HUBioDataLab/DrugGEN
Official implementation of DrugGEN: Target Specific De Novo Design of Drug Candidate Molecules with Graph Transformer-based Generative Adversarial Networks
DrugGEN helps medicinal chemists and drug discovery researchers accelerate the identification of new drug candidates. By taking a specific protein target and a dataset of known active molecules, it generates novel molecular structures predicted to bind effectively to that target. This tool is for scientists working on the early stages of drug development who need to explore a vast chemical space for potential new therapeutics.
Use this if you need to computationally design new small molecules that are highly likely to interact with a specific protein target, reducing the time and cost of experimental screening.
Not ideal if you are looking for a tool to predict the efficacy or safety of existing molecules, or if you don't have a dataset of known bioactive molecules for your target.
Stars
92
Forks
21
Language
Python
License
GPL-3.0
Category
Last pushed
Oct 30, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/generative-ai/HUBioDataLab/DrugGEN"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
ppjian19/PhoreGen
PhoreGen: Pharmacophore-Oriented 3D Molecular Generation towards Efficient Feature-Customized...
benstaf/ChemGAN-challenge
Code for the paper: ChemGAN challenge for drug discovery: can AI reproduce natural chemical...
isayevlab/geom-drugs-3dgen-evaluation
A refined evaluation pipeline for 3D molecular generative models trained on GEOM-Drugs.
DLS5-Omics/GEMGen
A generative model for phenotypic-based drug discovery
MATZGLCH/BioSyn-AI-Repurposing-Life
🌱 Unlock new cancer and rare disease treatments through AI-driven drug repurposing and synthetic...