As virtual libraries get ever larger the challenges of virtual screening get larger. Whilst docking into a target protein is a very popular and successful screening tool it is a computationally intensive task.
there is a need for automated tools capable of efficiently docking a large number of molecules using multiple computational nodes within a reasonable timeframe.
EasyDock https://doi.org/10.1186/s13321-023-00772-2 incorporates an automated docking protocol that supports distributed computing and provides a Python interface that can be used with a variety of docking tools (Autodock Vina, smina, and gnina) and could be expanded to other tools. It is built using the cheminformatics toolkit RDKit and the parallel processing tool dask.
EasyDock Availability and requirements
Project home page: e.g. https://github.com/ci-lab-cz/easydock.
Operating system(s): Platform independent.
Programming language: Python 3.
Other requirements: RDKit, vina, gnina, dask.
License: BSD 3-clause.
Any restrictions to use by non-academics: no limitation.