def bonds_of_type(gra, symb1, symb2, mbond=1):
""" Determine the indices of all a specific bond
specified by atom type and bond order.
:param gra: molecular graph
:type gra: molecular graph data structure
:param symb1: symbol of atom 1 in the bond
:type symb1: str
:param symb2: symbol of atom 2 in the bond
:type symb2: str
:param mbond: bond order of desired bond type
:type mbond: int
:rtype: tuple(int)
"""
# Get the dict that relates atom indices to symbols
idx_symb_dct = atom_symbols(gra)
# Loop over all the bonds and build a list of ones that match
_bonds_of_type = tuple()
_bonds = bonds_of_order(gra, mbond=mbond)
for bond in _bonds:
idx1, idx2 = bond
symb1, symb2 = idx_symb_dct[idx1], idx_symb_dct[idx2]
if (symb1, symb2) in ((symb1, symb2), (symb2, symb1)):
_bonds_of_type += ((idx1, idx2), )
return _bonds_of_type
def rotational_bond_keys(gra, lin_keys=None, with_h_rotors=True):
""" get all rotational bonds for a graph
:param gra: the graph
:param lin_keys: keys to linear atoms in the graph
"""
gra = explicit(gra)
sym_dct = atom_symbols(gra)
ngb_keys_dct = atoms_neighbor_atom_keys(gra)
bnd_ord_dct = resonance_dominant_bond_orders(gra)
rng_bnd_keys = list(itertools.chain(*rings_bond_keys(gra)))
def _is_rotational_bond(bnd_key):
ngb_keys_lst = [ngb_keys_dct[k] - bnd_key for k in bnd_key]
is_single = max(bnd_ord_dct[bnd_key]) <= 1
has_neighbors = all(ngb_keys_lst)
not_in_ring = bnd_key not in rng_bnd_keys
is_h_rotor = any(
set(map(sym_dct.__getitem__, ks)) == {'H'} for ks in ngb_keys_lst)
return is_single and has_neighbors and not_in_ring and (
not is_h_rotor or with_h_rotors)
rot_bnd_keys = frozenset(filter(_is_rotational_bond, bond_keys(gra)))
lin_keys_lst = linear_segments_atom_keys(gra, lin_keys=lin_keys)
dum_keys = tuple(atom_keys(gra, sym='X'))
for keys in lin_keys_lst:
bnd_keys = sorted((k for k in rot_bnd_keys if k & set(keys)),
key=sorted)
# Check whether there are neighboring atoms on either side of the
# linear segment
excl_keys = set(keys) | set(dum_keys)
end_key1 = atom_neighbor_atom_key(gra,
keys[0],
excl_atm_keys=excl_keys)
excl_keys |= {end_key1}
end_key2 = atom_neighbor_atom_key(gra,
keys[-1],
excl_atm_keys=excl_keys)
end_keys = {end_key1, end_key2}
ngb_keys_lst = [ngb_keys_dct[k] - excl_keys for k in end_keys]
has_neighbors = all(ngb_keys_lst)
if not has_neighbors:
rot_bnd_keys -= set(bnd_keys)
else:
rot_bnd_keys -= set(bnd_keys[:-1])
return rot_bnd_keys
def equivalent_bonds(gra, bnd_key, stereo=True, dummy=True):
""" Identify sets of isomorphically equivalent bonds
Two bonds are equivalent if they transform into each other under an
automorphism
:param gra: A graph
:param bnd_key: An bond key for the graph, which may be sorted or unsorted
:param backbone_only: Compare backbone atoms only?
:type stereo: bool
:param dummy: Consider dummy atoms?
:type dummy: bool
:returns: Keys to equivalent bonds
:rtype: frozenset
"""
bnd_key = tuple(bnd_key)
bnd_keys = list(map(tuple, map(sorted, bond_keys(gra))))
bnd_keys += list(map(tuple, map(reversed, bnd_keys)))
assert bnd_key in bnd_keys, f"{bnd_key} not in {bnd_keys}"
atm_symb_dct = atom_symbols(gra)
atm_ngbs_dct = atoms_neighbor_atom_keys(gra)
def _symbols(bnd_key):
return list(map(atm_symb_dct.__getitem__, bnd_key))
def _neighbor_symbols(bnd_key):
key1, key2 = bnd_key
nsymbs1 = sorted(map(atm_symb_dct.__getitem__, atm_ngbs_dct[key1]))
nsymbs2 = sorted(map(atm_symb_dct.__getitem__, atm_ngbs_dct[key2]))
return nsymbs1, nsymbs2
# 1. Find bonds with the same atom types
bnd_symbs = _symbols(bnd_key)
cand_keys = [k for k in bnd_keys if _symbols(k) == bnd_symbs]
# 2. Of those, find bonds with the same neighboring atom types
bnd_ngb_symbs = _neighbor_symbols(bnd_key)
cand_keys = [k for k in cand_keys
if _neighbor_symbols(k) == bnd_ngb_symbs]
# 3. Find the equivalent bonds from the list of candidates.
# Strategy: Change the atom symbols to 'Lv' and 'Ts' and check for
# isomorphism. Assumes none of the compounds have element 116 or 117.
bnd_keys = []
for key in cand_keys:
if are_equivalent_bonds(gra, bnd_key, key, stereo=stereo, dummy=dummy):
bnd_keys.append(key)
return frozenset(bnd_keys)
def from_graph(gra):
""" networkx graph object from a molecular graph
"""
nxg = networkx.Graph()
nxg.add_nodes_from(atom_keys(gra))
nxg.add_edges_from(bond_keys(gra))
networkx.set_node_attributes(nxg, atom_symbols(gra), 'symbol')
networkx.set_node_attributes(nxg, atom_implicit_hydrogen_valences(gra),
'implicit_hydrogen_valence')
networkx.set_node_attributes(nxg, atom_stereo_parities(gra),
'stereo_parity')
networkx.set_edge_attributes(nxg, bond_orders(gra), 'order')
networkx.set_edge_attributes(nxg, bond_stereo_parities(gra),
'stereo_parity')
return nxg
def equivalent_atoms(gra, atm_key, stereo=True, dummy=True):
""" Identify sets of isomorphically equivalent atoms
Two atoms are equivalent if they transform into each other under an
automorphism
:param gra: A graph
:param atm_key: An atom key for the graph
:param stereo: Consider stereo?
:type stereo: bool
:param dummy: Consider dummy atoms?
:type dummy: bool
:returns: Keys to equivalent atoms
:rtype: frozenset
"""
assert atm_key in atom_keys(gra), (
f"{atm_key} not in {atom_keys(gra)}")
atm_symb_dct = atom_symbols(gra)
atm_ngbs_dct = atoms_neighbor_atom_keys(gra)
def _neighbor_symbols(key):
return sorted(map(atm_symb_dct.__getitem__, atm_ngbs_dct[key]))
# 1. Find atoms with the same symbols
atm_symb = atm_symb_dct[atm_key]
cand_keys = atom_keys(gra, sym=atm_symb)
# 2. Of those, find atoms with the same neighboring atom types
atm_ngb_symbs = _neighbor_symbols(atm_key)
cand_keys = [k for k in cand_keys
if _neighbor_symbols(k) == atm_ngb_symbs]
# 3. Find the equivalent atoms from the list of candidates.
# Strategy: Change the atom symbol to 'Ts' and check for isomorphism.
# Assumes none of the compounds have element 117.
atm_keys = []
for key in cand_keys:
if are_equivalent_atoms(gra, atm_key, key, stereo=stereo, dummy=dummy):
atm_keys.append(key)
return frozenset(atm_keys)
def neighbors_of_type(gra, aidx, symb):
""" For a given atom, determine the indices of all the atoms
which neighbor it that are of the type specified.
:param gra: molecular graph
:type gra: molecular graph data structure
:param aidx: index of atom for which to find neighbors
:type aidx: int
:param symb: symbols of desired atom types for neighbors
:type symb: str
"""
idx_symb_dct = atom_symbols(gra)
neighs = atoms_neighbor_atom_keys(gra)[aidx]
neigh_symbs = _atom_idx_to_symb(neighs, idx_symb_dct)
idxs_of_type = tuple()
for nidx, nsymb in zip(neighs, neigh_symbs):
if nsymb == symb:
idxs_of_type += (nidx, )
return idxs_of_type
def two_bond_idxs(gra, symb1, cent, symb2):
""" Determine the triplet of indices of atoms of specified
types that are connected in a chain by two bonds:
(symb1_idx, cent_idx, symb2_idx).
:param gra: molecular graph
:type gra: molecular graph data structure
:param symb1: symbol of atom at one end of chain
:type symb1: str
:param cent: symbol of atom in the middle of a chain
:type cent: str
:param symb2: symbol of atom at other end of chain
:type symb2: str
"""
grps = tuple()
neigh_dct = atoms_neighbor_atom_keys(gra)
idx_symb_dct = atom_symbols(gra)
symb_idx_dct = atom_symbol_keys(gra)
cent_idxs = symb_idx_dct.get(cent, tuple())
for cent_idx in cent_idxs:
neighs = tuple(neigh_dct[cent_idx])
neigh_symbs = _atom_idx_to_symb(neighs, idx_symb_dct)
if neigh_symbs == (symb1, symb2):
grp_idxs = (neighs[0], cent_idx, neighs[1])
elif neigh_symbs == (symb2, symb1):
grp_idxs = (neighs[1], cent_idx, neighs[0])
else:
grp_idxs = ()
if grp_idxs:
grps += ((grp_idxs), )
return grps
def smiles(gra, stereo=True, local_stereo=False, res_stereo=False):
""" SMILES string from graph
:param gra: molecular graph
:type gra: automol graph data structure
:param stereo: Include stereo?
:type stereo: bool
:param local_stereo: Is the graph using local stereo assignments? That
is, are they based on atom keys rather than canonical keys?
:type local_stereo: bool
:param res_stereo: allow resonant double-bond stereo?
:type res_stereo: bool
:returns: the SMILES string
:rtype: str
"""
assert is_connected(gra), (
"Cannot form connection layer for disconnected graph.")
if not stereo:
gra = without_stereo_parities(gra)
# If not using local stereo assignments, canonicalize the graph first.
# From this point on, the stereo parities can be assumed to correspond to
# the neighboring atom keys.
if not local_stereo:
gra = canonical(gra)
# Convert to implicit graph
gra = implicit(gra)
# Insert hydrogens necessary for bond stereo
gra = _insert_stereo_hydrogens(gra)
# Find a dominant resonance
rgr = dominant_resonance(gra)
# Determine atom symbols
symb_dct = atom_symbols(rgr)
# Determine atom implicit hydrogens
nhyd_dct = atom_implicit_hydrogen_valences(rgr)
# Determine bond orders for this resonance
bnd_ord_dct = bond_orders(rgr)
# Find radical sites for this resonance
rad_atm_keys = radical_atom_keys_from_resonance(rgr)
# Determine neighbors
nkeys_dct = atoms_neighbor_atom_keys(rgr)
# Find stereo parities
atm_par_dct = dict_.filter_by_value(atom_stereo_parities(rgr),
lambda x: x is not None)
bnd_par_dct = dict_.filter_by_value(bond_stereo_parities(rgr),
lambda x: x is not None)
# Remove stereo parities if requested
if not res_stereo:
print('before')
print(bnd_par_dct)
bnd_par_dct = dict_.filter_by_key(bnd_par_dct,
lambda x: bnd_ord_dct[x] == 2)
print('after')
print(bnd_par_dct)
else:
raise NotImplementedError("Not yet implemented!")
def _atom_representation(key, just_seen=None, nkeys=(), closures=()):
symb = ptab.to_symbol(symb_dct[key])
nhyd = nhyd_dct[key]
needs_brackets = key in rad_atm_keys or symb not in ORGANIC_SUBSET
hyd_rep = f'H{nhyd}' if nhyd > 1 else ('H' if nhyd == 1 else '')
par_rep = ''
if key in atm_par_dct:
needs_brackets = True
skeys = [just_seen]
if nhyd:
assert nhyd == 1
skeys.append(-numpy.inf)
if closures:
skeys.extend(closures)
skeys.extend(nkeys)
can_par = atm_par_dct[key]
smi_par = can_par ^ util.is_odd_permutation(skeys, sorted(skeys))
par_rep = '@@' if smi_par else '@'
if needs_brackets:
rep = f'[{symb}{par_rep}{hyd_rep}]'
else:
rep = f'{symb}'
return rep
# Get the pool of stereo bonds for the graph and set up a dictionary for
# storing the ending representation.
ste_bnd_key_pool = list(bnd_par_dct.keys())
drep_dct = {}
def _bond_representation(key, just_seen=None):
key0 = just_seen
key1 = key
# First, handle the bond order
if key0 is None or key1 is None:
rep = ''
else:
bnd_ord = bnd_ord_dct[frozenset({key0, key1})]
if bnd_ord == 1:
rep = ''
elif bnd_ord == 2:
rep = '='
elif bnd_ord == 3:
rep = '#'
else:
raise ValueError("Bond orders greater than 3 not permitted.")
drep = drep_dct[(key0, key1)] if (key0, key1) in drep_dct else ''
bnd_key = next((b for b in ste_bnd_key_pool if key1 in b), None)
if bnd_key is not None:
# We've encountered a new stereo bond, so remove it from the pool
ste_bnd_key_pool.remove(bnd_key)
# Determine the atoms involved
key2, = bnd_key - {key1}
nkey1s = set(nkeys_dct[key1]) - {key2}
nkey2s = set(nkeys_dct[key2]) - {key1}
nmax1 = max(nkey1s)
nmax2 = max(nkey2s)
nkey1 = just_seen if just_seen in nkey1s else nmax1
nkey2 = nmax2
# Determine parity
can_par = bnd_par_dct[bnd_key]
smi_par = can_par if nkey1 == nmax1 else not can_par
# Determine bond directions
drep1 = drep if drep else '/'
if just_seen in nkey1s:
drep = drep1
flip = not smi_par
else:
drep_dct[(key1, nkey1)] = drep1
flip = smi_par
drep2 = _flip_direction(drep1, flip=flip)
drep_dct[(key2, nkey2)] = drep2
rep += drep
# Second, handle directionality (bond stereo)
return rep
# Get the pool of rings for the graph and set up a dictionary for storing
# their tags. As the SMILES is built, each next ring that is encountered
# will be given a tag, removed from the pool, and transferred to the tag
# dictionary.
rng_pool = list(rings_atom_keys(rgr))
rng_tag_dct = {}
def _ring_representation_with_nkeys_and_closures(key, nkeys=()):
nkeys = nkeys.copy()
# Check for new rings in the ring pool. If a new ring is found, create
# a tag, add it to the tags dictionary, and drop it from the rings
# pool.
for new_rng in rng_pool:
if key in new_rng:
# Choose a neighbor key for SMILES ring closure
clos_nkey = sorted(set(new_rng) & set(nkeys))[0]
# Add it to the ring tag dictionary with the current key first
# and the closure key last
tag = max(rng_tag_dct.values(), default=0) + 1
assert tag < 10, (
f"Ring tag exceeds 10 for this graph:\n{string(gra)}")
rng = cycle_ring_atom_key_to_front(new_rng, key, clos_nkey)
rng_tag_dct[rng] = tag
# Remove it from the pool of unseen rings
rng_pool.remove(new_rng)
tags = []
closures = []
for rng, tag in rng_tag_dct.items():
if key == rng[-1]:
nkeys.remove(rng[0])
closures.append(rng[0])
# Handle the special case where the last ring bond has stereo
if (rng[-1], rng[0]) in drep_dct:
drep = drep_dct[(rng[-1], rng[0])]
tags.append(f'{drep}{tag}')
else:
tags.append(f'{tag}')
if key == rng[0]:
nkeys.remove(rng[-1])
closures.append(rng[-1])
tags.append(f'{tag}')
rrep = ''.join(map(str, tags))
return rrep, nkeys, closures
# Determine neighboring keys
nkeys_dct_pool = dict_.transform_values(atoms_neighbor_atom_keys(rgr),
sorted)
def _recurse_smiles(smi, lst, key, just_seen=None):
nkeys = nkeys_dct_pool.pop(key) if key in nkeys_dct_pool else []
# Remove keys just seen from the list of neighbors, to avoid doubling
# back.
if just_seen in nkeys:
nkeys.remove(just_seen)
# Start the SMILES string and connection list. The connection list is
# used for sorting.
rrep, nkeys, closures = _ring_representation_with_nkeys_and_closures(
key, nkeys)
arep = _atom_representation(key, just_seen, nkeys, closures=closures)
brep = _bond_representation(key, just_seen)
smi = f'{brep}{arep}{rrep}'
lst = [key]
# Now, extend the layer/list along the neighboring atoms.
if nkeys:
# Build sub-strings/lists by recursively calling this function.
sub_smis = []
sub_lsts = []
while nkeys:
nkey = nkeys.pop(0)
sub_smi, sub_lst = _recurse_smiles('', [], nkey, just_seen=key)
sub_smis.append(sub_smi)
sub_lsts.append(sub_lst)
# If this is a ring, remove the neighbor on the other side of
# `key` to prevent repetition as we go around the ring.
if sub_lst[-1] == key:
nkeys.remove(sub_lst[-2])
# Now, join the sub-layers and lists together.
# If there is only one neighbor, we joint it as
# {arep1}{brep2}{arep2}...
if len(sub_lsts) == 1:
sub_smi = sub_smis[0]
sub_lst = sub_lsts[0]
# Extend the SMILES string
smi += f'{sub_smi}'
# Extend the list
lst.extend(sub_lst)
# If there are multiple neighbors, we joint them as
# {arep1}({brep2}{arep2}...)({brep3}{arep3}...){brep4}{arep4}...
else:
assert len(sub_lsts) > 1
# Extend the SMILES string
smi += (''.join(map("({:s})".format, sub_smis[:-1])) +
sub_smis[-1])
# Append the lists of neighboring branches.
lst.append(sub_lsts)
return smi, lst
# If there are terminal atoms, start from the first one
atm_keys = atom_keys(rgr)
term_keys = terminal_atom_keys(gra, heavy=False)
start_key = min(term_keys) if term_keys else min(atm_keys)
smi, _ = _recurse_smiles('', [], start_key)
return smi