Python Chem.MolToSmiles方法代碼示例

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def __getitem__(self, idx):
        mol = Chem.MolFromSmiles(self.batches[idx])
        leaves = get_leaves(mol)
        smiles_list = set( [Chem.MolToSmiles(mol, rootedAtAtom=i, isomericSmiles=False) for i in leaves] )
        smiles_list = sorted(list(smiles_list)) #To ensure reproducibility

        safe_list = []
        for s in smiles_list:
            hmol = MolGraph(s)
            ok = True
            for node,attr in hmol.mol_tree.nodes(data=True):
                if attr['label'] not in self.vocab.vmap:
                    ok = False
            if ok: safe_list.append(s)
        
        if len(safe_list) > 0:
            return MolGraph.tensorize(safe_list, self.vocab, self.avocab)
        else:
            return None 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def get_inter_label(mol, atoms, inter_atoms):
    new_mol = get_clique_mol(mol, atoms)
    if new_mol.GetNumBonds() == 0: 
        inter_atom = list(inter_atoms)[0]
        for a in new_mol.GetAtoms():
            a.SetAtomMapNum(0)
        return new_mol, [ (inter_atom, Chem.MolToSmiles(new_mol)) ]

    inter_label = []
    for a in new_mol.GetAtoms():
        idx = idxfunc(a)
        if idx in inter_atoms and is_anchor(a, inter_atoms):
            inter_label.append( (idx, get_anchor_smiles(new_mol, idx)) )

    for a in new_mol.GetAtoms():
        a.SetAtomMapNum( 1 if idxfunc(a) in inter_atoms else 0 )
    return new_mol, inter_label 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def align(xy_tuple):
    x,y = xy_tuple
    xmol, ymol = Chem.MolFromSmiles(x), Chem.MolFromSmiles(y)
    x = Chem.MolToSmiles(xmol, isomericSmiles=False)
    xmol = Chem.MolFromSmiles(x)

    xleaf = get_leaves(xmol)
    yleaf = get_leaves(ymol)

    best_i,best_j = 0,0
    best = 1000000
    for i in xleaf:
        for j in yleaf:
            new_x = Chem.MolToSmiles(xmol, rootedAtAtom=i, isomericSmiles=False)
            new_y = Chem.MolToSmiles(ymol, rootedAtAtom=j, isomericSmiles=False)
            le = min(len(new_x), len(new_y)) // 2
            dist = Levenshtein.distance(new_x[:le], new_y[:le])
            if dist < best:
                best_i, best_j = i, j
                best = dist

    return Chem.MolToSmiles(xmol, rootedAtAtom=best_i, isomericSmiles=False), Chem.MolToSmiles(ymol, rootedAtAtom=best_j, isomericSmiles=False) 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def _featurize(self, mol):
    """Featurizes a SMILES sequence."""
    from rdkit import Chem
    smile = Chem.MolToSmiles(mol)
    if len(smile) > self.max_len:
      return list()

    smile_list = list(smile)
    # Extend shorter strings with padding
    if len(smile) < self.max_len:
      smile_list.extend([PAD_TOKEN] * (self.max_len - len(smile)))

    # Padding before and after
    smile_list += [PAD_TOKEN] * self.pad_len
    smile_list = [PAD_TOKEN] * self.pad_len + smile_list

    smile_seq = self.to_seq(smile_list)
    return smile_seq 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def featurize(self, mols, verbose=True, log_every_n=1000):
    """
    Parameters
    ----------
    mols: obj
      List of rdkit Molecule Objects
    verbose: bool
      How much logging
    log_every_n:
      How often to log
    Returns

    -------
    obj
      numpy array of features
    """
    from rdkit import Chem
    smiles = [Chem.MolToSmiles(mol) for mol in mols]
    if self.charset is None:
      self.charset = self._create_charset(smiles)
    return np.array([self.one_hot_encoded(smile) for smile in smiles]) 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def compute_all_ecfp(mol, indices=None, degree=2):
  """Obtain molecular fragment for all atoms emanating outward to given degree.
  For each fragment, compute SMILES string (for now) and hash to an int.
  Return a dictionary mapping atom index to hashed SMILES.
  """

  ecfp_dict = {}
  from rdkit import Chem
  for i in range(mol.GetNumAtoms()):
    if indices is not None and i not in indices:
      continue
    env = Chem.FindAtomEnvironmentOfRadiusN(mol, degree, i, useHs=True)
    submol = Chem.PathToSubmol(mol, env)
    smile = Chem.MolToSmiles(submol)
    ecfp_dict[i] = "%s,%s" % (mol.GetAtoms()[i].GetAtomicNum(), smile)

  return ecfp_dict 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def score_candidates(reactants, candidate_list, xs):

	pred = model.predict(xs, batch_size = 20)[0]
	rank = ss.rankdata(pred)

	fname = raw_input('Enter file name to save to: ') + '.dat'
	with open(os.path.join(FROOT, fname), 'w') as fid:
		fid.write('FOR REACTANTS {}\n'.format(Chem.MolToSmiles(reactants)))
		fid.write('Candidate product\tCandidate edit\tProbability\tRank\n')
		for (c, candidate) in enumerate(candidate_list):
			candidate_smile = candidate[0]
			candidate_edit = candidate[1]
			fid.write('{}\t{}\t{}\t{}\n'.format(
				candidate_smile, candidate_edit, pred[c], 1 + len(pred) - rank[c]
			))
	print('Wrote to file {}'.format(os.path.join(FROOT, fname))) 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def decode_stereo(smiles2D):
    mol = Chem.MolFromSmiles(smiles2D)
    dec_isomers = list(EnumerateStereoisomers(mol))

    dec_isomers = [Chem.MolFromSmiles(Chem.MolToSmiles(mol, isomericSmiles=True)) for mol in dec_isomers]
    smiles3D = [Chem.MolToSmiles(mol, isomericSmiles=True) for mol in dec_isomers]

    chiralN = [atom.GetIdx() for atom in dec_isomers[0].GetAtoms()
               if int(atom.GetChiralTag()) > 0 and atom.GetSymbol() == "N"]
    if len(chiralN) > 0:
        for mol in dec_isomers:
            for idx in chiralN:
                mol.GetAtomWithIdx(idx).SetChiralTag(Chem.rdchem.ChiralType.CHI_UNSPECIFIED)
            smiles3D.append(Chem.MolToSmiles(mol, isomericSmiles=True))

    return smiles3D 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def load_sdf_files(input_files, clean_mols):
  """Load SDF file into dataframe."""
  dataframes = []
  for input_file in input_files:
    # Tasks are stored in .sdf.csv file
    raw_df = next(load_csv_files([input_file + ".csv"], shard_size=None))
    # Structures are stored in .sdf file
    print("Reading structures from %s." % input_file)
    suppl = Chem.SDMolSupplier(str(input_file), clean_mols, False, False)
    df_rows = []
    for ind, mol in enumerate(suppl):
      if mol is not None:
        smiles = Chem.MolToSmiles(mol)
        df_rows.append([ind, smiles, mol])
    mol_df = pd.DataFrame(df_rows, columns=('mol_id', 'smiles', 'mol'))
    dataframes.append(pd.concat([mol_df, raw_df], axis=1, join='inner'))
  return dataframes 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def decode_test():
        wrong = 0
        for tot,s in enumerate(sys.stdin):
            s = s.split()[0]
            tree = MolTree(s)
            tree.recover()

            cur_mol = copy_edit_mol(tree.nodes[0].mol)
            global_amap = [{}] + [{} for node in tree.nodes]
            global_amap[1] = {atom.GetIdx():atom.GetIdx() for atom in cur_mol.GetAtoms()}

            dfs_assemble(cur_mol, global_amap, [], tree.nodes[0], None)

            cur_mol = cur_mol.GetMol()
            cur_mol = Chem.MolFromSmiles(Chem.MolToSmiles(cur_mol))
            set_atommap(cur_mol)
            dec_smiles = Chem.MolToSmiles(cur_mol)

            gold_smiles = Chem.MolToSmiles(Chem.MolFromSmiles(s))
            if gold_smiles != dec_smiles:
                print gold_smiles, dec_smiles
                wrong += 1
            print wrong, tot + 1 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def randomize_smiles(mol, random_type="restricted"):
    """
    Returns a random SMILES given a SMILES of a molecule.
    :param mol: A Mol object
    :param random_type: The type (unrestricted, restricted) of randomization performed.
    :return : A random SMILES string of the same molecule or None if the molecule is invalid.
    """
    if not mol:
        return None

    if random_type == "unrestricted":
        return rkc.MolToSmiles(mol, canonical=False, doRandom=True, isomericSmiles=False)
    if random_type == "restricted":
        new_atom_order = list(range(mol.GetNumAtoms()))
        random.shuffle(new_atom_order)
        random_mol = rkc.RenumberAtoms(mol, newOrder=new_atom_order)
        return rkc.MolToSmiles(random_mol, canonical=False, isomericSmiles=False)
    raise ValueError("Type '{}' is not valid".format(random_type)) 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def get_rxn_smiles(prod, reactants):
    prod_smi = Chem.MolToSmiles(prod, True)

    # Get rid of reactants when they don't contribute to this prod
    prod_maps = set(re.findall('\:([[0-9]+)\]', prod_smi))
    reactants_smi_list = []
    for mol in reactants:
        if mol is None:
            continue
        used = False
        for a in mol.GetAtoms():
            if a.HasProp('molAtomMapNumber'):
                if a.GetProp('molAtomMapNumber') in prod_maps:
                    used = True 
                else:
                    a.ClearProp('molAtomMapNumber')
        if used:
            reactants_smi_list.append(Chem.MolToSmiles(mol, True))

    reactants_smi = '.'.join(reactants_smi_list)
    return '{}>>{}'.format(reactants_smi, prod_smi) 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def next_state(self):
        smiles = self.smiles
        # TODO: this seems dodgy...
        for i in range(100):
            mol = add_atom(self.mol, self.stats)
            smiles = Chem.MolToSmiles(mol)
            if smiles != self.smiles:
                break

        next_state = State(scoring_function=self.scoring_function,
                           mol=mol,
                           smiles=smiles,
                           max_atoms=self.turn - 1,
                           max_children=self.max_children,
                           stats=self.stats,
                           seed=self.seed)
        return next_state 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def _apply_transform(self, mol, rule):
        """Repeatedly apply normalization transform to molecule until no changes occur.

        It is possible for multiple products to be produced when a rule is applied. The rule is applied repeatedly to
        each of the products, until no further changes occur or after 20 attempts. If there are multiple unique products
        after the final application, the first product (sorted alphabetically by SMILES) is chosen.
        """
        mols = [mol]
        for n in six.moves.range(20):
            products = {}
            for mol in mols:
                for product in [x[0] for x in rule.RunReactants((mol,))]:
                    if Chem.SanitizeMol(product, catchErrors=True) == 0:
                        products[Chem.MolToSmiles(product, isomericSmiles=True)] = product
            if products:
                mols = [products[s] for s in sorted(products)]
            else:
                # If n == 0, the rule was not applicable and we return None
                return mols[0] if n > 0 else None 

# 需要導入模塊: from rdkit import Chem [as 別名]
# 或者: from rdkit.Chem import MolToSmiles [as 別名]
def load_fragments(fragments):
        fragments = [Chem.MolToSmiles(Chem.MolFromSmiles(x)) for x in fragments]
        MolGraph.FRAGMENTS = set(fragments)