物理有效生物分子扩散模型的推理时投影
Inference-Time Projection for Physically Valid Biomolecular Diffusion Models
- University of Oxford（牛津大学）
- University of Copenhagen（哥本哈根大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对生物分子扩散模型输出物理无效的问题，提出推理时闭式投影算子，无需重训即可恢复完美物理有效性并保持结构精度。
AI中文摘要：
AlphaFold 3 风格的共折叠模型能够以高结构精度预测生物分子复合物，但其输出中有很大一部分在物理上无效：链在界面处重叠，配体键长和键角发生畸变，环不呈平面，立体中心发生反转。当前的方法要么使用物理信息势引导采样器，这会成倍增加采样成本和内存开销，使得大型复合物的推理变得不可能；要么对模型进行微调，这既耗时又将修复绑定到单一架构。我们观察到，与结构精度不同，物理有效性可以在推理时从采样器已持有的量中完全验证。因此，我们将物理有效性视为一个约束推理问题，并引入两个应用于扩散模型去噪后的干净坐标估计 $\hat{x}_0$ 的闭式投影算子：一个链间范德华投影，用于推开最严重冲突的原子对；以及一个配体距离几何投影，用于恢复键长、键角、内部接触、平面性和手性。两个算子都是局部的、稀疏的且位移受限的，不需要网络评估、梯度或重要性采样，并且不触碰去噪器及其权重，因此可以无需重新训练即可插入任何 AF3 风格的采样器。应用于两个独立开发的模型 Boltz-2 和 OpenFold-3，跨越五个基准（CASP15、CASP16、PoseBusters 单体和复合物集，以及 Boltz 物理有效性测试集），我们的方法恢复了完美的物理有效性，同时保持了结构精度和配体放置指标。这些增益以可忽略的运行时和内存开销实现，为物理有效的全原子结构预测提供了一条实用的、模型无关的途径。
英文摘要：
AlphaFold 3-style cofolding models predict biomolecular complexes with high structural accuracy, yet a large fraction of their outputs are physically invalid: chains overlap at interfaces, ligand bond lengths and angles are distorted, rings are non-planar, and stereocentres are inverted. Current approaches either steer the sampler with physics-informed potentials, which multiplies sampling cost and memory overhead making inference impossible on large complexes, or finetune the model, costing time and tying the fix to one architecture. We observe that, unlike structural accuracy, physical validity is fully verifiable at inference time from quantities the sampler already holds. We therefore treat physical validity as a constrained inference problem and introduce two closed-form projection operators applied to the diffusion model's denoised clean-coordinate estimate, $\hat{x}_0$: an inter-chain van der Waals projection that pushes apart the most severely clashing atom pairs, and a ligand distance-geometry projection that restores bond lengths, angles, internal contacts, planarity and chirality. Both operators are local, sparse and displacement-capped, require no network evaluations, gradients or importance sampling, and leave the denoiser and its weights untouched, so they can be dropped into any AF3-style sampler without retraining. Applied to two independently developed models, Boltz-2 and OpenFold-3, across five benchmarks (CASP15, CASP16, the PoseBusters monomer and complex sets, and the Boltz physical-validity test set), our method recovers perfect physical validity while preserving structural-accuracy and ligand-placement metrics. These gains are achieved with negligible runtime and memory overhead, providing a practical, model-agnostic route to physically valid all-atom structure prediction.
