def test_adds_correct_number_of_restraints(self):
contents = '#\n2 N 2 H 10 0 10 25000 1.0 1\n'
results = parse.get_rdc_restraints(contents=contents,
system=self.system,
scaler=self.scaler)
self.assertEqual(len(results), 1)
def test_ignores_comment_lines(self):
contents = '#\n#\n'
results = parse.get_rdc_restraints(contents=contents,
system=self.system,
scaler=self.scaler)
self.assertEqual(len(results), 0)
def test_adds_correct_number_of_restraints(self):
contents = "#\n2 N 2 H 10 0 10 25000 1.0 1\n"
results = parse.get_rdc_restraints(
content=contents, system=self.system, scaler=self.scaler, patcher=self.patcher
)
self.assertEqual(len(results), 1)
def test_ignores_comment_lines(self):
contents = "#\n#\n"
results = parse.get_rdc_restraints(
content=contents, system=self.system, scaler=self.scaler, patcher=self.patcher
)
self.assertEqual(len(results), 0)
def setup_system():
# load the sequence
protein_sequence = parse.get_sequence_from_AA1(filename='protein.dat')
peptide_sequence = parse.get_sequence_from_AA1(filename='peptide.dat')
n_res_protein = len(protein_sequence.split())
n_res_peptide = len(peptide_sequence.split())
# build the system
protein = system.ProteinMoleculeFromSequence(protein_sequence)
peptide = system.ProteinMoleculeFromSequence(peptide_sequence)
protein.set_translation([100, 100, 150])
peptide.set_translation([100, 150, 100])
calcium1 = system.ProteinMoleculeFromSequence('CA')
calcium2 = system.ProteinMoleculeFromSequence('CA')
calcium3 = system.ProteinMoleculeFromSequence('CA')
calcium4 = system.ProteinMoleculeFromSequence('CA')
calcium1.set_translation([100, 105, 50])
calcium2.set_translation([100, 110, 50])
calcium3.set_translation([100, 115, 50])
calcium4.set_translation([100, 120, 50])
rdc_patcher = patchers.RdcAlignmentPatcher(n_tensors=1)
ond_patcher = patchers.VirtualSpinLabelPatcher({
17: 'OND',
34: 'OND',
42: 'OND',
53: 'OND',
86: 'OND',
110: 'OND',
117: 'OND',
127: 'OND',
143: 'OND',
149: 'OND'
})
b = system.SystemBuilder()
s = b.build_system_from_molecules(
[protein, calcium1, calcium2, calcium3, calcium4, peptide],
leap_header_cmds="source leaprc.water.tip3p",
patchers=[rdc_patcher, ond_patcher])
s.temperature_scaler = system.GeometricTemperatureScaler(
0, 0.3, 300., 550.)
ramp = s.restraints.create_scaler('linear_ramp',
start_time=1,
end_time=200,
start_weight=0,
end_weight=1)
#
# Secondary Structure
#
ss_scaler = s.restraints.create_scaler('constant')
protein_ss_rests = parse.get_secondary_structure_restraints(
filename='protein_ss.dat',
system=s,
scaler=ss_scaler,
ramp=ramp,
torsion_force_constant=2.5,
distance_force_constant=2.5,
min_secondary_match=5)
peptide_ss_rests = parse.get_secondary_structure_restraints(
filename='peptide_ss.dat',
system=s,
scaler=ss_scaler,
ramp=ramp,
torsion_force_constant=2.5,
distance_force_constant=2.5,
first_residue=int(n_res_protein) + 5) # + 4 due to calciums
# + 1 for 1-based indexing
protein_ss_keep = int(len(protein_ss_rests) * 0.95)
peptide_ss_keep = int(len(peptide_ss_rests) * 0.95)
s.restraints.add_selectively_active_collection(protein_ss_rests,
protein_ss_keep)
s.restraints.add_selectively_active_collection(peptide_ss_rests,
peptide_ss_keep)
#
# Confinement Restraints
#
conf_scaler = s.restraints.create_scaler('constant')
confinement_rests = []
n_res = n_res_protein + n_res_peptide + 4
for index in range(1, n_res + 1):
protein_rest = s.restraints.create_restraint('confine',
conf_scaler,
ramp=ramp,
res_index=index,
atom_name='CA',
radius=5,
force_const=250.0)
confinement_rests.append(protein_rest)
s.restraints.add_as_always_active_list(confinement_rests)
#
# Calcium restraints
#
scaler = s.restraints.create_scaler('nonlinear',
alpha_min=0.5,
alpha_max=1.0,
factor=4.0)
calcium_rests = get_dist_restraints('calcium_restraints.dat', s, scaler,
ramp)
n_keep_calcium = len(calcium_rests)
s.restraints.add_selectively_active_collection(calcium_rests,
n_keep_calcium)
#
# PRE restraints
#
scaler_short = s.restraints.create_scaler('nonlinear',
alpha_min=0.6,
alpha_max=1.0,
factor=4.0)
scaler_medium = s.restraints.create_scaler('nonlinear',
alpha_min=0.5,
alpha_max=0.6,
factor=4.0)
scaler_long = s.restraints.create_scaler('nonlinear',
alpha_min=0.4,
alpha_max=0.5,
factor=4.0)
scalers = [scaler_short, scaler_medium, scaler_long]
OND_list = [17, 34, 42, 53, 86, 110, 117, 127, 143, 149]
for ond in OND_list:
for length, i in zip(['short', 'medium', 'long'], range(3)):
scaler = scalers[int(i)]
pre_restraints = get_dist_restraints_pre(
'rest_files/' + str(ond) + '-pre-' + length + '.dat', s,
scaler, ramp)
n_keep_pre = int(len(pre_restraints) * 0.90)
s.restraints.add_selectively_active_collection(
pre_restraints, n_keep_pre)
#
# RDC Restraints
#
rdc_scaler = s.restraints.create_scaler('nonlinear',
alpha_min=0.3,
alpha_max=0.4,
factor=4.0,
strength_at_alpha_max=1.0e-2)
rdc_rests = parse.get_rdc_restraints(system=s,
patcher=rdc_patcher,
scaler=rdc_scaler,
ramp=ramp,
quadratic_cut=1.0,
scale_factor=1.0e4,
filename='rdc.dat')
s.restraints.add_as_always_active_list(rdc_rests)
# create the options
options = system.RunOptions()
options.implicit_solvent_model = 'obc'
options.use_big_timestep = False
options.cutoff = 1.8
options.remove_com = True
options.use_amap = True
options.amap_beta_bias = 1.0
options.timesteps = 25000
options.minimize_steps = 5000
# create a store
store = vault.DataStore(s.n_atoms,
N_REPLICAS,
s.get_pdb_writer(),
block_size=BLOCK_SIZE)
store.initialize(mode='w')
store.save_system(s)
store.save_run_options(options)
# create and store the remd_runner
l = ladder.NearestNeighborLadder(n_trials=48 * 48)
policy_1 = adaptor.AdaptationPolicy(2.0, 50, 50)
a = adaptor.EqualAcceptanceAdaptor(n_replicas=N_REPLICAS,
adaptation_policy=policy_1)
remd_runner = master_runner.MasterReplicaExchangeRunner(N_REPLICAS,
max_steps=N_STEPS,
ladder=l,
adaptor=a)
store.save_remd_runner(remd_runner)
# create and store the communicator
c = comm.MPICommunicator(s.n_atoms, N_REPLICAS)
store.save_communicator(c)
# create and save the initial states
states = [gen_state(s, i) for i in range(N_REPLICAS)]
store.save_states(states, 0)
# save data_store
store.save_data_store()
return s.n_atoms
