用三维密度图生成蛋白质结构，提升新颖性和设计性。
ProxelGen: Generating Proteins as 3D Densities
- 以体素化密度（proxels）替代点云表示蛋白质
- 生成样本新颖性更高，FID得分更优，设计性相当
- 支持灵活的形状条件控制，适合结构设计任务
我们开发了ProxelGen，一种基于三维密度而非传统点云表示的蛋白质结构生成模型。通过将蛋白质编码为体素化密度（proxels），该方法实现了新任务和更灵活的条件生成能力。采用基于3D CNN的变分自编码器结合其潜在空间中的扩散模型进行生成。相比现有最先进模型，ProxelGen生成的样本具有更高新颖性、更优的FID分数，并保持与训练集相当的设计性。在标准基序支架基准测试中验证了其优势，且展示了基于3D密度生成在形状条件控制上的灵活性。
原文摘要 · Abstract (English)
We develop ProxelGen, a protein structure generative model that operates on 3D densities as opposed to the prevailing 3D point cloud representations. Representing proteins as voxelized densities, or proxels, enables new tasks and conditioning capabilities. We generate proteins encoded as proxels via a 3D CNN-based VAE in conjunction with a diffusion model operating on its latent space. Compared to state-of-the-art models, ProxelGen's samples achieve higher novelty, better FID scores, and the same level of designability as the training set. ProxelGen's advantages are demonstrated in a standard motif scaffolding benchmark, and we show how 3D density-based generation allows for more flexible shape conditioning.
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