发表机构
The Chinese University of Hong Kong; University of Washington; Westlake University; Zhejiang University（香港中文大学; 华盛顿大学; 西湖大学; 浙江大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
CODesign通过一致性蒸馏数据和多模态联合流模型，实现全原子蛋白质结合物的序列与结构协同设计，显著提升计算机模拟成功率。
AI 中文摘要
从头蛋白质设计的核心挑战是生成合理且相互兼容的结构和序列，使得每个设计的序列折叠成其预期结构，且该结构能够容纳该序列。与典型的将相互依赖模态建模解耦的两阶段设计方法相比，协同设计模型通过联合生成序列和结构来改善跨模态一致性。然而，朴素地同时生成序列和结构并不能确保它们的一致性。为应对这一挑战，我们提出了CODesign框架。我们通过生成约105,000个一致性蒸馏二聚体来提升数据一致性。我们进一步通过一个多模态联合流模型来促进一致性，该模型捕获序列、骨架结构和局部原子构型的联合分布，并辅以一致性感知的联合重采样策略，该策略迭代优化序列和侧链。实验表明，CODesign在蛋白质和配体靶标结合物设计上均取得了最先进的性能，具有最高的计算机模拟成功率。消融研究还表明，我们的蒸馏数据集将性能提升了70.9%，而通过我们提出的重采样机制，性能可进一步提升，且额外计算成本可忽略不计。代码、模型权重和新数据集将完全开源。
英文摘要
The central challenge in de novo protein design is generating plausible, mutually compatible structures and sequences, such that each designed sequence folds into its intended structure and the structure accommodates that sequence. Compared to typical two-stage design methods, which decouple the modeling of the interdependent modalities, co-design models improve the cross-modal consistency by jointly generating sequences and structures. However, naively generating sequences and structures simultaneously does not ensure their consistency. To address this challenge, we propose CODesign framework. We improve data consistency by generating approximately 105,000 consistency-distilled dimers. We further promote consistency through a multimodal joint flow model that captures the joint distribution of sequences, backbone structures, and local atomic configurations, together with a consistency-aware joint resampling strategy that iteratively refines sequences and side chains. Experiments show that CODesign achieves state-of-the-art performance with the highest in silico success rates on both protein- and ligand-target binder design. Ablation studies also demonstrate our distilled dataset increases performance by 70.9%, which can be further improved by our proposed resampling mechanism with negligible additional computational cost. Code, model weights and the new dataset will be completely open-source.
