Rxn-INSIGHT is an open-source algorithm, written in python, to classify and name chemical reactions, and suggest reaction conditions based on similarity and popularity.
Rxn-INSIGHT relies on NumPy, Pandas, RDKit, RDChiral, and RXNMapper.
A virtual environment can be installed with Anaconda as follows:
conda env create -f environment.yml
conda activate rxn-insightTo add the rxn-insight environment to Jupyter Notebook:
python -m ipykernel install --user --name=rxn-insightfrom rxn_insight.reaction import Reaction
r = "c1ccccc1I.C=CC(=O)OC>>COC(=O)/C=C/c1ccccc1" # Define a Reaction SMILES identifier
rxn = Reaction(r)
ri = rxn.get_reaction_info()The reaction info contains most of the information:
{'REACTION': 'C=CC(=O)OC.Ic1ccccc1>>COC(=O)/C=C/c1ccccc1',
'MAPPED_REACTION': '[CH3:1][O:2][C:3](=[O:4])[CH:5]=[CH2:6].I[c:7]1[cH:8][cH:9][cH:10][cH:11][cH:12]1>>[CH3:1][O:2][C:3](=[O:4])/[CH:5]=[CH:6]/[c:7]1[cH:8][cH:9][cH:10][cH:11][cH:12]1',
'N_REACTANTS': 2,
'N_PRODUCTS': 1,
'FG_REACTANTS': ('Aromatic halide', 'Vinyl'),
'FG_PRODUCTS': (),
'PARTICIPATING_RINGS_REACTANTS': ('c1ccccc1',),
'PARTICIPATING_RINGS_PRODUCTS': ('c1ccccc1',),
'ALL_RINGS_PRODUCTS': ('c1ccccc1',),
'BY-PRODUCTS': ('HI',),
'CLASS': 'C-C Coupling',
'TAG': '55becfded1a3842d5a03bbf3e1610411c659aff0806930400c4db2ef61f9c87f',
'SOLVENT': ('',),
'REAGENT': ('',),
'CATALYST': ('',),
'REF': '',
'NAME': 'Heck terminal vinyl',
'SCAFFOLD': 'c1ccccc1'}A similarity search can be performed when a database with similar reactions is provided as a pandas DataFrame (df in this case). Another Pandas DataFrame is returned.
df_nbs = rxn.find_neighbors(df, fp="MACCS", concatenate=True, threshold=0.5, broaden=True, full_search=False)Reaction conditions can be suggested when a Pandas DataFrame is provided.
rxn.suggest_conditions(df)
suggested_solvents = rxn.suggested_solvent
suggested_catalysts = rxn.suggested_catalyst
suggested_reagents = rxn.suggested_reagentThe complete USPTO dataset that is analyzed by Rxn-INSIGHT,
as described in the manuscript, can be found on
Zenodo: https://doi.org/10.5281/zenodo.10171745.
The gzip file should be downloaded and placed in the folder data/.
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