Title: dyAb: Flow Matching for Flexible Antibody Design with AlphaFold-driven Pre-binding Antigen Show Chinese title

Title: dyAb：基于AlphaFold驱动的预结合抗原的灵活抗体设计流匹配

Abstract: The development of therapeutic antibodies heavily relies on accurate predictions of how antigens will interact with antibodies. Existing computational methods in antibody design often overlook crucial conformational changes that antigens undergo during the binding process, significantly impacting the reliability of the resulting antibodies. To bridge this gap, we introduce dyAb, a flexible framework that incorporates AlphaFold2-driven predictions to model pre-binding antigen structures and specifically addresses the dynamic nature of antigen conformation changes. Our dyAb model leverages a unique combination of coarse-grained interface alignment and fine-grained flow matching techniques to simulate the interaction dynamics and structural evolution of the antigen-antibody complex, providing a realistic representation of the binding process. Extensive experiments show that dyAb significantly outperforms existing models in antibody design involving changing antigen conformations. These results highlight dyAb's potential to streamline the design process for therapeutic antibodies, promising more efficient development cycles and improved outcomes in clinical applications. Show Chinese abstract

Abstract: 治疗性抗体的发展高度依赖于对抗原与抗体相互作用的准确预测。 现有的抗体设计计算方法常常忽略了抗原在结合过程中发生的重要的构象变化，这显著影响了所得抗体的可靠性。 为了弥补这一差距，我们引入了dyAb，这是一个灵活的框架，结合了AlphaFold2驱动的预测来模拟结合前的抗原结构，并特别针对抗原构象变化的动态特性。 我们的dyAb模型利用了一种独特的粗粒度界面对齐和细粒度流匹配技术的组合，以模拟抗原-抗体复合物的相互作用动力学和结构演化，提供了结合过程的真实表示。 大量实验表明，dyAb在涉及抗原构象变化的抗体设计中显著优于现有模型。 这些结果突显了dyAb在治疗性抗体设计过程中的潜力，有望缩短开发周期并在临床应用中提高效果。