https://doi.org/10.57745/V3URYA
conda env create --file recipes/worklow.yaml --name chebirgroup
pip install --no-deps -e .python -m chebirgroup.pubchem.download \
--output-pubchem-dir <output dir> \
--output-pubchem-db <output sql database>python -m chebirgroup.rhea.download \
--output-rhea-dir <output dir> \
--parameter-release-int <int>snakemake \
-p \
-j 48 \
-c 48 \
--workflow-profile template/chebirgroup \
-s ./src/chebirgroup/rgroup/Snakefile \
--use-conda \
--latency-wait 5 \
--rerun-incomplete \
--config depot_dir=./src/chebirgroup/rgroup input_chebi_csv=rhea-chebi-smiles.csv input_pubchem_db=pubchem.db output_dir_str=chebiThe Snakemake workflow produces a csv.gz file containing:
| column name | type |
|---|---|
| smiles_rhea | str |
| chebi | List[str] |
| num_heavy_atoms | int |
| exact_mol_wt | int |
| additional_substituents_smiles | List[str] |
| additional_substituents_pubchem_cid | List[List[str]] |
| only_match_rgroup_smiles | List[str] |
| only_match_rgroup_pubchem_cid | List[List[str]] |