semvec/pypi-packages huggingface dataset:
mrl-lib 0.0.1
Molecular reinforcement learning
License: MIT License
Requires Python: >=3.7
Keywords: machine learning,cheminformatics

# Molecular Reinforcement Learning
> Unlocking reinforcement learning for drug design


MRL is an open source python library designed to unlock the potential of drug design with reinforcement learning. 

MRL bridges the gap between generative models and practical drug discovery by enabling fine-tuned control over chemical spaces. Control what structures are generated and where they occur.

MRL is suitable for all stages of drug discovery, from high diversity hit expansion screens to hyper-focused lead optimization

<img src="nbs/files/mols.png" width="800" alt="rgroup optimization" style="max-width: 800px">

## Use Cases

MRL can be applied to:
- Small molecule design
- Peptide design

View our [tutorials](https://darkmatterai.github.io/mrl/tutorials.html) for more examples

## Install

Package coming soon

## How to use

## Contributing

## Acknowledgements
mrl-lib-pypi 0.0.1
Molecular reinforcement learning
License: MIT License
Requires Python: >=3.7
Keywords: machine learning,cheminformatics

# Molecular Reinforcement Learning
> Unlocking reinforcement learning for drug design


MRL is an open source python library designed to unlock the potential of drug design with reinforcement learning. 

MRL bridges the gap between generative models and practical drug discovery by enabling fine-tuned control over chemical spaces. Control what structures are generated and where they occur.

MRL is suitable for all stages of drug discovery, from high diversity hit expansion screens to hyper-focused lead optimization

<img src="nbs/files/mols.png" width="800" alt="rgroup optimization" style="max-width: 800px">

## Use Cases

MRL can be applied to:
- Small molecule design
- Peptide design

View our [tutorials](https://darkmatterai.github.io/mrl/tutorials.html) for more examples

## Install

Package coming soon

## How to use

## Contributing

## Acknowledgements