This code is part of the publication "Data-driven discovery of cardiolipin-selective small molecules by computational active learning", https://doi.org/10.1039/D2SC00116K. AutoFE is an automated workflow designed to calculate solvation free energies of small molecules in two compared environments. It includes an early-exit strategy if a small-molecule candidate does not show target properties. The components handling the simulation setup can be run in sequence or independently.
Clone the repository and install dependencies:
git clone https://github.com/Bernadette-Mohr/AutoFE.git
cd AutoFE
pip install -r requirements.txt- Python >= 3.8
- pandas
- scikit-learn
- numpy
(See requirements.txt for full dependency list.)
Contributions are welcome! Please see CONTRIBUTING.md for details.
This project is licensed under the MIT License. See the LICENSE file for details.
For questions, issues, or feature requests, please open an issue or contact Bernadette-Mohr.