Extract the desired enzymatic data from Brenda using the brendapy parser. Here, we have chosen to store the datasets in json files.
- Complete writing the unit test functions for the RXN_CMP_file_creator.py file.
- Finish setting up the module for RXN_CMP from the args file of src2 and main from the terminal.
git clone https://github.com/brsynth/extractor_brendapy.git
cd extractor_brendapy
conda env create -f environment.yaml -n <name_env>
conda activate <name_env>
The following 3 arguments are optional.
list_parameter : list of parameters below
path_files : path to the folder containing data_brenda.txt and file result json.
list_ec : if this argument is not set, list of all known ec is generated
In the terminal
python -m extractor_brendapy --list_parameters [PARAM1 PARAM2 ...] --path_file_databrenda [PATH] --list_ec [PARAM1 PARAM2 ...]
List of possible parameters :
ec; uniprot; organism; ID; substrate; value; comment; units; refs; data; chebi; KM; KKM; KI; TN; IC50; ref; TS; SY; SU; ST; SP; SA; PU; NSP; MW; LO; GI; IN; CL; CF; AP; tissues; SN; RT; RN; RE
Please note: When you want the parameters 'KM', 'KKM', 'KI', 'TN', 'IC50', you must add substrate to the list of requested elements. Other elements that may be requested, by 5 parameters are : substrate, value, comment, units, refs, data, chebi.
For parameters: "ref", "TS", "SY", "SU", "ST", "SP", "SA", "PU", "NSP", "MW", "LO", "GI", "IN", "CL", "CF", "AP" add data. Other elements that may be requested, by the list of parameters above are : data, refs, comment.
python -m RXM_CMP --path_file --input_file --file_RXM --file_RXM --file_CMP --mail --mdp
--path_file :
--input_file : The initial JSON files, which include the reaction, substrates, products, their stoichiometric coefficients, and whether the reaction is reversible.
--file_RXM : A dictionary where the values are lists of molecules.
--file_CMP : A dictionary where each key maps to a list of molecules, and each molecule in the list is associated with its SMILES representation.
--mail: mail for brenda --mdp : password
- Nolwenn Paris
- Joan Hérisson