Open reaction database

rxnutils contain two pipelines that together imports and prepares the reaction data from the Open reaction database so that it can be used on modelling.

It is a complete end-to-end pipeline that is designed to be transparent and reproducible.

Pre-requisites

The reason the pipeline is divided into two blocks is because the dependencies of the atom-mapper package (rxnmapper) is incompatible with the dependencies rxnutils package. Therefore, to be able to use to full pipeline, you need to setup two python environment.

  1. Install rxnutils according to the instructions in the README-file

  2. Install the ord-schema package in the `` rxnutils`` environment

    conda activate rxn-env python -m pip install ord-schema

  3. Download/Clone the ord-data repository according to the instructions here: https://github.com/Open-Reaction-Database/ord-data

Note down the path to the repository as this needs to be given to the preparation pipeline

  1. Install rxnmapper according to the instructions in the repo: https://github.com/rxn4chemistry/rxnmapper

conda create -n rxnmapper python=3.6 -y
conda activate rxnmapper
conda install -c rdkit rdkit=2020.03.3.0
python -m pip install rxnmapper

  1. Install Metaflow and rxnutils in the new environment

python -m pip install metaflow
python -m pip install --no-deps --ignore-requires-python .

Usage

Create a folder for the ORD data and in that folder execute this command in the rxnutils environment

conda activate rxn-env
python -m rxnutils.data.ord.preparation_pipeline run --nbatches 200  --max-workers 8 --max-num-splits 200 --ord-data ORD_DATA_REPO_PATH

and then in the environment with the rxnmapper run

conda activate rxnmapper
python -m rxnutils.data.mapping_pipeline run --data-prefix ord --nbatches 200  --max-workers 8 --max-num-splits 200

The -max-workers flag should be set to the number of CPUs available.

On 8 CPUs and 1 GPU the pipeline takes a couple of hours.

Artifacts

The pipelines creates a number of tab-separated CSV files:

  • ord_data.csv is the imported ORD data

  • ord_data_cleaned.csv is the cleaned and filter data

  • ord_data_mapped.csv is the atom-mapped, modelling-ready data

The cleaning is done to be able to atom-map the reactions and are performing the following tasks:

  • Ignore extended SMILES information in the SMILES strings

  • Remove molecules not sanitizable by RDKit

  • Remove reactions without any reactants or products

  • Move all reagents to reactants

  • Remove the existing atom-mapping

  • Remove reactions with more than 200 atoms when summing reactants and products

(the last is a requisite for rxnmapper that was trained on a maximum token size roughly corresponding to 200 atoms)

The ord_data_mapped.csv files will have the following columns:

  • ID - unique ID from the original database

  • Dataset - the name of the dataset from which this is reaction is taken

  • Date - the date of the experiment as given in the database

  • ReactionSmiles - the original reaction SMILES

  • Yield - the yield of the first product of the first outcome, if provided

  • ReactionSmilesClean - the reaction SMILES after cleaning

  • BadMolecules - molecules not sanitizable by RDKit

  • ReactantSize - number of atoms in reactants

  • ProductSize - number of atoms in products

  • mapped_rxn - the mapped reaction SMILES

  • confidence - the confidence of the mapping as provided by rxnmapper