def _molecule_as_grid(mol, g=None):
"""
Produces a grid representation of a molecule split by interaction type
:param mol: takes any ccdc molecule
:type mol: `ccdc.molecule.Molecule`
:param g: a blank grid
:type g: `hotspots.grid_extension.Grid`
:return: a dictionary of grids by interaction type
:rtype: dict
"""
if not g:
g = Grid.initalise_grid(coords=[a.coordinates for a in mol.atoms],
padding=3)
grid_dict = {"donor": g.copy(), "acceptor": g.copy(), "apolar": g.copy()}
for p, g in grid_dict.items():
atms = [a for a in mol.atoms if Helper.get_atom_type(a) == p]
for atm in atms:
g.set_sphere(point=atm.coordinates,
radius=atm.vdw_radius,
value=1,
scaling='None')
return grid_dict
def _get_atomic_overlap(self, cav_id, other_id, lig_id):
"""
find the highest median bcv from all cavities, calculate percentage over between the best bcv
and each query ligand
:return:
"""
# inputs
mol = io.MoleculeReader(self.extracted_ligands[other_id][lig_id])[0]
path = os.path.join(self.bcv[cav_id][other_id][lig_id], "out.zip")
if os.path.exists(path):
hr = HotspotReader(path).read()
# tasks
out = hr.atomic_volume_overlap(mol)
else:
print("no BCV for cavity {}, BCV {}".format(cav_id, lig_id))
out = {"donor": {}, "acceptor": {}, "apolar": {}}
for a in mol.heavy_atoms:
t = Helper.get_atom_type(a)
if t == "doneptor":
out["donor"].update({a.label: 0.0})
out["acceptor"].update({a.label: 0.0})
else:
out[t].update({a.label: 0.0})
# output
with open(self.atomic_overlaps[cav_id][other_id][lig_id], 'w') as writer:
writer.write(str(out))