Skip to content

hnlab/oddt

 
 

Repository files navigation

Open Drug Discovery Toolkit

Open Drug Discovery Toolkit (ODDT) is modular and comprehensive toolkit for use in cheminformatics, molecular modeling etc. ODDT is written in Python, and make extensive use of Numpy/Scipy

Documentation Status Build Status Coverage Status Code Health Conda packages Latest Version

Documentation, Discussion and Contribution:

Requrements

  • Python 3.6+
  • OpenBabel (3.0+) or/and RDKit (2018.03+)
  • Numpy (1.12+)
  • Scipy (0.19+)
  • Sklearn (0.18+)
  • joblib (0.10+)
  • pandas (0.19.2+)
  • Skimage (0.12.3+) (optional, only for surface generation)

Install

Using PyPi (pip)

When all requirements are met, then installation process is simple

python setup.py install

You can also use pip. All requirements besides toolkits (OpenBabel, RDKit) are installed if necessary. Installing inside virtualenv is encouraged, but not necessary.

pip install oddt

To upgrade oddt using pip (without upgrading dependencies):

pip install -U --no-deps oddt

Using conda

Install a clean Miniconda environment, if you already don't have one.

Install ODDT:

conda install -c oddt oddt

You can add a toolkit of your choice or install them along with oddt:

conda install -c conda-forge oddt rdkit openbabel

(Optionally) Install OpenBabel (using official channel):

conda install -c conda-forge openbabel

(Optionally) install RDKit (using official channel):

conda install -c conda-forge rdkit

Upgrading procedure using conda is straightforward:

conda update -c oddt oddt

Documentation

Automatic documentation for ODDT is available on Readthedocs.org. Additionally it can be build localy:

cd docs

make html

make latexpdf

License

ODDT is released under permissive 3-clause BSD license

Reference

If you found Open Drug Discovery Toolkit useful for your research, please cite us!

  1. Wójcikowski, M., Zielenkiewicz, P., & Siedlecki, P. (2015). Open Drug Discovery Toolkit (ODDT): a new open-source player in the drug discovery field. Journal of Cheminformatics, 7(1), 26. doi:10.1186/s13321-015-0078-2

Analytics

Packages

No packages published

Languages

  • Python 99.9%
  • Shell 0.1%