用高斯-赛德尔投影让蛋白质结构生成更物理合理，速度提升10倍
Physically Valid Biomolecular Interaction Modeling with Gauss-Seidel Projection
- 引入可微分投影模块，在生成过程中强制满足空间位阻约束
- 仅需2步去噪即可达到200步基线的结构精度，速度提升约10倍
- 适合需要高精度且物理可行蛋白复合物生成的研究者使用
基于基础模型的生物分子相互作用建模虽取得显著进展，但常生成违反基本空间可行性（立体阻碍）的全原子结构。本文通过在训练和推理中统一引入严格物理有效性约束，解决该问题。核心是一个可微分投影模块，将扩散模型生成的临时原子坐标映射至最近的物理可行构型。该投影采用高斯-赛德尔算法，利用约束的局部性和稀疏性，在大规模场景下实现稳定快速收敛。通过隐式微分获取梯度，模块可无缝集成至现有框架，支持端到端微调。加入该模块后，仅需两步去噪即可生成既物理有效又结构准确的生物分子复合物。在六个基准测试中，2步模型达到与最先进的200步扩散基线相当的结构精度，同时实现约10倍的实时加速，并确保物理合理性。代码已开源：https://github.com/chensiyuan030105/ProteinGS.git。
原文摘要 · Abstract (English)
Biomolecular interaction modeling has been substantially advanced by foundation models, yet they often produce all-atom structures that violate basic steric feasibility. We address this limitation by enforcing physical validity as a strict constraint during both training and inference with a uniffed module. At its core is a differentiable projection that maps the provisional atom coordinates from the diffusion model to the nearest physically valid conffguration. This projection is achieved using a Gauss-Seidel scheme, which exploits the locality and sparsity of the constraints to ensure stable and fast convergence at scale. By implicit differentiation to obtain gradients, our module integrates seamlessly into existing frameworks for end-to-end ffnetuning. With our Gauss-Seidel projection module in place, two denoising steps are sufffcient to produce biomolecular complexes that are both physically valid and structurally accurate. Across six benchmarks, our 2-step model achieves the same structural accuracy as state-of-the-art 200-step diffusion baselines, delivering approximately 10 times faster wall-clock speed while guaranteeing physical validity. The code is available at https://github.com/chensiyuan030105/ProteinGS.git.
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