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# REINVENT
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Molecular De Novo design using Recurrent Neural Networks and Reinforcement Learning
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=============
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Source code for the method described in:
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[Molecular De Novo Design through Deep Reinforcement Learning](https://arxiv.org/abs/1704.07555)
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## Requirements
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This package requires:
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* Python 2.7
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* Tensorflow 1.0
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* [RDkit](http://www.rdkit.org/docs/Install.html)
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* Scikit-Learn (for QSAR scoring function)
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## Usage
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To use with a custom SMILES file:
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* Create MolData and Vocabulary instances using "python data_structs.py [location of SMILES file]"
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* Run the model.py pretrain_rnn method pointing to the MolData and Vocabulary files created
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* The Prior will be saved in the folder specified.
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* Run the model.py train_agent method to train agent, and the model.py sample method (after, or both before and after for comparison) to generate samples
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The datasets and pretrained Priors used in the paper can be found under "Releases"
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## To Do
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* Make a package
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* Add argparser to facilitate usage
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Any further comments/suggestions/criticism/questions are welcome!
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For contact outside of GitHub: [email protected]

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