DiffSBDD and DiffLinker

DiffSBDD
52
Established
DiffLinker
45
Emerging
Maintenance 2/25
Adoption 10/25
Maturity 16/25
Community 24/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 19/25
Stars: 488
Forks: 119
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stars: 371
Forks: 53
Downloads:
Commits (30d): 0
Language: Python
License: MIT
Stale 6m No Package No Dependents
Stale 6m No Package No Dependents

About DiffSBDD

arneschneuing/DiffSBDD

A Euclidean diffusion model for structure-based drug design.

This tool helps drug discovery scientists design new drug-like molecules that fit precisely into a protein's binding pocket. You provide a protein structure and optionally a reference ligand or specific residues, and it generates potential new small molecules as SDF files. Medicinal chemists, computational chemists, and researchers in drug design would use this for early-stage lead generation and optimization.

drug-discovery medicinal-chemistry molecular-design ligand-generation structure-based-design

About DiffLinker

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.

molecular-design drug-discovery medicinal-chemistry ligand-design materials-science

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