def Match(self, mol, flg=True):
# Find all the hetero-aromatic atoms
hetero_atoms = [atom for atom in mol.GetAtoms(_is_hetereo_aromatic)]
if len(hetero_atoms) < 2:
# The caller just needs an iterable
return hetero_atoms
# There are at least two hetero-aromatic atoms.
# Are there multiple ring systems?
num_aromatic_systems, parts = OEDetermineAromaticRingSystems(mol)
assert num_aromatic_systems >= 1
# Are there hetero-atoms in different systems?
atom_components = set(parts[atom.GetIdx()] for atom in hetero_atoms)
if len(atom_components) > 1:
return (1, 2)
# The answer now is "at least one". But are there two?
# All of the hetero-aromatic atoms are in the same ring system
# This is the best answer I could think of, and it only works
# with the OEChem toolkit: remove one of the bonds, re-find
# the rings, and see if there's still an aromatic hetero-atom.
hetero_atom = hetero_atoms[0]
for bond in hetero_atom.GetBonds(OEIsAromaticBond()):
newmol = OEGraphMol(mol)
newmol_bond = newmol.GetBond(OEHasBondIdx(bond.GetIdx()))
newmol.DeleteBond(newmol_bond)
OEFindRingAtomsAndBonds(newmol)
for atom in mol.GetAtoms(_is_hetereo_aromatic):
return (1, 2)
return (1, )
def save_profile_as_sd(mol: oechem.OEGraphMol):
oechem.OEDeleteSDData(mol, TOTAL_STRAIN_TAG)
oechem.OESetSDData(mol, TOTAL_STRAIN_TAG, '') # place holder
oechem.OEDeleteSDData(mol, NUM_TORSION_PROFILES_TAG)
oechem.OESetSDData(mol, NUM_TORSION_PROFILES_TAG, '')
oechem.OEDeleteSDData(mol, NUM_LOW_CONFIDENCE_TORSIONS_TAG)
oechem.OESetSDData(mol, NUM_LOW_CONFIDENCE_TORSIONS_TAG, '')
strain_arr = np.zeros(1)
strain_arr_high_conf_preds = np.zeros(1)
num_torsion_profiles = 0
num_low_confidence_torsions = 0
can_torsions = get_canonical_torsions(mol)
for num, can_torsion in enumerate(can_torsions):
bond = mol.GetBond(can_torsion.b, can_torsion.c)
if bond is not None and bond.HasData(ENERGY_PROFILE_TAG):
num_torsion_profiles += 1
bond_strains = bond.GetData(STRAIN_TAG)
profile_offset = bond.GetData(PROFILE_OFFSET_TAG)
if profile_offset < OFFSET_THRESHOLD and (
not bond.HasData(SKIP_TORSION_TAG)):
strain_arr_high_conf_preds += np.array(bond_strains)
strain_arr += np.array(bond_strains)
offset = bond.GetData(PROFILE_OFFSET_TAG)
profile_str = bond.GetData(ENERGY_PROFILE_TAG)
pred_confidence_value = HIGH_PREDICTION_CONFIDENCE_TAG
if offset > OFFSET_THRESHOLD or bond.HasData(SKIP_TORSION_TAG):
profile_str = 'LOW CONFIDENCE - ' + profile_str
pred_confidence_value = LOW_PREDICTION_CONFIDENCE_TAG
num_low_confidence_torsions += 1
#tor_atoms_str = bond.GetData(TORSION_ATOMS_FRAGMENT_TAG)
#tor_atoms_str_list = tor_atoms_str.split(':')
#a_idx, b_idx, c_idx, d_idx = list(map(int, tor_atoms_str_list[0].split()))
tor_atoms_str1 = bond.GetData(TORSION_ATOMS_FRAGMENT_TAG)
ca, cb, cc, cd = list(map(int, tor_atoms_str1.split()))
apStr = "{}:{}:{}:{}".format(ca + 1, cb + 1, cc + 1, cd + 1)
atom_ca = mol.GetAtom(oechem.OEHasAtomIdx(ca))
atom_cb = mol.GetAtom(oechem.OEHasAtomIdx(cb))
atom_cc = mol.GetAtom(oechem.OEHasAtomIdx(cc))
atom_cd = mol.GetAtom(oechem.OEHasAtomIdx(cd))
angle_float = oechem.OEGetTorsion(mol, atom_ca, atom_cb, atom_cc,
atom_cd) * oechem.Rad2Deg
sd_tag1 = 'TORSION_%s_ATOMS' % (num + 1)
sd_tag2 = 'TORSION_%d_TORSIONNET_%s' % (num + 1,
ENERGY_PROFILE_TAG)
sd_tag3 = 'TORSION_%d_TORSIONNET_PRED_CONFIDENCE' % (num + 1)
sd_tag4 = 'TORSION_%d_TORSIONNET_PROFILE_OFFSET' % (num + 1)
oechem.OEDeleteSDData(mol, sd_tag1)
oechem.OEDeleteSDData(mol, sd_tag2)
oechem.OEDeleteSDData(mol, sd_tag3)
oechem.OEDeleteSDData(mol, sd_tag4)
oechem.OESetSDData(mol, sd_tag1, apStr)
oechem.OESetSDData(mol, sd_tag2, profile_str)
sd_tag6 = 'TORSION_%d_%s' % ((num + 1), STRAIN_TAG)
oechem.OEDeleteSDData(mol, sd_tag6)
oechem.OESetSDData(mol, sd_tag6, '%.1f' % bond_strains)
angle = '%.1f' % angle_float
sd_tag5 = 'TORSION_%d_ANGLE' % (num + 1)
oechem.OEDeleteSDData(mol, sd_tag5)
oechem.OESetSDData(mol, sd_tag5, angle)
oechem.OESetSDData(mol, sd_tag3, pred_confidence_value)
oechem.OESetSDData(mol, sd_tag4, '%.2f' % offset)
strain_str = '%.1f' % strain_arr_high_conf_preds[0]
oechem.OESetSDData(mol, TOTAL_STRAIN_TAG, strain_str)
oechem.OESetSDData(mol, NUM_TORSION_PROFILES_TAG,
str(num_torsion_profiles))
oechem.OESetSDData(mol, NUM_LOW_CONFIDENCE_TORSIONS_TAG,
str(num_low_confidence_torsions))
reorder_sd_props(mol)
return mol
