Supplementary materials for "Improving diffusion-based protein backbone generation with global-geometry-aware latent encoding"
Authors/Creators
-
1.
Tsinghua University
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2.
National Institute of Biological Sciences, Beijing
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3.
University of California San Diego
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.tar.gz
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).
evaluation.tar.gz
Precomputed CATH reference data for coverage metric computation. Need to be downloaded for using evaluation scripts.
Files
design.zip
Files
(7.7 GB)
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md5:5293ae9e5faa29ba01605e8905ec4b70
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384.9 MB | Preview Download |
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md5:ef7f6d12244155630b47d2c2b66d2ef6
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666.1 MB | Preview Download |
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md5:ebff2aa83163878ab9064b1aa3217815
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2.2 MB | Preview Download |
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md5:3670a1bbbabdd78537e2e5628cb7cef5
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3.9 GB | Download |
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md5:4e4afddcd51b102ef52fafad418de059
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33.5 MB | Download |
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md5:60df7eb1964a8c2b43ce5d42d4d1d53d
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2.5 GB | Download |
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md5:1e88234f869fbd129778cca8076af035
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223.1 MB | Download |
Additional details
Related works
- Is supplement to
- Preprint: 10.1101/2024.10.05.616664 (DOI)
- Journal article: 10.1038/s42256-025-01059-x (DOI)
Software
- Repository URL
- https://github.com/meneshail/TopoDiff/tree/main
- Programming language
- Python , Jupyter Notebook
- Development Status
- Active