def generateAA(aaName):
geo = Geometry.geometry(aaName)
geo.phi = 0
geo.psi_im1 = 0
structure = PeptideBuilder.initialize_res(geo)
tx = -np.pi / 2.0
Rx = np.array([[1, 0, 0], [0, cos(tx), -sin(tx)], [0, sin(tx), cos(tx)]])
for atom in structure.get_atoms():
atom.transform(Rx, np.array([0, 0, 0]))
nAtom = list(structure.get_atoms())[0]
nV = nAtom.get_coord()
I = np.identity(3)
for atom in structure.get_atoms():
atom.transform(I, -nV)
R = rotaxis(np.pi, list(structure.get_atoms())[1].get_vector())
for atom in structure.get_atoms():
atom.transform(R, np.array([0, 0, 0]))
# print(list(structure.get_atoms())[1].get_coord(), list(structure.get_atoms())[1])
out = Bio.PDB.PDBIO()
out.set_structure(structure)
out.save("example.pdb")
return structure[0]['A'][1]
def test_Vector_angles(self):
"""Test Vector angles."""
angle = random() * numpy.pi
axis = Vector(random(3) - random(3))
axis.normalize()
m = rotaxis(angle, axis)
cangle, caxis = m2rotaxis(m)
self.assertAlmostEqual(angle, cangle, places=3)
self.assertTrue(
numpy.allclose(list(map(int, (axis - caxis).get_array())),
[0, 0, 0]), "Want %r and %r to be almost equal" %
(axis.get_array(), caxis.get_array()))
def transform(structure):
tx = -np.pi / 2.0
Rx = np.array([[1, 0, 0], [0, cos(tx), -sin(tx)], [0, sin(tx), cos(tx)]])
for atom in structure.get_atoms():
atom.transform(Rx, np.array([0, 0, 0]))
nAtom = list(structure.get_atoms())[0]
nV = nAtom.get_coord()
I = np.identity(3)
for atom in structure.get_atoms():
atom.transform(I, -nV)
R = rotaxis(np.pi, list(structure.get_atoms())[1].get_vector())
for atom in structure.get_atoms():
atom.transform(R, np.array([0, 0, 0]))
return structure
def randomize_starting_position(ligand_file, complex_file, outputfolder=".", nposes=200, test=False, user_center=None,
logger=None):
"""
Randomize initial ligand position around the receptor.
Default number of poses = 200.
:param ligand_file:
:param complex_file:
:param nposes:
:return:
"""
if test: np.random.seed(42)
# read in files
parser = PDBParser()
output = []
structure = parser.get_structure('protein', complex_file)
ligand = parser.get_structure('ligand', ligand_file)
COI = np.zeros(3)
# get center of interface (if PPI)
if user_center:
try:
chain_id, res_number, atom_name = user_center.split(":")
except ValueError:
raise cs.WrongAtomStringFormat(f"The specified atom is wrong '{user_center}'. \
Should be 'chain:resnumber:atomname'")
for chain in structure.get_chains():
if chain.id == chain_id:
for residue in chain.get_residues():
if residue.id[1] == int(res_number):
for atom in residue.get_atoms():
if atom.name == atom_name:
COI = np.array(list(atom.get_vector()))
# calculate protein and ligand COM
com_protein = calculate_com(structure)
com_ligand = calculate_com(ligand)
# calculating the maximum d of the ligand
coor_ligand = []
for atom in ligand.get_atoms():
coor_ligand.append(list(atom.get_vector() - com_ligand))
coor_ligand = np.array(coor_ligand)
coor_ligand_max = np.amax(coor_ligand, axis=0)
d_ligand = np.sqrt(np.sum(coor_ligand_max ** 2))
# set threshold for near and far contacts based on ligand d
if d_ligand / 2 < 5.0:
d5_ligand = 5.0
else:
d5_ligand = d_ligand / 2 + 1
if d_ligand > 8.0:
d8_ligand = d_ligand / 2 + 4
else:
d8_ligand = 8.0
# calculate vector to move the ligandi
if user_center:
move_vector = com_ligand - COI
else:
move_vector = com_ligand - com_protein
# translate the ligand to the protein COM (COI for PPI)
original_coords = []
for atom in ligand.get_atoms():
ligand_origin = np.array(list(atom.get_vector())) - move_vector
original_coords.append(ligand_origin)
atom.set_coord(ligand_origin)
# calculating the maximum radius of the protein from the origin
coor = []
for atom in structure.get_atoms():
coor.append(list(atom.get_vector() - com_protein))
coor = np.array(coor)
coor_max = np.amax(coor, axis=0)
d = np.sqrt(np.sum(coor_max ** 2))
# radius of the sphere from the origin
D = 10.0 if user_center else np.ceil(6.0 + d)
D_initial = D
logger.info("Sampling {}A spherical box around the centre of the receptor/interface.".format(D))
if user_center:
sphere_cent = COI
else:
sphere_cent = com_protein
j = 0
logger.info("Generating {} poses...".format(nposes))
start_time = time.time()
while (j < nposes):
# generate random coordinates
phi = np.random.uniform(0, 2 * np.pi)
costheta = np.random.uniform(-1, 1)
u = np.random.uniform(0, 1)
theta = np.arccos(costheta)
r = D * np.cbrt(u)
x = r * np.sin(theta) * np.cos(phi)
y = r * np.sin(theta) * np.sin(phi)
z = r * np.cos(theta)
# move ligand to the starting point (protein COM)
for atom, coord in zip(ligand.get_atoms(), original_coords):
atom.set_coord(coord)
# translate ligand to a random position
translation = (x, y, z)
for atom in ligand.get_atoms():
new_pos_lig_trans = np.array(list(atom.get_vector())) - translation
atom.set_coord(new_pos_lig_trans)
# calculate ligand COM in the new position
new_ligand_COM = calculate_com(ligand)
# rotate ligand
vector = Vector(new_ligand_COM)
rotation_matrix = rotaxis(np.random.randint(0, 2 * np.pi), vector)
for atom in ligand.get_atoms():
coords_after = atom.get_vector().left_multiply(rotation_matrix)
atom.set_coord(coords_after)
# check if it's inside the sampling sphere
dist = np.sqrt((new_ligand_COM[0] - sphere_cent[0]) ** 2 + (new_ligand_COM[1] - sphere_cent[1]) ** 2 + (
new_ligand_COM[2] - sphere_cent[2]) ** 2)
if dist < D:
# check contacts at: 5A (no contacts) and 8A (needs contacts)
protein_list = Selection.unfold_entities(structure, "A")
contacts5 = []
contacts8 = []
ligand_atoms = list(ligand.get_atoms())
contacts5.append( NeighborSearch(protein_list).search(new_ligand_COM, d5_ligand, "S"))
contacts8 = NeighborSearch(protein_list).search(new_ligand_COM, d8_ligand, "S")
if contacts8 and not any(contacts5):
j += 1
io = PDBIO()
io.set_structure(ligand)
output_name = os.path.join(outputfolder, 'ligand{}.pdb'.format(j))
io.save(output_name)
output.append(output_name)
start_time = time.time()
end_time = time.time()
total_time = end_time - start_time
if total_time > 60:
D += 1
if D - D_initial >= 20:
logger.info("Original box increased by 20A. Aborting...")
break
start_time = end_time
logger.info("Increasing sampling box by 1A.")
logger.info("{} poses created successfully.".format(j))
return output, D, list(sphere_cent)
def randomize_starting_position(parameters, box_center=None, box_radius=None):
"""
Randomize initial ligand position around the receptor.
Parameters
----------
parameters : Parameters
Parameters object passed from Adaptive.simulation.
box_center : Union[List[float], str]
Box center defined by the user, either using a list of coordinates or by specifying an atom, e.g. A:123:CA
box_radius : float
Box radius defined by the user.
Returns
-------
A list of PDB files with random ligand positions.
"""
np.random.seed(parameters.seed)
# When running SiteFinder, the users can narrow down the area where inputs will be
# spawned by setting box radius and center. We're setting box_center as COI to avoid crazy code changes until 2.0.
if parameters.site_finder:
parameters.center_of_interface = box_center if box_center else None
# Retrieve atom information from the string (if PPI or SF)
if parameters.center_of_interface:
pattern = r"([A-z]\:\d{1,4}\:[A-Z0-9]{1,4})"
match = re.match(pattern, parameters.center_of_interface)
if not match:
raise cs.WrongAtomStringFormat(f"The specified atom is wrong '{parameters.center_of_interface}'. "
f"Should be 'chain:residue number:atom name'.")
else:
chain_id, res_number, atom_name = parameters.center_of_interface.split(":")
# Load PDB files into biopython
parser = PDBParser()
structure = parser.get_structure('protein', parameters.receptor)
ligand = parser.get_structure('ligand', parameters.ligand_ref)
output = []
COI = np.zeros(3) # initializing to [0, 0, 0]
# Get center of interface (if PPI or custom SF box)
if parameters.center_of_interface:
for chain in structure.get_chains():
if chain.id == chain_id:
for residue in chain.get_residues():
if residue.id[1] == int(res_number):
for atom in residue.get_atoms():
if atom.name == atom_name:
COI = np.array(list(atom.get_vector()))
print("Center of interface:", COI)
# calculate protein and ligand COM
com_protein = calculate_com(structure)
com_ligand = calculate_com(ligand)
# calculating the maximum dimensions of the ligand
coor_ligand = []
for atom in ligand.get_atoms():
coor_ligand.append(list(atom.get_vector() - com_ligand))
coor_ligand = np.array(coor_ligand)
coor_ligand_max = np.amax(coor_ligand, axis=0)
d_ligand = np.sqrt(np.sum(coor_ligand_max ** 2))
# set threshold for near and far contacts based on ligand dimensions
if d_ligand / 2 < 5.0:
d5_ligand = 5.0
else:
d5_ligand = d_ligand / 2 + 1
if d_ligand > 8.0:
d8_ligand = d_ligand / 2 + 4
else:
d8_ligand = 8.0
# calculate vector to move the ligand respectively to the center of interface of center of mass of the protein
if parameters.center_of_interface:
move_vector = com_ligand - COI
else:
move_vector = com_ligand - com_protein
# translate the ligand to the protein COM (COI for PPI)
original_coords = []
for atom in ligand.get_atoms():
ligand_origin = np.array(list(atom.get_vector())) - move_vector
original_coords.append(ligand_origin)
atom.set_coord(ligand_origin)
# calculating the maximum radius of the protein from the origin
coor = []
for atom in structure.get_atoms():
coor.append(list(atom.get_vector() - com_protein))
coor = np.array(coor)
coor_max = np.amax(coor, axis=0)
d = np.sqrt(np.sum(coor_max ** 2))
# Calculate radius of the sphere from the origin
if parameters.center_of_interface:
if parameters.site_finder and box_radius:
D = box_radius
elif box_radius: # GPCR and OutIn
D = box_radius
else: # ppi
D = 10
else:
D = np.ceil(6.0 + d)
D_initial = D
parameters.logger.info("Sampling {}A spherical box around the centre of the receptor/interface.".format(D))
if parameters.center_of_interface:
sphere_cent = COI
else:
sphere_cent = com_protein
j = 0
parameters.logger.info("Generating {} poses...".format(parameters.poses))
start_time = time.time()
while j < parameters.poses:
# generate random coordinates
phi = np.random.uniform(0, 2 * np.pi)
costheta = np.random.uniform(-1, 1)
u = np.random.uniform(0, 1)
theta = np.arccos(costheta)
r = D * np.cbrt(u)
x = r * np.sin(theta) * np.cos(phi)
y = r * np.sin(theta) * np.sin(phi)
z = r * np.cos(theta)
# move ligand to the starting point (protein COM)
for atom, coord in zip(ligand.get_atoms(), original_coords):
atom.set_coord(coord)
# translate ligand to a random position
translation = (x, y, z)
for atom in ligand.get_atoms():
new_pos_lig_trans = np.array(list(atom.get_vector())) - translation
atom.set_coord(new_pos_lig_trans)
# calculate ligand COM in the new position
new_ligand_COM = calculate_com(ligand)
# rotate ligand
vector = Vector(new_ligand_COM)
rotation_matrix = rotaxis(np.random.randint(0, 2 * np.pi), vector)
for atom in ligand.get_atoms():
coords_after = atom.get_vector().left_multiply(rotation_matrix)
atom.set_coord(coords_after)
# check if it's inside the sampling sphere
dist = np.sqrt((new_ligand_COM[0] - sphere_cent[0]) ** 2 + (new_ligand_COM[1] - sphere_cent[1]) ** 2 + (
new_ligand_COM[2] - sphere_cent[2]) ** 2)
if dist < D:
# check contacts at: 5A (no contacts) and 8A (needs contacts)
protein_list = Selection.unfold_entities(structure, "A")
contacts5 = NeighborSearch(protein_list).search(new_ligand_COM, d5_ligand, "S")
contacts8 = NeighborSearch(protein_list).search(new_ligand_COM, d8_ligand, "S")
if contacts8 and not any(contacts5):
j += 1
io = PDBIO()
io.set_structure(ligand)
output_name = os.path.join(parameters.inputs_dir, 'ligand{}.pdb'.format(j))
io.save(output_name)
output.append(output_name)
start_time = time.time()
end_time = time.time()
total_time = end_time - start_time
if total_time > 60:
D += 1
if D - D_initial >= 20:
parameters.logger.info("Original box increased by 20A. Aborting...")
break
start_time = end_time
parameters.logger.info("Increasing sampling box by 1A.")
parameters.logger.info("{} poses created successfully.".format(j))
return output, D, list(sphere_cent)