igashov/DiffLinker
DiffLinker: Equivariant 3D-Conditional Diffusion Model for Molecular Linker Design
This project helps medicinal chemists and drug discovery scientists design new molecules to connect existing molecular fragments. You provide the 3D structures of two or more disconnected molecular fragments (and optionally, a protein binding pocket), and the tool generates a new linker molecule that bridges them. This allows researchers to explore novel chemical structures for drug candidates and materials science applications.
371 stars. No commits in the last 6 months.
Use this if you need to computationally generate diverse and chemically valid linker molecules between multiple existing molecular fragments, especially when considering a specific protein binding environment.
Not ideal if you need to design entire molecules from scratch or if you are not working with 3D molecular structures as input.
Stars
371
Forks
53
Language
Python
License
MIT
Category
Last pushed
Apr 17, 2024
Commits (30d)
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