End-to-end application for predicting binding affinity of small molecules to protein targets with deep learning.
This package requires Python 3.10 or later. Please verify your Python version by running python --version in your terminal. If you're not running Python 3.10+, please adjust your environment accordingly (for example, if you use pyenv: pyenv local 3.10 or any later version like pyenv local 3.11).
Note
To install pyenv, follow the instructions here, then run eval "$(pyenv init -)".
Dependencies are managed in pyproject.toml. To install the dependencies, run the following commands, based on your Operating System:
POSIX Systems (MacOS/Linux):
python --version # Ensure this outputs Python 3.10 or later
python -m venv .venv
source .venv/bin/activate
pip install -U pip
pip install -e '.[dev]' # Install in editable modeWindows Systems:
python --version # Ensure this outputs Python 3.10 or later
python -m venv .venv
.venv\Scripts\activate
pip install -U pip
pip install -e '.[dev]' # Install in editable modeOnce installed, you can use the package with:
import adjacentmol as amNote
If using VSCode, make sure to set the interpreter to the .venv environment using Cmd + Shift + P -> Python: Select Interpreter.
Before submitting changes, please run pre-commit hooks to ensure that the code is formatted correctly. To do so, run the following command:
pre-commit run --aThe linter should run without any errors and autofix any issues that it can. If there are any issues that the linter cannot fix, please fix them manually before committing your changes.
Please ensure that all tests pass before submitting your changes. To run the tests, run the following command:
pytestOnce all tests pass, you may submit your changes.
We welcome contributions to this package! If you have any ideas for new features, bug fixes, or improvements, please feel free to open an issue or a pull request. We appreciate your help in making this package better!
This package is licensed under the MIT License. See the LICENSE file for more details.