def __new__(cls, molecule, *args, **kwargs):
if cls.__bb__ is None:
from .rules import rules
bb = [smiles(x.strip()) for x in TextIOWrapper(resource_stream(__name__, 'data/building_blocks.smiles'))]
for b in bb: # recalculate canonic forms. prevent errors when CGRtools rules set changes.
b.canonicalize()
cls.__bb__ = frozenset(str(b) for b in bb)
cls.__reactors__ = tuple((1., Reactor(x, delete_atoms=True, automorphism_filter=False, one_shot=False))
for x in rules)
return super().__new__(cls, *args, **kwargs)
def convert(dct):
out = {}
for k, (tuples, value) in dct.items():
k = smiles(k)
k.canonicalize()
new_mols = []
for prob, mols in tuples:
synth = []
for mol in mols:
new_mol = smiles(mol)
new_mol.canonicalize()
synth.append(new_mol)
rxn = ReactionContainer((k,), synth)
ext_center = set(rxn.extended_centers_list[0])
qk = k.substructure(ext_center.intersection(k), as_query=True)
qsynth = [m.substructure(ext_center.intersection(m), as_query=True) for m in synth]
template = ReactionContainer((qk,), qsynth)
new_mols.append((prob, Reactor(template), set(synth)))
out[k] = (tuple(new_mols), value)
return out
def __new__(cls, molecule, *args, **kwargs):
if cls.__bb__ is None:
with resource_stream(__name__, 'data/rules.pkl') as f:
rules = load(f)
cls.__reactors__ = [Reactor(x, delete_atoms=True) for x in rules]
cls.__bb__ = frozenset(
str(m) for m in SMILESRead(
TextIOWrapper(resource_stream(__name__, 'data/bb.smi'))))
cls.__fragmentor__ = LinearFingerprint(length=4096,
min_radius=2,
max_radius=4,
number_bit_pairs=4)
if cls.__filter__ is None:
cls.__filter__ = FilterNet().load_from_checkpoint(
cls.__filter_path__)
cls.__filter__.eval()
cls.__sorter__ = SorterNet(
(8000, )).load_from_checkpoint(cls.__sorter_path__,
hid=(8000, ))
cls.__sorter__.eval()
return super().__new__(cls, molecule, *args, **kwargs)
def add_reagent(self, action):
print('self STATE', self.state)
action = self.map[action]
if action == 'next':
if self.reactions_list:
if len(self.reactions_list) == 1:
reaction = self.reactions_list[0]
state = reaction.products[0]
reward = reaction.meta['tanimoto']
if self.path:
self.path[
-1] = reaction # заменяем последнюю реакцию в пути
else:
self.path.append(reaction)
self.reactions_list = self.saved_reactions
return state, reward, {
'info': 'the last molecule at the list'
}
else:
reaction = self.reactions_list.pop(0)
state = reaction.products[0]
reward = reaction.meta['tanimoto']
if self.path:
self.path[
-1] = reaction # заменяем последнюю реакцию в пути
else:
self.path.append(reaction)
return state, reward, {}
else:
if self.state is None:
return None, -1, {'info': 'no reaction products found'}
else:
reward = evaluation(self.state, self.target)
return self.state, reward, {
'info': 'no another reaction products at the list'
}
if action == 'none': # однореагентная реакция
if self.state is None:
return None, -1, {'info': 'no current molecule'}
else:
reactions_list = []
groups_list = group_list(self.state, self.db)
rules = reactions_by_fg(groups_list)
for rule in rules:
reactor = Reactor(rule, delete_atoms=True)
reaction = next(reactor([self.state]), None)
if reaction:
# for new_mol in reactions[0].products:
# print('!self.state, new_mol!', self.state, new_mol)
reactions_list.append((reaction, rule))
else:
reactions_list = []
with db_session:
reagent = self.db.Molecule[action].structure
if self.state:
# print('if self.state')
groups_list = group_list(self.state, self.db)
rules = reactions_by_fg(groups_list, single=False)
# print('RULES', rules)
for rule in rules:
reactor = Reactor(rule, delete_atoms=True)
reaction = next(reactor([self.state, reagent]), None)
# print('REACTIONS', reactions)
if reaction:
# for new_mol in reactions[0].products:
# print('!(2) self.state, new_mol!', self.state, new_mol)
reactions_list.append((reaction, rule))
else:
self.state = reagent
# print('reagent', reagent)
# print('LOGPPPPPPPPPP', logp(reagent))
reward = evaluation(self.state, self.target)
return self.state, reward, {
'info': 'the first molecule in the path'
}
# groups_list = group_list(reagent, self.db)
# rules = reactions_by_fg(groups_list)
# # print('RULES', rules)
# for rule in rules:
# reactor = Reactor(rule, delete_atoms=True)
# reaction = next(reactor([reagent]), None)
# # print('REACTIONS', reactions)
# if reaction:
# # for new_mol in reactions[0].products:
# # print('!(1) new_mol!', new_mol)
# reactions_list.append((reaction, rule))
if reactions_list:
reactions_list = list(set(reactions_list))
react_list = []
for i in reactions_list:
product = max(i[0].products,
key=lambda x: len(list(x.atoms())))
meta = {
'tanimoto': evaluation(product, self.target),
'rule': i[1]
}
new_reaction = ReactionContainer(reactants=i[0].reactants,
products=[product],
meta=meta)
react_list.append(new_reaction)
# print('REACT LIST1', len(reactions_list), reactions_list)
reactions_list = best_n_molecules(react_list, 10)
print('REACT LIST 10 best', (len(reactions_list)), reactions_list)
self.saved_reactions = reactions_list
if len(reactions_list) > 1:
reaction = reactions_list.pop(0)
state = reaction.products[0]
reward = reaction.meta['tanimoto']
self.path.append(reaction)
self.reactions_list = reactions_list
return state, reward, {}
else:
reaction = reactions_list[0]
state = reaction.products[0]
reward = reaction.meta['tanimoto']
self.path.append(reaction)
self.reactions_list = reactions_list
return state, reward, {'info': 'the last molecule at the list'}
else:
reward = evaluation(self.state, self.target)
return self.state, reward, {
'info': 'no new reaction products at the list'
}