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Getting Started

Prerequisites

  • Conda is the easiest way to install RDKit and the rest of the scientific stack.
  • Python 3.11 is the pinned runtime in environment.yml.
  • Internet access is only required for DeepPK submissions and package installation.

Create the environment

conda env create -f environment.yml
conda activate lig-cls

The environment file includes:

  • chemistry and modeling packages such as rdkit, scikit-learn, xgboost, lightgbm, imbalanced-learn, mordred, and umap-learn
  • tooling such as pytest, requests, tqdm, mkdocs, and mkdocs-material

First commands

Generate current-format example features from the checked-in raw example:

python -m src.cli.process_features data/example/raw/psychlight_a.csv \
    --output-dir data/example/processed/psychlight_a

Run a narrow training pass with the canonical default config:

python -m src.cli.train --config configs/train.yaml \
    --datasets psychlight_a_descriptors \
    --models logisticregression

The starter config expects:

  • data/example/processed/psychlight_a/psychlight_a_descriptors.csv
  • data/example/processed/psychlight_a/psychlight_a_mordred.csv
  • data/example/processed/psychlight_a/psychlight_a_morgan.csv

Optional DeepPK flow

DeepPK is a third-party web service. When you enable it, the processed SMILES are sent to a remote server rather than computed locally.

python -m src.cli.process_features data/example/raw/psychlight_a.csv \
    --output-dir data/example/processed/psychlight_a \
    --deeppk-post \
    --deeppk-pred-type admet \
    --deeppk-timeout 3600

Then train with the DPK-aware config:

python -m src.cli.train --config configs/train_example_dpk.yaml --models logisticregression

Verify the installation

Run the repository checks that matter for this project:

pytest -q
conda run -n lig-cls python -m src.cli.process_features --help
conda run -n lig-cls python -m src.cli.train --help
conda run -n lig-cls python -m src.cli.evaluate --help
conda run -n lig-cls python -m src.cli.predict --help
conda run -n lig-cls python -m src.cli.explore --help
mkdocs build --strict

If python -m src.cli.process_features --help fails outside the project environment, that usually means RDKit is missing from the active interpreter.