def explore_network(self):
processed = set()
for node_id in self.net.network.nodes():
name = gtostr(self.net.network.nodes[node_id]['struct'])
name = ''.join(sorted(name))
if node_id < self.net.num_monomers:
self.net.network.nodes[node_id]['first'] = True
else:
self.net.network.nodes[node_id]['first'] = False
for predecessors in self.net.get_reactant_sets(node_id):
if name not in processed:
# this pattern has not yet been processed.
r_score, pr_score = self.score_reaction(predecessors)
self.net.network.nodes[node_id][
'first'] = True # attribute to tell whether score is inherited from previous node with this pattern
processed.add(name)
else:
# we will write the score to every node, and tell whether is energetically meaningful with "first" attribute.
r_score = pr_score = self.written[name][1]
self.net.network.nodes[node_id][
'score'] = pr_score # add score attribute
for n in predecessors:
self.net.network.edges[(
n, node_id)]['rxn_score'] = pr_score - r_score
self.net.is_energy_set = True
def score_reaction(self, reactant_ids: Union[list, set]):
names = [
''.join(sorted(gtostr(self.net.network.nodes[rid]['struct'])))
for rid in reactant_ids
]
prebound_score = sum([self.written[n][1] for n in names])
new_pdb_str = ''
for name in names:
reactant_file = os.path.join(self.sub_dir, name + '.clean.pdb')
with open(reactant_file, 'r') as f:
new_pdb_str += f.read()
new_pdb_name = ''.join(sorted(names))
new_pdb_path = os.path.join(self.sub_dir, new_pdb_name + '.clean.pdb')
with open(new_pdb_path, 'w') as f:
f.write(new_pdb_str)
new_pose, bound_score = self._pose_from_pdb(new_pdb_path)
self.written[new_pdb_name] = (new_pose, bound_score)
return bound_score, prebound_score
def __init__(self, net: ReactionNetwork, subunit_dir: str):
rosetta_init()
self.net = net
self.monomer_pdb = [
os.path.join(subunit_dir, subunit)
for subunit in os.listdir(os.path.join(subunit_dir, 'monomers'))
]
self.sub_dir = subunit_dir
self.written = dict()
self.scorefxn = get_fa_scorefxn # note this score function is only guaranteed consistent in this instance!
self._preprocess()
for file in os.listdir(subunit_dir):
if ".clean.pdb" in file:
m_pose = os.path.join(subunit_dir, file)
self.written[strip_pdb_ext(file)] = self._pose_from_pdb(m_pose)
for i in range(self.net.num_monomers):
self.net.network.nodes[i]['score'] = self.written[gtostr(
self.net.network.nodes[i]['struct'])][1]
def __init__(self, net: ReactionNetwork, subunit_dir: str):
rosetta_init()
self.net = net
self.monomer_pdb = [
os.path.abspath(os.path.join(subunit_dir, 'monomers', subunit))
for subunit in os.listdir(os.path.join(subunit_dir, 'monomers'))
]
self.sub_dir = os.path.abspath(subunit_dir)
self.written = dict()
self.scorefxn = get_fa_scorefxn(
) # note this score function is only guaranteed consistent in this instance!
self.relaxer = relax.FastRelax()
self.relaxer.set_scorefxn(self.scorefxn)
self.relaxer.max_iter(200)
self._preprocess()
self._load_existing()
subunit_files = set([
os.path.join(self.sub_dir, file)
if '.clean' in file and '.relaxed' not in file else ''
for file in os.listdir(subunit_dir)
])
subunit_files.remove('')
subunit_files = list(subunit_files)
try:
with Pool(len(subunit_files)) as p:
results = p.map(self._pose_from_pdb, subunit_files)
except Exception:
print(
"Lacking serializable rosetta build. Parallel processing disabled. "
"Recommend compiling from source with --serialization flag \n "
"Continuing to process sequentially", sys.stderr)
results = [self._pose_from_pdb(sunit) for sunit in subunit_files]
for i, res in enumerate(results):
self.written[strip_pdb_ext(os.path.split(
subunit_files[i])[1])] = res
for i in range(self.net.num_monomers):
self.net.network.nodes[i]['score'] = self.written[gtostr(
self.net.network.nodes[i]['struct'])][1]