HySonLab/Ligand_Generation
Target-aware Variational Auto-encoders for Ligand Generation with Multimodal Protein Representation Learning
This project helps drug discovery scientists accelerate the early stages of drug development by generating potential drug-like molecules (ligands) for specific protein targets. You provide a protein's 3D structure, and it suggests novel ligands with high binding affinity and synthesizability. This is intended for medicinal chemists, pharmacologists, and researchers in drug design looking for new molecular candidates.
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Use this if you need to quickly identify potential drug candidates (ligands) that are likely to bind to a specific protein target, reducing the need for extensive experimental screening.
Not ideal if you require a method that focuses solely on optimizing existing ligands rather than generating completely new molecular structures.
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32
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5
Language
Python
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Last pushed
May 17, 2024
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