def fix_valence_charge(mol: Chem.rdchem.Mol, inplace: bool = False) -> Optional[Chem.rdchem.Mol]:
"""Fix valence issues that are due to incorrect charges.
Args:
mol: Input molecule with incorrect valence for some atoms
inplace: Whether to modify in place or make a copy.
Returns:
Fixed molecule via charge correction or original molecule if failed.
"""
vm = rdMolStandardize.RDKitValidation()
# Don't fix something that is not broken
if len(vm.validate(mol)) > 0:
if not inplace:
mol = copy.copy(mol)
mol.UpdatePropertyCache(False)
for a in mol.GetAtoms():
n_electron = (
a.GetImplicitValence()
+ a.GetExplicitValence()
- dm.PERIODIC_TABLE.GetDefaultValence(a.GetSymbol())
)
a.SetFormalCharge(n_electron)
return mol
def center_of_mass(
mol: Chem.rdchem.Mol,
use_atoms: bool = True,
digits: int = None,
conf_id: int = -1,
) -> np.ndarray:
"""Compute the center of mass of a conformer of a molecule.
Args:
mol: a molecule
use_atoms: Whether to compute the true center of mass or the geometrical center.
digits: Number of digits to round to.
conf_id: the conformer id.
Returns
cm: Center of mass or geometrical center
"""
coords = get_coords(mol)
atom_weight = np.ones((coords.shape[0]))
if use_atoms:
atom_weight = np.array([atom.GetMass() for atom in mol.GetAtoms()])
atom_weight = atom_weight[:, None]
atom_weight /= atom_weight.sum()
center = (coords * atom_weight).sum(axis=0)
if digits is not None:
center = center.round(digits)
return center
def num_atom_in_ring(mol: Chem.rdchem.Mol):
"""
Check the number of the atoms that are in the ring,, count vector.
"""
count = 0
for atom in mol.GetAtoms():
if atom.IsInRing():
count += 1
return [count]
def is_zwitterion(mol: Chem.rdchem.Mol):
"""
To identify whether the molecule is zwitterion or not
"""
zwitterion = 0
for atom in mol.GetAtoms():
if atom.GetFormalCharge() != 0:
zwitterion = 1
break
return [zwitterion]
def copy_edit_mol(mol: Chem.rdchem.Mol) -> Chem.rdchem.Mol:
new_mol = Chem.RWMol(Chem.MolFromSmiles(''))
for atom in mol.GetAtoms():
new_atom = copy_atom(atom)
new_mol.AddAtom(new_atom)
for bond in mol.GetBonds():
a1 = bond.GetBeginAtom().GetIdx()
a2 = bond.GetEndAtom().GetIdx()
bt = bond.GetBondType()
new_mol.AddBond(a1, a2, bt)
return new_mol
def atom_indices_to_mol(mol: Chem.rdchem.Mol, copy: bool = False):
"""Add the `molAtomMapNumber` property to each atoms.
Args:
mol: a molecule
copy: Whether to copy the molecule.
"""
if copy is True:
mol = copy_mol(mol)
for atom in mol.GetAtoms():
atom.SetProp("molAtomMapNumber", str(atom.GetIdx()))
return mol
def adjust_singleton(mol: Chem.rdchem.Mol) -> Optional[Chem.rdchem.Mol]:
"""Remove all atoms that are essentially disconnected singleton nodes in the molecular graph.
For example, the chlorine atom and methane fragment will be removed in Cl.[N:1]1=CC(O)=CC2CCCCC12.CC.C",
but not the ethane fragment.
Args:
mol: a molecule.
"""
to_rem = []
em = Chem.RWMol(mol)
for atom in mol.GetAtoms():
if atom.GetExplicitValence() == 0:
to_rem.append(atom.GetIdx())
to_rem.sort(reverse=True)
for a_idx in to_rem:
em.RemoveAtom(a_idx)
return em.GetMol()
def to_neutral(mol: Chem.rdchem.Mol) -> Optional[Chem.rdchem.Mol]:
"""Neutralize the charge of a molecule.
Args:
mol: a molecule.
Returns:
mol: a molecule.
"""
if mol is None:
return mol
for a in mol.GetAtoms():
if a.GetFormalCharge() < 0 or (
a.GetExplicitValence() >= PERIODIC_TABLE.GetDefaultValence(a.GetSymbol())
and a.GetFormalCharge() > 0
):
a.SetFormalCharge(0)
a.UpdatePropertyCache(False)
return mol
def atom_graph(mol: Chem.rdchem.Mol):
"""
Generates the atom graph from an RDKit Mol object.
Function taken from https://github.com/maxhodak/keras-molecules/pull/32/files.
"""
if mol:
G = nx.Graph()
for atom in mol.GetAtoms():
G.add_node(
atom.GetIdx(),
atomic_num=atom.GetAtomicNum(
), # this should be instantiated once, and later reused for defining the feature vector
formal_charge=atom.GetFormalCharge(),
chiral_tag=atom.GetChiralTag(),
hybridization=atom.GetHybridization(),
num_explicit_hs=atom.GetNumExplicitHs(),
is_aromatic=atom.GetIsAromatic(),
mass=atom.GetMass(),
implicit_valence=atom.GetImplicitValence(),
total_hydrogens=atom.GetTotalNumHs(),
features=np.array([
atom.GetAtomicNum(),
atom.GetFormalCharge(),
atom.GetChiralTag(),
atom.GetHybridization(),
atom.GetNumExplicitHs(),
atom.GetIsAromatic(),
atom.GetMass(),
atom.GetImplicitValence(),
atom.GetTotalNumHs(),
]),
)
for bond in mol.GetBonds():
G.add_edge(
bond.GetBeginAtomIdx(),
bond.GetEndAtomIdx(),
bond_type=bond.GetBondType(),
)
return G
def bond_graph(mol: Chem.rdchem.Mol):
"""
Generates the bond graph from an RDKit Mol object.
Here, unlike the atom gaph, bonds are nodes, and are
connected to each other by atoms.
:returns: a NetworkX graph.
"""
if mol:
G = nx.Graph()
for bond in mol.GetBonds():
G.add_node(
(bond.GetBeginAtomIdx(), bond.GetEndAtomIdx()),
bond_type=bond.GetBondTypeAsDouble(),
aromatic=bond.GetIsAromatic(),
stereo=bond.GetStereo(),
in_ring=bond.IsInRing(),
is_conjugated=bond.GetIsConjugated(),
features=[
bond.GetBondTypeAsDouble(),
int(bond.GetIsAromatic()),
# bond.GetStereo(),
int(bond.IsInRing()),
int(bond.GetIsConjugated()),
],
)
for atom in mol.GetAtoms():
bonds = atom.GetBonds()
if len(bonds) >= 2:
for b1, b2 in combinations(bonds, 2):
n1 = (b1.GetBeginAtomIdx(), b1.GetEndAtomIdx())
n2 = (b2.GetBeginAtomIdx(), b2.GetEndAtomIdx())
joining_node = list(set(n1).intersection(n2))[0]
G.add_edge(n1, n2, atom=joining_node)
G.add_edge(n2, n1)
return G
def sasa(
mol: Chem.rdchem.Mol,
conf_id: Union[int, List[int]] = None,
n_jobs: int = 1,
) -> np.ndarray:
"""Compute Solvent Accessible Surface Area of all the conformers
using FreeSASA (https://freesasa.github.io/). Values are returned
as an array and also stored within each conformer as a property
called `rdkit_free_sasa`.
Example:
```python
smiles = "O=C(C)Oc1ccccc1C(=O)O"
mol = dm.to_mol(smiles)
mol = dm.conformers.generate(mol)
# Compute SASA for all the conformers without parallelization
sasa_values = dm.conformers.sasa(mol, conf_id=None, n_jobs=1)
# If minimization has been enabled (default to True)
# you can access the computed energy.
conf = mol.GetConformer(0)
props = conf.GetPropsAsDict()
print(props)
# {'rdkit_uff_energy': 1.7649408317784008}
```
Args:
mol: a molecule
conf_id: Id of the conformers to compute. If None, compute all.
n_jobs: Number of jobs for parallelization. Set to 1 to disable
and -1 to use all cores.
Returns:
mol: the molecule with the conformers.
"""
from rdkit.Chem import rdFreeSASA
if mol.GetNumConformers() == 0:
raise ValueError(
"The molecule has 0 conformers. You can generate conformers with `dm.conformers.generate(mol)`."
)
# Get Van der Waals radii (angstrom)
radii = [
dm.PERIODIC_TABLE.GetRvdw(atom.GetAtomicNum())
for atom in mol.GetAtoms()
]
# Which conformers to compute
conf_ids = []
if conf_id is None:
# If None compute for all the conformers
conf_ids = list(range(mol.GetNumConformers())) # type: ignore
elif isinstance(conf_id, int):
conf_ids = [conf_id]
else:
conf_ids = conf_id
# Compute solvent accessible surface area
def _get_sasa(i):
conf = mol.GetConformer(i)
sasa = rdFreeSASA.CalcSASA(mol, radii, confIdx=conf.GetId())
conf.SetDoubleProp("rdkit_free_sasa", sasa)
return sasa
runner = dm.JobRunner(n_jobs=n_jobs)
sasa_values = runner(_get_sasa, conf_ids)
return np.array(sasa_values)
def tree_decomp(
mol: Chem.rdchem.Mol) -> Tuple[List[List[int]], List[Tuple[int, int]]]:
n_atoms = mol.GetNumAtoms()
cliques = []
for atom in mol.GetAtoms():
if atom.GetDegree() == 0:
cliques.append([atom.GetIdx()])
for bond in mol.GetBonds():
a1 = bond.GetBeginAtom().GetIdx()
a2 = bond.GetEndAtom().GetIdx()
if not bond.IsInRing():
cliques.append([a1, a2])
ssr = [list(x) for x in Chem.GetSymmSSSR(mol)]
cliques.extend(ssr)
nei_list = [[] for i in range(n_atoms)]
for i in range(len(cliques)):
for atom in cliques[i]:
nei_list[atom].append(i)
# Merge Rings with intersection > 2 atoms
for i in range(len(cliques)):
if len(cliques[i]) <= 2: continue
for atom in cliques[i]:
for j in nei_list[atom]:
if i >= j or len(cliques[j]) <= 2: continue
inter = set(cliques[i]) & set(cliques[j])
if len(inter) > 2:
cliques[i].extend(cliques[j])
cliques[i] = list(set(cliques[i]))
cliques[j] = []
cliques = [c for c in cliques if len(c) > 0]
nei_list = [[] for i in range(n_atoms)]
for i in range(len(cliques)):
for atom in cliques[i]:
nei_list[atom].append(i)
# Build edges and add singleton cliques
edges = defaultdict(int)
for atom in range(n_atoms):
if len(nei_list[atom]) <= 1:
continue
cnei = nei_list[atom]
bonds = [c for c in cnei if len(cliques[c]) == 2]
rings = [c for c in cnei if len(cliques[c]) > 4]
if len(bonds) > 2 or (
len(bonds) == 2 and len(cnei) > 2
): # In general, if len(cnei) >= 3, a singleton should be added, but 1 bond + 2 ring is currently not dealt with.
cliques.append([atom])
c2 = len(cliques) - 1
for c1 in cnei:
edges[(c1, c2)] = 1
elif len(rings) > 2: # Multiple (n>2) complex rings
cliques.append([atom])
c2 = len(cliques) - 1
for c1 in cnei:
edges[(c1, c2)] = MST_MAX_WEIGHT - 1
else:
for i in range(len(cnei)):
for j in range(i + 1, len(cnei)):
c1, c2 = cnei[i], cnei[j]
inter = set(cliques[c1]) & set(cliques[c2])
if edges[(c1, c2)] < len(inter):
edges[(c1, c2)] = len(
inter) # cnei[i] < cnei[j] by construction
edges = [u + (MST_MAX_WEIGHT - v, ) for u, v in edges.items()]
if len(edges) == 0:
return cliques, edges
# Compute Maximum Spanning Tree
row, col, data = zip(*edges)
n_clique = len(cliques)
clique_graph = csr_matrix((data, (row, col)), shape=(n_clique, n_clique))
junc_tree = minimum_spanning_tree(clique_graph)
row, col = junc_tree.nonzero()
edges = [(row[i], col[i]) for i in range(len(row))]
return cliques, edges
def has_charge(mol: Chem.rdchem.Mol) -> bool:
for atom in mol.GetAtoms():
if atom.GetFormalCharge() != 0:
return True
return False
