ReQFlow：用於高效高質量蛋白質骨架生成的校正四元數流

ReQFlow: Rectified Quaternion Flow for Efficient and High-Quality Protein Backbone Generation

February 20, 2025

作者: Angxiao Yue, Zichong Wang, Hongteng Xu

cs.AI

摘要

蛋白質骨架生成在從頭蛋白質設計中扮演著核心角色，並對許多生物學和醫學應用具有重要意義。儘管基於擴散和流動的生成模型為這一挑戰性任務提供了潛在解決方案，但它們往往生成具有不理想可設計性的蛋白質，且存在計算效率低下的問題。在本研究中，我們提出了一種新穎的校正四元數流（ReQFlow）匹配方法，用於快速且高質量的蛋白質骨架生成。具體而言，我們的方法為蛋白質鏈中的每個殘基從隨機噪聲生成局部平移和三維旋轉，將每個三維旋轉表示為單位四元數，並通過指數形式的球面線性插值（SLERP）構建其流動。我們通過具有數值穩定性的四元數流（QFlow）匹配來訓練模型，並校正QFlow模型以加速其推理並提高生成蛋白質骨架的可設計性，從而提出ReQFlow模型。實驗表明，ReQFlow在蛋白質骨架生成中達到了最先進的性能，同時需要更少的採樣步驟和顯著更短的推理時間（例如，在生成長度為300的骨架時，比RFDiffusion快37倍，比Genie2快62倍），展示了其有效性和效率。代碼可在https://github.com/AngxiaoYue/ReQFlow獲取。

English

Protein backbone generation plays a central role in de novo protein design and is significant for many biological and medical applications. Although diffusion and flow-based generative models provide potential solutions to this challenging task, they often generate proteins with undesired designability and suffer computational inefficiency. In this study, we propose a novel rectified quaternion flow (ReQFlow) matching method for fast and high-quality protein backbone generation. In particular, our method generates a local translation and a 3D rotation from random noise for each residue in a protein chain, which represents each 3D rotation as a unit quaternion and constructs its flow by spherical linear interpolation (SLERP) in an exponential format. We train the model by quaternion flow (QFlow) matching with guaranteed numerical stability and rectify the QFlow model to accelerate its inference and improve the designability of generated protein backbones, leading to the proposed ReQFlow model. Experiments show that ReQFlow achieves state-of-the-art performance in protein backbone generation while requiring much fewer sampling steps and significantly less inference time (e.g., being 37x faster than RFDiffusion and 62x faster than Genie2 when generating a backbone of length 300), demonstrating its effectiveness and efficiency. The code is available at https://github.com/AngxiaoYue/ReQFlow.