microsoft/molecule-generation
Implementation of MoLeR: a generative model of molecular graphs which supports scaffold-constrained generation
This tool helps chemists and material scientists design new molecules by generating novel chemical structures. You provide it with a collection of known molecular structures (SMILES strings), and it learns to create new ones, including those with specific desired scaffolds. The output is a list of new molecular structures that adhere to chemical rules and can be tailored for specific properties or substructures.
319 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to rapidly explore new chemical spaces for drug discovery, material science, or other applications by generating diverse molecular structures based on existing scaffolds.
Not ideal if you need to predict specific physical or biological properties of molecules without generating new structures.
Stars
319
Forks
45
Language
Python
License
MIT
Category
Last pushed
Jan 04, 2024
Commits (30d)
0
Dependencies
7
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