/tools/Drug_Design_Models

Drug_Design_Models

EdoardoGruppi/Drug_Design_Models

21 stars7 forksJupyter NotebookAdded February 8, 2026
summary

Drug_Design_Models is a reimplementation of various models for de novo drug design, utilizing techniques such as recurrent neural networks and graph convolutional networks. It aims to generate and optimize molecular structures based on established research in the field.

description

This project is a reimplementation of the models introduced in the following papers: "Multiobjective de novo drug design with recurrent neural networks and nondominated sorting", "REINVENT 2.0: An AI Tool for De Novo Drug Design", "Hierarchical generation of molecular graphs using structural motifs", "Mol-CycleGAN: a generative model for molecular optimization", "Multi-objective de novo drug design with conditional graph generative model" and "Graph convolutional policy network for goal-directed molecular graph generation".

topics

drug-designdrug-discoverygraph-neural-networksreinforcement-learning

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