pengxingang/MolDiff
MolDiff: Addressing the Atom-Bond Inconsistency Problem in 3D Molecule Diffusion Generation
MolDiff helps drug discovery scientists quickly generate novel 3D molecular structures. You provide parameters for the desired molecular properties, and it outputs a diverse set of drug-like molecules in standard SDF file format. This tool is for medicinal chemists or computational biologists looking to explore new chemical spaces efficiently.
No commits in the last 6 months.
Use this if you need to generate realistic, novel 3D drug-like molecules with high fidelity between atoms and bonds for drug discovery or materials science applications.
Not ideal if your primary goal is virtual screening of existing molecule libraries or if you need to predict molecular properties without generating new structures.
Stars
89
Forks
14
Language
Python
License
MIT
Category
Last pushed
Jul 23, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/pengxingang/MolDiff"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
MinkaiXu/GeoDiff
Implementation of GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation (ICLR 2022).
MinkaiXu/GeoLDM
Geometric Latent Diffusion Models for 3D Molecule Generation
caio-freitas/GraphARM
An implementation of the Autoregressive Diffusion Model for Graph Generation from [Kong et al. 2023]
microsoft/foldingdiff
Diffusion models of protein structure; trigonometry and attention are all you need!
Membrizard/ml_conformer_generator
Shape-constrained molecule generation via Equivariant Diffusion and GCN