def get_residue_vdw(self, residue, res_num, padding=3.0):
"""
generates a mask for the residue where points within VdW distance of residue heavy atoms are
:param residue: `ccdc.prottein.Residue`
:param res_num: The value which to assign to voxels in the masked area
:param padding: float, padding around minimal coordinates in Angstroms
:return: `hotspots.grid_extension.Grid`
"""
coords = np.array([a.coordinates for a in residue.atoms])
min_coords = (np.min(coords[:, 0]), np.min(coords[:, 1]),
np.min(coords[:, 2]))
max_coords = (np.max(coords[:, 0]), np.max(coords[:, 1]),
np.max(coords[:, 2]))
# Put some padding around the minimal and maximum values:
g_origin = tuple(x - padding for x in min_coords)
g_far_corner = tuple(y + padding for y in max_coords)
layer = Grid(origin=g_origin,
far_corner=g_far_corner,
spacing=self.g_spacing,
default=0.0,
_grid=None)
for a in residue.atoms:
layer.set_sphere(point=a.coordinates,
radius=a.vdw_radius,
value=1,
scaling='None')
layer = self.set_uniform_values(layer, res_num)
print("Size of layer: {}".format(layer.count_grid()))
return layer
def _as_grid(self, feature_type=None, tolerance=2):
"""
returns _features as grid
"""
if feature_type == None:
filtered_features = self._features
else:
filtered_features = [
feat for feat in self._features
if feat.feature_type == feature_type
]
x = [feat.feature_coordinates.x for feat in filtered_features]
y = [feat.feature_coordinates.y for feat in filtered_features]
z = [feat.feature_coordinates.z for feat in filtered_features]
origin = [min(x) - tolerance, min(y) - tolerance, min(z) - tolerance]
far_corner = [
max(x) + tolerance,
max(y) + tolerance,
max(z) + tolerance
]
grd = Grid(origin=origin,
far_corner=far_corner,
spacing=0.5,
default=0,
_grid=None)
for feat in filtered_features:
grd.set_sphere(point=feat.feature_coordinates,
radius=self.settings.radius,
value=1,
scaling='None')
return grd
def get_grid_from_plip_coords(probe, coords, out_path, padding=4.0):
"""
:param probe:
:param coords:
:param padding:
:return:
"""
Coordinates = collections.namedtuple('Coordinates', ['x', 'y', 'z'])
dims = np.array(coords)
min_coords = np.array(
[np.min(dims[:, 0]),
np.min(dims[:, 1]),
np.min(dims[:, 2])])
max_coords = np.array(
[np.max(dims[:, 0]),
np.max(dims[:, 1]),
np.max(dims[:, 2])])
origin = Coordinates(x=round(min_coords[0] - padding),
y=round(min_coords[1] - padding),
z=round(min_coords[2] - padding))
far_corner = Coordinates(x=round(max_coords[0] + padding),
y=round(max_coords[1] + padding),
z=round(max_coords[2] + padding))
plip_grid = Grid(origin=origin,
far_corner=far_corner,
spacing=0.5,
default=0,
_grid=None)
for coo in coords:
plip_grid.set_sphere(point=coo, radius=1, value=1, scaling='None')
plip_grid.write(str(Path(out_path, f"plip_{probe}.ccp4").resolve()))
return plip_grid
