def create_decoys(lig_file):
"""
creates MAX_DECOYS number of translated/rotated decoys
:param lig_file: (string) file of glide ligand pose that will be translated/rotated
:return:
"""
code = lig_file.split('/')[-1].split('_')[-1]
if code == 'lig0.mae':
modify_file(lig_file, '_pro_ligand')
else:
modify_file(lig_file, '_ligand')
for i in range(MAX_DECOYS):
s = list(structure.StructureReader(lig_file))[0]
#translation
x, y, z = random_three_vector()
dist = np.random.normal(MEAN_TRANSLATION, STDEV_TRANSLATION)
transform.translate_structure(s, x * dist, y * dist, z * dist)
#rotation
x_angle = np.random.uniform(MIN_ANGLE, MAX_ANGLE)
y_angle = np.random.uniform(MIN_ANGLE, MAX_ANGLE)
z_angle = np.random.uniform(MIN_ANGLE, MAX_ANGLE)
rot_center = list(get_centroid(s))
transform.rotate_structure(s, x_angle, y_angle, z_angle, rot_center)
decoy_file = lig_file[:-4] + chr(ord('a') + i) + '.mae'
with structure.StructureWriter(decoy_file) as decoy:
decoy.append(s)
if code == 'lig0.mae':
modify_file(decoy_file, lig_file.split('/')[-1])
else:
modify_file(decoy_file, lig_file.split('/')[-1])
def create_cartesian_decoys(lig_file):
"""
creates MAX_DECOYS number of translated/rotated decoys
:param lig_file: (string) file of glide ligand pose that will be translated/rotated
:return:
"""
code = lig_file.split('/')[-1].split('_')[-1]
if code == 'lig0.mae':
modify_file(lig_file, '_pro_ligand')
else:
modify_file(lig_file, '_ligand')
for i in range(6):
s = list(structure.StructureReader(lig_file))[0]
#translation
x, y, z = cartesian_vector(i)
dist = np.random.normal(MEAN_TRANSLATION, STDEV_TRANSLATION)
transform.translate_structure(s, x * dist, y * dist, z * dist)
decoy_file = lig_file[:-4] + chr(ord('a') + i) + '.mae'
with structure.StructureWriter(decoy_file) as decoy:
decoy.append(s)
if code == 'lig0.mae':
modify_file(decoy_file, lig_file.split('/')[-1])
else:
modify_file(decoy_file, lig_file.split('/')[-1])
def jiggleStructure(self, st, x_range=0.2, y_range=0.2, z_range=0.2):
"""
Adjusts each atom position by a small, non-zero, random amount
along +/-x, +/-y, +/-z.
@param st:
The structure to manipulate.
@type st:
structure.Structure
@param x_range:
The maximum amplitude of a change, in units of angstrom.
Each coordinate change will be within -x_range and +x_range.
@type x_range:
float
@param y_range:
The maximum amplitude of a change, in units of angstrom.
Each coordinate change will be within -y_range and +y_range.
@type y_range:
float
@param z_range:
The maximum amplitude of a change, in units of angstrom.
Each coordinate change will be within -z_range and +z_range.
@type z_range:
float
McRee suggests a value near 0.25 angstroms for removing model
bias from omit difference maps.
"""
for atom in st.atom:
x_sign = 1
if random.random() < 0.5:
x_sign = -1
y_sign = 1
if random.random() < 0.5:
y_sign = -1
z_sign = 1
if random.random() < 0.5:
z_sign = -1
x_rand = x_range * random.random() * x_sign
y_rand = y_range * random.random() * y_sign
z_rand = z_range * random.random() * z_sign
transform.translate_structure(
st,
x_rand,
y_rand,
z_rand,
[atom.index]
)
return
def create_conformer_decoys(conformers, grid_size, start_lig_center, prot,
pose_path, target, max_poses, min_angle,
max_angle):
num_iter_without_pose = 0
num_valid_poses = 1
grid = []
for dx in range(-grid_size, grid_size):
for dy in range(-grid_size, grid_size):
for dz in range(-grid_size, grid_size):
grid.append([[dx, dy, dz], 0])
while num_valid_poses < max_poses:
num_iter_without_pose += 1
conformer = random.choice(conformers)
conformer_center = list(get_centroid(conformer))
# translation
index = random.randint(0, len(grid) - 1)
grid_loc = grid[index][0]
transform.translate_structure(
conformer, start_lig_center[0] - conformer_center[0] + grid_loc[0],
start_lig_center[1] - conformer_center[1] + grid_loc[1],
start_lig_center[2] - conformer_center[2] + grid_loc[2])
conformer_center = list(get_centroid(conformer))
# rotation
x_angle = np.random.uniform(min_angle, max_angle)
y_angle = np.random.uniform(min_angle, max_angle)
z_angle = np.random.uniform(min_angle, max_angle)
transform.rotate_structure(conformer, x_angle, y_angle, z_angle,
conformer_center)
if steric_clash.clash_volume(prot, struc2=conformer) < 200:
decoy_file = os.path.join(
pose_path, "{}_lig{}.mae".format(target, num_valid_poses))
with structure.StructureWriter(decoy_file) as decoy:
decoy.append(conformer)
modify_file(decoy_file, '_pro_ligand')
modify_file(decoy_file, '{}_lig0.mae'.format(target))
num_valid_poses += 1
grid[index][1] = 0
num_iter_without_pose = 0
elif num_iter_without_pose == 5 and len(grid) > 1:
max_val = max(grid, key=lambda x: x[1])
grid.remove(max_val)
num_iter_without_pose = 0
else:
grid[index][1] += 1
def main():
parser = argparse.ArgumentParser()
parser.add_argument('task', type=str, help='either align or search')
parser.add_argument('docked_prot_file',
type=str,
help='file listing proteins to process')
parser.add_argument(
'run_path',
type=str,
help='directory where script and output files will be written')
parser.add_argument('raw_root',
type=str,
help='directory where raw data will be placed')
parser.add_argument('--protein', type=str, default='', help='protein name')
parser.add_argument('--target',
type=str,
default='',
help='target ligand name')
parser.add_argument('--start',
type=str,
default='',
help='start ligand name')
parser.add_argument('--align_n',
type=int,
default=10,
help='number of alignments processed in each job')
parser.add_argument('--rotation_search_step_size',
type=int,
default=1,
help='step size between each angle '
'checked, in degrees')
parser.add_argument('--index',
type=int,
default=-1,
help='grid point group index')
parser.add_argument(
'--rmsd_cutoff',
type=int,
default=2,
help='rmsd accuracy cutoff between predicted ligand pose '
'and true ligand pose')
parser.add_argument('--num_conformers',
type=int,
default=300,
help='maximum number of conformers considered')
parser.add_argument('--grid_size',
type=int,
default=6,
help='grid size in positive and negative x, y, z '
'directions')
parser.add_argument('--grid_n',
type=int,
default=30,
help='number of grid_points processed in each job')
parser.add_argument('--time', dest='get_time', action='store_true')
parser.add_argument('--no_time', dest='get_time', action='store_false')
parser.set_defaults(get_time=False)
parser.add_argument('--remove_prot_h',
dest='no_prot_h',
action='store_true')
parser.add_argument('--keep_prot_h',
dest='no_prot_h',
action='store_false')
parser.set_defaults(no_prot_h=False)
parser.add_argument('--prot_pocket_only',
dest='pocket_only',
action='store_true')
parser.add_argument('--all_prot', dest='pocket_only', action='store_false')
parser.set_defaults(pocket_only=False)
args = parser.parse_args()
random.seed(0)
if not os.path.exists(args.run_path):
os.mkdir(args.run_path)
pair = '{}-to-{}'.format(args.target, args.start)
protein_path = os.path.join(args.raw_root, args.protein)
pair_path = os.path.join(protein_path, pair)
if args.task == 'conformer_all':
process = get_prots(args.docked_prot_file)
random.shuffle(process)
run_conformer_all(process, args.raw_root, args.run_path,
args.docked_prot_file)
elif args.task == 'conformer_group':
target_lig_file = os.path.join(pair_path, 'ligand_poses',
'{}_lig0.mae'.format(args.target))
gen_ligand_conformers(target_lig_file, pair_path, args.num_conformers)
if os.path.exists(
os.path.join(pair_path, '{}_lig0.log'.format(args.target))):
os.remove(
os.path.join(pair_path, '{}_lig0.log'.format(args.target)))
if args.task == 'conformer_check':
process = get_prots(args.docked_prot_file)
random.shuffle(process)
run_conformer_check(process, args.raw_root)
if args.task == 'align_all':
process = get_prots(args.docked_prot_file)
random.shuffle(process)
run_align_all(process, args.raw_root, args.run_path,
args.docked_prot_file, args.align_n)
elif args.task == 'align_group':
grouped_files = get_conformer_groups(args.align_n, args.target,
args.start, args.protein,
args.raw_root)
run_align_group(grouped_files, args.index, args.n, args.protein,
args.target, args.start, args.raw_root)
elif args.task == 'align_check':
process = get_prots(args.docked_prot_file)
random.shuffle(process)
run_align_check(process, args.raw_root)
elif args.task == 'align_combine':
process = get_prots(args.docked_prot_file)
random.shuffle(process)
run_align_combine(process, args.raw_root)
elif args.task == 'run_search':
process = get_prots(args.docked_prot_file)
random.shuffle(process)
grouped_files = get_grid_groups(args.grid_size, args.grid_n)
search_system_caller(process, args.raw_root, args.run_path,
args.docked_prot_file,
args.rotation_search_step_size, args.grid_size,
grouped_files)
elif args.task == 'search':
grouped_files = get_grid_groups(args.grid_size, args.grid_n)
run_search(args.protein, args.target, args.start, args.index,
args.raw_root, args.get_time, args.rmsd_cutoff,
args.rotation_search_step_size, grouped_files[args.index],
args.no_prot_h, args.pocket_only)
elif args.task == 'check_search':
process = get_prots(args.docked_prot_file)
random.shuffle(process)
grouped_files = get_grid_groups(args.grid_size, args.grid_n)
counter = 0
unfinished = []
for protein, target, start in process:
if counter == 10:
break
pair = '{}-to-{}'.format(target, start)
protein_path = os.path.join(args.raw_root, protein)
pair_path = os.path.join(protein_path, pair)
conformer_file = os.path.join(pair_path,
"{}_lig0-out.maegz".format(target))
conformers = list(structure.StructureReader(conformer_file))
if len(conformers) == 1:
continue
else:
counter += 1
save_folder = os.path.join(
os.getcwd(), 'decoy_timing_data',
'{}_{}-to-{}'.format(protein, target, start))
for i in range(len(grouped_files)):
if not os.path.exists(
os.path.join(save_folder, '{}.csv'.format(i))):
unfinished.append((protein, target, start, i))
print("Missing:", len(unfinished))
print(unfinished)
elif args.task == 'test_search':
run_test_search(args.protein, args.target, args.start, args.raw_root,
args.rmsd_cutoff, args.rotation_search_step_size,
pair_path, args.no_prot_h, args.pocket_only,
args.get_time)
elif args.task == 'get_grid_data':
process = get_prots(args.docked_prot_file)
random.shuffle(process)
grouped_files = get_grid_groups(args.grid_size, args.grid_n)
get_data(process, grouped_files, args.raw_root, args.grid_size)
elif args.task == 'combine_search_data':
process = get_prots(args.docked_prot_file)
random.shuffle(process)
grouped_files = get_grid_groups(args.grid_size, args.grid_n)
get_data(process, grouped_files, args.raw_root, args.grid_size, True)
elif args.task == 'get_dist':
process = get_prots(args.docked_prot_file)
random.shuffle(process)
counter = 0
for protein, target, start in process:
if counter == 10:
break
pair = '{}-to-{}'.format(target, start)
protein_path = os.path.join(args.raw_root, protein)
pair_path = os.path.join(protein_path, pair)
conformer_file = os.path.join(pair_path,
"{}_lig0-out.maegz".format(target))
conformers = list(structure.StructureReader(conformer_file))
if len(conformers) == 1:
continue
else:
counter += 1
start_lig_file = os.path.join(pair_path,
'{}_lig.mae'.format(start))
start_lig = list(structure.StructureReader(start_lig_file))[0]
start_lig_center = list(get_centroid(start_lig))
target_lig_file = os.path.join(pair_path, 'ligand_poses',
'{}_lig0.mae'.format(target))
target_lig = list(structure.StructureReader(target_lig_file))[0]
target_lig_center = list(get_centroid(target_lig))
dist = math.sqrt((
(start_lig_center[0] - target_lig_center[0])**2) + (
(start_lig_center[1] - target_lig_center[1])**2) +
((start_lig_center[2] - target_lig_center[2])**2))
print(protein, target, start, dist)
elif args.task == 'test_rotate_translate':
prot_file = os.path.join(pair_path, '{}_prot.mae'.format(args.start))
schrodinger_prot = list(structure.StructureReader(prot_file))[0]
custom_prot = list(structure.StructureReader(prot_file))[0]
translation_vector = np.random.uniform(low=-100, high=100, size=(3))
transform.translate_structure(schrodinger_prot, translation_vector[0],
translation_vector[1],
translation_vector[2])
translate_structure(custom_prot, translation_vector[0],
translation_vector[1], translation_vector[2])
schrodinger_atoms = np.array(schrodinger_prot.getXYZ(copy=False))
custom_atoms = np.array(custom_prot.getXYZ(copy=False))
if np.array_equal(schrodinger_atoms, custom_atoms):
print("Translate function works properly")
else:
print("Error in translate function")
schrodinger_prot = list(structure.StructureReader(prot_file))[0]
custom_prot = list(structure.StructureReader(prot_file))[0]
rotation_vector = np.random.uniform(low=-2 * np.pi,
high=2 * np.pi,
size=(3))
rotation_center = np.random.uniform(low=-100, high=100, size=(3))
rotation_center = [
rotation_center[0], rotation_center[1], rotation_center[2]
]
transform.rotate_structure(schrodinger_prot, rotation_vector[0],
rotation_vector[1], rotation_vector[2],
rotation_center)
coords = rotate_structure(custom_prot.getXYZ(copy=False),
rotation_vector[0], rotation_vector[1],
rotation_vector[2], rotation_center)
custom_prot.setXYZ(coords)
schrodinger_atoms = np.array(schrodinger_prot.getXYZ(copy=False))
custom_atoms = np.array(custom_prot.getXYZ(copy=False))
if np.amax(np.absolute(schrodinger_atoms - custom_atoms)) < 10**-7:
print("Rotate function works properly")
else:
print("Error in rotate function")
elif args.task == 'get_rmsd':
conformer_file = os.path.join(
pair_path,
"aligned_to_start_without_hydrogen_conformers.mae".format(
args.target))
conformers = list(structure.StructureReader(conformer_file))
target_lig_file = os.path.join(pair_path, 'ligand_poses',
'{}_lig0.mae'.format(args.target))
target_lig = list(structure.StructureReader(target_lig_file))[0]
build.delete_hydrogens(target_lig)
start_lig_file = os.path.join(pair_path,
'{}_lig.mae'.format(args.start))
start_lig = list(structure.StructureReader(start_lig_file))[0]
start_lig_center = list(get_centroid(start_lig))
rmsds = []
for i, conformer in tqdm(enumerate(conformers),
desc='going through conformers'):
conformer_center = list(get_centroid(conformer))
translate_structure(conformer,
start_lig_center[0] - conformer_center[0],
start_lig_center[1] - conformer_center[1],
start_lig_center[2] - conformer_center[2])
rmsds.append(
(conformer,
rmsd.calculate_in_place_rmsd(conformer,
conformer.getAtomIndices(),
target_lig,
target_lig.getAtomIndices()), i))
# best_match_conformer = min(rmsds, key=lambda x: x[1])
# print(best_match_conformer[1], best_match_conformer[2])
# file = os.path.join(pair_path, 'best_match_conformer.mae')
# with structure.StructureWriter(file) as best_match:
# best_match.append(best_match_conformer[0])
print(rmsds[248][1], rmsds[248][2])
file = os.path.join(pair_path, 'translated_conformer_248.mae')
with structure.StructureWriter(file) as best_match:
best_match.append(rmsds[248][0])
elif args.task == 'check_rotation':
target_lig_file = os.path.join(pair_path, 'ligand_poses',
'{}_lig0.mae'.format(args.target))
target_lig = list(structure.StructureReader(target_lig_file))[0]
remove = [i for i in target_lig.getAtomIndices() if i != 1]
target_lig.deleteAtoms(remove)
center = list(get_centroid(target_lig))
print("ROTATE 5,5,5")
rotate_structure(target_lig, math.radians(5), math.radians(5),
math.radians(5), center)
target_lig_2 = list(structure.StructureReader(target_lig_file))[0]
target_lig_2.deleteAtoms(remove)
center = list(get_centroid(target_lig_2))
print("ROTATE 5,0,0")
rotate_structure(target_lig_2, math.radians(5), 0, 0, center)
print("ROTATE 0,5,0")
rotate_structure(target_lig_2, 0, math.radians(5), 0, center)
print("ROTATE 0,0,5")
rotate_structure(target_lig_2, 0, 0, math.radians(5), center)
print(
rmsd.calculate_in_place_rmsd(target_lig,
target_lig.getAtomIndices(),
target_lig_2,
target_lig_2.getAtomIndices()))
print(target_lig.getXYZ(copy=False))
print(target_lig_2.getXYZ(copy=False))
def create_conformer_decoys(grid, target_lig, cutoff,
rotation_search_step_size, protein, target, start,
index, pair_path, test, x_rot, y_rot, z_rot):
counter = 0
data_dict = {
'protein': [],
'target': [],
'start': [],
'num_conformers': [],
'num_poses_searched': [],
'num_correct_poses_found': [],
'time_elapsed': [],
'time_elapsed_per_conformer': [],
'grid_loc_x': [],
'grid_loc_y': [],
'grid_loc_z': []
}
for grid_loc in grid:
num_correct_found = 0
conformer_file = os.path.join(
pair_path, "aligned_to_start_without_hydrogen_conformers.mae")
conformers = list(structure.StructureReader(conformer_file))
decoy_start_time = time.time()
for conformer in conformers:
transform.translate_structure(conformer, grid_loc[0], grid_loc[1],
grid_loc[2])
conformer_center = list(get_centroid(conformer))
coords = conformer.getXYZ(copy=True)
for x in range(-30, 30 + rotation_search_step_size,
rotation_search_step_size):
for y in range(-30, 30 + rotation_search_step_size,
rotation_search_step_size):
for z in range(-30, 30 + rotation_search_step_size,
rotation_search_step_size):
new_coords = rotate_structure(coords, math.radians(x),
math.radians(y),
math.radians(z),
conformer_center)
conformer.setXYZ(new_coords)
if test and x_rot == x and y_rot == y and z_rot == z:
return conformer
rmsd_val = rmsd.calculate_in_place_rmsd(
conformer, conformer.getAtomIndices(), target_lig,
target_lig.getAtomIndices())
if rmsd_val < cutoff:
num_correct_found += 1
decoy_end_time = time.time()
data_dict['protein'].append(protein)
data_dict['target'].append(target)
data_dict['start'].append(start)
data_dict['num_conformers'].append(len(conformers))
data_dict['num_poses_searched'].append(counter)
data_dict['num_correct_poses_found'].append(num_correct_found)
data_dict['time_elapsed'].append(decoy_end_time - decoy_start_time)
data_dict['time_elapsed_per_conformer'].append(
(decoy_end_time - decoy_start_time) / len(conformers))
data_dict['grid_loc_x'].append(grid_loc[0])
data_dict['grid_loc_y'].append(grid_loc[1])
data_dict['grid_loc_z'].append(grid_loc[2])
df = pd.DataFrame.from_dict(data_dict)
data_folder = os.path.join(os.getcwd(), 'decoy_timing_data')
if not os.path.exists(data_folder):
os.mkdir(data_folder)
save_folder = os.path.join(data_folder,
'{}_{}-to-{}'.format(protein, target, start))
if not os.path.exists(save_folder):
os.mkdir(save_folder)
df.to_csv(os.path.join(save_folder, '{}.csv'.format(index)))
return None
def time_conformer_decoys(pair_path, start_lig_center, target_lig, prot,
rotation_search_step_size):
translate_times = []
rotate_times = []
conformer_file = os.path.join(
pair_path, "aligned_to_start_without_hydrogen_conformers.mae")
conformers = list(structure.StructureReader(conformer_file))
for conformer in conformers:
conformer_center = list(get_centroid(conformer))
# translation
grid_loc = [0, 0, 0]
start = time.time()
transform.translate_structure(
conformer, start_lig_center[0] - conformer_center[0] + grid_loc[0],
start_lig_center[1] - conformer_center[1] + grid_loc[1],
start_lig_center[2] - conformer_center[2] + grid_loc[2])
end = time.time()
translate_times.append(end - start)
# rotation
start = time.time()
transform.rotate_structure(
conformer, math.radians(-30 - rotation_search_step_size), 0, 0,
conformer_center)
end = time.time()
rotate_times.append(end - start)
print("Average schrodinger translate time =",
statistics.mean(translate_times))
print("Average schrodinger rotate time =", statistics.mean(rotate_times))
translate_times = []
rotate_times = []
conformer_file = os.path.join(
pair_path, "aligned_to_start_without_hydrogen_conformers.mae")
conformers = list(structure.StructureReader(conformer_file))
for conformer in conformers:
conformer_center = list(get_centroid(conformer))
# translation
grid_loc = [0, 0, 0]
start = time.time()
translate_structure(
conformer, start_lig_center[0] - conformer_center[0] + grid_loc[0],
start_lig_center[1] - conformer_center[1] + grid_loc[1],
start_lig_center[2] - conformer_center[2] + grid_loc[2])
end = time.time()
translate_times.append(end - start)
# rotation
start = time.time()
rotate_structure(conformer,
math.radians(-30 - rotation_search_step_size), 0, 0,
conformer_center)
end = time.time()
rotate_times.append(end - start)
print("Average custom translate time =", statistics.mean(translate_times))
print("Average custom rotate time =", statistics.mean(rotate_times))
clash_iterator_times = []
clash_volume_times = []
rmsd_times = []
rotation_search_step_size_rad = math.radians(rotation_search_step_size)
conformer_file = os.path.join(
pair_path, "aligned_to_start_without_hydrogen_conformers.mae")
conformers = list(structure.StructureReader(conformer_file))
for conformer in conformers:
conformer_center = list(get_centroid(conformer))
# translation
grid_loc = [0, 0, 0]
translate_structure(
conformer, start_lig_center[0] - conformer_center[0] + grid_loc[0],
start_lig_center[1] - conformer_center[1] + grid_loc[1],
start_lig_center[2] - conformer_center[2] + grid_loc[2])
conformer_center = list(get_centroid(conformer))
# keep track of rotation angles
rotate_structure(conformer,
math.radians(-30 - rotation_search_step_size), 0, 0,
conformer_center)
x_so_far = -30 - rotation_search_step_size
y_so_far = 0
z_so_far = 0
for _ in range(-30, 30, rotation_search_step_size):
# x rotation
rotate_structure(
conformer, rotation_search_step_size_rad,
math.radians(-30 - rotation_search_step_size - y_so_far), 0,
conformer_center)
x_so_far += 1
y_so_far += -30 - rotation_search_step_size - y_so_far
for _ in range(-30, 30, rotation_search_step_size):
# y rotation
rotate_structure(
conformer, 0, rotation_search_step_size_rad,
math.radians(-30 - rotation_search_step_size - z_so_far),
conformer_center)
y_so_far += 1
z_so_far += -30 - rotation_search_step_size - z_so_far
for _ in range(-30, 30, rotation_search_step_size):
# z rotation
rotate_structure(conformer, 0, 0,
rotation_search_step_size_rad,
conformer_center)
z_so_far += 1
# get clash_iterator
start = time.time()
max([
x[2] for x in list(
steric_clash.clash_iterator(prot,
struc2=conformer))
])
end = time.time()
clash_iterator_times.append(end - start)
# get clash_volume
start = time.time()
steric_clash.clash_volume(prot, struc2=conformer)
end = time.time()
clash_volume_times.append(end - start)
# get rmsd
start = time.time()
rmsd.calculate_in_place_rmsd(conformer,
conformer.getAtomIndices(),
target_lig,
target_lig.getAtomIndices())
end = time.time()
rmsd_times.append(end - start)
if len(clash_iterator_times) == 1000:
print("Average clash iterator time =",
statistics.mean(clash_iterator_times))
print("Average clash volume time =",
statistics.mean(clash_volume_times))
print("Average rmsd time =",
statistics.mean(rmsd_times))
return
def create_conformer_decoys(save_path, run_path, conformers, grid,
num_jobs_submitted, start_lig_center, target_lig,
prot, min_angle, max_angle, rmsd_cutoff, protein,
target, start, index):
conformer_ls = [[c, 0] for c in conformers]
rot_ls = []
for rot_x in range(int(math.degrees(min_angle)),
int(math.degrees(max_angle)) + 1):
for rot_y in range(int(math.degrees(min_angle)),
int(math.degrees(max_angle)) + 1):
for rot_z in range(int(math.degrees(min_angle)),
int(math.degrees(max_angle)) + 1):
rot_ls.append([[
math.radians(rot_x),
math.radians(rot_y),
math.radians(rot_z)
], 0])
output_file = os.path.join(
run_path, '{}_{}_{}_{}.txt'.format(protein, target, start, index))
num_iter_without_pose = 0
num_valid_poses = 0
num_total_poses = 0
while True:
num_iter_without_pose += 1
num_total_poses += 1
if num_total_poses % 1000 == 0:
num_jobs_in_queue = get_jobs_in_queue('{}{}{}'.format(
protein[0], target[0], start[0]))
f = open(output_file, "a")
f.write(
"num_total_poses: {}, len(grid): {}, len(conformer_ls): {}, len(rot_ls): {}, num_jobs_in_queue: "
"{}\n".format(num_total_poses, len(grid), len(conformer_ls),
len(rot_ls), num_jobs_in_queue))
f.close()
if num_jobs_in_queue != num_jobs_submitted:
break
conformer_index = random.randint(0, len(conformer_ls) - 1)
conformer = conformer_ls[conformer_index][0]
conformer_center = list(get_centroid(conformer))
# translation
index = random.randint(0, len(grid) - 1)
grid_loc = grid[index][0]
transform.translate_structure(
conformer, start_lig_center[0] - conformer_center[0] + grid_loc[0],
start_lig_center[1] - conformer_center[1] + grid_loc[1],
start_lig_center[2] - conformer_center[2] + grid_loc[2])
conformer_center = list(get_centroid(conformer))
# rotation
if len(grid) > 1:
x_angle = np.random.uniform(min_angle, max_angle)
y_angle = np.random.uniform(min_angle, max_angle)
z_angle = np.random.uniform(min_angle, max_angle)
else:
rot_index = random.randint(0, len(rot_ls) - 1)
x_angle, y_angle, z_angle = rot_ls[rot_index][0]
transform.rotate_structure(conformer, x_angle, y_angle, z_angle,
conformer_center)
if steric_clash.clash_volume(prot, struc2=conformer) < 200:
num_valid_poses += 1
if rmsd.calculate_in_place_rmsd(
conformer, conformer.getAtomIndices(), target_lig,
target_lig.getAtomIndices()) < rmsd_cutoff:
save_file = os.path.join(
save_path, '{}_{}_{}.txt'.format(protein, target, start))
f = open(output_file, "a")
f.write("Num poses searched = {}\n".format(num_total_poses))
f.write("Num acceptable clash poses searched = {}\n".format(
num_valid_poses))
f.close()
if not os.path.exists(save_file):
with open(save_file, 'w') as f:
f.write("Num poses searched = {}\n".format(
num_total_poses))
f.write("Num acceptable clash poses searched = {}\n".
format(num_valid_poses))
break
grid[index][1] = 0
num_iter_without_pose = 0
elif num_iter_without_pose == 5 and len(grid) > 1:
max_val = max(grid, key=lambda x: x[1])
grid.remove(max_val)
num_iter_without_pose = 0
elif num_iter_without_pose == 5 and len(grid) == 1:
if len(conformer_ls) == 1 and len(rot_ls) == 1:
save_file = os.path.join(
save_path, '{}_{}_{}.txt'.format(protein, target, start))
f = open(output_file, "a")
f.write("Num poses searched = {}\n".format(num_total_poses))
f.write("Num acceptable clash poses searched = {}\n".format(
num_valid_poses))
f.write("No correct poses found\n")
f.close()
if not os.path.exists(save_file):
with open(save_file, 'w') as f:
f.write("Num poses searched = {}\n".format(
num_total_poses))
f.write("Num acceptable clash poses searched = {}\n".
format(num_valid_poses))
f.write("No correct poses found\n")
break
elif len(conformer_ls) > 1 and (len(rot_ls) == 1 or
(len(conformer_ls) + len(rot_ls)) %
2 == 0):
max_val = max(conformer_ls, key=lambda x: x[1])
conformer_ls.remove(max_val)
else:
max_val = max(rot_ls, key=lambda x: x[1])
rot_ls.remove(max_val)
num_iter_without_pose = 0
else:
grid[index][1] += 1
conformer_ls[conformer_index][1] += 1
if len(grid) == 1:
rot_ls[rot_index][1] += 1