Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2024
|
| Online Access: | https://doi.org/10.5281/zenodo.15572019 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Table of Contents:
- <p>The modified version of the COACH420 dataset that was used for GrASP evaluation.</p> <ol> <li><strong>unprocessed_pdb.zip</strong>: PDB structures from the original COACH420 dataset.</li> <li><strong>ready_to_parse_mol2.zip</strong>: Protein and ligand structures after our additional processing was applied.</li> <li><strong>raw.zip</strong>: NumPy arrays of the features used to construct PyTorch Geometric graphs.</li> <li><strong>processed.zip</strong>: Processed protein graphs used as graph neural network inputs.</li> <li><strong>mol2.zip</strong>: Protein with hydrogens removed and atoms renumbered accordingly. Indices match the node feature order in the NumPy and PyTorch files.</li> <li><strong>coach420(mlig)_uniprot.pkl</strong>: Pickle containing UniProt ID for each receptor, used to define train/test splits.</li> </ol>