def setup_fastrelax(sf): """ Creates FastRelax mover with appropriate score function, movemap, and packer rules. List of neighbor residues was generated using a 10A neighborhood residue selector around the peptide chain. """ relax = FastRelax() relax.set_scorefxn(sf) # MoveMap mm = MoveMap() mm.set_bb_true_range(212,216) neighbors = [28, 29, 41, 42, 43, 44, 45, 46, 59, 60, 61, 62, 91, 125, 126, 127, 128, 129, 145, 147, 148, 149, 150, 151, 157, 164, 165, 166, 167, 168, 169, 170, 171, 183, 184, 185, 186, 187, 188, 189, 192, 193, 194, 212, 213, 214, 215, 216, 217, 218, 219, 220] # Did 10A selection separately for n in neighbors: mm.set_chi(n, True) relax.set_movemap(mm) # Packer tasks tf = standard_task_factory() tf.push_back(RestrictToRepacking()) tf.push_back(IncludeCurrent()) tf.push_back(ExtraRotamers(0, 1, 1)) tf.push_back(ExtraRotamers(0, 2, 1)) relax.set_task_factory(tf) return relax
def setup_fastrelax(sf):
"""
Creates FastRelax mover with appropriate score function, movemap, and
packer rules. List of neighbor residues was generated using a 8A
PyMOL selection expansion around the peptide chain.
"""
relax = FastRelax()
relax.set_scorefxn(sf)
# MoveMap
mm = MoveMap()
mm.set_bb_true_range(106, 112)
neighbors = [
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 22, 37,
38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 53, 59, 62, 69, 70, 71, 72,
73, 74, 75, 76, 77, 78, 79, 83, 85, 98, 100, 101, 103, 104, 105, 106,
107, 108, 109, 110, 111, 112
] # Did 8A selection separately
for n in neighbors:
mm.set_chi(n, True)
relax.set_movemap(mm)
# Packer tasks
tf = standard_task_factory()
tf.push_back(RestrictToRepacking())
tf.push_back(IncludeCurrent())
tf.push_back(ExtraRotamers(0, 1, 1))
tf.push_back(ExtraRotamers(0, 2, 1))
relax.set_task_factory(tf)
return relax
def setup_fastrelax(sf, pose):
"""
Creates FastRelax mover with appropriate score function, movemap, and
packer rules. All sidechains are mobile, only substrate backbone is mobile.
"""
relax = FastRelax()
relax.set_scorefxn(sf)
# MoveMap
mm = MoveMap()
mm.set_chi(True)
for i in range(1, pose.total_residue() + 1):
if pose.residue(i).chain() == 2:
mm.set_bb(i, True)
relax.set_movemap(mm)
# Packer tasks
tf = standard_task_factory()
tf.push_back(RestrictToRepacking())
tf.push_back(IncludeCurrent())
tf.push_back(ExtraRotamers(0, 1, 1))
tf.push_back(ExtraRotamers(0, 2, 1))
relax.set_task_factory(tf)
return relax
def main(args):
# Destination folder for PDB files
od = out_directory(args.out_dir)
# Determining file name
if args.name:
file_name = args.name
else:
file_name = basename(args.pdb_file).replace('.pdb',
'').replace('.gz', '')
file_name += '_relaxed'
out_name = join(od, file_name)
# Loading pose and applying constraints, symmetry,
pose = load_pose(args.pdb_file,
enzdes_cst=args.constraints,
coord_cst=True,
symmetry=args.symmetry,
membrane=None)
# Setting up the scorefunction with the desired constraint weights
sf = get_sf(rep_type='hard',
symmetry=args.symmetry,
membrane=0,
constrain=args.constraint_weight)
# Creating FastRelax protocol with the given score function
fr = FastRelax()
fr.set_scorefxn(sf)
# Packer tasks
tf = standard_task_factory()
tf.push_back(RestrictToRepacking())
tf.push_back(IncludeCurrent())
tf.push_back(ExtraRotamers(0, 1, 1))
tf.push_back(ExtraRotamers(0, 2, 1))
fr.set_task_factory(tf)
# RMSD metric
rmsdm = RMSDMetric()
rmsdm.set_comparison_pose(pose)
# Running relax set
jd = PyJobDistributor(out_name, args.n_decoys, sf)
while not jd.job_complete:
pp = Pose(pose)
fr.apply(pp)
rmsdm.apply(pp)
jd.output_decoy(pp)
print("Starting relax {}".format(pdb_name))
pose = fastrelax(pose, sf, mm, taskfactory=tf)
def make_point_mutant_task_factory(site_1,
change_1,
site_2=None,
change_2=None,
fast=True):
"""
Given a site integer and a 1-letter residue name (or two sites and two
residue names), generates a TaskFactory to repack all residues
in a pose with the altered sites repacking to the new sequence.
"""
# Initialize selection of all altered residues
modified_residues = OrResidueSelector() # Keep list of mobile residues
# Make TaskFactory to input changes
task_factory = TaskFactory()
task_factory.push_back(IncludeCurrent())
if not fast:
task_factory.push_back(ExtraRotamers(0, 1, 1))
task_factory.push_back(ExtraRotamers(0, 2, 1))
# Force packing to new residue for the mutated site
res_selection_1 = ResidueIndexSelector(str(site_1))
aa_force_1 = RestrictAbsentCanonicalAASRLT()
aa_force_1.aas_to_keep(change_1)
task_factory.push_back(OperateOnResidueSubset(aa_force_1, res_selection_1))
modified_residues.add_residue_selector(res_selection_1)
# Add second site if necessary
if site_2 and change_2:
res_selection_2 = ResidueIndexSelector(str(site_2))
aa_force_2 = RestrictAbsentCanonicalAASRLT()
aa_force_2.aas_to_keep(change_2)
task_factory.push_back(
OperateOnResidueSubset(aa_force_2, res_selection_2))
modified_residues.add_residue_selector(res_selection_2)
# Repack all other residues to accommodate substitutions
unchanged_residues = NotResidueSelector(modified_residues)
repack = RestrictToRepackingRLT()
task_factory.push_back(OperateOnResidueSubset(repack, unchanged_residues))
return task_factory
def make_task_factory(residue_selectors):
"""
Makes a TaskFactory with operations that leave the mutable residues
designable, restricts the nearby residues to repacking, and prevents
repacking of other residues.
"""
mutable_set = residue_selectors['mutable']
repack_set = residue_selectors['packable']
immobile_set = residue_selectors['immobile']
prevent = PreventRepackingRLT() # No repack, no design
repack = RestrictToRepackingRLT() # No design
tf = TaskFactory()
tf.push_back(IncludeCurrent())
tf.push_back(ExtraRotamers(0, 1, 1))
tf.push_back(ExtraRotamers(0, 2, 1))
tf.push_back(OperateOnResidueSubset(prevent, immobile_set))
tf.push_back(OperateOnResidueSubset(repack, repack_set))
# Everything else left designable by default
return tf
def task_factory_builder(repacking_residues='all', designing_residues=None, \
extra_rotamers=[1,2]):
#Setting this up for now, need to implement these conditions:
#Repackable set, Designable Set, prevent ligand repacking
#Building a Task Factory for repacking/design around the neighbors residues
#Task factory builder should accept: repackable residues, designable
#residues, specifically preventing repacking residues, and prevent the rest.
#tf = task_factory_builder(repack=repacking_neighbors)
#distance - distance for Neighborhood residue selector - need to remov
print_out("Building task factory")
#Start up Task factory, starting ex1 and ex2, and include current
tf = TaskFactory()
tf.push_back(IncludeCurrent())
if extra_rotamers:
for x in extra_rotamers:
tf.push_back(ExtraRotamers(0, x, 1))
print(repacking_residues)
#Set up repack and prevent repack
repack = RestrictToRepackingRLT()
prevent = PreventRepackingRLT()
prevent_everything_else = NotResidueSelector()
residues_for_repack = None
residues_for_design = None
changing_residues = OrResidueSelector()
if repacking_residues != 'all':
print_out("Repacking these residues: " + str(repacking_residues))
residues_for_repack = ResidueIndexSelector(
','.join(repacking_residues))
changing_residues.add_residue_selector(residues_for_repack)
tf.push_back(OperateOnResidueSubset(repack, residues_for_repack))
if designing_residues:
residues_for_design = ResidueIndexSelector(designing_residues)
changing_residues.add_residue_selector(residues_for_design)
prevent_everything_else.set_residue_selector(changing_residues)
if repack == 'all':
tf.push_back(OperateOnResidueSubset(repack, prevent_everything_else))
else:
tf.push_back(OperateOnResidueSubset(prevent, prevent_everything_else))
return tf
def main(args):
# Destination folder for PDB files
if args.out_dir:
dir_name = args.out_dir
if not isdir(dir_name):
makedirs(dir_name)
else:
dir_name = ""
# Creating coordinate constraints for the entire molecule
cg = CoordinateConstraintGenerator()
ac = AddConstraints()
ac.add_generator(cg)
# Create enzdes constraints
if args.constraints:
enz_cst = AddOrRemoveMatchCsts()
enz_cst.set_cst_action(ADD_NEW)
# Creating symmetry setup
if args.symmetry:
sfsm = SetupForSymmetryMover(args.symmetry)
# Setting up the scorefunction with the desired constraint weights
if args.symmetry:
sf = SymmetricScoreFunction()
sf.add_weights_from_file(args.score_function)
else:
sf = create_score_function(args.score_function)
if args.coord_wt:
sf.set_weight(st.coordinate_constraint, args.coord_wt)
if args.enzdes_wt:
sf.set_weight(st.atom_pair_constraint, args.enzdes_wt)
sf.set_weight(st.angle_constraint, args.enzdes_wt)
sf.set_weight(st.dihedral_constraint, args.enzdes_wt)
# Creating FastRelax protocol with the given score function
fr = FastRelax()
fr.set_scorefxn(sf)
# Packer tasks
tf = standard_task_factory()
tf.push_back(RestrictToRepacking())
tf.push_back(IncludeCurrent())
tf.push_back(ExtraRotamers(0, 1, 1))
tf.push_back(ExtraRotamers(0, 2, 1))
fr.set_task_factory(tf)
# Determining file name
if args.name:
file_name = args.name
else:
file_name = basename(args.pdb_file).replace('.pdb', '').replace('.gz', '')
file_name += '_relaxed'
out_name = join(dir_name, file_name)
# Loading PDB file, applying constraints
pose = pose_from_pdb(args.pdb_file)
ac.apply(pose)
if args.constraints:
enz_cst.apply(pose)
if args.symmetry:
sfsm.apply(pose)
# RMSD metric
rmsdm = RMSDMetric()
rmsdm.set_comparison_pose(pose)
# Running relax set
jd = PyJobDistributor(out_name, args.n_decoys, sf)
while not jd.job_complete:
pp = Pose()
pp.assign(pose)
fr.apply(pp)
rmsdm.apply(pp)
jd.output_decoy(pp)
'R386V-M388R-K394V-T415K-E416Y': 'pdz_relaxed_2.pdb_designed_13.pdb',
'Y382W-R386V-M388R-K394V-T415K-E416Y': 'pdz_relaxed_2.pdb_designed_13.pdb',
'S389D-S444R-N446Q': 'pdz_relaxed_3.pdb_designed_47.pdb',
'N446E': 'pdz_relaxed_2.pdb_designed_9.pdb'
}
for des, muts in res_changes.items():
pp = pose_from_pdb('pdz_designs/examples/' + start_pdb[des])
peptide = ChainSelector('B')
shell = NeighborhoodResidueSelector()
shell.set_focus_selector(peptide)
shell.set_include_focus_in_subset(True)
shell.set_distance(12)
mobile_residues = OrResidueSelector()
tf = TaskFactory()
tf.push_back(IncludeCurrent())
tf.push_back(ExtraRotamers(0, 1, 1))
tf.push_back(ExtraRotamers(0, 2, 1))
for r, aa in muts.items():
res_selection = ResidueIndexSelector(str(r))
restriction = RestrictAbsentCanonicalAASRLT()
restriction.aas_to_keep(aa.upper())
tf.push_back(OperateOnResidueSubset(restriction, res_selection))
mobile_residues.add_residue_selector(res_selection)
packable = AndResidueSelector(shell, NotResidueSelector(mobile_residues))
tf.push_back(OperateOnResidueSubset(RestrictToRepackingRLT(), packable))
not_changing = NotResidueSelector(shell)
tf.push_back(OperateOnResidueSubset(PreventRepackingRLT(), not_changing))
pt = tf.create_task_and_apply_taskoperations(pose)
prm = PackRotamersMover(sf, pt)
prm.apply(pp)
pp.dump_pdb('pdz_designs/design_models/pdz_' + des + '.pdb')
def main(args):
# Destination folder for PDB files
if args.out_dir:
dir_name = args.out_dir
if not isdir(dir_name):
makedirs(dir_name)
else:
dir_name = ""
# Creating coordinate constraints for the entire molecule
cg = CoordinateConstraintGenerator()
ac = AddConstraints()
ac.add_generator(cg)
# Create enzdes constraints
if args.constraints:
enz_cst = AddOrRemoveMatchCsts()
enz_cst.set_cst_action(ADD_NEW)
''' Declare the score function. '''
if args.symmetry: # Declare symmetric score functions
score_function = SymmetricScoreFunction()
if args.repulsive_type == 'hard':
if args.membrane:
score_function.add_weights_from_file('franklin2019')
else:
score_function.add_weights_from_file('ref2015')
elif args.repulsive_type == 'soft':
if args.membrane: # Set up a soft-rep version of franklin2019 manually
score_function.add_weights_from_file('ref2015_soft')
score_function.set_weight(ScoreType.fa_water_to_bilayer, 1.0)
else:
score_function.add_weights_from_file('ref2015_soft')
else: # Declare ordinary score functions
if args.repulsive_type == 'hard':
if args.membrane:
score_function = create_score_function('franklin2019')
else:
score_function = create_score_function('ref2015')
elif args.repulsive_type == 'soft':
if args.membrane: # Set up a soft-rep version of franklin2019 manually
score_function = create_score_function('ref2015_soft')
score_function.set_weight(ScoreType.fa_water_to_bilayer, 1.0)
else:
score_function = create_score_function('ref2015_soft')
if args.coord_wt:
score_function.set_weight(ScoreType.coordinate_constraint,
args.coord_wt)
if args.enzdes_wt:
score_function.set_weight(ScoreType.atom_pair_constraint,
args.enzdes_wt)
score_function.set_weight(ScoreType.angle_constraint, args.enzdes_wt)
score_function.set_weight(ScoreType.dihedral_constraint,
args.enzdes_wt)
# Loading PDB file
pose = pose_from_pdb(args.pdb_file)
if args.symmetry: # Applying symmetry if specified
sfsm = SetupForSymmetryMover(args.symmetry)
sfsm.apply(pose)
if args.membrane: # Set up membrane for membrane protein
add_memb = SymmetricAddMembraneMover(args.span_file)
add_memb.apply(pose)
else:
if args.membrane: # Set up membrane for membrane protein
add_memb = AddMembraneMover(args.span_file)
add_memb.apply(pose)
# Creating FastRelax protocol with the given score function
fr = FastRelax()
fr.set_scorefxn(score_function)
# Packer tasks
tf = standard_task_factory()
tf.push_back(IncludeCurrent())
tf.push_back(ExtraRotamers(0, 1, 1))
tf.push_back(ExtraRotamers(0, 2, 1))
protein_selector = ResiduePropertySelector(ResidueProperty.PROTEIN)
repack = RestrictToRepackingRLT()
tf.push_back(OperateOnResidueSubset(repack, protein_selector))
prevent = PreventRepackingRLT()
tf.push_back(OperateOnResidueSubset(prevent, protein_selector, True))
fr.set_task_factory(tf)
move_map = MoveMap()
if args.repulsive_type == 'hard':
move_map.set_bb(True)
elif args.repulsive_type == 'soft':
''' When using the soft-rep score function, backbone should be fixed. '''
move_map.set_bb(False)
protein_res_true_vector = protein_selector.apply(pose)
move_map.set_chi(protein_res_true_vector)
fr.set_movemap(move_map)
# Determining file name
if args.name:
file_name = args.name
else:
file_name = basename(args.pdb_file).replace('.pdb', '_relaxed')
out_name = join(dir_name, file_name)
# Applying constraints
ac.apply(pose)
if args.constraints:
enz_cst.apply(pose)
# RMSD metric
rmsdm = RMSDMetric()
rmsdm.set_comparison_pose(pose)
print(tf.create_task_and_apply_taskoperations(pose))
# Running relax set
jd = PyJobDistributor(out_name, args.n_decoys, score_function)
while not jd.job_complete:
pp = Pose()
pp.assign(pose)
fr.apply(pp)
rmsdm.apply(pp)
jd.output_decoy(pp)