REINVENT is a molecular design tool for de novo design, scaffold hopping, R-group replacement, linker design, molecule optimization, and other small molecule design tasks. At its heart, REINVENT uses a Reinforcement Learning (RL) algorithm to generate optimized molecules compliant with a user defined property profile defined as a multi-component score.

REINVENT is being developed on and for Linux but is also known to work on MacOSX. The code is written in Python 3 (>= 3.10). The list of dependencies can be found in the repository (see also Installation below). A GPU is not strictly necessary but it is stronlgy recommended to run on GPU for performance reasons. Note that if no GPU is installed in your computer the code attempts to run on the CPU only.

All code is available on GitHub

Apache License Version 2.0,

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