Supplementary materials for "Improving diffusion-based protein backbone generation with global-geometry-aware latent encoding"

<h1>Info</h1> <p>This dataset contains the supplementary materials for &nbsp;"Improving diffusion-based protein backbone generation with global-geometry-aware latent encoding".&nbsp;</p> <p>For&nbsp;<strong>source code&nbsp;</strong>and&nbsp;<strong>detailed instructions on usage,&nbsp;</strong>please refer to our <a href="https://github.com/meneshail/TopoDiff/tree/main" target="_blank" rel="noopener">github</a> .</p> <h1>Supplementary data</h1> <h2>weights.tar.gz</h2> <p>The trained model weights used in the paper.</p> <h2>dataset.zip</h2> <p>CATH-60 Dataset used in the paper. In the notebook directory of our <a href="https://github.com/meneshail/TopoDiff/tree/main" target="_blank" rel="noopener">github</a> , we provide an example on encoding and visualize it with our trained encoder.</p> <h2>design.zip</h2> <p>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.</p> <h2>benchmark_sample.zip</h2> <p>Sampled backbones used for all benchmark experiment (All methods and variants included).</p> <h2>evaluation.tar.gz</h2> <p>Precomputed CATH reference data for coverage metric computation. Need to be downloaded for using evaluation scripts.&nbsp;</p>