def test_read_write(self):
pdb_file = self.golden_data_path / 'nm_dna' / '1DIZ_lig.pdb.H'
_, _, chains = parse_complex_from_file(pdb_file)
molecule = Complex(chains)
nmodes = calculate_nmodes(pdb_file, n_modes=10, molecule=molecule)
write_nmodes(nmodes, self.test_path / 'test_nm')
expected_nmodes = read_nmodes(self.golden_data_path / 'nm_dna' / 'lightdock_lig.nm.npy')
other_nmodes = read_nmodes(self.test_path / 'test_nm.npy')
assert np.allclose(expected_nmodes, other_nmodes)
def test_read_write(self):
pdb_file = os.path.join(self.golden_data_path, 'nm_dna',
'1DIZ_lig.pdb.H')
atoms, residues, chains = parse_complex_from_file(pdb_file)
molecule = Complex(chains)
nmodes = calculate_nmodes(pdb_file, n_modes=10, molecule=molecule)
write_nmodes(nmodes, os.path.join(self.test_path, 'test_nm'))
expected_nmodes = read_nmodes(
os.path.join(self.golden_data_path, 'nm_dna',
'lightdock_lig.nm.npy'))
other_nmodes = read_nmodes(os.path.join(self.test_path, 'test_nm.npy'))
assert np.allclose(expected_nmodes, other_nmodes)
def test_calculate_anm_protein_2(self):
pdb_file = self.golden_data_path / 'nm_prot' / '2UUY_rec.pdb'
_, _, chains = parse_complex_from_file(pdb_file)
molecule = Complex(chains)
nmodes = calculate_nmodes(pdb_file, n_modes=10, molecule=molecule)
expected_nmodes = read_nmodes(self.golden_data_path / 'nm_prot' / 'lightdock_rec.nm.npy')
assert np.allclose(expected_nmodes, nmodes)
def test_calculate_anm_protein_2(self):
pdb_file = os.path.join(self.golden_data_path, 'nm_prot',
'2UUY_rec.pdb')
atoms, residues, chains = parse_complex_from_file(pdb_file)
molecule = Complex(chains)
nmodes = calculate_nmodes(pdb_file, n_modes=10, molecule=molecule)
expected_nmodes = read_nmodes(
os.path.join(self.golden_data_path, 'nm_prot',
'lightdock_rec.nm.npy'))
assert np.allclose(expected_nmodes, nmodes)
# Read receptor
log.info("Reading %s receptor PDB file..." % receptor_pdb)
atoms, residues, chains = parse_complex_from_file(receptor_pdb)
receptor = Complex(chains, atoms)
log.info("%s atoms, %s residues read." % (len(atoms), len(residues)))
# Read ligand
log.info("Reading %s ligand PDB file..." % ligand_pdb)
atoms, residues, chains = parse_complex_from_file(ligand_pdb)
ligand = Complex(chains, atoms)
log.info("%s atoms, %s residues read." % (len(atoms), len(residues)))
try:
nm_path = os.path.abspath(os.path.dirname(receptor_pdb))
nmodes_rec = read_nmodes(
os.path.join(nm_path, DEFAULT_REC_NM_FILE + '.npy'))
except:
nmodes_rec = None
try:
nm_path = os.path.abspath(os.path.dirname(ligand_pdb))
nmodes_lig = read_nmodes(
os.path.join(nm_path, DEFAULT_LIG_NM_FILE + '.npy'))
except:
nmodes_lig = None
for step in xrange(0, num_steps + 1):
try:
# Parse each stored step file
file_name = 'gso_%d.out' % step
translation, rotation, nm_rec, nm_lig = parse_file(
file_name, glowworm_id)
def run_simulation(parser):
"""Main program"""
try:
parser = CommandLineParser()
args = parser.args
# Read setup and add it to the actual args object
setup = get_setup_from_file(args.setup_file)
for k, v in setup.items():
setattr(args, k, v)
info_file = create_simulation_info_file(args)
log.info("simulation parameters saved to %s" % info_file)
# Read input structures (use parsed ones)
parsed_lightdock_receptor = os.path.join(
os.path.dirname(args.receptor_pdb),
DEFAULT_LIGHTDOCK_PREFIX % os.path.basename(args.receptor_pdb))
receptor = read_input_structure(parsed_lightdock_receptor, args.noxt,
args.noh, args.verbose_parser)
parsed_lightdock_ligand = os.path.join(
os.path.dirname(args.ligand_pdb),
DEFAULT_LIGHTDOCK_PREFIX % os.path.basename(args.ligand_pdb))
ligand = read_input_structure(parsed_lightdock_ligand, args.noxt,
args.noh, args.verbose_parser)
# CRITICAL to not break compatibility with previous results
receptor.move_to_origin()
ligand.move_to_origin()
if args.use_anm:
try:
receptor.n_modes = read_nmodes(
"%s%s" % (DEFAULT_REC_NM_FILE, NUMPY_FILE_SAVE_EXTENSION))
except:
log.warning("No ANM found for receptor molecule")
receptor.n_modes = None
try:
ligand.n_modes = read_nmodes(
"%s%s" % (DEFAULT_LIG_NM_FILE, NUMPY_FILE_SAVE_EXTENSION))
except:
log.warning("No ANM found for ligand molecule")
ligand.n_modes = None
starting_points_files = load_starting_positions(
args.swarms, args.glowworms, args.use_anm, args.anm_rec,
args.anm_lig)
scoring_functions, adapters = set_scoring_function(
parser, receptor, ligand)
tasks = prepare_gso_tasks(parser, adapters, scoring_functions,
starting_points_files)
# Preparing the parallel execution
kraken = Kraken(tasks, parser.args.cores, parser.args.profiling)
log.info("Monster spotted")
reports_queue = kraken.release()
log.info("Finished.")
except KeyboardInterrupt:
log.info("Caught interrupt...")
try:
kraken.sink()
except:
pass
log.info("bye.")
except OSError as e:
log.error("OS error found")
try:
kraken.sink()
except:
pass
raise e
def run_simulation(parser):
"""Main program, includes MPI directives"""
try:
comm = MPI.COMM_WORLD
parser = CommandLineParser()
args = parser.args
# Read setup and add it to the actual args object
setup = get_setup_from_file(args.setup_file)
for k, v in setup.items():
setattr(args, k, v)
minion_id = comm.rank
if minion_id == 0:
info_file = create_simulation_info_file(args)
log.info("simulation parameters saved to %s" % info_file)
comm.Barrier()
# Read input structures (use parsed ones)
parsed_lightdock_receptor = os.path.join(
os.path.dirname(args.receptor_pdb),
DEFAULT_LIGHTDOCK_PREFIX % os.path.basename(args.receptor_pdb))
receptor = read_input_structure(parsed_lightdock_receptor, args.noxt,
args.noh, args.verbose_parser)
parsed_lightdock_ligand = os.path.join(
os.path.dirname(args.ligand_pdb),
DEFAULT_LIGHTDOCK_PREFIX % os.path.basename(args.ligand_pdb))
ligand = read_input_structure(parsed_lightdock_ligand, args.noxt,
args.noh, args.verbose_parser)
# CRITICAL to not break compatibility with previous results
receptor.move_to_origin()
ligand.move_to_origin()
if args.use_anm:
try:
receptor.n_modes = read_nmodes(
"%s%s" % (DEFAULT_REC_NM_FILE, NUMPY_FILE_SAVE_EXTENSION))
except:
log.warning("No ANM found for receptor molecule")
receptor.n_modes = None
try:
ligand.n_modes = read_nmodes(
"%s%s" % (DEFAULT_LIG_NM_FILE, NUMPY_FILE_SAVE_EXTENSION))
except:
log.warning("No ANM found for ligand molecule")
ligand.n_modes = None
starting_points_files = load_starting_positions(
args.swarms, args.glowworms, args.use_anm, args.anm_rec,
args.anm_lig)
comm.Barrier()
num_workers = comm.size
for worker_id in range(num_workers):
if worker_id == minion_id:
starting_points_files = glob.glob(
'init/initial_positions*.dat')
scoring_functions, adapters = set_scoring_function(
parser, receptor, ligand, minion_id)
# Check if scoring functions are compatible with ANM if activated
if args.use_anm and minion_id == 0:
for s in scoring_functions:
if not s.anm_support:
raise NotSupportedInScoringError(
f"ANM is activated while {type(s).__name__} has no support for it"
)
# Prepare tasks depending on swarms to simulate
if parser.args.swarm_list:
swarm_ids = parser.args.swarm_list
if min(swarm_ids) < 0 or max(
swarm_ids) >= parser.args.swarms:
raise SwarmNumError("Wrong list of swarms")
else:
swarm_ids = list(range(parser.args.swarms))
for id_swarm in swarm_ids:
if worker_id == (id_swarm % num_workers):
print('GSO cluster %d - Minion %d' %
(id_swarm, minion_id))
gso = set_gso(
parser.args.glowworms, adapters, scoring_functions,
starting_points_files[id_swarm],
parser.args.gso_seed, parser.args.translation_step,
parser.args.rotation_step,
parser.args.configuration_file,
parser.args.use_anm, parser.args.nmodes_step,
parser.args.anm_rec, parser.args.anm_lig,
parser.args.local_minimization)
saving_path = "%s%d" % (DEFAULT_SWARM_FOLDER, id_swarm)
task = GSOClusterTask(id_swarm, gso, parser.args.steps,
saving_path)
task.run()
comm.Barrier()
except NotSupportedInScoringError as score_error:
log.error("Error found in selected scoring function:")
log.error(score_error)
except KeyboardInterrupt:
log.info("Caught interrupt...")
log.info("bye.")
log.info("%s atoms, %s residues read." % (len(atoms), len(residues)))
ligand = Complex.from_structures(structures)
# Read ranking file
predictions = read_ranking_file(args.lightdock_ranking_file)
# Destination path is the same as the lightdock output
destination_path = os.path.dirname(args.lightdock_ranking_file)
# If normal modes used, need to read them
nmodes_rec = nmodes_lig = None
nm_path = os.path.abspath(os.path.dirname(args.receptor_structures))
# Check NM file for receptor
nm_rec_file = os.path.join(nm_path, DEFAULT_REC_NM_FILE + '.npy')
if os.path.exists(nm_rec_file):
nmodes_rec = read_nmodes(nm_rec_file)
# Check NM file for ligand
nm_lig_file = os.path.join(nm_path, DEFAULT_LIG_NM_FILE + '.npy')
if os.path.exists(nm_lig_file):
nmodes_lig = read_nmodes(nm_lig_file)
for i, glowworm in enumerate(predictions):
if i < args.top:
receptor_pose = receptor.atom_coordinates[
glowworm.receptor_id].clone()
ligand_pose = ligand.atom_coordinates[glowworm.ligand_id].clone()
# Use normal modes if provided:
if nmodes_rec.any():
for nm in range(num_anm_rec):
rec_extent = np.array(
[float(x) for x in glowworm.pose[7:7 + num_anm_rec]])
def run_simulation(parser):
"""Main program, includes MPI directives"""
try:
comm = MPI.COMM_WORLD
parser = CommandLineParser()
args = parser.args
# Read setup and add it to the actual args object
setup = get_setup_from_file(args.setup_file)
for k, v in setup.iteritems():
setattr(args, k, v)
minion_id = comm.rank
if minion_id == 0:
info_file = create_simulation_info_file(args)
log.info("simulation parameters saved to %s" % info_file)
comm.Barrier()
# Read input structures
receptor = read_input_structure(args.receptor_pdb, args.noxt)
ligand = read_input_structure(args.ligand_pdb, args.noxt)
# CRITICAL to not break compatibility with previous results
receptor.move_to_origin()
ligand.move_to_origin()
if args.use_anm:
try:
receptor.n_modes = read_nmodes(
"%s%s" % (DEFAULT_REC_NM_FILE, NUMPY_FILE_SAVE_EXTENSION))
except:
log.warning("No ANM found for receptor molecule")
receptor.n_modes = None
try:
ligand.n_modes = read_nmodes(
"%s%s" % (DEFAULT_LIG_NM_FILE, NUMPY_FILE_SAVE_EXTENSION))
except:
log.warning("No ANM found for ligand molecule")
ligand.n_modes = None
starting_points_files = load_starting_positions(
args.swarms, args.glowworms, args.use_anm, args.anm_rec,
args.anm_lig)
comm.Barrier()
num_workers = comm.size
for worker_id in xrange(num_workers):
if worker_id == minion_id:
starting_points_files = glob.glob(
'init/initial_positions*.dat')
scoring_functions, adapters = set_scoring_function(
parser, receptor, ligand, minion_id)
for id_swarm in xrange(parser.args.swarms):
if worker_id == (id_swarm % num_workers):
print 'GSO cluster %d - Minion %d' % (id_swarm,
minion_id)
gso = set_gso(
parser.args.glowworms, adapters, scoring_functions,
starting_points_files[id_swarm],
parser.args.gso_seed, parser.args.translation_step,
parser.args.rotation_step,
parser.args.configuration_file,
parser.args.use_anm, parser.args.nmodes_step,
parser.args.anm_rec, parser.args.anm_lig,
parser.args.local_minimization)
saving_path = "%s%d" % (DEFAULT_SWARM_FOLDER, id_swarm)
task = GSOClusterTask(id_swarm, gso, parser.args.steps,
saving_path)
task.run()
comm.Barrier()
except KeyboardInterrupt:
log.info("Caught interrupt...")
log.info("bye.")
# Read receptor
log.info("Reading %s receptor PDB file..." % receptor_pdb)
atoms, residues, chains = parse_complex_from_file(receptor_pdb)
receptor = Complex(chains, atoms)
log.info("%s atoms, %s residues read." % (len(atoms), len(residues)))
# Read ligand
log.info("Reading %s ligand PDB file..." % ligand_pdb)
atoms, residues, chains = parse_complex_from_file(ligand_pdb)
ligand = Complex(chains, atoms)
log.info("%s atoms, %s residues read." % (len(atoms), len(residues)))
try:
nm_path = os.path.abspath(os.path.dirname(receptor_pdb))
nmodes_rec = read_nmodes(os.path.join(nm_path, DEFAULT_REC_NM_FILE + '.npy'))
except:
nmodes_rec = None
try:
nm_path = os.path.abspath(os.path.dirname(ligand_pdb))
nmodes_lig = read_nmodes(os.path.join(nm_path, DEFAULT_LIG_NM_FILE + '.npy'))
except:
nmodes_lig = None
for step in xrange(0, num_steps+1):
try:
# Parse each stored step file
file_name = 'gso_%d.out' % step
translation, rotation, nm_rec, nm_lig = parse_file(file_name, glowworm_id)
receptor_pose = receptor.atom_coordinates[0].clone()
def run_simulation(parser):
"""Main program, includes MPI directives"""
try:
comm = MPI.COMM_WORLD
parser = CommandLineParser()
args = parser.args
# Read setup and add it to the actual args object
setup = get_setup_from_file(args.setup_file)
for k, v in setup.iteritems():
setattr(args, k, v)
minion_id = comm.rank
if minion_id == 0:
info_file = create_simulation_info_file(args)
log.info("simulation parameters saved to %s" % info_file)
comm.Barrier()
# Read input structures
receptor = read_input_structure(args.receptor_pdb, args.noxt)
ligand = read_input_structure(args.ligand_pdb, args.noxt)
# CRITICAL to not break compatibility with previous results
receptor.move_to_origin()
ligand.move_to_origin()
if args.use_anm:
try:
receptor.n_modes = read_nmodes("%s%s" % (DEFAULT_REC_NM_FILE, NUMPY_FILE_SAVE_EXTENSION) )
except:
log.warning("No ANM found for receptor molecule")
receptor.n_modes = None
try:
ligand.n_modes = read_nmodes("%s%s" % (DEFAULT_LIG_NM_FILE, NUMPY_FILE_SAVE_EXTENSION) )
except:
log.warning("No ANM found for ligand molecule")
ligand.n_modes = None
starting_points_files = load_starting_positions(args.swarms, args.glowworms, args.use_anm,
args.anm_rec, args.anm_lig)
comm.Barrier()
num_workers = comm.size
for worker_id in xrange(num_workers):
if worker_id == minion_id:
starting_points_files = glob.glob('init/initial_positions*.dat')
scoring_functions, adapters = set_scoring_function(parser, receptor, ligand, minion_id)
for id_swarm in xrange(parser.args.swarms):
if worker_id == (id_swarm % num_workers):
print 'GSO cluster %d - Minion %d' % (id_swarm, minion_id)
gso = set_gso(parser.args.glowworms, adapters, scoring_functions,
starting_points_files[id_swarm],
parser.args.gso_seed, parser.args.translation_step,
parser.args.rotation_step, parser.args.configuration_file,
parser.args.use_anm, parser.args.nmodes_step,
parser.args.anm_rec, parser.args.anm_lig,
parser.args.local_minimization)
saving_path = "%s%d" % (DEFAULT_SWARM_FOLDER, id_swarm)
task = GSOClusterTask(id_swarm, gso, parser.args.steps, saving_path)
task.run()
comm.Barrier()
except KeyboardInterrupt:
log.info("Caught interrupt...")
log.info("bye.")
log.info("%s atoms, %s residues read." % (len(atoms), len(residues)))
ligand = Complex.from_structures(structures)
# Read ranking file
glowworms = read_lightdock_output(args.lightdock_ranking_file, initial=1, final=args.top)
# Destination path is the same as the lightdock output
destination_path = os.path.dirname(args.lightdock_ranking_file)
# If normal modes used, need to read them
nmodes_rec = nmodes_lig = None
nm_path = os.path.abspath(os.path.dirname(args.receptor_structures))
# Check NM file for receptor
nm_rec_file = os.path.join(nm_path, DEFAULT_REC_NM_FILE + '.npy')
if os.path.exists(nm_rec_file):
nmodes_rec = read_nmodes(nm_rec_file)
# Check NM file for ligand
nm_lig_file = os.path.join(nm_path, DEFAULT_LIG_NM_FILE + '.npy')
if os.path.exists(nm_lig_file):
nmodes_lig = read_nmodes(nm_lig_file)
for i, glowworm in enumerate(glowworms):
receptor_pose = receptor.atom_coordinates[glowworm.receptor_id].clone()
ligand_pose = ligand.atom_coordinates[glowworm.ligand_id].clone()
# Use normal modes if provided:
if nmodes_rec.any():
for nm in range(DEFAULT_NMODES_REC):
rec_extent = np.array([float(x) for x in glowworm.pose[7:7 + DEFAULT_NMODES_REC]])
receptor_pose.coordinates += nmodes_rec[nm] * rec_extent[nm]
if nmodes_lig.any():
for nm in range(DEFAULT_NMODES_LIG):
