prescient-design/jamun
Bridging Smoothed Molecular Dynamics and Score-Based Learning for Conformational Ensembles
This project helps computational chemists and drug discovery scientists quickly generate diverse 3D shapes (conformational ensembles) for small peptide molecules. It takes a peptide sequence or initial 3D structure as input and outputs a collection of its possible stable shapes, which is crucial for understanding how proteins function or designing new drugs. This tool is designed for researchers who work with molecular simulations and need to explore peptide conformations more efficiently than traditional methods.
Use this if you need to rapidly generate accurate conformational ensembles for small peptides and require faster computation than standard molecular dynamics, especially for peptides not seen during training.
Not ideal if you primarily work with very large proteins or require highly precise quantum mechanical simulations for extremely detailed molecular interactions.
Stars
19
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 05, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/prescient-design/jamun"
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