THUNLP-MT/PepGLAD
Codes for our paper "Full-Atom Peptide Design with Geometric Latent Diffusion" (NeurIPS 2024)
This tool helps researchers in drug discovery and biochemistry design new peptides or predict how existing ones will interact with target proteins. You provide a protein structure (PDB file) and identify a binding site, then the system generates novel peptide sequences and their 3D structures, or predicts the optimal binding conformation for a given peptide sequence. It's intended for scientists working on developing new therapeutics or studying protein-peptide interactions.
109 stars. No commits in the last 6 months.
Use this if you need to rapidly explore potential peptide candidates for a specific protein target or predict how a known peptide sequence will bind to a protein.
Not ideal if you are looking for a simple web-based interface or do not have experience with command-line tools and managing computational environments.
Stars
109
Forks
9
Language
Python
License
MIT
Category
Last pushed
Apr 16, 2025
Commits (30d)
0
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