def _surface_from_sasa(
self,
elements: Iterable[int] | Iterable[str],
coordinates: ArrayLike2D,
) -> None:
"""Get surface from SASA."""
sasa = SASA(
elements,
coordinates,
radii=self._radii,
density=self._density,
probe_radius=0,
)
self._atoms = sasa._atoms
self.area = sum(
[
atom.area
for atom in self._atoms
if atom.index not in self._excluded_atoms
]
)
self.atom_areas = sasa.atom_areas
self.volume = sum(
[
atom.volume
for atom in self._atoms
if atom.index not in self._excluded_atoms
]
)
# Get point areas and map from point to atom
point_areas: list[Array1DFloat] = []
point_map = []
for atom in self._atoms:
n_points = len(atom.accessible_points)
if n_points > 0:
point_area = atom.area / n_points
else:
point_area = 0.0
atom.point_areas = np.repeat(point_area, n_points)
point_areas.extend(atom.point_areas)
point_map.extend([atom.index] * n_points)
self._point_areas = np.array(point_areas)
self._point_map = np.array(point_map)
def surface_from_radii(self, density: float = 0.01) -> "Sterimol":
"""Create surface points from vdW surface.
Args:
density: Area per point on surface (Ų)
Returns:
self: Self
"""
# Calculate vdW surface for all active atoms
elements = []
coordinates = []
radii = []
for atom in self._atoms:
if atom.index not in self._excluded_atoms and atom is not self._dummy_atom:
elements.append(atom.element)
coordinates.append(atom.coordinates)
radii.append(atom.radius)
elements = np.array(elements)
coordinates = np.vstack(coordinates)
radii = radii
sasa = SASA(elements,
coordinates,
radii=radii,
density=density,
probe_radius=0)
# Take out points of vdW surface
points = np.vstack([
atom.accessible_points for atom in sasa._atoms
if atom.index not in self._excluded_atoms
and atom.accessible_points.size > 0
])
self._points = points
return self
def compute_distal_volume(self,
method: str = "sasa",
octants: bool = False,
sasa_density: float = 0.01) -> "BuriedVolume":
"""Computes the distal volume.
Uses either SASA or Buried volume with large radius to calculate the molecular
volume.
Args:
method: Method to get total volume: 'buried_volume' or 'sasa'
octants: Whether to compute distal volume for quadrants and octants.
Requires method='buried_volume'
sasa_density: Density of points on SASA surface. Ignored unless
method='sasa'
Returns:
self: Self
Raises:
ValueError: When method is not specified correctly.
"""
loop_coordinates: list[Array1DFloat]
# Use SASA to calculate total volume of the molecule
if method == "sasa":
# Calculate total volume
elements: list[int] = []
loop_coordinates = []
radii: list[float] = []
for atom in self._atoms:
elements.append(atom.element)
loop_coordinates.append(atom.coordinates)
radii.append(atom.radius)
coordinates: Array2DFloat = np.vstack(loop_coordinates)
sasa = SASA(
elements,
coordinates,
radii=radii,
probe_radius=0.0,
density=sasa_density,
)
self.molecular_volume = sasa.volume
# Calculate distal volume
self.distal_volume = self.molecular_volume - self.buried_volume
elif method == "buried_volume":
if octants is True and self.octants is None:
raise ValueError("Needs octant analysis.")
# Save the values for the old buried volume calculation
temp_bv = copy.deepcopy(self)
# Determine sphere radius to cover the whole molecule
loop_coordinates = []
radii = []
for atom in self._atoms:
loop_coordinates.append(atom.coordinates)
radii.append(atom.radius)
coordinates = np.vstack(loop_coordinates)
distances = scipy.spatial.distance.cdist(
self._sphere.center.reshape(1, -1), coordinates)
new_radius = np.max(distances + radii) + 0.5
# Compute the distal volume
temp_bv._compute_buried_volume(
center=self._sphere.center,
radius=new_radius,
density=self._sphere.density,
)
self.molecular_volume = temp_bv.buried_volume
self.distal_volume = self.molecular_volume - self.buried_volume
if octants is True:
temp_bv.octant_analysis()
# Octant analysis
distal_volume = {}
molecular_volume = {}
for name in self.octants["buried_volume"].keys():
molecular_volume[name] = temp_bv.octants["buried_volume"][
name]
distal_volume[name] = (
temp_bv.octants["buried_volume"][name] -
self.octants["buried_volume"][name])
self.octants["distal_volume"] = distal_volume
self.octants["molecular_volume"] = molecular_volume
# Quadrant analyis
distal_volume = {}
molecular_volume = {}
for name, octants_ in QUADRANT_OCTANT_MAP.items():
distal_volume[name] = sum([
self.octants["distal_volume"][octant]
for octant in octants_
])
molecular_volume[name] = sum([
self.octants["molecular_volume"][octant]
for octant in octants_
])
self.quadrants["distal_volume"] = distal_volume
self.quadrants["molecular_volume"] = molecular_volume
else:
raise ValueError(f"Method {method} is not valid.")
return self
def __init__(
self,
elements: Iterable[int] | Iterable[str],
coordinates: ArrayLike2D,
metal_index: int,
include_hs: bool = True,
radii: ArrayLike1D | None = None,
radii_type: str = "pyykko",
radius: float = 3.5,
density: float = 0.01,
) -> None:
# Set up arrays and get radii
elements: Array1DInt = np.array(
convert_elements(elements, output="numbers"))
coordinates: Array2DFloat = np.array(coordinates)
if radii is None:
radii = get_radii(elements, radii_type=radii_type)
radii: Array1DFloat = np.array(radii)
# Check so that no atom is within vdW distance of metal atom
within = check_distances(elements,
coordinates,
metal_index,
radii=radii)
if len(within) > 0:
atom_string = " ".join([str(i) for i in within])
raise Exception("Atoms within vdW radius of central atom:",
atom_string)
# Center coordinate system around metal and remove it
coordinates -= coordinates[metal_index - 1]
elements: Array1DFloat = np.delete(elements, metal_index - 1)
coordinates: Array2DFloat = np.delete(coordinates,
metal_index - 1,
axis=0)
radii: Array1DFloat = np.delete(radii, metal_index - 1)
# Remove H atoms
if include_hs is False:
h_mask = elements == 1
elements = elements[~h_mask]
coordinates = coordinates[~h_mask]
radii = radii[~h_mask]
# Construct SASA object
sasa = SASA(
elements,
coordinates,
radii=radii,
radii_type=radii_type,
probe_radius=0.0,
density=density,
)
# Set invisible and proximal masks for each atom
atoms = sasa._atoms
for atom in atoms:
atom.invisible_mask = np.zeros(len(atom.accessible_points),
dtype=bool)
atom.proximal_mask = np.linalg.norm(atom.accessible_points,
axis=1) < radius
# Check points on other atoms against cone for each atom
atom_coordinates: Array2DFloat = np.array(
[atom.coordinates for atom in atoms])
atoms: Array1DAny = np.array(atoms)
for atom in atoms:
# Calculate distances to other atoms
atom.get_cone()
cone = Cone(atom.cone.angle, [atom.index], atom.cone.normal)
atom_dist = np.linalg.norm(atom.coordinates)
other_distances = np.dot(atom_coordinates, cone.normal)
# Check whether points are (1) within cone and (2) beyond atom
# center
check_atoms = atoms[other_distances >= (atom_dist - atom.radius)]
for check_atom in check_atoms:
if check_atom == atom:
continue
is_inside_mask = cone.is_inside_points(
check_atom.accessible_points, method="cross")
is_beyond_mask = (np.dot(check_atom.accessible_points,
cone.normal) >= atom_dist)
invisible_mask = np.logical_and(is_inside_mask, is_beyond_mask)
check_atom.invisible_mask = np.logical_or(
check_atom.invisible_mask, invisible_mask)
# Calculate visible, invisible and proximal_visible volume
visible_volume = 0
invisible_volume = 0
proximal_visible_volume = 0
proximal_volume = 0
visible_area = 0
invisible_area = 0
proximal_visible_area = 0
proximal_area = 0
for atom in atoms:
point_areas = atom.point_areas[atom.accessible_mask]
point_volumes = atom.point_volumes[atom.accessible_mask]
invisible_volume += point_volumes[atom.invisible_mask].sum()
visible_volume += point_volumes[~atom.invisible_mask].sum()
proximal_visible_volume += point_volumes[np.logical_and(
~atom.invisible_mask, atom.proximal_mask)].sum()
proximal_volume += point_volumes[atom.proximal_mask].sum()
invisible_area += point_areas[atom.invisible_mask].sum()
visible_area += point_areas[~atom.invisible_mask].sum()
proximal_visible_area += point_areas[np.logical_and(
~atom.invisible_mask, atom.proximal_mask)].sum()
proximal_area += point_areas[atom.proximal_mask].sum()
# Store attributes
self.total_volume = sasa.volume
self.proximal_volume = proximal_volume
self.distal_volume = sasa.volume - proximal_volume
self.invisible_volume = invisible_volume
self.visible_volume = visible_volume
self.proximal_visible_volume = proximal_visible_volume
self.distal_visible_volume = visible_volume - proximal_visible_volume
self.total_area = sasa.area
self.proximal_area = proximal_area
self.distal_area = sasa.area - proximal_area
self.invisible_area = invisible_area
self.visible_area = visible_area
self.proximal_visible_area = proximal_visible_area
self.distal_visible_area = visible_area - proximal_visible_area
self._atoms = atoms