple[str, rdchem.Mol]:
"""Prepare both smiles and mol by standardizing to common rules.
This method should be called before `get_input_feats`.
Params:
-------
mol: rdkit.Chem.rdchem.Mol
Molecule of interest.
Returns:
--------
canonical_smiles: str
Canonical SMILES representation of the molecule.
mol: rdkit.Chem.rdchem.Mol
Modified molecule w/ kekulization and Hs added, if specified.
"""
canonical_smiles = rdmolfiles.MolToSmiles(mol, canonical=True)
mol = rdmolfiles.MolFromSmiles(canonical_smiles)
if self.add_Hs:
mol = rdmolops.AddHs(mol)
if self.kekulize:
rdmolops.Kekulize(mol)
return canonical_smiles, mol
def to_graph(mol, dataset):
if mol is None:
return [], []
if need_kekulize(mol):
rdmolops.Kekulize(mol)
if mol is None:
return None, None
Chem.RemoveStereochemistry(mol)
edges = []
nodes = []
atom_types = get_atom_types(dataset)
for bond in mol.GetBonds():
edges.append(
(bond.GetBeginAtomIdx(), bond_dict[str(bond.GetBondType())],
bond.GetEndAtomIdx()))
assert bond_dict[str(bond.GetBondType())] != 3
for atom in mol.GetAtoms():
nodes.append(
onehot(atom_types.index(str(atom.GetSymbol())), len(atom_types)))
return nodes, edges
if test_mol != None:
energy = get_BO_energy(raw_mol)
if smiles not in smiles_list and energy_of_reactant - energy < E_cutoff:
smiles_list.append(smiles)
molecules.append(raw_mol)
smiles_list.insert(0, Chem.MolToSmiles(mol))
molecules.insert(0, mol)
return smiles_list, molecules
if __name__ == "__main__":
smiles_list = ['CC', 'C=C', 'C#C']
smiles_list = ['C=C.C=CC=C']
smiles_list = ['C(=O)O']
heterolytic = False
E_cutoff = 200
for smiles in smiles_list:
mol = Chem.MolFromSmiles(smiles)
rdmolops.Kekulize(mol, clearAromaticFlags=True)
charge = Chem.GetFormalCharge(mol)
mol = Chem.AddHs(mol)
elementary_smiles, elementary_mols = take_elementary_step(
mol, charge, E_cutoff, heterolytic)
print "len(elementary_smiles)", len(elementary_smiles)
print elementary_smiles
