Supplementary materials for "Improving diffusion-based protein backbone generation with global-geometry-aware latent encoding"
Authors/Creators
Description
Info
This dataset contains the supplementary materials for "Improving diffusion-based protein backbone generation with global-geometry-aware latent encoding".
For source code and detailed instructions on usage, please refer to our github .
Supplementary data
weights.zip
The trained model weights used in the paper.
dataset.zip
CATH-60 Dataset used in the paper. In the notebook directory of our github , we provide an example on encoding and visualize it with our trained encoder.
design.zip
The 21 novel mainly-beta designs selected for experiment validation. Along with the generated backbone, we also provide the prediction results from AlphaFold and ESMFold.
benchmark_sample.zip
Sampled backbones used for all benchmark experiment (All methods and variants included).
Files
weights.zip
Additional details
Related works
- Is supplement to
- Preprint: 10.1101/2024.10.05.616664 (DOI)
Software
- Repository URL
- https://github.com/meneshail/TopoDiff/tree/main
- Programming language
- Python , Jupyter Notebook
- Development Status
- Active