def get_conformer_energy(mol: Chem.Mol, confId: int = None) -> float:
"""Returns the energy of the conformer with `confId` in `mol`.
"""
if confId is None:
confId = mol.GetNumConformers() - 1
Chem.MMFFSanitizeMolecule(mol)
mmff_props = Chem.MMFFGetMoleculeProperties(mol)
ff = Chem.MMFFGetMoleculeForceField(mol, mmff_props, confId=confId)
energy = ff.CalcEnergy()
return energy
def prune_last_conformer(
mol: Chem.Mol, tfd_thresh: float,
energies: List[float]) -> Tuple[Chem.Mol, List[float]]:
"""Prunes the last conformer of the molecule.
If no conformers in `mol` have a TFD (Torsional Fingerprint Deviation) with the last conformer of less than `tfd_thresh`,
the last conformer is kept. Otherwise, the lowest energy conformer with TFD less than `tfd_thresh` is kept and all other conformers
are discarded.
Parameters
----------
mol : RDKit Mol
The molecule to be pruned. The conformers in the molecule should be ordered by ascending energy.
tfd_thresh : float
The minimum threshold for TFD between conformers.
energies : list of float
A list of all the energies of the conformers in `mol`.
Returns
-------
mol : RDKit Mol
The updated molecule after pruning, with conformers sorted by ascending energy.
energies : list of float
A list of all the energies of the conformers in `mol` after pruning and sorting by ascending energy.
"""
if tfd_thresh < 0 or mol.GetNumConformers() <= 1:
return mol, energies
idx = bisect.bisect(energies[:-1], energies[-1])
tfd = TorsionFingerprints.GetTFDBetweenConformers(
mol,
range(0,
mol.GetNumConformers() - 1), [mol.GetNumConformers() - 1],
useWeights=False)
tfd = np.array(tfd)
# if lower energy conformer is within threshold, drop new conf
if not np.all(tfd[:idx] >= tfd_thresh):
energies = energies[:-1]
mol.RemoveConformer(mol.GetNumConformers() - 1)
return mol, energies
else:
keep = list(range(0, idx))
keep.append(mol.GetNumConformers() - 1)
keep += [
x for x in range(idx,
mol.GetNumConformers() - 1)
if tfd[x] >= tfd_thresh
]
new = Chem.Mol(mol)
new.RemoveAllConformers()
for i in keep:
conf = mol.GetConformer(i)
new.AddConformer(conf, assignId=True)
return new, [energies[i] for i in keep]
def prune_conformers(mol: Chem.Mol, tfd_thresh: float) -> Chem.Mol:
"""Prunes all the conformers in the molecule.
Removes conformers that have a TFD (torsional fingerprint deviation) lower than
`tfd_thresh` with other conformers. Lowest energy conformers are kept.
Parameters
----------
mol : RDKit Mol
The molecule to be pruned.
tfd_thresh : float
The minimum threshold for TFD between conformers.
Returns
-------
mol : RDKit Mol
The updated molecule after pruning.
"""
if tfd_thresh < 0 or mol.GetNumConformers() <= 1:
return mol
energies = get_conformer_energies(mol)
tfd = tfd_matrix(mol)
sort = np.argsort(energies) # sort by increasing energy
keep = [] # always keep lowest-energy conformer
discard = []
for i in sort:
this_tfd = tfd[i][np.asarray(keep, dtype=int)]
# discard conformers within the tfd threshold
if np.all(this_tfd >= tfd_thresh):
keep.append(i)
else:
discard.append(i)
# create a new molecule to hold the chosen conformers
# this ensures proper conformer IDs and energy-based ordering
new = Chem.Mol(mol)
new.RemoveAllConformers()
for i in keep:
conf = mol.GetConformer(int(i))
new.AddConformer(conf, assignId=True)
return new