YangLing0818/IPDiff
[ICLR 2024] Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models
This project helps computational chemists and drug designers generate new 3D drug-like molecules that are likely to bind effectively with a specific protein target. You input the 3D structure of a protein, and it outputs a set of novel 3D molecular structures predicted to interact favorably with that protein. Medicinal chemists, pharmacologists, and researchers in drug discovery would find this useful.
No commits in the last 6 months.
Use this if you need to computationally design and generate new small molecules that are optimized to bind to a particular protein target in a drug discovery pipeline.
Not ideal if you are looking for a tool to simulate existing molecular dynamics, analyze binding energies of known compounds, or perform general chemistry calculations unrelated to de novo drug design.
Stars
55
Forks
6
Language
Python
License
MIT
Category
Last pushed
Sep 06, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/YangLing0818/IPDiff"
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