def test_pdbqt_to_pdb(self):
"""Test that a PDBQT molecule can be converted back in to PDB."""
xyz, mol = rdkit_utils.load_molecule(self.protein_file,
calc_charges=False,
add_hydrogens=False)
with tempfile.TemporaryDirectory() as tmp:
out_pdb = os.path.join(tmp, "mol.pdb")
out_pdbqt = os.path.join(tmp, "mol.pdbqt")
rdkit_utils.write_molecule(mol, out_pdb, is_protein=True)
rdkit_utils.write_molecule(mol, out_pdbqt, is_protein=True)
pdb_block = pdbqt_utils.pdbqt_to_pdb(out_pdbqt)
from rdkit import Chem
pdb_mol = Chem.MolFromPDBBlock(pdb_block,
sanitize=False,
removeHs=False)
xyz, pdbqt_mol = rdkit_utils.load_molecule(out_pdbqt,
add_hydrogens=False,
calc_charges=False)
assert pdb_mol.GetNumAtoms() == pdbqt_mol.GetNumAtoms()
for atom_idx in range(pdb_mol.GetNumAtoms()):
atom1 = pdb_mol.GetAtoms()[atom_idx]
atom2 = pdbqt_mol.GetAtoms()[atom_idx]
assert atom1.GetAtomicNum() == atom2.GetAtomicNum()
def _featurize(self, mol_pdb_file, protein_pdb_file):
try:
frag1_coords, frag1_mol = load_molecule(
mol_pdb_file, is_protein=False, sanitize=True, add_hydrogens=False)
frag2_coords, frag2_mol = load_molecule(
protein_pdb_file, is_protein=True, sanitize=True, add_hydrogens=False)
except MoleculeLoadException:
# Currently handles loading failures by returning None
# TODO: Is there a better handling procedure?
logging.warning("Some molecules cannot be loaded by Rdkit. Skipping")
return None
system_mol = merge_molecules([frag1_mol, frag2_mol])
system_coords = get_xyz_from_mol(system_mol)
frag1_coords, frag1_mol = self._strip_hydrogens(frag1_coords, frag1_mol)
frag2_coords, frag2_mol = self._strip_hydrogens(frag2_coords, frag2_mol)
system_coords, system_mol = self._strip_hydrogens(system_coords, system_mol)
try:
frag1_coords, frag1_neighbor_list, frag1_z = self.featurize_mol(
frag1_coords, frag1_mol, self.frag1_num_atoms)
frag2_coords, frag2_neighbor_list, frag2_z = self.featurize_mol(
frag2_coords, frag2_mol, self.frag2_num_atoms)
system_coords, system_neighbor_list, system_z = self.featurize_mol(
system_coords, system_mol, self.complex_num_atoms)
except ValueError:
logging.warning(
"max_atoms was set too low. Some complexes too large and skipped")
return None
return frag1_coords, frag1_neighbor_list, frag1_z, frag2_coords, frag2_neighbor_list, frag2_z, \
system_coords, system_neighbor_list, system_z
def test_merge_molecules(self):
current_dir = os.path.dirname(os.path.realpath(__file__))
ligand_file = os.path.join(current_dir, "../../dock/tests/1jld_ligand.sdf")
xyz, mol = rdkit_utils.load_molecule(
ligand_file, calc_charges=False, add_hydrogens=False)
num_mol_atoms = mol.GetNumAtoms()
# self.ligand_file is for 3ws9_ligand.sdf
oth_xyz, oth_mol = rdkit_utils.load_molecule(
self.ligand_file, calc_charges=False, add_hydrogens=False)
num_oth_mol_atoms = oth_mol.GetNumAtoms()
merged = rdkit_utils.merge_molecules([mol, oth_mol])
merged_num_atoms = merged.GetNumAtoms()
assert merged_num_atoms == num_mol_atoms + num_oth_mol_atoms
def test_load_molecule2(self):
current_dir = os.path.dirname(os.path.realpath(__file__))
ligand_file = os.path.join(current_dir, "../../dock/tests/1jld_ligand.sdf")
xyz, mol = rdkit_utils.load_molecule(
ligand_file, calc_charges=False, add_hydrogens=False)
assert xyz is not None
assert mol is not None
def _featurize(self, complex: Tuple[str, str]):
"""
Compute neighbor list for complex.
Parameters
----------
complex: Tuple[str, str]
Filenames for molecule and protein.
"""
mol_pdb_file, protein_pdb_file = complex
mol_coords, ob_mol = load_molecule(mol_pdb_file)
protein_coords, protein_mol = load_molecule(protein_pdb_file)
system_coords = merge_molecules_xyz([mol_coords, protein_coords])
system_neighbor_list = compute_neighbor_list(
system_coords, self.neighbor_cutoff, self.max_num_neighbors, None)
return (system_coords, system_neighbor_list)
def test_write_molecule(self):
current_dir = os.path.dirname(os.path.realpath(__file__))
ligand_file = os.path.join(current_dir, "../../dock/tests/1jld_ligand.sdf")
xyz, mol = rdkit_utils.load_molecule(
ligand_file, calc_charges=False, add_hydrogens=False)
with tempfile.TemporaryDirectory() as tmp:
outfile = os.path.join(tmp, "mol.sdf")
rdkit_utils.write_molecule(mol, outfile)
xyz, mol2 = rdkit_utils.load_molecule(
outfile, calc_charges=False, add_hydrogens=False)
assert mol.GetNumAtoms() == mol2.GetNumAtoms()
for atom_idx in range(mol.GetNumAtoms()):
atom1 = mol.GetAtoms()[atom_idx]
atom2 = mol.GetAtoms()[atom_idx]
assert atom1.GetAtomicNum() == atom2.GetAtomicNum()
def test_get_xyz_from_mol(self):
current_dir = os.path.dirname(os.path.realpath(__file__))
ligand_file = os.path.join(current_dir, "../../dock/tests/1jld_ligand.sdf")
xyz, mol = rdkit_utils.load_molecule(
ligand_file, calc_charges=False, add_hydrogens=False)
xyz2 = rdkit_utils.get_xyz_from_mol(mol)
equal_array = np.all(xyz == xyz2)
assert equal_array
def _featurize(self, mol_pdb_file, protein_pdb_file):
"""
Compute neighbor list for complex.
Parameters
----------
mol_pdb_file: str
Filename for ligand pdb file.
protein_pdb_file: str
Filename for protein pdb file.
"""
mol_coords, ob_mol = load_molecule(mol_pdb_file)
protein_coords, protein_mol = load_molecule(protein_pdb_file)
system_coords = merge_molecules_xyz([mol_coords, protein_coords])
system_neighbor_list = compute_neighbor_list(
system_coords, self.neighbor_cutoff, self.max_num_neighbors, None)
return (system_coords, system_neighbor_list)
def test_convert_protein_to_pdbqt(self):
"""Test a protein in a PDB can be converted to PDBQT."""
from rdkit import Chem
xyz, mol = rdkit_utils.load_molecule(self.protein_file,
calc_charges=False,
add_hydrogens=False)
with tempfile.TemporaryDirectory() as tmp:
outfile = os.path.join(tmp, "mol.pdbqt")
writer = Chem.PDBWriter(outfile)
writer.write(mol)
writer.close()
pdbqt_utils.convert_protein_to_pdbqt(mol, outfile)
pdbqt_xyz, pdbqt_mol = rdkit_utils.load_molecule(
outfile, add_hydrogens=False, calc_charges=False)
assert pdbqt_mol.GetNumAtoms() == pdbqt_mol.GetNumAtoms()
for atom_idx in range(pdbqt_mol.GetNumAtoms()):
atom1 = pdbqt_mol.GetAtoms()[atom_idx]
atom2 = pdbqt_mol.GetAtoms()[atom_idx]
assert atom1.GetAtomicNum() == atom2.GetAtomicNum()
def test_get_face_boxes_for_protein(self):
"""Tests that binding pockets are detected."""
current_dir = os.path.dirname(os.path.realpath(__file__))
protein_file = os.path.join(current_dir, "1jld_protein.pdb")
coords = rdkit_utils.load_molecule(protein_file)[0]
boxes = box_utils.get_face_boxes(coords)
assert isinstance(boxes, list)
# Pocket is of form ((x_min, x_max), (y_min, y_max), (z_min, z_max))
for pocket in boxes:
assert isinstance(pocket, box_utils.CoordinateBox)
def test_merge_molecules_xyz(self):
current_dir = os.path.dirname(os.path.realpath(__file__))
ligand_file = os.path.join(current_dir, "../../dock/tests/1jld_ligand.sdf")
xyz, mol = rdkit_utils.load_molecule(
ligand_file, calc_charges=False, add_hydrogens=False)
merged = rdkit_utils.merge_molecules_xyz([xyz, xyz])
for i in range(len(xyz)):
first_atom_equal = np.all(xyz[i] == merged[i])
second_atom_equal = np.all(xyz[i] == merged[i + len(xyz)])
assert first_atom_equal
assert second_atom_equal
def test_load_molecule(self):
# adding hydrogens and charges is tested in dc.utils
from rdkit.Chem.AllChem import Mol
for add_hydrogens in (True, False):
for calc_charges in (True, False):
mol_xyz, mol_rdk = rdkit_utils.load_molecule(
self.ligand_file, add_hydrogens, calc_charges)
num_atoms = mol_rdk.GetNumAtoms()
self.assertIsInstance(mol_xyz, np.ndarray)
self.assertIsInstance(mol_rdk, Mol)
self.assertEqual(mol_xyz.shape, (num_atoms, 3))
def setUp(self):
current_dir = os.path.dirname(os.path.realpath(__file__))
# simple flat ring
from rdkit.Chem import MolFromSmiles
from rdkit.Chem.rdDepictor import Compute2DCoords
self.cycle4 = MolFromSmiles('C1CCC1')
# self.cycle4.Compute2DCoords()
Compute2DCoords(self.cycle4)
# load and sanitize two real molecules
_, self.prot = load_molecule(os.path.join(
current_dir, '../../feat/tests/data/3ws9_protein_fixer_rdkit.pdb'),
add_hydrogens=False,
calc_charges=False,
sanitize=True)
_, self.lig = load_molecule(os.path.join(
current_dir, '../../feat//tests/data/3ws9_ligand.sdf'),
add_hydrogens=False,
calc_charges=False,
sanitize=True)
def test_compute_charges(self):
current_dir = os.path.dirname(os.path.realpath(__file__))
ligand_file = os.path.join(current_dir, "../../dock/tests/1jld_ligand.sdf")
xyz, mol = rdkit_utils.load_molecule(
ligand_file, calc_charges=False, add_hydrogens=True)
rdkit_utils.compute_charges(mol)
has_a_charge = False
for atom_idx in range(mol.GetNumAtoms()):
atom = mol.GetAtoms()[atom_idx]
value = atom.GetProp(str("_GasteigerCharge"))
if value != 0:
has_a_charge = True
assert has_a_charge
def extract_active_site(
protein_file: str,
ligand_file: str,
cutoff: float = 4.0) -> Tuple[CoordinateBox, np.ndarray]:
"""Extracts a box for the active site.
Parameters
----------
protein_file : str
Location of protein PDB
ligand_file : str
Location of ligand input file
cutoff : float, optional (default 4.0)
The distance in angstroms from the protein pocket to
consider for featurization.
Returns
-------
Tuple[CoordinateBox, np.ndarray]
A tuple of `(CoordinateBox, np.ndarray)` where the second entry is
of shape `(N, 3)` with `N` the number of atoms in the active site.
"""
protein = load_molecule(protein_file, add_hydrogens=False)
ligand = load_molecule(ligand_file, add_hydrogens=True, calc_charges=True)
protein_contacts, ligand_contacts = get_contact_atom_indices(
[protein, ligand], cutoff=cutoff)
protein_coords = protein[0]
pocket_coords = protein_coords[protein_contacts]
x_min = int(np.floor(np.amin(pocket_coords[:, 0])))
x_max = int(np.ceil(np.amax(pocket_coords[:, 0])))
y_min = int(np.floor(np.amin(pocket_coords[:, 1])))
y_max = int(np.ceil(np.amax(pocket_coords[:, 1])))
z_min = int(np.floor(np.amin(pocket_coords[:, 2])))
z_max = int(np.ceil(np.amax(pocket_coords[:, 2])))
box = CoordinateBox((x_min, x_max), (y_min, y_max), (z_min, z_max))
return box, pocket_coords
def _featurize(self, datapoint, **kwargs):
"""
Compute neighbor list for complex.
Parameters
----------
datapoint: Tuple[str, str]
Filenames for molecule and protein.
"""
if 'complex' in kwargs:
datapoint = kwargs.get("complex")
raise DeprecationWarning(
'Complex is being phased out as a parameter, please pass "datapoint" instead.'
)
mol_pdb_file, protein_pdb_file = datapoint
mol_coords, ob_mol = load_molecule(mol_pdb_file)
protein_coords, protein_mol = load_molecule(protein_pdb_file)
system_coords = merge_molecules_xyz([mol_coords, protein_coords])
system_neighbor_list = compute_neighbor_list(
system_coords, self.neighbor_cutoff, self.max_num_neighbors, None)
return (system_coords, system_neighbor_list)
def find_all_pockets(self, protein_file: str) -> List[CoordinateBox]:
"""Find list of binding pockets on protein.
Parameters
----------
protein_file : str
Protein to load in.
Returns
-------
List[CoordinateBox]
List of binding pockets on protein. Each pocket is a `CoordinateBox`
"""
coords, _ = load_molecule(protein_file)
return get_face_boxes(coords, self.pad)
def featurize( # type: ignore[override]
self, protein_file: str,
pockets: List[CoordinateBox]) -> np.ndarray:
"""
Calculate atomic coodinates.
Parameters
----------
protein_file: str
Location of PDB file. Will be loaded by MDTraj
pockets: List[CoordinateBox]
List of `dc.utils.CoordinateBox` objects.
Returns
-------
np.ndarray
A numpy array of shale `(len(pockets), n_residues)`
"""
try:
import mdtraj
except ModuleNotFoundError:
raise ImportError("This class requires mdtraj to be installed.")
protein_coords = load_molecule(protein_file,
add_hydrogens=False,
calc_charges=False)[0]
mapping = boxes_to_atoms(protein_coords, pockets)
protein = mdtraj.load(protein_file)
n_pockets = len(pockets)
n_residues = len(BindingPocketFeaturizer.residues)
res_map = dict(zip(BindingPocketFeaturizer.residues,
range(n_residues)))
all_features = np.zeros((n_pockets, n_residues))
for pocket_num, pocket in enumerate(pockets):
pocket_atoms = mapping[pocket]
for ind, atom in enumerate(pocket_atoms):
atom_name = str(protein.top.atom(atom))
# atom_name is of format RESX-ATOMTYPE
# where X is a 1 to 4 digit number
residue = atom_name[:3]
if residue not in res_map:
logger.info("Warning: Non-standard residue in PDB file")
continue
all_features[pocket_num, res_map[residue]] += 1
return all_features
def test_apply_pdbfixer(self):
current_dir = os.path.dirname(os.path.realpath(__file__))
ligand_file = os.path.join(current_dir, "../../dock/tests/1jld_ligand.sdf")
xyz, mol = rdkit_utils.load_molecule(
ligand_file, calc_charges=False, add_hydrogens=False)
original_hydrogen_count = 0
for atom_idx in range(mol.GetNumAtoms()):
atom = mol.GetAtoms()[atom_idx]
if atom.GetAtomicNum() == 1:
original_hydrogen_count += 1
assert mol is not None
mol = rdkit_utils.apply_pdbfixer(mol, hydrogenate=True, is_protein=False)
assert mol is not None
after_hydrogen_count = 0
for atom_idx in range(mol.GetNumAtoms()):
atom = mol.GetAtoms()[atom_idx]
if atom.GetAtomicNum() == 1:
after_hydrogen_count += 1
assert after_hydrogen_count >= original_hydrogen_count
def featurize(self, protein_file, pockets):
"""
Calculate atomic coodinates.
Parameters
----------
protein_file: str
Location of PDB file. Will be loaded by MDTraj
pockets: list[CoordinateBox]
List of `dc.utils.CoordinateBox` objects.
Returns
-------
A numpy array of shale `(len(pockets), n_residues)`
"""
import mdtraj
protein_coords = load_molecule(protein_file,
add_hydrogens=False,
calc_charges=False)[0]
mapping = boxes_to_atoms(protein_coords, pockets)
protein = mdtraj.load(protein_file)
n_pockets = len(pockets)
n_residues = len(BindingPocketFeaturizer.residues)
res_map = dict(zip(BindingPocketFeaturizer.residues,
range(n_residues)))
all_features = np.zeros((n_pockets, n_residues))
for pocket_num, pocket in enumerate(pockets):
pocket_atoms = mapping[pocket]
for ind, atom in enumerate(pocket_atoms):
atom_name = str(protein.top.atom(atom))
# atom_name is of format RESX-ATOMTYPE
# where X is a 1 to 4 digit number
residue = atom_name[:3]
if residue not in res_map:
logger.info("Warning: Non-standard residue in PDB file")
continue
atomtype = atom_name.split("-")[1]
all_features[pocket_num, res_map[residue]] += 1
return all_features
def find_pockets(self, macromolecule_file: str) -> List[CoordinateBox]:
"""Find list of suitable binding pockets on protein.
This function computes putative binding pockets on this protein.
This class uses the `ConvexHull` to compute binding pockets. Each
face of the hull is converted into a coordinate box used for
binding.
Parameters
----------
macromolecule_file : str
Location of the macromolecule file to load
Returns
-------
List[CoordinateBox]
List of pockets. Each pocket is a `CoordinateBox`
"""
coords, _ = load_molecule(macromolecule_file,
add_hydrogens=False,
calc_charges=False)
boxes = get_face_boxes(coords, self.pad)
boxes = merge_overlapping_boxes(boxes)
return boxes
def test_strip_hydrogens(self):
mol_xyz, mol_rdk = rdkit_utils.load_molecule(self.ligand_file)
_ = MolecularFragment(mol_rdk.GetAtoms(), mol_xyz)
# Test on RDKit
_ = strip_hydrogens(mol_xyz, mol_rdk)
def generate_poses(
self,
molecular_complex: Tuple[str, str],
centroid: Optional[np.ndarray] = None,
box_dims: Optional[np.ndarray] = None,
exhaustiveness: int = 10,
num_modes: int = 9,
num_pockets: Optional[int] = None,
out_dir: Optional[str] = None,
generate_scores: bool = True,
**kwargs) -> Union[Tuple[DOCKED_POSES, np.ndarray], DOCKED_POSES]:
"""Generates the docked complex and outputs files for docked complex.
Parameters
----------
molecular_complexes: Tuple[str, str]
A representation of a molecular complex. This tuple is
(protein_file, ligand_file).
centroid: np.ndarray, optional (default None)
The centroid to dock against. Is computed if not specified.
box_dims: np.ndarray, optional (default None)
A numpy array of shape `(3,)` holding the size of the box to dock.
If not specified is set to size of molecular complex plus 4 angstroms.
exhaustiveness: int (default 8)
Tells GNINA how exhaustive it should be with pose
generation.
num_modes: int (default 9)
Tells GNINA how many binding modes it should generate at
each invocation.
out_dir: str, optional
If specified, write generated poses to this directory.
generate_scores: bool, optional (default True)
If `True`, the pose generator will return scores for complexes.
This is used typically when invoking external docking programs
that compute scores.
kwargs:
Any args supported by GNINA as documented
https://github.com/gnina/gnina#usage
Returns
-------
Tuple[`docked_poses`, `scores`] or `docked_poses`
Tuple of `(docked_poses, scores)` or `docked_poses`. `docked_poses`
is a list of docked molecular complexes. Each entry in this list
contains a `(protein_mol, ligand_mol)` pair of RDKit molecules.
`scores` is an array of binding affinities (kcal/mol),
CNN pose scores, and CNN affinities predicted by GNINA.
"""
if out_dir is None:
out_dir = tempfile.mkdtemp()
if not os.path.exists(out_dir):
os.makedirs(out_dir)
# Parse complex
if len(molecular_complex) > 2:
raise ValueError(
"GNINA can only dock protein-ligand complexes and not more general molecular complexes."
)
(protein_file, ligand_file) = molecular_complex
# check filetypes
if not protein_file.endswith('.pdb'):
raise ValueError('Protein file must be in .pdb format.')
if not ligand_file.endswith('.sdf'):
raise ValueError('Ligand file must be in .sdf format.')
protein_mol = load_molecule(protein_file,
calc_charges=True,
add_hydrogens=True)
ligand_name = os.path.basename(ligand_file).split(".")[0]
# Define locations of log and output files
log_file = os.path.join(out_dir, "%s_log.txt" % ligand_name)
out_file = os.path.join(out_dir, "%s_docked.pdbqt" % ligand_name)
logger.info("About to call GNINA.")
# Write GNINA conf file
conf_file = os.path.join(out_dir, "conf.txt")
write_gnina_conf(protein_filename=protein_file,
ligand_filename=ligand_file,
conf_filename=conf_file,
num_modes=num_modes,
exhaustiveness=exhaustiveness,
**kwargs)
# Run GNINA
args = [
self.gnina_cmd, "--config", conf_file, "--log", log_file, "--out",
out_file
]
process = Popen(args, stdout=PIPE, stderr=PIPE)
stdout, stderr = process.communicate()
# read output and log
ligands, _ = load_docked_ligands(out_file)
docked_complexes = [(protein_mol[1], ligand) for ligand in ligands]
scores = read_gnina_log(log_file)
if generate_scores:
return docked_complexes, scores
else:
return docked_complexes
def generate_poses(
self,
molecular_complex: Tuple[str, str],
centroid: Optional[np.ndarray] = None,
box_dims: Optional[np.ndarray] = None,
exhaustiveness: int = 10,
num_modes: int = 9,
num_pockets: Optional[int] = None,
out_dir: Optional[str] = None,
generate_scores: Optional[bool] = False,
**kwargs) -> Union[Tuple[DOCKED_POSES, List[float]], DOCKED_POSES]:
"""Generates the docked complex and outputs files for docked complex.
Parameters
----------
molecular_complexes: Tuple[str, str]
A representation of a molecular complex. This tuple is
(protein_file, ligand_file). The protein should be a pdb file
and the ligand should be an sdf file.
centroid: np.ndarray, optional
The centroid to dock against. Is computed if not specified.
box_dims: np.ndarray, optional
A numpy array of shape `(3,)` holding the size of the box to dock. If not
specified is set to size of molecular complex plus 5 angstroms.
exhaustiveness: int, optional (default 10)
Tells Autodock Vina how exhaustive it should be with pose generation. A
higher value of exhaustiveness implies more computation effort for the
docking experiment.
num_modes: int, optional (default 9)
Tells Autodock Vina how many binding modes it should generate at
each invocation.
num_pockets: int, optional (default None)
If specified, `self.pocket_finder` must be set. Will only
generate poses for the first `num_pockets` returned by
`self.pocket_finder`.
out_dir: str, optional
If specified, write generated poses to this directory.
generate_score: bool, optional (default False)
If `True`, the pose generator will return scores for complexes.
This is used typically when invoking external docking programs
that compute scores.
kwargs:
The kwargs - cpu, min_rmsd, max_evals, energy_range supported by VINA
are as documented in https://autodock-vina.readthedocs.io/en/latest/vina.html
Returns
-------
Tuple[`docked_poses`, `scores`] or `docked_poses`
Tuple of `(docked_poses, scores)` or `docked_poses`. `docked_poses`
is a list of docked molecular complexes. Each entry in this list
contains a `(protein_mol, ligand_mol)` pair of RDKit molecules.
`scores` is a list of binding free energies predicted by Vina.
Raises
------
`ValueError` if `num_pockets` is set but `self.pocket_finder is None`.
"""
if "cpu" in kwargs:
cpu = kwargs["cpu"]
else:
cpu = 0
if "min_rmsd" in kwargs:
min_rmsd = kwargs["min_rmsd"]
else:
min_rmsd = 1.0
if "max_evals" in kwargs:
max_evals = kwargs["max_evals"]
else:
max_evals = 0
if "energy_range" in kwargs:
energy_range = kwargs["energy_range"]
else:
energy_range = 3.0
try:
from vina import Vina
except ModuleNotFoundError:
raise ImportError("This function requires vina to be installed")
if out_dir is None:
out_dir = tempfile.mkdtemp()
if num_pockets is not None and self.pocket_finder is None:
raise ValueError(
"If num_pockets is specified, pocket_finder must have been provided at construction time."
)
# Parse complex
if len(molecular_complex) > 2:
raise ValueError(
"Autodock Vina can only dock protein-ligand complexes and not more general molecular complexes."
)
(protein_file, ligand_file) = molecular_complex
# Prepare protein
protein_name = os.path.basename(protein_file).split(".")[0]
protein_hyd = os.path.join(out_dir, "%s_hyd.pdb" % protein_name)
protein_pdbqt = os.path.join(out_dir, "%s.pdbqt" % protein_name)
protein_mol = load_molecule(protein_file,
calc_charges=True,
add_hydrogens=True)
write_molecule(protein_mol[1], protein_hyd, is_protein=True)
write_molecule(protein_mol[1], protein_pdbqt, is_protein=True)
# Get protein centroid and range
if centroid is not None and box_dims is not None:
centroids = [centroid]
dimensions = [box_dims]
else:
if self.pocket_finder is None:
logger.info(
"Pockets not specified. Will use whole protein to dock")
centroids = [compute_centroid(protein_mol[0])]
dimensions = [compute_protein_range(protein_mol[0]) + 5.0]
else:
logger.info("About to find putative binding pockets")
pockets = self.pocket_finder.find_pockets(protein_file)
logger.info("%d pockets found in total" % len(pockets))
logger.info("Computing centroid and size of proposed pockets.")
centroids, dimensions = [], []
for pocket in pockets:
(x_min, x_max), (y_min, y_max), (
z_min,
z_max) = pocket.x_range, pocket.y_range, pocket.z_range
# TODO(rbharath: Does vina divide box dimensions by 2?
x_box = (x_max - x_min) / 2.
y_box = (y_max - y_min) / 2.
z_box = (z_max - z_min) / 2.
centroids.append(pocket.center())
dimensions.append(np.array((x_box, y_box, z_box)))
if num_pockets is not None:
logger.info(
"num_pockets = %d so selecting this many pockets for docking."
% num_pockets)
centroids = centroids[:num_pockets]
dimensions = dimensions[:num_pockets]
# Prepare ligand
ligand_name = os.path.basename(ligand_file).split(".")[0]
ligand_pdbqt = os.path.join(out_dir, "%s.pdbqt" % ligand_name)
ligand_mol = load_molecule(ligand_file,
calc_charges=True,
add_hydrogens=True)
write_molecule(ligand_mol[1], ligand_pdbqt)
docked_complexes = []
all_scores = []
vpg = Vina(sf_name='vina',
cpu=cpu,
seed=0,
no_refine=False,
verbosity=1)
for i, (protein_centroid,
box_dims) in enumerate(zip(centroids, dimensions)):
logger.info("Docking in pocket %d/%d" % (i + 1, len(centroids)))
logger.info("Docking with center: %s" % str(protein_centroid))
logger.info("Box dimensions: %s" % str(box_dims))
# Write Vina conf file
conf_file = os.path.join(out_dir, "conf.txt")
write_vina_conf(protein_pdbqt,
ligand_pdbqt,
protein_centroid,
box_dims,
conf_file,
num_modes=num_modes,
exhaustiveness=exhaustiveness)
# Define locations of output files
out_pdbqt = os.path.join(out_dir, "%s_docked.pdbqt" % ligand_name)
logger.info("About to call Vina")
vpg.set_receptor(protein_pdbqt)
vpg.set_ligand_from_file(ligand_pdbqt)
vpg.compute_vina_maps(center=protein_centroid, box_size=box_dims)
vpg.dock(exhaustiveness=exhaustiveness,
n_poses=num_modes,
min_rmsd=min_rmsd,
max_evals=max_evals)
vpg.write_poses(out_pdbqt,
n_poses=num_modes,
energy_range=energy_range,
overwrite=True)
ligands, scores = load_docked_ligands(out_pdbqt)
docked_complexes += [(protein_mol[1], ligand)
for ligand in ligands]
all_scores += scores
if generate_scores:
return docked_complexes, all_scores
else:
return docked_complexes
def _featurize(self, complex):
"""Computes grid featurization of protein/ligand complex.
Takes as input filenames pdb of the protein, pdb of the ligand.
This function then computes the centroid of the ligand; decrements this
centroid from the atomic coordinates of protein and ligand atoms, and then
merges the translated protein and ligand. This combined system/complex is
then saved.
This function then computes a featurization with scheme specified by the user.
Parameters
----------
complex: Tuple[str, str]
Filenames for molecule and protein.
"""
try:
mol_pdb_file, protein_pdb_file = complex
time1 = time.time()
protein_xyz, protein_rdk = load_molecule(protein_pdb_file,
calc_charges=True,
sanitize=self.sanitize)
time2 = time.time()
logger.info(
"TIMING: Loading protein coordinates took %0.3f s" %
(time2 - time1), self.verbose)
time1 = time.time()
ligand_xyz, ligand_rdk = load_molecule(mol_pdb_file,
calc_charges=True,
sanitize=self.sanitize)
time2 = time.time()
logger.info(
"TIMING: Loading ligand coordinates took %0.3f s" %
(time2 - time1), self.verbose)
except MoleculeLoadException:
logger.warning(
"Some molecules cannot be loaded by Rdkit. Skipping")
return None
time1 = time.time()
centroid = compute_centroid(ligand_xyz)
ligand_xyz = subtract_centroid(ligand_xyz, centroid)
protein_xyz = subtract_centroid(protein_xyz, centroid)
time2 = time.time()
logger.info(
"TIMING: Centroid processing took %0.3f s" % (time2 - time1),
self.verbose)
pairwise_distances = compute_pairwise_distances(
protein_xyz, ligand_xyz)
transformed_systems = {}
transformed_systems[(0, 0)] = [protein_xyz, ligand_xyz]
for i in range(self.nb_rotations):
rotated_system = rotate_molecules([protein_xyz, ligand_xyz])
transformed_systems[(i + 1, 0)] = rotated_system
features_dict = {}
for system_id, (protein_xyz,
ligand_xyz) in transformed_systems.items():
feature_arrays = []
for is_flat, function_name in self.feature_types:
result = self._compute_feature(
function_name,
protein_xyz,
protein_rdk,
ligand_xyz,
ligand_rdk,
pairwise_distances,
)
feature_arrays += result
if self.flatten:
features_dict[system_id] = np.concatenate([
feature_array.flatten()
for feature_array in feature_arrays
])
else:
features_dict[system_id] = np.concatenate(feature_arrays,
axis=-1)
# TODO(rbharath): Is this squeeze OK?
features = np.squeeze(np.array(list(features_dict.values())))
return features
def generate_poses(
self,
molecular_complex: Tuple[str, str],
centroid: Optional[np.ndarray] = None,
box_dims: Optional[np.ndarray] = None,
exhaustiveness: int = 10,
num_modes: int = 9,
num_pockets: Optional[int] = None,
out_dir: Optional[str] = None,
generate_scores: bool = False
) -> Union[Tuple[DOCKED_POSES, List[float]], DOCKED_POSES]:
"""Generates the docked complex and outputs files for docked complex.
TODO: How can this work on Windows? We need to install a .msi file and
invoke it correctly from Python for this to work.
Parameters
----------
molecular_complexes: Tuple[str, str]
A representation of a molecular complex. This tuple is
(protein_file, ligand_file).
centroid: np.ndarray, optional
The centroid to dock against. Is computed if not specified.
box_dims: np.ndarray, optional
A numpy array of shape `(3,)` holding the size of the box to dock. If not
specified is set to size of molecular complex plus 5 angstroms.
exhaustiveness: int, optional (default 10)
Tells Autodock Vina how exhaustive it should be with pose
generation.
num_modes: int, optional (default 9)
Tells Autodock Vina how many binding modes it should generate at
each invocation.
num_pockets: int, optional (default None)
If specified, `self.pocket_finder` must be set. Will only
generate poses for the first `num_pockets` returned by
`self.pocket_finder`.
out_dir: str, optional
If specified, write generated poses to this directory.
generate_score: bool, optional (default False)
If `True`, the pose generator will return scores for complexes.
This is used typically when invoking external docking programs
that compute scores.
Returns
-------
Tuple[`docked_poses`, `scores`] or `docked_poses`
Tuple of `(docked_poses, scores)` or `docked_poses`. `docked_poses`
is a list of docked molecular complexes. Each entry in this list
contains a `(protein_mol, ligand_mol)` pair of RDKit molecules.
`scores` is a list of binding free energies predicted by Vina.
Raises
------
`ValueError` if `num_pockets` is set but `self.pocket_finder is None`.
"""
if out_dir is None:
out_dir = tempfile.mkdtemp()
if num_pockets is not None and self.pocket_finder is None:
raise ValueError(
"If num_pockets is specified, pocket_finder must have been provided at construction time."
)
# Parse complex
if len(molecular_complex) > 2:
raise ValueError(
"Autodock Vina can only dock protein-ligand complexes and not more general molecular complexes."
)
(protein_file, ligand_file) = molecular_complex
# Prepare protein
protein_name = os.path.basename(protein_file).split(".")[0]
protein_hyd = os.path.join(out_dir, "%s_hyd.pdb" % protein_name)
protein_pdbqt = os.path.join(out_dir, "%s.pdbqt" % protein_name)
protein_mol = load_molecule(protein_file,
calc_charges=True,
add_hydrogens=True)
write_molecule(protein_mol[1], protein_hyd, is_protein=True)
write_molecule(protein_mol[1], protein_pdbqt, is_protein=True)
# Get protein centroid and range
if centroid is not None and box_dims is not None:
centroids = [centroid]
dimensions = [box_dims]
else:
if self.pocket_finder is None:
logger.info(
"Pockets not specified. Will use whole protein to dock")
protein_centroid = compute_centroid(protein_mol[0])
protein_range = compute_protein_range(protein_mol[0])
box_dims = protein_range + 5.0
centroids, dimensions = [protein_centroid], [box_dims]
else:
logger.info("About to find putative binding pockets")
pockets = self.pocket_finder.find_pockets(protein_file)
logger.info("%d pockets found in total" % len(pockets))
logger.info("Computing centroid and size of proposed pockets.")
centroids, dimensions = [], []
for pocket in pockets:
protein_centroid = pocket.center()
(x_min, x_max), (y_min, y_max), (
z_min,
z_max) = pocket.x_range, pocket.y_range, pocket.z_range
# TODO(rbharath: Does vina divide box dimensions by 2?
x_box = (x_max - x_min) / 2.
y_box = (y_max - y_min) / 2.
z_box = (z_max - z_min) / 2.
box_dims = (x_box, y_box, z_box)
centroids.append(protein_centroid)
dimensions.append(box_dims)
if num_pockets is not None:
logger.info(
"num_pockets = %d so selecting this many pockets for docking."
% num_pockets)
centroids = centroids[:num_pockets]
dimensions = dimensions[:num_pockets]
# Prepare protein
ligand_name = os.path.basename(ligand_file).split(".")[0]
ligand_pdbqt = os.path.join(out_dir, "%s.pdbqt" % ligand_name)
ligand_mol = load_molecule(ligand_file,
calc_charges=True,
add_hydrogens=True)
write_molecule(ligand_mol[1], ligand_pdbqt)
docked_complexes = []
all_scores = []
for i, (protein_centroid,
box_dims) in enumerate(zip(centroids, dimensions)):
logger.info("Docking in pocket %d/%d" % (i + 1, len(centroids)))
logger.info("Docking with center: %s" % str(protein_centroid))
logger.info("Box dimensions: %s" % str(box_dims))
# Write Vina conf file
conf_file = os.path.join(out_dir, "conf.txt")
write_vina_conf(protein_pdbqt,
ligand_pdbqt,
protein_centroid,
box_dims,
conf_file,
num_modes=num_modes,
exhaustiveness=exhaustiveness)
# Define locations of log and output files
log_file = os.path.join(out_dir, "%s_log.txt" % ligand_name)
out_pdbqt = os.path.join(out_dir, "%s_docked.pdbqt" % ligand_name)
logger.info("About to call Vina")
if platform.system() == 'Windows':
args = [
self.vina_cmd, "--config", conf_file, "--log", log_file,
"--out", out_pdbqt
]
else:
# I'm not sure why specifying the args as a list fails on other platforms,
# but for some reason it only works if I pass it as a string.
# FIXME: Incompatible types in assignment
args = "%s --config %s --log %s --out %s" % ( # type: ignore
self.vina_cmd, conf_file, log_file, out_pdbqt)
# FIXME: We should use `subprocess.run` instead of `call`
call(args, shell=True)
ligands, scores = load_docked_ligands(out_pdbqt)
docked_complexes += [(protein_mol[1], ligand)
for ligand in ligands]
all_scores += scores
if generate_scores:
return docked_complexes, all_scores
else:
return docked_complexes
def test_create_molecular_fragment(self): mol_xyz, mol_rdk = rdkit_utils.load_molecule(self.ligand_file) fragment = MolecularFragment(mol_rdk.GetAtoms(), mol_xyz) assert len(mol_rdk.GetAtoms()) == len(fragment.GetAtoms()) assert (fragment.GetCoords() == mol_xyz).all()
def test_merge_molecular_fragments(self): mol_xyz, mol_rdk = rdkit_utils.load_molecule(self.ligand_file) fragment1 = MolecularFragment(mol_rdk.GetAtoms(), mol_xyz) fragment2 = MolecularFragment(mol_rdk.GetAtoms(), mol_xyz) joint = merge_molecular_fragments([fragment1, fragment2]) assert len(mol_rdk.GetAtoms()) * 2 == len(joint.GetAtoms())
